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ABSTRACT: A Simple Remote Sensing EvapoTranspiration (ET) model (Sim-ReSET) has been proposed but tested only using field measurements at a site with a semiarid climate. However, its performance of mapping ET only using satellite data keeps unknown. In this study, the Sim-ReSET model was further evaluated for ET estimation driven by only MODIS data products. The estimated ET rates were compared with ground-based observational data from a variety of ecosystems and climates across China. Results show that MODIS-based ET estimates are consistent with both the ET measurements from eddy covariance flux towers and the ET estimates from the Penman-Monteith method along with micrometeorological data. Evaporation fraction (EF) is indicative of land surface moisture. The derivative EF maps demonstrate that the proposed ET dataset obtained from the Sim-ReSET model and MODIS data is capable of capturing the spatiotemporal pattern of land surface moisture for different land covers with different climates.
Hydrological Sciences Journal/Journal des Sciences Hydrologiques 04/2013; 58(5). · 1.54 Impact Factor
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ABSTRACT: Evapotranspiration (ET) is the total amount of water lost by plant transpiration and soil evaporation. Since about 90% of precipitation received in semi-arid and sub-humid climates is lost to the atmosphere through evapotranspiration, accurate estimations of ET are of crucial need for climate studies, weather forecasts, hydrological surveys, ecological monitoring, and water resource management. This book reviews research on new developments in all areas of evapotranspiration application. It examines the evapotranspiration processes under different environmental and climatic conditions as well as the different methods for modeling and measurement of evapotranspiration at both local and regional scales.
02/2013; , ISBN: 978-1-62417-146-8
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ABSTRACT: The Medium Resolution Imaging Spectrometer (MERIS) sensor, with its good physical design, can provide excellent data for water colour monitoring. However, owing to the shortage of shortwave-infrared (SWIR) bands, the traditional near-infrared (NIR)–SWIR algorithm for atmospheric correction in inland turbid case II waters cannot be extended to the MERIS data directly, which limits its applications. In this study, we developed a modified NIR black pixel method for atmospheric correction of MERIS data in inland turbid case II waters. In the new method, two special NIR bands provided by MERIS data, an oxygen absorption band (O2 A-band, 761 nm) and a water vapour absorption band (vapour A-band, 900 nm), were introduced to keep the assumption of zero water-leaving reflectance valid according to the fact that both atmospheric transmittance and water-leaving reflectance are very small at these two bands. After addressing the aerosol wavelength dependence for the cases of single- and multiple-scattering conditions, we further validated the new method in two case lakes (Lake Dianchi in China and Lake Kasumigaura in Japan) by comparing the results with in situ measurements and other atmospheric correction algorithms, including Self-Contained Atmospheric Parameters Estimation for MERIS data (SCAPE-M) and the Basic ERS (European Remote Sensing Satellite) & ENVISAT (Environmental Satellite) (A)ATSR ((Advanced) Along-Track Scanning Radiometer) and MERIS (BEAM) processor. We found that the proposed method had acceptable accuracy in the bands within 560–754 nm (MERIS bands 5–10) (average absolute deviation (AAD) = 0.0081, average deviation (AD) = 0.0074), which are commonly used in the estimation models of chlorophyll-a (chl-a) concentrations. In addition, the performance of the new method was superior to that of the BEAM processor and only slightly worse than that of SCAPE-M in these bands. Considering its acceptable accuracy and simplicity both in principle and at implementation compared with the SCAPE-M method, the new method provides an option for atmospheric correction of MERIS data in inland turbid case II waters with applications aiming for chl-a estimation.
International Journal of Remote Sensing 06/2012; 33(12):3713-3732. · 1.12 Impact Factor
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ABSTRACT: We examined the effects of dams on freshwater fish species based on data collected during 1990–2004 from 200 drainage systems
in Japan. Of the 76 fish species examined, the occurrence of 20 species within Petromyzontidae, Cyprinidae, Cobitididae, Salmonidae,
Cottidae, and Gobiidae was negatively affected by the presence of dams located in the downstream reaches of fish survey sites,
whereas the occurrence of 12 species within Cyprinidae, Adrianichthyidae, Centrarchidae, and Gobiidae was positively associated
with the presence of dams. A significantly higher proportion of the fishes with a negative damming effect were diadromous
species as compared to the fishes with a positive damming effect. Conversely, the latter group had a significantly higher
proportion of nonnative species than the former. A significant interaction existed between the effects of damming and the
effects of elevation on family-specific species richness. Families dominated by native migratory species showed a greater
reduction in the number of species above dams at lower elevations, whereas families represented primarily by nonnative species
had higher species richness above dams at higher elevations, except for Centrarchidae, which was always higher in species
richness above dams regardless of elevation. Based on our findings, dams in Japan have adversely affected native freshwater
fishes by blocking their migration routes, favoring nonnative fishes, or altering existing habitats.
Ecological Research 04/2012; 23(4):735-743. · 1.57 Impact Factor
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ISPRS Journal of Photogrammetry and Remote Sensing 01/2012; 69:74-87. · 2.88 Impact Factor
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ABSTRACT: Two conditions are required when a remotely sensed vegetation index–land surface temperature (VI–T s) diagram is used to estimate the land surface moisture index (LSMI) and air temperature (T a). First, a suitable sampling window size is required to define an ideal VI–T s diagram. Second, T a must be homogeneous across the sampling window. In this study, the Shannon diversity index (SDI) and the semivariogram method were used to evaluate the VI–T s diagram for estimating LSMI and T a from Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) and MODerate-resolution Imaging Spectroradiometer (MODIS) datasets. The results show that T a is homogeneous across a sampling window with a width of several tens of kilometres (46.0–83.6 km) based on the semivariogram method and spatial autocorrelation analysis of the T a from 83 meteorological stations in the North China Plain (NCP) in 2003. When the SDIs of VI and T s are respectively larger than 77% and 63% of their maximums within predetermined sampling windows, LSMI estimations by ASTER and T a estimations by ASTER and MODIS are reliable.
International Journal of Remote Sensing 11/2011; 32:7257-7278. · 1.12 Impact Factor
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03/2011; , ISBN: 978-953-307-251-7
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IEEE T. Geoscience and Remote Sensing. 01/2011; 49:3381-3392.
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ABSTRACT: A three-band index was previously proposed and successfully utilized to estimate the chlorophyll-a concentration (Chl-a) in case-II waters. However, this index shows uncertainties in highly turbid situations. In this study, an enhanced three-band index is proposed to solve this problem. Since the new index employs bands that are identical to those of the original threeband index, it can be applied to Medium Resolution Imaging Spectrometer (MERIS) data. The performance of the index was evaluated using the data collected from two turbid Asian lakes: Lake Kasumigaura, Japan, and Lake Dianchi, China. The results showed that the Chl-a predicted by the enhanced threeband index was strongly correlated with the measured Chl-a (R2 > 0.83), and the root-mean-square error (rmse) and the normalized root-mean-square error (NRMS) were both reduced for the two lakes (for Lake Kasumigaura, rmse from 13.97 to 8.68 mg · m-3 and NRMS from 19.01% to 12.30%; for Lake Dianchi, rmse from 41.29 to 15.28 mg · m-3 and NRMS from 35.83% to 21.34%). These findings imply that, if accurately atmospheric-corrected MERIS data are available, the enhanced three-band index could be used for mapping Chl-a even in highly turbid case-II waters.
IEEE Geoscience and Remote Sensing Letters 11/2010; · 1.56 Impact Factor
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ABSTRACT: The spectral decomposition algorithm (SDA), which is a new approach for the simultaneous estimation of chlorophyll-a (Chl-a) and non-phytoplankton suspended solid (NPSS) concentrations in Case 2 waters using satellite data, was proposed by our previous study. Here, we investigated the effect of phytoplankton composition on the SDA based on the tank experiments using cultured samples for five phytoplankton species (three cyanobacteria, one green algae and one diatom) and lake water samples collected from Lake Kasumigaura from September 2004 to August 2005 except for April 2005. The results showed that the SDA-based models obtained from the cultured samples (culture-based models) showed high accuracies for Chl-a and NPSS estimations in all phytoplankton species (root mean square error [RMSE] about 16.2 μg l − 1 for Chl-a and about 11.0 mg l − 1 for NPSS). However, the Landsat Thematic Mapper (TM) band combinations, which gave the smallest RMSE of the Chl-a and NPSS estimations, differed among the species. In addition, the culture-based models could apply to lake water samples with similar accuracies if the optimal standard reflectance spectra (SRS) of end-members in the water body could be determined. This implies the potential of the SDA-based model as follows: (1) it is less site- and time-specific compared with conventional empirical methods (single band, band ratio, and arithmetic band calculation); (2) it can be proposed by a tank experiment or by a simulation using bio-optical modelling.
International Journal of Remote Sensing 03/2010; 31(6):1605-1623. · 1.12 Impact Factor
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SCIENCE CHINA Information Sciences. 01/2010; 53:1277-1286.
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ABSTRACT: To improve the estimation of aboveground biomass of grassland having a high canopy cover based on remotely sensed data, we measured in situ hyperspectral reflectance and the aboveground green biomass of 42 quadrats in an alpine meadow ecosystem on the Qinghai–Tibetan Plateau. We examined the relationship between aboveground green biomass and the spectral features of original reflectance, first-order derivative reflectance (FDR), and band-depth indices by partial least squares (PLS) regression, as well as the relationship between the aboveground biomass and narrow-band vegetation indices by linear and nonlinear regression analyses. The major findings are as follows. (1) The effective portions of spectra for estimating aboveground biomass of a high-cover meadow were within the red-edge and near infrared (NIR) regions. (2) The band-depth ratio (BDR) feature, using NIR region bands (760–950 nm) in combination with the red-edge bands, yields the best predictive accuracy (RMSE = 40.0 g m−2) for estimating biomass among all the spectral features used as independent variables in the partial least squares regression method. (3) The ratio vegetation index (RVI2) and the normalized difference vegetation index (NDVI2) proposed by Mutanga and Skidmore (Mutanga, O. and Skidmore, A.K., 2004a40.
Mutanga , O. and Skidmore , A. K. 2004a . Narrow band vegetation indices solve the saturation problem in biomass estimation . International Journal of Remote Sensing , 25 : 1 – 16 . View all references, Narrow band vegetation indices solve the saturation problem in biomass estimation. International Journal of Remote Sensing, 25, pp. 1–6) are better correlated to the aboveground biomass than other VIs (R 2 = 0.27 for NDVI2 and 0.26 for RVI2), while RDVI, TVI and MTV1 predicted biomass with higher accuracy (RMSE = 37.2 g m−2, 39.9 g m−2 and 39.8 g m−2, respectively). Although all of the models developed in this study are probably acceptable, the models developed in this study still have low accuracy, indicating the urgent need for further efforts.
International Journal of Remote Sensing 12/2009; 30(24):6497-6517. · 1.12 Impact Factor
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ABSTRACT: Remote sensing (RS) has been considered as the most promising tool for evapotranspiration (ET) estimations from local, regional to global scales. Many studies have been conducted to estimated ET using RS data, however, most of them are based partially on ground observations. In this study, we developed a new dual-source Simple Remote Sensing EvapoTranspiration model (Sim-ReSET) based only on RS data. One merit of this model is that the calculation of aerodynamic resistance can be avoided by means of a reference dry bare soil and an assumption that wind speed at the upper boundary of atmospheric surface layer is homogenous, but the aerodynamic characters are still considered by means of canopy height. The other merit is that all inputs (net radiation, soil heat flux, canopy height, variables related to land surface temperature) can be potentially obtained from remote sensing data, which allows obtaining regular RS-driven ET product. For the purposes of sensitivity analysis and performance evaluation of the Sim-ReSET model without the effect of potential uncertainties and errors from remote sensing data, the Sim-ReSET model was tested only using intensive ground observations at the Yucheng ecological station in the North China Plain from 2006 to 2008. Results show that the model has a good performance for instantaneous ET estimations with a mean absolute difference (MAD) of 34.27 W/m2 and a root mean square error (RMSE) of 41.84 W/m2 under neutral or near-neutral atmospheric conditions. On 12 cloudless days, the MAD of daily ET accumulated from instantaneous estimations is 0.26 mm/day, and the RMSE is 0.30 mm/day.
Journal of Hydrology 10/2009; 376(3-4):476-458. · 2.66 Impact Factor
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ABSTRACT: As human populations and resource use continue to increase, water quality and water resource management will become major problems. With its advantages of large area coverage, high spatial resolution, frequent update and consistent quality, remote sensing has been widely used for hydrological studies and water resources management. This paper focuses on three potential functions of remote sensing for hydrological analysis in east Asia: (1) monitoring water quality in turbid lakes; (2) extracting impervious surface areas (ISAs) from watersheds and (3) estimating evapotranspiration in semi-arid areas. Reviewing the results of the above three topics, it becomes clear that the ability of the current remote sensing technique is still limited in terms of its use in hydrological simulations. An alternative to improving the sensors is developing effective algorithms to compensate for the limitations of current satellite sensors. Copyright © 2008 John Wiley & Sons, Ltd.
Hydrological Processes 11/2008; 23(4):524 - 533. · 2.49 Impact Factor
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ABSTRACT: The VI-Ts diagram determined by the scatter points of the vegetation index (VI) and surface temperature (Ts) has been widely applied in land surface studies. In the VI-Ts diagram, dry point is defined as a pixel with maximum Ts and minimum VI, while wet point is defined as a pixel with minimum Ts and maximum VI. If both dry and wet points can be obtained simultaneously, a triangular VI-Ts diagram can be readily defined. However, traditional methods cannot define an ideal VI-Ts diagram if there are no full ranges of land surface moisture and VI, such as during rainy season or in a period with a narrow VI range. In this study, a new method was proposed to define the VI-Ts diagram based on the subpixel vegetation and soil information, which was independent of the full ranges of land surface moisture and VI. In this method, a simple approach was firstly proposed to decompose Ts of a given pixel into two components, the surface temperatures of soil (Tsoil) and vegetation (Tveg), by means of Ts and VI information of neighboring pixels. The minimum Tveg and maximum Tsoil were then used to determine the wet and dry points respectively within a given sampling window. This method was tested over a 30 km × 30 km semiarid agricultural area in the North China Plain through 2003 using Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) and MODerate-resolution Imaging Spectroradiometer (MODIS) data. The wet and dry points obtained from our proposed method and from a traditional method were compared with those obtained from ground data within the sampling window with the 30 km × 30 km size. Results show that Tsoil and Tveg can be obtained with acceptable accuracies, and that our proposed method can define reasonable VI-Ts diagrams over a semiarid agricultural region throughout the whole year, even for both cases of rainy season and narrow range of VI.
Sensors 08/2008; 8(10):6260-6279. · 1.74 Impact Factor
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ABSTRACT: Land use/land cover (LULC) changes in the watershed (2,157km2) of Lake Kasumigaura during 1979–1996 (Period-1: 1979–1990, Period-2: 1990–1996) were analyzed, and their socio-economic
and biophysical drivers were compared using time-series, high-quality GIS datasets in order to examine the characteristics
of a model forecasting the future LULC. The changes occurred over an area of more than 90km2 during the overall period at changing rates of 0.22% year−1 in Period-1 and 0.25% year−1 in Period-2. Forestland decreased most in both periods at changing rates of 0.45% year−1 in Period-1 and 0.61% year−1 in Period-2. However, predominant changing patterns differed, i.e., from forest to golf course in Period-1 and from forest
to artificial field in Period-2. Particularly in Period-2, a significant LULC change was observed in an area of high population
increase on the edge of an already high-population area. Relationships examined among LULC change, population, and rate of
population change suggested that the urbanized area was highly resistant to LULC change, and that such change was less frequent
in areas of population decline. Statistical analyses indicated that the most influential drivers for total LULC changes were
population in Period-1 and distance from the Tokyo Station in Period-2. Since the change potentials differed between the periods,
we could not assume a stationary process for the corresponding drivers. Somewhat low S values (indices for demonstrability) show that LULC changes in the watershed of Lake Kasumigaura occurred rather randomly,
probably resulting in fragmentation of the landscape.
Landscape and Ecological Engineering 04/2007; 3(1):21-31. · 0.64 Impact Factor
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ABSTRACT: Evapotranspiration (ET) is an important factor for understanding hydrological processes and climate dynamics. Remote sensing is considered as the most promising tool for estimation of ET over a large spatial scale. The purpose of this study is to analyse and evaluate the MOD16 algorithm, developed by Nishida et al. (2003a,b), in winter wheat fields by using MODIS land products, MOD11-land surface temperature and MOD13-standard normalized difference vegetation index (NDVI), as well as observations at the Yucheng Experimental Station, China in 2002. The original MOD16 is a dual-source ET model in which the evaporation fraction (EF) for bare soil surface is estimated using the VI-Ts diagram method, and EF for vegetation is determined by a function of canopy resistance, aerodynamic resistance and air temperature. We analysed a radiation budget sub-model and found that the estimate for solar radiation is acceptable only on cloud-free days. We also found that, in the original MOD16, seasonal variations of minimum canopy resistance and physiological temperatures are not considered, which results in overestimation of canopy resistance when leaf area index (LAI) is less than 2·5. Because the strong unstable thermal stratification over the dry bare soil surface is ignored in the original algorithm, wind speed is overestimated and aerodynamic resistance above the vegetation surface is underestimated. We then modified the original MOD16 algorithm. The result shows that both EF and ET for vegetation estimated with the modified algorithm are in consistent with both the observations of an eddy covariance system and the calculations using the Penman-Monteith method. Copyright © 2007 John Wiley & Sons, Ltd.
Hydrological Processes 04/2007; 21(9):1196 - 1206. · 2.49 Impact Factor
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ABSTRACT: The remote sensing of Case 2 water has been far less successful than that of Case 1 water, due mainly to the complex interactions among optically active substances (e.g., phytoplankton, suspended sediments, colored dissolved organic matter, and water) in the former. To address this problem, we developed a spectral decomposition algorithm (SDA), based on a spectral linear mixture modeling approach. Through a tank experiment, we found that the SDA-based models were superior to conventional empirical models (e.g. using single band, band ratio, or arithmetic calculation of band) for accurate estimates of water quality parameters. In this paper, we develop a method for applying the SDA to Landsat-5 TM data on Lake Kasumigaura, a eutrophic lake in Japan characterized by high concentrations of suspended sediment, for mapping chlorophyll-a (Chl-a) and non-phytoplankton suspended sediment (NPSS) distributions. The results show that the SDA-based estimation model can be obtained by a tank experiment. Moreover, by combining this estimation model with satellite-SRSs (standard reflectance spectra: i.e., spectral end-members) derived from bio-optical modeling, we can directly apply the model to a satellite image. The same SDA-based estimation model for Chl-a concentration was applied to two Landsat-5 TM images, one acquired in April 1994 and the other in February 2006. The average Chl-a estimation error between the two was 9.9%, a result that indicates the potential robustness of the SDA-based estimation model. The average estimation error of NPSS concentration from the 2006 Landsat-5 TM image was 15.9%. The key point for successfully applying the SDA-based estimation model to satellite data is the method used to obtain a suitable satellite-SRS for each end-member.
ISPRS Journal of Photogrammetry and Remote Sensing.
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ABSTRACT: The impervious surface area (ISA) has emerged not only as an indicator of the degree of urbanization, but also as a major indicator of environmental quality for drainage basin management. However, since almost all of the methods for estimating ISA have been developed for urban environments, it is questionable whether these methods can be successfully applied to drainage basins, such as those found in Japan, which usually have more complicated vegetation components (e.g. paddy field, plowed field and dense forest). This paper presents a pre-screened and normalized multiple endmember spectral mixture analysis (PNMESMA) method, which includes a new endmember selection strategy and an integration of the normalized spectral mixture analysis (NSMA) and multiple endmember spectral mixture analysis (MESMA), for estimating the ISA fraction in Lake Kasumigaura Basin, Japan. This new proposed method is superior to the previous methods in that the estimation error of the proposed method is much smaller than the previous SMA- or NSMA-based methods for drainage basin environments. The overall root mean square error was reduced to 5.2%, and no obvious underestimation or overestimation occurred for high or low ISA areas. Through the assessment of environmental quality in Lake Kasumigaura Basin using the ISA fraction, the results showed that the basin has been in the impacted category since 1987, and that in the two decades since, the environmental quality has continued to decline. If this decline continues, then Lake Kasumigaura Basin will fall into the degraded category by 2017.
