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Using conservation reserve program maps derived from satellite imagery to characterize landscape structure
Abstract
The Conservation Reserve Program (CRP) instituted one of the largest and most rapid land use/land cover conversions in US history. Approximately 14.8 million ha (36.5 million acres) of cropland were converted to grassland, woodland, and other conservation uses between 1986 and 1995. As policy makers continue to evaluate the future of the program and as scientists examine its effects, it is critical that the impact of CRP on landscape structure be considered because of its potential influence on wildlife populations. Utilizing multi-seasonal Landsat thematic mapper imagery in an unsupervised classification technique, we produced highly accurate maps of cropland and grassland for 1987 and 1992 for Finney County, Kansas. Post-classification differencing identified regions of cropland that had been converted to CRP. We then used the Finney County CRP map to examine changes in landscape structure caused by the introduction of CRP. Using the fragstats spatial pattern analysis program, we calculated the number of patches, mean patch size, patch density, edge density, mean shape index, nearest neighbor distance, and an interspersion/juxtaposition index. In addition, we calculated total grassland area and percent of area in grassland for the pre- and post-CRP enrollment years. We found that the total grassland area and the percent area in grassland in Finney County increased due to CRP and that mean grassland patch size also increased. The total number of grassland patches decreased, however, due to coalescence of smaller grassland patches. Patch density, edge density, mean shape index, nearest neighbor distance, and the interspersion/juxtaposition index all showed relatively small changes. These small changes appear to reflect geographic differences in CRP effects within the county—large aggregating patches in the northeast were offset by a number of isolated patches of CRP in other areas. The implication of these findings for wildlife managers is that, for species that require large areas of grassland habitat, especially habitat that is contiguous, CRP in Finney County represents a substantial increase in potential habitat. This holds for species at all levels of management interest, ranging from economically valuable species to species that are rare, threatened, and endangered. These findings emphasize the importance of CRP for wildlife conservation and should further inform ongoing debate concerning the importance of the CRP.
... This results in a novel and policy driven landscape, in which CRP lands impact the patterns within both grassland and agricultural matrices. Though the trade-off between cropland loss to grassland gain is not always one-to-one when implementing CRP (i.e., the occurrence of slippage, in which existing grasslands are converted to croplands to offset CRP enrollment [Erickson and Collins, 1985]), the direct benefits of CRP mentioned earlier suggest that this program is important in maintaining ecological processes and functions indicative of grasslands throughout the Great Plains (Egbert et al., 2002). ...
... An AES such as the CRP may offer a promising way to maintain coverage and connectivity of grasslands within Oklahoma, yet identifying direct impacts of this program through spatially explicit modeling across scales is necessary to fully understand how this program is affecting the landscape. Though previous research has demonstrated that CRP can positively influence grassland connectivity (Egbert et al., 2002;Park and Egbert, 2008;Spencer et al., 2017), these studies have focused on smaller extents (i.e, county level) in areas with relatively high coverage of CRP lands. By focusing on a much larger extent, we are able to determine the circumstances in which CRP begins to really impact landscape patterns. ...
... There is a potential to overcomplicate landscape analyses using FRAGSTATS as the number of unique variables measured by this program can exceed 100 metrics (Lustig et al., 2015). To limit the complexity of our analyses, we incorporated variables previously used to estimate the impact of CRP on landscape patterns at smaller extents within the Great Plains (Egbert et al., 2002;Park and Egbert, 2008), while also ensuring that we included variables representing dominance, complexity, and contagion of the landscape (O'Neill et al., 1996). At the patch scale, we analyzed patch perimeter (m), shape index (index = 1 when patch is square and increases positively as the shape deviates from a square), core area (ha), Euclidean nearest-neighbor distance (ENN; m), and mean patch size (ha). ...
Human culture and policy play an important role in structuring landscape patterns. Agriculture is an example of a land use practice that has altered landscape patterns worldwide and agricultural intensification coupled with broad patterns in land use change have resulted in decreased cover of native plant communities and a loss in biodiversity. The Conservation Reserve Program (CRP) was initially developed to address large agricultural surpluses by transitioning highly erodible cropland into conservation-related perennial cover types. Research has demonstrated that this program can help restore ecological processes across landscapes. However, this program can also impact landscape patterns across multiple spatial scales, though its direct influence to these patterns is poorly understood. To understand the contribution of currently enrolled CRP lands to broadscale landscape patterns, we used FRAGSTATS and non-metric multidimensional scaling (NMDS) to assess how patch- and class- scale landscape patterns change in relation to grasslands across the state of Oklahoma with the presence and theoretical absence of CRP. Furthermore, we determined how these patterns vary across three spatial extents: the statewide, the Environmental Protection Agency (EPA) defined ecoregions, and the county extents within Oklahoma. Though impacts at the statewide extent were minimal, NMDS results indicated shifts in landscape patterns across ecoregions and counties that were primarily associated with increases in effective mesh size and largest patch index. Our results indicate that CRP can help maintain complexity of the grassland matrix through improving connectivity. However, the direct impacts of CRP on landscape patterns is dynamic across spatial scales and these effects influence the overall perceived impact of CRP to grassland patterns.
... Nowadays the rapid development of land surface detection and analysis techniques motivate researchers to find a simple objective method to estimate the changes of land cover and the effects of changes on the pattern and structure of land cover [10][11][12]. Spatially explicit information about landscapes and vegetation cover, both in small and large scales, are increasingly sought by biodiversity modelers and by management and restoration programs [13][14][15][16]. Furthermore, assessing and monitoring the state of the Earth's surface is a key requirement for global change research [14,[17][18][19]. ...
... Also, these techniques were applied in many studies using the two data source parallel and they produced useful information from structural plant diversity, land cover and from effects of land use on forest ecosystem [13,43,72]. ...
Manual Land Cover Mapping using aerial photographs provides sufficient level of resolution for detailed vegetation or land cover maps. However, in some cases it is not possible to achieve the desired information over large areas, for example from historical data where the quality and amount of available images is definitely lower than from modern data. The use of automated and semi-automated methods offers the means to identify the vegetation cover using remotely sensed data. In this paper automated methods were tested on aerial photographs and satellite images to extract better and more reliable information about vegetation cover. These tests were performed by using automated analysis of LANDSAT7 images (with and without the surface model of the Shuttle Radar Topography Mission (SRTM)) and two temporally similar aerial photographs. The spectral bands were analyzed with supervised (maximum likelihood) methods. In conclusion, the SRTM and the combination of two temporally similar aerial photographs from earlier years were useful in separating the vegetation cover on a floodplain area. In addition the different date of the vegetation season also gave reliable information about the land cover. High quality information about old and present vegetation on a large area is an essential prerequisites ensuring the conservation of ecosystems.
... During the 1970s, the National Environmental Policy Act (NEPA, 1970) and Forest and Rangeland Renewable Resources Planning Act (RPA, 1974) were enacted to stop the creeping encroachment on grasslands and protect natural resources. Studies have suggested that grassland and scrub areas have increased since the Conservation Reserve Program (CRP) in 1985 [67]. In the 21st century, the U.S. has further strengthened its vegetation conservation efforts through scientific research, legislation, public education, and international cooperation to address the challenges posed by climate change, energy shortages, and other contemporary issues. ...
Spatially explicit reconstruction of historical land cover change is a prerequisite for a more comprehensive understanding of environmental changes. Anthropogenic activities have dramatically altered the land cover of the conterminous United States (CONUS), encroaching heavily on the primary vegetation. However, few datasets exist that depict the historical trajectory of forest and grassland cover changes in CONUS over the last millennium, and previous efforts have only focused on reconstructions for the last four centuries. By integrating remote sensing-derived land use/cover change (LUCC) data and potential vegetation data, we determined the potential extent of natural forest (PENF) and grassland (PENG) in CONUS. Based on a qualitative analysis of the trends and driving forces of forest and grassland changes, we devised a method of subtracting reconstructed historical cropland (1000–2000 AD) and built-up land (1850–2000 AD) from PENG and PENF to reconstruct a 5 min × 5 min grid dataset of forest and grassland cover at 13 time-points over the past millennium. The results showed that forest and grassland cover in CONUS underwent a slow decline (1000–1600 AD), an accelerated decline (1600–1800 AD), a dramatic decline (1800–1950 AD), and finally, a recovery (1950–2000 AD) over the study period. The modelled forest fraction decreased from 49% in 1000 AD to 33% in 2000 AD, representing a 32% area reduction, whereas the modelled grassland fraction decreased from 37% to 22%, representing a 42% area reduction. The reduction occurred primarily in the last 200 years, with forest and grassland reductions accounting for 86% and 97% of the total reduction over the millennium, respectively. Spatially, more than 80% of the land was originally covered by forests and grasslands, and the loss occurred mainly in the eastern CONUS and Great Plains over the past millennium. After the 1930s, farmland abandonment began in central and eastern CONUS, simultaneously with environmental protection laws. Federal government regeneration programs for forest and grassland resources and the Shelterbelt Project all contributed to a slowdown in forest and grassland decline and recovery in cover.
... Such changes have important consequences on biodiversity, as well as water and carbon fluxes, both at local and regional levels (Herkert et al., 2003). Landscape fragmentation studies have been mostly concentrated in forests (Roy and Tomar, 2000;Riitters et al., 2002), but this kind of analysis has been extended to other natural systems, such 3 as shrub lands (Kemper et al., 2000), grasslands (Coppedge et al., 2002;Egbert et al., 2002) and even aquatic environments (Bell et al., 2001). The relatively small number of studies on grassland fragmentation might be due not only to the long history of land cover conversion of these systems, but also to the traditional lack of recognition of the conservation value of grasslands (Baldi et al., 2006). ...
... Accurate mapping of vegetation cover in an ecosystem can help to initiate its protection and restoration programmes efficiently [1]. It is, therefore, necessary to acquire accurate and up-to-date information about the status of the vegetation cover of an ecosystem through regular monitoring. ...
In complex classification tasks, such as the classification of heterogeneous vegetation covers, the high similarity between classes can confuse the classification algorithm when assigning the correct class labels to unlabelled samples. To overcome this problem, this study aimed to develop a classification method by integrating graph-based semi-supervised learning (SSL) and an expert system (ES). The proposed method was applied to vegetation cover classification in a wetland in the Netherlands using Sentinel-2 and RapidEye imagery. Our method consisted of three main steps: object-based image analysis (OBIA), integration of SSL and an ES (SSLES), and finally, random forest classification. The generated image objects and the related features were used to construct the graph in SSL. Then, an independently developed and trained ES was used in the labelling stage of SSL to reduce the uncertainty of the process, before the final classification. Different spectral band combinations of Sentinel-2 were then considered to improve the vegetation classification. Our results show that integrating SSL and an ES can result in significantly higher classification accuracy (83.6%) compared to a supervised classifier (64.9%), SSL alone (71.8%), and ES alone (69.5%). Moreover, utilisation of all Sentinel-2 red-edge spectral band combinations yielded the highest classification accuracy (overall accuracy of 83.6% with SSLES) compared to the inclusion of other band combinations. The results of this study indicate that the utilisation of an ES in the labelling process of SSL improves the reliability of the process and provides robust performance for the classification of vegetation cover.
... Supportive information regarding the physico-social environments that contain natural and human modified features can also be extracted in the course of quantifying vegetation cover in different spatial scales in a single point of time as well as over a chronological period that may be monthly, seasonal, or in an annual manner (Xiao, 2004;Xie, Sha, & Yu, 2008). Thus restoration programs for vegetation protection and assessment of environmental system in holistic manner are urgent need for the society (Egbert et al., 2002;He, Zhang, Li, Li, & Shi, 2005;Knight, Lunetta, Ediriwickrema, & Khorram, 2006). Conventional method of vegetation monitoring includes a review-based study of various literatures, field surveys, interpretation of maps, and supplementary data analysis that are tedious, least efficient to obtain information, expensive, and reasonably sturdy to carry out (Xie et al., 2008;Almeida et al., 2014). ...
Assessment of vegetation status plays a crucial role in maintaining the ecological viability of the environment. Climate parameters i.e., rainfall, temperature, relative humidity, evapotranspiration, etc., play essential roles in maintaining the health of the vegetation. Thus, analyzing the influence of climate parameters on vegetation is essential to maintain their potentiality and sustainability. In the present study, relationship between rainfall and NDVI was analyzed at annual and seasonal scales in Bankura district of West Bengal. Rainfall data during 1901-2018 of 6 stations located in study area was obtained from CRU and Swat datasets. Trend Free Pre-whitening Mann Kendall (TFPW-MK) and Sen’s slope test were employed in RStudio to examine the seasonal and annual variability in rainfall at different stations. Normalized Difference Vegetation Index (NDVI) for different seasons were prepared from Landsat 8 OLI data of 2019. Relationship between NDVI and TFPW-MK values of rainfall were analyzed through regression to assess the influence of rainfall on vegetation. Results indicated strong increasing trend in rainfall at annual scale as well as during monsoon and post-monsoon seasons. Neither decreasing nor increasing trend in rainfall was observed during summer and winter seasons. Significant variability in vegetation was also identified from the seasonal analysis. Significant relationship between NDVI and rainfall advocated influence of rainfall on vegetation in the study area. The methodology used in this study will be instructive for formulating effective management strategies for planning in the forest dominated region at various scales.
... The knowledge generated from this study can be useful to both researchers and the users of the wetland ecosystems, such as farmers and the tourism industry especially if there are any projected and/or predicted risks associated with changes within the system because it can help them curb some of these predicted threats early. Availability of such information can also allow management and preservation of riparian woodland species into their natural state (Egbert et al., 2002;He et al., 2005). ...
Riparian vegetation in the Okavango Delta has extensive economic, social and environmental benefits. However, despite its importance, it is threatened by changes in variation in hydrology, anthropogenic activities, and other environmental conditions. Some riparian vegetation communities may change rapidly in response to both long term and short term disturbances. Long term monitoring of riparian woodland vegetation can help reveal changes in these woodland species, enabling timeous management interventions. In this study we classified, mapped and conducted change detection analysis of the spatial extent of different communities of riparian woodland in the Okavango Delta. Woodland species were identified in the field and their percentage cover estimated. Agglomerative hierarchical cluster analysis in PC-ORD was used to classify woodland vegetation into four communities. These communities were Croton megalobotrys-Hyphaene petersiana, Vachellia erioloba-Gymnosporia senegalensis, Phoenix reclinata-Syzygium cordatum and Vachellia tortilis-Combretum imberbe. Multi response permutation procedures (MRPP) was used to test if there was any significant difference in plant species composition between different vegetation communities. MRPP showed that communities varied significantly (p<0.05) from each other in composition, which may be indicative of the prevailing environmental conditions in the Delta. Landsat data was used to produce land cover maps at 3 time-steps which were then used in the change detection analysis for riparian woodland vegetation. Phoenix reclinata-Syzygium cordatum areal extent increased from 1991 to 2019, whilst Croton megalobotrys-Hyphaene petersiana decreased. The area covered by Vachellia tortilis-Combretum imberbe and Vachellia erioloba-Gymnosporia senegalensis was fluctuating over the study period. The results suggest that the Phoenix reclinata-Syzygium cordatum community is more susceptible to variations in hydrology whilst the Vachellia erioloba-Gymnosporia senegalensis community is more stable. The Croton megalobotrys-Hyphaene petersiana and Vachellia tortilis-Combretum imberbe communities are also susceptible to prevailing environmental conditions including the hydrology, soil nutrient status as well as the occurrence of elephants in large densities in the Delta and anthropogenic activities. This information will serve as baseline for monitoring of riparian woodland vegetation in the Okavango Delta.
... One of the most rapidly growing applications of remotely sensed data is the derivation of landscape pattern metrics for the assessment of land use condition and landscape dynamics (Betts et al., 2003;Colombo et al., 2004;Egbert et al., 2002;Griffith et al., 2003;Hansen et al., 2001;Imbernon and Branthomme, 2001;Ji et al., 2008;Millington et al., 2003;Santiago et al., 2007;Yu and Ng, 2006). The characteristics of green areas are generally analyzed with raster data by many scholars. ...
... To alleviate these restraints, high-resolution, long-term, large-scale satellite remote sensing datasets are remarkably beneficial. For example, Wu et al. (1997) used multi-temporal Landsat images to map land use and land cover, so as to evaluate the soil properties of CRP land; Egbert et al. (2002) used Landsat images to map change from cropland to grassland between 1987 and 1992, so as to analyze the impact of CRP enrollment on the landscape structure. Using the Landsat data which is now freely available to the public, we can ideally conduct land use change analysis across the globe at up to 16-day intervals. ...
Water quality is affected by croplands. The Conservation Reserve Program (CRP), where farmers convert croplands to natural land cover (e.g., trees), is expected to improve water quality. However, whether such improvements are achieved alongside cropland area change has not been verified at river-basin scales, due to challenges in large scale observations. Therefore, aiming to quantify the relationship between CRP enrollment, cropland area, and the downstream water quality, we propose an approach that combines archived survey data, water quality monitoring data (total nitrogen content, TN), and remote sensing observations. By constructing the long-term datasets (1999–2014 annually) in Google Earth Engine and conducting multiple linear regression, we explained 79% variation in TN by the area of total CRP enrollment (CRP_all), area of corn and soybeans croplands, and discharge. Moreover, 78% is explained if we consider only water quality targeted conservation practices (CRP_WQ). Our results indicate significant positive correlation between CRP enrollment (both CRP_all and CRP_WQ) and the downstream water quality. Nevertheless, it should be noted that correlation does not necessarily represent causation. While this pioneer effort of quantifying impacts of the CRP on water quality from large scale observations has achieved some success, we call for more research to expand the spatial and/or temporal scales and consider more water quality variables, so as to further enhance our understanding of the coupled natural-and-human system.
... It is pertinent to acquire current status of vegetation cover to initiate vegetation protection and restoration programs. (Egbert et al. 2002;He et al. 2005). ...
Classifying and mapping of vegetated area in Al- Baha region, Saudi Arabia using remote sensing shows that the medium-high density vegetation is mostly found at the central part of Al-Baha region separating the highlands and the low lands. Results obtained show that only 862.5 km2 (7.7%) Al-Baha region is covered with medium-high density vegetation found mainly at the 6-15km width horizontal central belt (at districts of Al-Mandaq, Al-Baha and south Baljurashi) along high foggy mountainous plateau. Whereas, about 65% of Al-Baha region has very low-none density vegetation mainly occurred extensively at Tihama low plain towards the Red Sea and at the north-eastern desert plain. In addition, study reveals that the highlands of Al-Baha have the most numbers of trees represents the areas of the highest elevations in the region (range between 1940 and 2366 m above sea level. This indicates that there is relationship between this elevation range with medium to high vegetation density. Similarly, the low surface temperatures are mainly located at the central belt across Al-Baha region. When overlaid with medium-high vegetation density zone with the temperature map, it was visually observed that it almost fit with lower temperature zone of less than 15°C. This also indicates that there is relationship between lower temperature with medium-high vegetation density.
... Additionally, it will be a very useful approach to initiate ecological revegetation and restoration projects (Y. Tang et al. 2019;Egbert et al. 2002), as well as to monitor environmental infringements such as camping, overgrazing, off-road vehicles, logging, and uprooting of woody shrubs. ...
Restoration programs require long-term monitoring and assessment of vegetation growth and productivity. Remote sensing technology is considered to be one of the most powerful technologies for assessing vegetation. However, several limitations have been observed with regard to the use of satellite imagery, especially in drylands, due to the special structure of desert plants. Therefore, this study was conducted in Kuwait’s Al Abdali protected area, which is dominated by a Rhanterium epapposum community. This work aimed to determine whether Unmanned Aerial Vehicle (UAV) multispectral imagery could eliminate the challenges associated with satellite imagery by examining the vegetation indices and classification methods for very high multispectral resolution imagery using UAVs. The results showed that the transformed difference vegetation index (TDVI) performed better with arid shrubs and grasses than did the normalized difference vegetation index (NDVI). It was found that the NDVI underestimated the vegetation coverage, especially in locations with high vegetation coverage. It was also found that Support Vector Machine (SVM) and Maximum Likelihood (ML) classifiers demonstrated a higher accuracy, with a significant overall accuracy of 93% and a kappa coefficient of 0.89. Therefore, we concluded that SVM and ML are the best classifiers for assessing desert vegetation and the use of UAVs with multispectral sensors can eliminate some of the major limitations associated with satellite imagery, particularly when dealing with tiny plants such as native desert vegetation. We also believe that these methods are suitable for the purpose of assessing vegetation coverage to support revegetation and restoration programs.
... Numerous studies have shown how landscape metrics can provide a large amount of information on landscape composition and configuration [16]. In many cases, landscape metrics are also used to assess how the landscape changes over time under human pressure or to evaluate the effectiveness of conservative plans in protected zones [17][18][19]. Other studies focused on fluvial landscape configuration and dynamics [20][21][22]. ...
Engineers have shaped the environment across the centuries in order to improve the quality and safety of human life. The unrestrained invasion of nature led to significant environmental problems, for this reason nowadays engineering projects should be based on ecological concepts to protect our environment. This paper presents an integrated methodology that involves GIS tools, hydraulic numerical models, and landscape metrics to investigate ecological consequences caused by river restoration activities. The combined use of these different tools represents a bridge to connect the field of engineering with ecological techniques. The proposed method was tested to predict and assess the influence of a river restoration plan on a reach of the Orco river located in the northwest of Italy. Morphological alterations were simulated to reconnect remnant meanders and provide water to the floodplain, enhancing the ecological value of riparian ecosystems. The application of the hydraulic model permitted to evaluate the distribution of water inside the study area before and after the restoration plan. Thereafter, spatial configuration and temporal dynamics of the landscape structures were quantified using landscape metrics. The increase of patch density (PD) by 9% and edge density (ED) up to 10% highlights that restoration activities lead to a new configuration characterized by a higher level of fragmentation and heterogeneity. The characteristics of versatility, repeatability, and the possibility to predict the outcomes of a specific plan make the proposed method a useful tool that could help decision-makers to manage the territory while safeguarding natural ecosystems.
... In this regard, monitoring and assessing the status of vegetation is one of the significant aspects of environmental health assessment and mitigating global climate change (Alberdi et al., 2019;Bjorkman et al., 2019; UN report on environment, 2019). Apart from this, it also provides valuable information regarding the natural and man-made environments through quantifying vegetation cover from smaller to larger scales at a given point of time or over a continuous period (Xiao, 2004;Xie, Sha, & Yu, 2008) and helps in the protection and restoration programmes of vegetation (Egbert, Park, Price, Lee, & Nellis, 2002;He, Zhang, Li, & Shi., 2005). Above all, Knight, Lunetta, Ediriwickrema and Khorram (2006) argued that strong pretences should be given towards close monitoring of vegetation for the assessment of the environmental system, which is also an urgent need for the society. ...
Intra-annual dynamics of vegetation status is very important to understand the spatial ecological environment. In this study, pixel wise temporal variation of vegetation status has been assessed using normalized differential vegetation index (NDVI) from Landsat 8 OLI data of 2014. Month-wise vegetation statuses were employed to understand the status of vegetation dynamics for the Sali River watershed. We have found that vegetation status (VS) of this study area varied with respect to space and time. We have identified two dominant natures of NDVI fluctuation, one with a single peak coming out of Sal forest and another with multiple peaks which is from paddy fields. NDVI curve of natural vegetation follows a rainfall pattern and depicts a single peak during the rainy season with the moderate standard deviation (S.D.) and coefficient of variation (C.V.). On the other hand, the area associated with population pressure and agricultural fields shows multiple peaks as well as a high degree of S.D. and C.V. of NDVI during the months of April, August and December.
... В наш час данi ДЗЗ є важливим джерелом отримання оперативної та об'єктивної iнформацiї про стан сiльськогосподарського виробництва на великих i вiддалених вiд центрiв управлiння територiях, що особливо актуально для нашої країни [2,4,8,10,12,14]. Сiльськогосподарський монiторинг виник на базi використання матерiалiв наземних спостережень та оцiнок, а також використання моделей прогнозування врожаю за метеорологiчними даними [2,4,10,14]. ...
The article is devoted to the problem of the agrophytocenoses classification with satellite observation data and noise filtration methods. The model of agricultural crop types determination with multispectral data and the support vector machine method was conducted. The modified algorithm for agricultural crops classification approbation was carried out on the satellite imageries of the “Steppe” farm of the Kamyansko-Dniprovsky district of the Zaporizhzhya region. Ground-based reference data on crop types, normative base of agricultural development phases for heavy-loamy and medium-loamy soils characteristics of the southern Ukraine steppe zone and remote sensing data of the studied territory gathered by Landsat ТМ and ETM+ satellites for 2001 and 2003 were used for digital processing. It was investigated that a significant number of false-detected pixels (>5%) belong to the interface zones (field boundaries) and chaotic scattered segments of incorrectly classified crops within the field (≈12). This error is mainly due to spatial variations in soil moisture, plant health, type of projective surface, cultures spectral similarity, phenological stage of plants development, time of satellite observation. Median and rank filtration methods were used to minimize the effect of the above-mentioned problems on the final classification result. The method of median filtration allowed to increase the classification accuracy up to 3%, and the rank filtration method up to 2% compared with the simple procedure of the support vector machine method. The classification error and the disadvantages of filtration are largely due to the interface zones of the different crops, the fields boundaries. Since the spatial resolution is 30×30 meters, it would be advisable to reject the pixels of the transition (on the boundary) from the training sample to identify more accurate classification model.
... For example, we hypothesize that areas with large patches are more likely to be in areas that may experience higher fire activity while any landscape can have a high proportion of grassland, irrespective of the size of the patches that make up this proportion. Furthermore, our study was aimed to retain the six variables as these metrics have been shown to be useful in modeling fragmentation and connectivity in landscape scale studies within in the grasslands of the Great Plains (Egbert et al. 2002;Tanner and Fuhlendorf 2018). ...
Context
Woodland and agricultural expansion are major causes of grassland fragmentation. Fire and rainfall play important roles in maintaining grasslands, however, fire activity has been reduced in fragmented landscapes.
Objectives
Quantify the degree to which basic landscape fragmentation metrics could be used as drivers of woody cover potential.
Methods
Woody plant percent cover was calculated between 2004 and 2008 at > 2000 sites. At each site, we calculated these fragmentation metrics for grassland cover type (classified by the National Land Cover Database); # patches, landscape proportion, edge density, largest patch index, effective mesh size and patch cohesion index within 3 circular areas (10 km², 360 km² and 3600 km²) surrounding the sampling site. A quantile regression was performed to identify which metrics were useful at predicting the 25th, 50th, 75th or 95th quantile of woody cover distribution.
Results
Grassland proportion and edge density were significant predictors of the woody plant potential (75th and 95th quantile). Woody cover potential was positively associated with edge density suggesting that fragmented areas (i.e., areas with high number of edges) maintained higher woody cover, while grassland proportion was negatively associated with woody plant potential.
Conclusion
We propose that in addition to a lack of fire, fragmented landscapes may facilitate further woodland expansion by reducing natural land and restricting grasslands to smaller, less connected patches, which can maintain higher woody cover. Given current trends in woodland expansion, special attention should be given to areas that are found within a fragmented landscape and climatically prone to woodland expansion.
... It is beneficial to obtain the current state of vegetation cover in order to trigger the vegetation protection and rehabilitation program. Classifying and mapping vegetation is an integral and technical task because vegetation is the key factor and plays a substantial role for the survival of all living entities [1] [2]. Since the population is growing at an alarming rate, the competition for sustenance increases. ...
Vegetation cover mapping is an imperative
task of monitoring the change in vegetation as it can help us meet
sustenance requirements. In this study, we explore the future
potential of multilayer Deep learning framework (DL) that
comprises of hybrid of CNN's, for mapping vegetation cover area
as DL is a congenial state-of-art algorithm for implementing image
processing. This study proposes a novel DL framework exploiting
hybrids of CNN’s with Local binary pattern and GIST features.
Every CNN is fed with disparate combination of multi-spectral
Sentinel 2 satellite imagery bands (spatial resolution of 10m),
texture and topographic parameters of Uttarakhand (30° 15' N, 79°
15' E) region, India. Our proposed DL framework outperformed
the state-of-art algorithms with a classification accuracy of 88.43%
... 第 9 期 冯喆 等：基于生态系统服务视角的 " 土地分离与共享框架 " 解析 减少。在粮食供给方面， 美国实施土地共享策略 后， 粮食产量呈现下降趋势(Egbert et al, 2002; Rao et al, 2010的生态系统， 这并非 " 是 " 或 " 非 " 的互斥策略(Ra mankutty et al, 2013)， 其中存在着灰色地带， 可以相 互融合(Lusiana et al, 2012)。例如在 " 分离 " 策略中， 可在保护区或禁耕区内继续划分出完全禁止区和 可 " 共享 " 使用区域， 这与自然保护区中 " 核心区 " 和 " 实验区 " 的划分较为相似。土地 " 分离 " 强调从时 间上给予生态环境充分的恢复， 即时间上的集约， 而 " 共享 " 侧重于释放更多的空间减少人类干扰来 保护生态环境， 因此在土地的集约利用中， 也应同 时考虑分离与共享的策略(Minang et al, 2013[D]. Chongqing, China: Southwest University] Aillery M, Shoemaker R, Caswell M. 2001. ...
... Remote sensing has undeniably played a vital role for mapping abandoned agriculture worldwide, including the United States (Egbert et al. 2002), Europe (Kristensen, Thenail, and Kristensen 2004;Falcucci, Maiorano, and Boitani 2006) and the former USSR (Bergen et al. 2008;Baumann et al. 2011). However, currently, there is a little attention paid to the study of detecting abandoned agriculture in Malaysia. ...
Agricultural crop abandonment negatively impacts local economy and environment since land, as a resource for agriculture, is not optimally utilized. To take necessary actions to rehabilitate abandoned agricultural lands, the identification of the spatial distribution of these lands must be acknowledged. While optical images had previously illustrated potentials in the identification of agricultural land abandonment, tropical areas often suffer cloud coverage problem that limits the availability of the imageries. Therefore, this study was conducted to investigate the potential of ALOS-1 and 2 (Advanced Land Observing Satellite-1 and 2) PALSAR (Phased Array L-band Synthetic Aperture Radar) images for the identification and classification of abandoned agricultural crop areas, namely paddy, rubber and oil palm fields. Distinct crop phenology for paddy and rubber was identified from ALOS-1 PALSAR; nonetheless, oil palm did not demonstrate any useful phenology for discriminating between the abandoned classes. The accuracy obtained for these abandoned lands of paddy, rubber and oil palm was 93.33% ± 0.06%, 78% ± 2.32% and 63.33% ± 1.88%, respectively. This study confirmed that the understanding of crop phenology in relation to image date selection is essential to obtain high accuracy for classifying abandoned and non-abandoned agricultural crops. The finding also portrayed that PALSAR offers a huge advantage for application of vegetation in tropical areas.
... Vegetative cover dynamics play an important role in various mechanism of earth surface which are directly linked with hydro-meteorological phenomenon (Tyson et al., 2001). Monitoring the current state of green areas available at any place is somehow important for initiating any plan of plant conservation (Egbert et al., 2002; He et al., 2005). Pakistan is at the top among the climate risk index and ranked 2 nd amongst highly water stressed countries of Asia and susceptible to hydro-meteorological hazards such as drought. ...
The decline in vegetation cover of the cities is a serious issue around the globe. Karachi, as the largest city of Pakistan is experiencing the removal of vegetation at the cost of the construction of the builtup land. Karachi experiences semi-arid climate thus availability of vegetation and water is quite dynamic. Soil moisture can be predicted by density of vegetation cover. Growth of Karachi in terms of population is very high so as high consumption of food, which is grown in the nearby pockets of Malir and Gadap valley. In Karachi Hydrometeorological hazard (Drought) is common hence, monitoring and mapping of Land resources is essential. This Study assesses the role of Geoinformatics techniques for monitoring spatio-periodic variation of surface vegetation in Karachi. Four satellite imagries of Landsat-7 TM were selected to perform various process. Through NDVI spatio-Temporal and seasonal distribution of vegetation dynamics were observed and tabulated for each Union council of Karachi using software ArcMap 10.1. Maps developed for the quick and comparative understanding. Use of remote sensing and GIS technology for the monitoring and evaluation of substantial spatio-temporal variations of land resources such as vegetation cover is ideal. Therefore, this study would be beneficial for environmentalist and planners.
... This class from USDA-ERS and our modeled grassland and shrubland data both show a general decline from 1945 to present, although the rate of decline is substantially greater in the Lubowski, Vesterby, Bucholtz, Baez, and Roberts, (2006) data. The USDA-ERS data do not depict the CRP-influenced rise in grassland/shrubland that is shown in the Trends data and these modeled results, yet most studies do indicate a decline in cropland and resultant increase in grassland after implementation of CRP (Coppedge, Engle, Fuhlendorf, Masters, & Gregory, 2001;Egbert et al., 2002;Johnson & Schwartz, 1993). ...
The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes. Assessment of model results showed good agreement with trends and spatial patterns in historical data sources such as the Census of Agriculture and historical housing density data, although comparison with historical data is complicated by definitional and methodological differences. The completion of this dataset allows researchers to assess historical LULC impacts on a range of ecological processes.
... This is the case of pastures located in the alpine areas, affected by various factors that led to their fragmentation. The relatively low number of studies on pasture fragmentation (Coppedge et al. 2002;Egbert et al. 2002;Baldi et al. 2006) can be due both to the inexistence of a long history of land cover conversion of these systems and to the traditional lack of acknowledgement of the preserving value of grasslands (Risser et al. 1981;Joern and Keeler 1995). This leads to the need of development of appropriate tools for monitoring and assessing these landscape changes that can support their protection and the improvement of economic and heritage values (Pôças et al. 2011). ...
Protected areas of Romania have enjoyed particular importance after 1989, but, at the same time, they were subject to different anthropogenic and natural pressures which resulted in the occurrence of land cover changes. These changes have generally led to landscape degradation inside and at the borders of the protected areas. In this article, 12 landscape metrics were used in order to quantify landscape pattern and assess land cover changes in two protected areas, Piatra Craiului National Park (PCNP) and Bucegi Natural Park (BNP). The landscape metrics were obtained from land cover maps derived from Landsat Thematic Mapper (TM) and Landsat Enhanced Thematic Mapper Plus (ETM+) images from 1987, 1993, 2000, 2009 and 2010. Three land cover classes were analysed in PCNP and five land cover map classes in BNP. The results show a landscape fragmentation trend for both parks, affecting different types of land covers. Between 1987 and 2010, in PCNP fragmentation was, in principle, the result not only of anthropogenic activities such as forest cuttings and illegal logging but also of natural causes. In BNP, between 1987 and 2009, the fragmentation affected the pasture which resulted in the occurrence of bare land and rocky areas because of the erosion on the Bucegi Plateau.
... Accurate assessment of the current status of the vegetation cover is critical for initiating vegetation protection and restoration programs. (Egbert et al., 2002;He et al., 2005). Forest vegetation is particularly sensitive to climate change because the long life-span of trees does not allow rapid adaptation. ...
... Unsupervised methods, especially ISODATA, continue to be a popular choice for analysts without extensive a priori field knowledge (e.g., for classifying historical or time-series data (Lucas, et al., 2000;Wang, et al., 2002)), or for those wanting to avoid introduced bias in classification analysis. As with the supervised methods described above, unsupervised applications range broadly in context and scale; unsupervised methods have been successful in mapping vegetation using AVHRR, TM or ETM imagery in several studies (Egbert, et al., 2002;Lucas, et al., 2000;Lunetta, et al., 2002;Xiao, et al., 2002). ...
The sudden oak death (SOD) epidemic in California has resulted in hundreds of thousands of dead trees in the complex of oak (Quercus) and tanoak (Lithocarpus) woodland that exist in patches along the California coast. Monitoring SOD occurrence and spread is an on-going necessity in the state. Remote sensing methods have proved to be successful in mapping and monitoring forest health and distribution when a sufficiently small ground resolution is used. Supervised, unsupervised, and “hybrid” classification methods were evaluated for their accuracy in discriminating dead and dying tree crowns from bare areas and the surrounding forest mosaic utilizing 1-m ADAR imagery covering both tanoak/redwood forest and mixed hardwood stands. In both study areas the hybrid classifier significantly outperformed the other methods, producing low omission and commission errors among information classes. The hybrid method was then further refined by varying three parameters of the algorithm (iteration number, homogeneity threshold, and number of classes) and accuracy was assessed. The results demonstrate that while the hybrid method outperformed the other classifiers, the parameters that yielded highest accuracy for the algorithm differed between the two study areas. The use of a randomly selected subsample of training pixels was compared to the use of polygonal training areas, and we found that polygonal training data provided better classification accuracies in both cases.
... Accurate assessment of the current status of the vegetation cover is critical for initiating vegetation protection and restoration programs. (Egbert et al., 2002;He et al., 2005). Forest vegetation is particularly sensitive to climate change because the long life-span of trees does not allow rapid adaptation. ...
... Accurate assessment of the current status of the vegetation cover is critical for initiating vegetation protection and restoration programs. (Egbert et al., 2002;He et al., 2005). Forest vegetation is particularly sensitive to climate change because the long life-span of trees does not allow rapid adaptation. ...
A seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by Champion and Seth in 1968. We characterized and mapped further the vegetation type distribution in the country in terms of occurrence and distribution, area occupancy, percentage of protected area (PA) covered by each vegetation type, range of elevation, mean annual temperature and precipitation over the past 100 years. A remote sensing-amenable hierarchical classification scheme that accommodates natural and semi-natural systems was conceptualized, and the natural vegetation was classified into forests, scrub/shrub lands and grasslands on the basis of extent of vegetation cover. We discuss the distribution and potential utility of the vegetation type map in a broad range of ecological, climatic and conservation applications from global, national and local perspectives. We used 15,565 ground control points to assess the accuracy of products available globally (i.e., GlobCover, Holdridge’s life zone map and potential natural vegetation (PNV) maps). Hence we recommend that the map prepared herein be used widely. This vegetation type map is the most comprehensive one developed for India so far. It was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil. The digital map is now available through a web portal (http://bis.iirs.gov.in).
... It is also useful in planning protected areas and developing forest corridors. And accurate assessment of the current status of the vegetation cover is critical for initiating vegetation protection and restoration programs (Egbert et al., 2002;He et al., 2005). Forest vegetation is particularly sensitive to climate change because the long life-span of trees does not allow rapid adaptation. ...
... Accurate assessment of the current status of the vegetation cover is critical for initiating vegetation protection and restoration programs. (Egbert et al., 2002;He et al., 2005). Forest vegetation is particularly sensitive to climate change because the long life-span of trees does not allow rapid adaptation. ...
A seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by Champion and Seth in 1968. We characterized and mapped further the vegetation type distribution in the country in terms of occurrence and distribution, area occupancy, percentage of protected area (PA) covered by each vegetation type, range of elevation, mean annual temperature and precipitation over the past 100 years. A remote sensing-amenable hierarchical classification scheme that accommodates natural and semi-natural systems was conceptualized, and the natural vegetation was classified into forests, scrub/shrub lands and grasslands on the basis of extent of vegetation cover. We discuss the distribution and potential utility of the vegetation type map in a broad range of ecological, climatic and conservation applications from global, national and local perspectives. We used 15,565 ground control points to assess the accuracy of products available globally (i.e., GlobCover, Holdridge’s life zone map and potential natural vegetation (PNV) maps). Hence we recommend that the map prepared herein be used widely. This vegetation type map is the most comprehensive one developed for India so far. It was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil. The digital map is now available through a web portal (http://bis.iirs.gov.in).
... It is also useful in planning protected areas and developing forest corridors. And accurate assessment of the current status of the vegetation cover is critical for initiating vegetation protection and restoration programs (Egbert et al., 2002;He et al., 2005). Forest vegetation is particularly sensitive to climate change because the long life-span of trees does not allow rapid adaptation. ...
A seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by Champion and Seth in 1968. We characterized and mapped further the vegetation type distribution in the country in terms of occurrence and distribution, area occupancy, percentage of protected area (PA) covered by each vegetation type, range of elevation, mean annual temperature and precipitation over the past 100 years. A remote sensing-amenable hierarchical classification scheme that accommodates natural and semi-natural systems was conceptualized, and the natural vegetation was classified into forests, scrub/shrub lands and grasslands on the basis of extent of vegetation cover. We discuss the distribution and potential utility of the vegetation type map in a broad range of ecological, climatic and conservation applications from global, national and local perspectives. We used 15,565 ground control points to assess the accuracy of products available globally (i.e., GlobCover, Holdridge’s life zone map and potential natural vegetation (PNV) maps). Hence we recommend that the map prepared herein be used widely. This vegetation type map is the most comprehensive one developed for India so far. It was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil. The digital map is now available through a web portal (http://bis.iirs.gov.in).
... Accurate assessment of the current status of the vegetation cover is critical for initiating vegetation protection and restoration programs. (Egbert et al., 2002;He et al., 2005). Forest vegetation is particularly sensitive to climate change because the long life-span of trees does not allow rapid adaptation. ...
... As a consequence of increased exposure of land through removal of natural vegetation cover, the proportion of land prone to soil erosion increased. Therefore, it is critical to obtain current states of vegetation cover as a basis for initiating vegetation protection and restoration programmes (Egbert et al. 2002;He et al. 2005;Xie et al. 2008). In this respect, remote sensing technology offers a practical and economical means to study vegetation cover changes, especially over large areas (Langley et al. 2001;Nordberg and Evertson 2003;Sulieman 2010). ...
The pastoral resources in eastern Sudan are changing under the combined impact of increasing anthropogenic activities such as clearance of natural vegetation and the effect of state policies that favour crop farming against pastoralism. Remotely sensed data are used to detect spatial and temporal changes from 1979 to 2009 in the land use/land cover (LULC) across three study sites. Areas of natural vegetation have been reduced from 26.1% in 1979 to 12.6% in 1999 and further to 9.4% in 2007. The majority of this reduction went into agricultural land. Local knowledge of pastoralists on their perceived changes in plant species is obtained. Major LULC trends are progressive degradation and loss of grazing areas, loss of biodiversity and depletion of other ecological support provided by natural vegetation. Declining rainfall, land clearance due to agricultural expansion, overgrazing and herbicide applications by crop farmers are identified as underlying forces changing plant species in the region. The study revealed that pastoralists have considerable knowledge and experience in dealing with degradation and climate variability. However, pastoralists are marginalized in decisions concerning expansion of large-scale agriculture at the expense of pasture land. Their lack of education and other basic services restricts the pastoralists' potential to adapt to the new situation.
... year Landsat TM imagery is discussed in [8] and [9]. An unsupervised classification was performed first to create crop and grass maps. ...
... Program participants withdraw erodible land from production and receive annual payments for maintaining permanent vegetative cover. The CRP program has resulted in the conversion of previously cultivated agricultural land to perennial grassland habitat (Ribaudo et al. 2001;Egbert et al. 2002;Lovell and Sullivan 2006) with related environmental benefits including decreased soil erosion, improved water quality, and enhanced wildlife habitat (McCoy et al. 1999;Weber et al. 2002;Lovell and Sullivan 2006). However, in areas of the Midwest with extensive rowcrop production, linear grassland habitats (Fig. 1), such as roadsides, field borders, fencerows, and conservation buffers (e.g., filter strips, grassed waterways), constitute a significant amount of the grassland habitat available to wildlife (Warner 1994). ...
In regions of the United States that are predominately devoted to agricultural production, most grassland habitat remains as linear strips, including areas along roads and within conservation buffer strips. While land management agencies in the United States promote conservation buffer strips as beneficial to wildlife populations, we know little about snake use of these habitats, especially in relation to multiscale factors. Our poor understanding of these relationships hinders effective design and management of these habitats to conserve biodiversity. We evaluated the influence of buffer design, management, and surrounding landscape characteristics on snake occurrence in grassed waterways in southeastern Iowa. We documented snakes at nearly 80% of the grassed waterways and captured 119 individual snakes of five species; one of which, the Smooth Green Snake (Lioclonorophis vernalis), is listed as a species of conservation concern in Iowa. We used a multiple logistic regression and an information theoretic approach to determine the most parsimonious local and landscape variable models that best explained snake species occurrence. The "local" waterway design variable, width, occurred in the best local variable models for three of the five species and was positively associated with snake presence for all three species. Landscape variable models also helped explain snake presence; individual species responded differently to the various landscape metrics. Insights gained from this study may provide opportunities for improving the conservation value of buffer strips to snakes in these fragmented landscapes.
... year Land sat TM imagery is discussed in [23] [24]. An unsupervised classification was performed first to create crop and grass maps. ...
... Most of these are covered by the computer program FRAGSTATS (McGarigal & Marks, 1995). Since the emergence of FRAGTATS in 1993, the measures and methods incorporated in this software have been very widely used in characterizing patterns (Li et al., 2001;Corry, 2004), detecting land use changes (Egbert et al., 2002;Southworth et al., 2004) and predicting ecological processes (Bender et al., 2003;Coulson et al., 2005;Fearer et al., 2007). ...
... Minimum mapping unit was 0.1 ha. A review of literature concerning the application of landscape metrics (Arnot et al., 2004;Botequilha Leitȃo and Ahern, 2002;Colson et al., 2011;Egbert et al., 2002;Hargis et al., 1998;Ritters et al., 1995) was performed to select a set of indices reflecting the structure of different types of ecosystems in the most comprehensive manner. Next, in order to reduce the number of indices to a manageable level, the smallest set of indices was selected, still adequately reflecting major landscape properties, but avoiding doubling-up. ...
... Several studies have incorporated satellite-image analysis for the monitoring of reclaimed lands (Rathore and Wright, 1993; Schmidt and Glaesser, 1998; Bricklemyer et al., 2003). Studies have reported high classification accuracy in the detection of CR vegetation (Price et al., 1997; Egbert et al., 1998; Egbert et al., 2002), and crop and fallow parcels (Xie et al., 2007) through image classification. Obtaining land use data is also essential in determining how much SOC might be sequestered through the increased adoption of these management practices throughout the region. ...
Terrestrial carbon sequestration, using land management adjustments to increase soil carbon levels within degraded lands, has been advocated as a practical and immediate approach for carbon mitigation. Carbon sequestration and credit programs have recently been established within north central Montana; carbon storage potential within this region, however, had not been assessed previously. This study consisted of a two-part approach. A combination of satellite-image analyses and field survey was first used to obtain regional land use data. Literature-based carbon rate data were then applied to the land use data to generate a regional estimate of carbon sequestration potential given specific land use adjustments. An object-oriented approach was used in conjunction with the Random Forest algorithm to classify agricultural practices set forth in carbon contract agreements associated with the Chicago Climate Exchange and included tillage type, vegetation intensity, and conservation reserve practices. Random Forest is an advanced classification algorithm that avoids data over-fitting and incorporates an internal accuracy assessment. An object-oriented approach allowed for per-field classifications and the incorporation of contextual elements such as shape, texture, area, and neighborhood relationships in addition to spectral features. Landsat satellite imagery was chosen for its continuous coverage, cost effectiveness, and image accessibility. Results from this study found that in most cases satellite image analysis allowed for an effective way to classify land use types within the region. Results from this study estimated that approximately 77,049 t organic carbon yr -1 might be sequestered through the universal adoption of no-till management and the maintaining of land currently under grassland-based conservation reserve. Land use analyses via satellite monitoring and carbon sequestration efforts illustrated within this study can easily be applied to many types of situations involving degraded lands, included mined lands, and need not be restricted to an agricultural setting.
... While general information about areal land use is abundant (Cook, 2002;Skanes and Bunce, 1997), specific studies about linear landscape structures are rare (see Kantelhardt et al., 2003). Many of these studies are based on satellite data (Egbert et al., 2002;Griffith et al., 2000;Hladnik, 2004;Lausch and Menz, 1999), in which linear landscape structures such as hedges and ditches are rarely detected. In order to derive such occurrence information in high (Hirt, 2003). ...
The structure of a landscape is highly relevant for research and planning (such as fulfilling the requirements of the Water Framework Directive – WFD – and for implementation of comprehensive catchment planning). There is a high potential for restoration of linear landscape elements in most European landscapes. By implementing the WFD in Germany, the restoration of linear landscape elements could be a valuable measure, for example to reduce nutrient input into rivers.Despite this importance of landscape structures for water and nutrients fluxes, biodiversity and the appearance of a landscape, specific studies of the linear elements are rare for larger catchment areas. Existing studies are limited because they either use remote sensing data, which does not adequately differentiate all types of linear landscape elements, or they focus only on a specific type of linear element. To address these limitations, we developed a framework allowing comprehensive quantification of linear landscape elements for catchment areas, using publicly available biotope type data. We analysed the dependence of landscape structures on natural regions and regional soil characteristics. Three data sets (differing in biotopes, soil parameters and natural regions) were generated for the catchment area of the middle Mulde River (2700km2) in Germany, using overlay processes in geographic information systems (GIS), followed by statistical evaluation. The linear landscape components of the total catchment area are divided into roads (55%), flowing water (21%), tree rows (14%), avenues (5%), and hedges (2%). The occurrence of these landscape components varies regionally among natural units and different soil regions. For example, the mixed deciduous stands (3.5m/ha) are far more frequent in foothills (6m/ha) than in hill country (0.9m/ha). In contrast, fruit trees are more frequent in hill country (5.2m/ha) than in the cooler foothills (0.5m/ha). Some 70% of avenues, and 40% of tree rows, are discontinuous; in contrast, only 20% of hedges are discontinuous.Using our innovative framework, comprehensive information about landscape elements can now be obtained for regional applications. This approach can be applied to other regions and is highly relevant for landscape planning, erosion control, protection of waters and preservation of biotopes and species.
... Studies in the Prairie Pothole region of North Dakota, South Dakota, and Northeastern Montana found that the CRP land is vital in maintaining a vibrant waterfowl population (Kantrud 1993;Reynolds et al. 2001;Niemuth et al. 2007). CRP lands can also lead to increased acreage of viable habitat and help to connect previously disparate habitat patches, thus aiding species with large habitat range requirements (Egbert et al. 2002). ...
Field margin vegetation (FMV) lies between an agricultural field and another land use land cover type, which is an interface of immense socioecological significance. This research has made an attempt to develop a three-step framework that distinguish FMV from other features or vegetation, which was found to be almost impossible using available classifiers. This research is first of its kind and preliminary effort to develop an accurate method to map and quantify vegetation in field margins in a rural-urban interface of the northern transect of Bengaluru using high resolution (0.3 m × 0.3 m) satellite imagery (WorldView3). The conditions for delineation of FMV are set based on neighbourhood features using Julia programming language for three methods of image classification and analysis. Third algorithm has been found to perform better (with 86% accuracy) where reclassification of the vegetation to delineate FMV from other vegetation was done with an input of classified image. Further accuracy assessment of three algorithms was done using manually digitized FMV and ground verification of sampled plots. Based on the results and their accuracy, it is suggestive that the method is scalable for identifying, assessing and mapping FMVs for sustainable socioecological development, and future research should be adopted for enhancing efficiency and accuracy of the method.
Classifying and mapping vegetation is an important technical task for managing natural resources; the primary objective of the vegetation-mapping inventory is to produce high quality, standardized maps and associated data sets of vegetation. Satellite remote sensing has proven to be effective technology for mapping forest vegetation at the landscape to regional scale. In the remote sensing technique, vegetation density can be directly indicated by vegetation indices. Although there are several vegetation indices, the most widely used is the Normalized Difference Vegetation Index (NDVI), formulated by transforming raw satellite data into NDVI values, ranging from -1 to 1. NDVI enables the creation of images and other products that provide a rough measure of vegetation type, amount, and condition on land surfaces. The results show that medium to high density vegetation is mostly found in the central part of Al-Baha region separating the highlands and lowlands. The relationship study between NDVI and vegetation cover percentage in this study depicts an NDVI value of only 0.20–1.00, which indicates that vegetation covers over 60% of Al-Baha. This is probably because vegetation here may not only comprise trees but also other plant forms such as herbs and shrubs. However, only 862.5 km2 (7.7%) of Al-Baha is covered with medium-high density vegetation, found mainly at the 6 –15km width horizontal central belt (in the Al-Mandaq, Al-Baha, and south Baljurashi districts) along a high, foggy mountainous plateau. Conversely, about 65% of Al-Baha region has very low to no vegetation density; vegetation is found extensively in the Tihama low plain towards the Red Sea and in the north-eastern desert plain. This study has provided a comprehensive report on vegetation mapping in the Al-Baha region.
The mechanism of recognizing the transformations in the form of an object or phenomenon by perceiving it at different times is termed as change detection. For efficient management and utilization of the earth's natural resources, it is obligatory to establish a strong empathetic interactive relationship between human beings and natural environment, which requires precise and timely information of the change occurring on the Earth surface. Vegetation cover is one of the most dynamic phenomenon's occurring on the surface of the earth, and detection of its change across a time period proves to be very critical for various ecosystem services, such as fortification of the land surface, the modification or enrichment of the native weather conditions, the conservation of perilous ecosystem processes, and the maintenance of biodiversity. This paper presents an overview of the change detection over a period of 30 years from 1988 to 2018 change matrix and evaluating the net loss and gain of different land use and land cover.
Saudi Arabia is located within an arid to semi-arid region, however, it is a biological diverse area, because species have adapted to the adverse ecological circumstances. One of the most important habitats in Saudi Arabia is the Mahazat Alsayd natural reserve. Understanding changes in vegetation cover over time is important for studying the habitats present in the reserve, and for analyzing the availability of animal fodder, as well as the extent of vegetation regeneration. Using remote sensing data and field observations, we detected that the vegetation coverage of Mahazat Alsayd decreased by 80% from 1995 to 2015. Multiple factors are currently affecting the structure of the plant and animal communities within the reserve. Such factors include ecological changes and human activities. These factors might lead to the extinction of some plant and/or animal species in the near future, either directly or indirectly. Thus, a comprehensive management plan must be implemented in the reserve as soon as possible to maintain and recover vegetation to provide sufficient animal feed, facilitating the sustainable conservation of animals and plants within the reserve. The vegetation cover assessment presented here provides an important source of information for conservation planning.
Mapping and monitoring rainforest vegetation through remotely sensed images involve various considerations, processes and techniques. Satellite imageries are known for their differences in spectral, spatial, radioactive and temporal characteristics and thus are suitable for different mapping purposes. Achieving these purposes involves various considerations, processes and techniques. For rainforest vegetation assessment, it is important to identify discernible spectral characteristics of satellite imageries and therefore develop a preliminary vegetation classification for mapping vegetation cover. It is based on these that this paper demonstrated the potential of NigeriaSat-1 in assessing rainforest vegetation of the Southwestern Nigeria using Landsat ETM as a means of validation. In this study, the spectral classes of the NigeriaSat-1 and Landsat ETM were translated into the land use land cover classes in the image processing. The findings revealed that of the total area of about 9,700km2, NigeriaSat-1 and Landsat ETM captured 68.0% and 56.4% respectively for rainforest vegetation. Using the accuracy values generated from the two images, the results of Landsat ETM was subsequently used to establish the potentials of NigeriaSat-1 in the assessment of rainforest cover. For vegetation representation in this study, the NigeriaSat-1 data produced better and consistent producer and user’s accuracies of 98.41% and 96.88% respectively as compared to the Landsat ETM image with producer and user’s accuracies of 80.28% and 98.28% respectively.
Habitat fragmentation is one of the main threats to ecosystems integrity. In this study we assessed the influence of forest fragmentation on vegetation structure of populations of tree specie Legrandia concinna in south-central Chile. Occupancy pattern of Legrandia populations in remaining fragments of native forests was described, and relationship between landscape indices and vegetation structure variables were evaluated. Landscape indices, such as area, proximity mean index, shape and edge distance to fragment were applied to forest cover maps generated from a Landsat ETM+ satellite scene for the year 2001. Results showed high predominance of reduced size fragments, high isolation levels and regulars shapes of the fragments. Occupancy pattern suggests that Legrandia populations are found mainly in small and more isolated fragments. No significant difference was found between fragment distribution with and without presence of Legrandia related to size and isolation. However, we found that size, isolation and distance to fragment edge are significantly related to the presence of this specie. As conservation measures for this specie, we propose to include populations with high disappearance risk in protected areas, promote ex situ conservation and set up a monitoring program. This study sets a precedent related by linking landscape scale information obtained from satellite imagery and vegetation structure information measured in the field with conservation status of threatened populations. This innovative method allows monitoring changes over time to assess effectiveness of conservation strategies for these populations.
Conservation biologists are devoting an increasing amount of energy to debating whether land sparing (high-yielding agriculture on a small land footprint) or land sharing (low-yielding, wildlife-friendly agriculture on a larger land footprint) will promote better outcomes for local and global biodiversity. In turn, concerns are mounting about how to feed the world, given increasing demands for food. In this review, I evaluate the land-sparing/land-sharing framework-does the framework stimulate research and policy that can reconcile agricultural land use with biodiversity conservation, or is a revised framing needed? I review (1) the ecological evidence in favor of sparing versus sharing; (2) the evidence from land-use change studies that assesses whether a relationship exists between agricultural intensification and land sparing; and (3) how that relationship may be affected by socioeconomic and political factors. To address the trade-off between biodiversity conservation and food production, I then ask which forms of agricultural intensification can best feed the world now and in the future. On the basis of my review, I suggest that the dichotomy of the land-sparing/land-sharing framework limits the realm of future possibilities to two, largely undesirable, options for conservation. Both large, protected regions and favorable surrounding matrices are needed to promote biodiversity conservation; they work synergistically and are not mutually exclusive. A "both-and" framing of large protected areas surrounded by a wildlife-friendly matrix suggests different research priorities from the "either-or" framing of sparing versus sharing. Furthermore, wildlife-friendly farming methods such as agroecology may be best adapted to provide food for the world's hungry people.
© 2015 New York Academy of Sciences.
This study develops an integrated economic, hydrologic, and ecological modelling framework to examine cost-effective targeting of riparian buffers to achieve water quality and wildlife habitat benefits. The framework is empirically applied to the Canagagigue Creek watershed in Ontario, Canada to compare the economic costs for establishing riparian buffers under three alternative environmental and ecological constraints: sediment abatement only, habitat improvement only, and riparian buffer acreage only. The results show that riparian buffers targeted for achieving sediment abatement goal are not effective in improving habitat quality. Similarly, riparian buffers identified through habitat improvement goal achieve less sediment abatement as compared to those targeted in the sediment abatement scenario. The trade-offs suggest that agricultural stewardship programmes with joint water quality and habitat improvement goals may need to allocate funds independently for targeting two pools of riparian buffers: for improving water quality only or for improving habitat only.
The aim of this study was to predict landscape structural metrics using the features extracted from the ASTER multispectral satellite imagery with 15 m spatial resolution. The landscape structural metrics were calculated on the basis of forest map polygons generated from 1:15000 scaled aerial photos by photo-interpretation technique. The landscape metrics and corresponding image features that are texture parameters and segmentation polygons were determined for four different landscape extents. A stepwise multiple linear regression analysis was carried out to identify the most significant image-derived predictors of landscape metrics for each extent. The regression models established for the landscape metrics including the Number of Patches (NUMP), Edge Density (ED), Shannon's Diversity Index (SDI) and Patch Richness (PR) performed moderately with adjusted R values of 0.50 and 0.53 (P
Changes in landscape structure caused by the introduction of the U.S. Conservation Reserve Program (CRP) were examined. Using imagery-derived land cover maps for the pre- and post-CRP enrollment periods, we identified regions of cropland that had been converted to CRP in a six-county area in southwestern Kansas. The major impact of CRP in the study area has been the reversal of an overall trend of grassland fragmentation. The introduction of CRP has substantially modified the spatial structure of the southwest Kansas landscape, generally with important positive implications for wildlife habitat, by changing the count, size, shape, interior areas, and connectivity of grassland patches. The authors also concluded that CRP enrollments had a strong spatial association with the distribution of points of water diversion for irrigation.
Habitat fragmentation,has been,implicated,as a major,cause of population decline in grassland,birds. We tested the hypothesis,that a combination,of area and shape determines,the use,of grassland,patches,by breeding,birds. We compared,both,species richness and,individual species presence,in 45 wet meadow,grasslands in the floodplain of the central Platte River, Nebraska. Bird data were collected through the use of belt transects and,supplemented,by walking,and listening outside transects. Our data supported,our pri- mary hypothesis that perimeter‐area ratio, which reflects both the area and shape of a patch, is the strongest predictor of both individual species presence,and overall species richness. The probability of occurrence for all six common species (Grasshopper Sparrows, Bobo- links, Upland Sandpipers, Western Meadowlarks, Dickcissels, and Red-winged Blackbirds) was,significantly,inversely correlated with perimeter‐area,ratio. The probability of occur- rence of Grasshopper Sparrows, Bobolinks, Upland Sandpipers, and Western Meadowlarks was,also correlated with area. We conclude,that species richness is maximized,when,patches are large (.50 ha) and shaped so that they provide abundant interior areas, free from the impacts,of edges. Key words: birds, grassland; habitat fragmentation; landscape ecology; Nebraska; patch area;
The influence of area and vegetation structure on breeding bird communities associated with 24 Illinois grassland fragments (0.5-600 ha) was studied between 1987 and 1989 to document the effects of habitat fragmentation in a severely fragmented midwestern landscape. Fragment area strongly influenced bird communities within grasslands and accounted for a high percentage of the variation in mean breeding bird species richness among fragments (R^2 = 0.84). Breeding bird species richness patterns within 4.5-ha subsections of these grasslands also significantly increased with fragment size. Eight of the 15 (53%) most common bird species had distributions among fragments that were significantly influenced by habitat area, whereas six species (40%) had distributions within fragments that were significantly influenced by vegetation structure only. The Dickcissel (Spiza americana) was the only species with a distribution within fragments that was not significantly associated with either habitat area or vegetation structure. Four groups of birds were identified by an analysis of habitat area and vegetation structure preferences of individual species: area-sensitive species (5 species), edge species (3), vegetation-restricted species (6), and the Dickcissel. Estimates of minimal area requirements for the five area-sensitive species ranged from 5 to 55 ha. Discriminant analyses of habitat suitability within fragments suggests that the absence of area-sensitive grassland bird species form some small fragments may result, in part, from limited habitat availability. All five area-sensitive species, however, also regularly avoided structurally suitable habitat on small grassland fragments. As a result of the considerable extent to which native and, more recently, agricultural grasslands have declined in the Midwest, habitat fragmentation is likely to have caused midwestern grassland bird declines, especially for area-sensitive species.
We evaluated the conditions under which patch size effects are important determinants of local population density for animals living in patchy landscapes. This information was used to predict when patch size effects will be expected to occur following habitat loss and fragmentation. Using meta-analysis, we quantitatively reviewed the results of 25 published studies that tested for a relationship between patch size and population density. Patch size effects were strong for edge and interior species (negative and positive patch size effects, respectively), but negligible for generalist species that use both edge and interior habitat. We found significant differences in mean patch size effects between migratory and residential species, between herbivores and carnivores, and among taxonomic groups. We found no evidence that patch size effects were related to landscape characteristics such as the proportion of landscape covered by habitat, median patch size, or the scale at which a study was conducted. However, species in the Western Hemisphere tended to have larger absolute effect sizes, and eastern species tended to be more variable in their response. For landscapes undergoing habitat loss and fragmentation, our results predict the following: (1) among generalist species that use both the edge and the interior of a habitat patch, the decline in population size associated with habitat destruction should be accounted for by pure habitat loss alone; (2) for interior species, the decline in population size associated with habitat fragmentation per se will be greater than that predicted from pure habitat loss alone; (3) for edge species, the decline in population size will be less than that predicted by pure habitat loss alone; (4) these relative effects will not be influenced by the extent of habitat loss, but they will be affected by the pattern of habitat when large or small patches are preferentially removed; and (5) as loss and fragmentation increase within a landscape, migratory species will generally suffer less of a decline in population size than resident species.
The effects of landscape patchiness on the diversity of birds of the Georgia Piedmont were investigated during 1993. Birds were sampled along line transects within relatively large (10–13.25 ha) and small (less than 3.25 ha) forest patches located within nonforest agricultural landscapes. Patterns of habitat use in these patches were compared to those in contiguous forest patches larger than 13.25 ha. Analysis of variance revealed significant differences in diversity between large and small woodlots and between contiguous and fragmented landscapes, especially in terms of the numbers of edge and interior species and winter-resident, summer-resident, and year-round birds observed.
Remotely sensed data for Southeastern United States (Standard Federal Region 4) are used to examine the scale problems involved
in reporting landscape pattern for a large, heterogeneous region. Frequency distributions of landscape indices illustrate
problems associated with the grain or resolution of the data. Grain should be 2 to 5 times smaller than the spatial features
of interest. The analyses also reveal that the indices are sensitive to the calculation scale,i.e., the unit area or extent over which the index is computed. This “sample area” must be 2 to 5 times larger than landscape
patches to avoid bias in calculating the indices.
The Conservation Reserve Program (CRP) began in 1986 with the primary purpose of reducing soil erosion. It also was intended to help the development of sutainable agriculture and associated environmental harmony. However, in effectiveness has been questioned because of the large costs and extensive staff required to conduct the program. The objectives of our study were to test procedures for integrating remote sensing and geographic information sytems (GIS) techniques to evaluate the present CRP in terms of its main goal, and to give recommendations for the future of the program in Finney County, Kansas. Three seasonal Landsat Thematic Mapper (TM) images were used to derive tha land-uselland cover (LULC) map. This information was incorporated with spatial dimensions of soil surface horizon thickness, surface horizon texture, soil family, soil subgroup, and soil erodibility index (EI), all of which were extracted or calculated from the Natural Resources, Consrevation Sevice (NRCS) soil survey geographic (SSURGO) data base. With GIS techniques, calculation of EI was more efficient and the value was more accurate than that calculated by hand. We found the average EI o the county to be 20, with the highest EI of 77 in the southwest portion of the study area. CRP land had higher soil fertility and a lower EI than land currently used for farming; therefore, the CRP for this county did not necessarily include the lands most susceptible to erosion. We suggest continuing the CRP program in Finney County, because the soils are generally at serious risk of erosion. We also suggest modifying the eligibility rules of the program inorder to target the most environmentally sensitive lands.
A new vegetation map of Kansas has been prepared, accompanied by a commentary. In the latter, some historical remarks on mapping the vegetation of Kansas are followed by a presentation of some basic aspects of vegetation. Comments on Kansas vegetation units, a discussion of vegetation boundaries, and the description of the vegetation types help the reader of the new vegetation map to appreciate its content. In an elaboration of the map legend, each vegetation type is described threefold: its physiognomy and structure, the dominant species (in English and Latin), and other characteristic components (Latin only). A brief comment on location and habitat and a photograph of each vegetation type complete the legend elaboration. See full-text article at JSTOR
Given the optimal situation, error matrices should be provided whenever accuracy is assessed so that the users can compute and interpret these values for themselves.-from Authors
Habitat fragmentation from intensified farming has concentrated nesting waterfowl and their predators in the remaining, relatively small untitled habitats of the prairie pothole region in the USA. The areas of land that have been enrolled in the Conservation Reserve Program (CPR) in this area could help disperse these concentrations and reduce losses to predators. During 1989-1991, waterfowl nest success on CRP fields in areas of high wetland density in the prairie pothole region of Minnesota and North Dakota was 23.1% compared to 8.2% on similar covers on federal waterfowl production areas. CRP fields thus provided more secure nesting cover for upland-nesting ducks than waterfowl production areas, but nest success and use of the fields by ducks varied greatly. -from Author
The objective of this study was to develop a repeatable procedure for modeling land use and land cover (LULC) within one of the most agriculturally developed and economically significant areas of the High Plains region: Finney County in southwestern Kansas. The technique involved the use of Landsat Thematic Mapper (TM) images for three seasons for each of three years (1987, 1989, and 1992). Through a series of image preprocessing and automated classification procedures we were able to discriminate between grassland and croplands more than 95% of the time (previous to this study, less than 70% classification accuracy was usual). As we refined the approach further, we were able to identify crop types: wheat, grain sorghum (milo), corn, and alfalfa, and fallowed lands with greater than 80% accuracy for all five classes, with most crop types mapped at more than 90% accuracy. We also developed a technique that correctly mapped U.S. Department of Agriculture (USDA) Conservation Reserve Program (CRP) lands more than 90% of the time. An analysis of our Finney County crop-type maps for the three study years showed little change in acreage of wheat, grain sorghum, corn, and alfalfa, but large increases in grassland, primarily agricultural lands that were converted to the CRP. Lands in fallow declined by about 36,400 ha (90,000 acres) between 1987 and 1992.
We measured the activity of mammalian predators, numbers of singing male songbirds, and predation rates on nests of songbirds (152 natural, open-cup nests and 380 artificial nests) on 38 250 m transects located along various types of forest-field edges in a wildlife management area in east-central Illinois. We then related these variables to each other and to measures of the vegetative structure of our transects that we anticipated might influence predator activity or predation rates on nests of birds characteristic of edge and shrubland habitats. Mammalian predators, particularly raccoons (Procyon lotor), were abundant in the wildlife area and present on all transects surveyed. We did not find significant relationships among the variables we measured. Rather, rates of nest predation were consistently high (>70%) and generally evenly distributed around our study site. Medium-sized, generalist mammalian predators in the midwestern United States reach their highest population densities in fragmented landscapes with abundant edge habitat, particularly agricultural edges. Areas of natural habitat in these landscapes dominated by agriculture may concentrate predators and act as ecological traps for nesting birds because they attract high densities of breeding birds that are subjected to high rates of nest predation.
This report describes a program, FRAGSTATS, developed to quantify landscape structure. Two separate versions of FRAGSTATS exist: one for vector images and one for raster images. In this report, each metric calculated by GRAGSTATS is described in terms of its ecological application and limitations. Example landscapes are included, and a discussion is provided of each metric as it relates to the sample landscapes. -from Authors
The CRP conservation reserve program has added more than three million acres of permanent grass cover to the Texas Southern High Plains, one of the most intensively cultivated regions in North America. The dominant species nesting in CRP cover types were grasshopper sparrow Ammodramus savannarum (1.5 nests/ac), Cassin's sparrow Aimophila casinii (0.7 nests/ac), red-winged blackbird Ageliaus phoeniceus (1.5 nests/ac), and western meadowlark Sturnella neglecta (0.5 nests/ac). Nest success was lower in 1989 than 1988 for grasshopper sparrow (30% vs. 48%), red winged blackbird (16% vs 28%), and western meadowlark (32% va. 71%), but increased in Cassin's sparrow (66% vs. 41%). Clutch size also decreased in 1989 vs. 1988 for grasshopper sparrow (3.7 vs. 4.7%), Cassin's sparrow (3.8 vs. 4.6) and red-winged blackbird (3.1 vs. 3.5), but there was no change (P>0.10) in western meadowlark. -from Authors
Error matrices or contingency tables were taken from the literature and then analyzed using three techniques. The first technique permitted direct comparison of corresponding cell values in different matrices by 'normalizing' each matrix through a process called 'iterative proportional fitting'. The second technique provided a method of testing for significant differences between error matrices which vary by only a single variable. The third allowed for multivariable comparisons between matrices to be made and is the most powerful of the techniques. It was concluded that these techniques could help researchers better evaluate variables or factors affecting land-cover classification accuracy.-Authors
Sustainability of our use of the environment, including sustainability of both the resource base and the economic system, has been of increasing interest in rural land use analysis. The U.S. Conservation Reserve Program (CRP) is part of a series of land and soil conservation measures dating back to the Dust Bowl era of the 1930's that have significant implications for preserving quality grassland resources. In order to assess the natural resource capability of CRP lands and make appropriate long term recommendations relative to rural land use management, this study incorporated remote sensing and GIS approaches to evaluate interrelationships among spatially co‐varying physical resource variables. Results indicate an inverse relationship between CRP lands and aquifer thickness, and a direct relationship between soil quality and physiography with CRP lands. In addition, findings support the use of CRP lands for grasslands in southwest Kansas as more conducive to longer term regional sustainability.
This is a critical time for evaluating the status and success of the U.S. Conservation Reserve Program (CRP), a program that has resulted in the conversion of millions of hectares of cropland to grassland, woodland, and other conservation uses. In order to evaluate the effects of CRP on soil erosion, wildlife habitat, water pollution, and groundwater recharge, however, it is essential to have detailed digital maps that accurately identify CRP lands. Remote sensing techniques offer a means for developing such a database in an economical and accurate way. Utilizing multi‐seasonal imagery in an unsupervised classification technique, highly accurate maps of cropland and grassland were produced for 1987 and 1992 for Finney County, Kansas. Post‐classification differencing identified regions of cropland that had changed to grassland between the two years, indicating land that had been converted to CRP. Comparison of the CRP map with ground truth sources produced an accuracy of approximately 88%. Digital maps of CRP thus derived can be incorporated effectively into decision support models for assessing how CRP lands influence environmental conditions.
We investigated the role of patch attributes and context on patch occupancy of the Lower Keys marsh rabbit (Sylvilagus palustris hefneri). The Lower Keys marsh rabbit is a federally endangered lagomorph endemic to the Lower Keys of Florida. The marsh rabbit occurs in subpopulations on patches of high marsh that interact to form a metapopulation. Between March 1991 and July 1993, all known patches of high marsh in the Lower Keys were surveyed for presence or absence of marsh rabbit pellets three times per year. Of the 59 habitat patches, 20 had pellets present during all of the surveys (occupied patches), 22 had pellets present during at least one survey (variable patches), and 17 never had any pellets present (empty). Ten variables were measured at each of the 59 patches; seven of these variables concerned attributes of the patch (food, cover, patch size), and three were patch context variables (distance of patch to other patches, distance of patch to other features). Two discriminant function analysis (DFA) were performed. The first DFA compared empty patches to occupied patches (both variably and consistently occupied). Patch isolation explained the most variation in patch occupancy followed by area. The second DFA compared the variably occupied sites with the consistently occupied sites, and patch attributes variables involving the type and height of vegetation were significant. Management efforts for the Lower Keys marsh rabbit should be aimed at both improving habitat quality and decreasing distance between patches.
This paper reviews the necessary considerations and available techniques for assessing the accuracy of remotely sensed data. Included in this review are the classification system, the sampling scheme, the sample size, spatial autocorrelation, and the assessment techniques. All analysis is based on the use of an error matrix or contingency table. Example matrices and results of the analysis are presented. Future trends including the need for assessment of other spatial data are also discussed.
This second edition continues to focus on digital image processing of satellite and aircraft derived remotely sensed data for Earth resource management applications. Following an introduction, chapter two describes new methods of remote sensing data acquisition alternatives such as the National Aerial Photography Program (NAPP), multispectral imaging using discrete detectors and scanning mirrors, and imaging spectrometry using linear and area arrays. Chapter three summarizes the state of the art digital image processing hardware and software configurations using mainframe, workstation, and personal computers, including an introduction to serial versus parallel computing. Chapter four provides information on initial statistics extraction. Chapter five introduces the concept of initial display alternatives and scientific visualization both in black and white and in colour. Chapter six contains detailed information on how to radiometrically correct for atmospheric attenuation in remote sensing data using relative image normalization and absolute radiometric correction techniques. Image enhancement is continued in chapter seven including new graphics and text to describe how linear and non-linear contrast enhancement are performed with an in-depth treatment of histogram visualization. Thematic information extration-image classification continued in chapter eight includes an overview of hard versus fuzzy logic. Digital change detection featured in chapter nine contains an outline of the general steps required to perform digital change detection of remotely sensed data. Finally, chapter ten includes a description of the major vector and raster data sets available as well as a discussion of the various GIS data analysis functions.
Thesis (Ph. D.)--University of Kansas, Geography, 2000. Includes bibliographical references.
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Wiens, J.A., 1989. The Ecology of Bird Communities. Cambridge University Press, Cambridge. Wildlife Legacy Partners, 1994. The Conservation Reserve Program: a Wildlife Conservation Legacy, Washington, DC, Wildlife Management Institute.
Buying more environmental protection with limited dollars. Proceedings, When Conservation Reserve Program Contracts Expire: The Policy Options
- R E Heimlich
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Habitat loss and population decline: a meta-analysis of the patch size effect Nongame bird nesting on CRP lands in the Texas southern high plains
- Kansas Lawrence S L Egbert
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Duck nest success on Conservation Reserve Program land in the prairie pothole region A new vegetation map of Kansas Soil erosion and sediment control. Proceedings, When Conservation Reserve Program Contracts Expire: The Policy Options
- H A Kantrud
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The Kansas land cover mapping project: regional scale land use/land cover mapping using Landsat thematic mapper data
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Identifying and understanding land use/land cover changes in Kansas
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Developing a land cover modeling protocol for the high plains using multi-seasonal thematic mapper imagery
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Does CRP spell quail? Quail Unlimited Magazine
- D Howell
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Soil erosion and sediment control. Proceedings, When Conservation Reserve Program Contracts Expire: The Policy Options
- G A Margheim