Zongyao Sha

• Ph. D in GIS & RS
• Professor at Wuhan University

In this study, we proposed an optimal agricultural site selection method based on the third law of geography and geographic similarity, and took the vegetable moss growing area in Hongshan District, Wuhan, China, as an example. The geography of the source region (Hongshan District) and the target region (Hubei Province) was examined and the tempera...

A major source of carbon dioxide emissions (CO2) arises from the household sector. Recent studies have reported increasing household CO2 emissions (HCO2) in many countries. Cities represent a key administrative level in China and can be managed to mitigate HCO2 if spatial and temporal variations in HCO2 are understood at fine scales. Here, we appli...

In situations where natural disasters damage public communication networks, self-organized emergency communication networks play a vital role as important resources for disaster monitoring and emergency response. Geographical conditions, communication capacity, power availability, terminals' position changes during disasters, and data volume, on th...

The net primary productivity (NPP) of vegetation is an important indicator reflecting the vegetation dynamics and carbon sequestration capacity in a region. In recent years, China has implemented policies to carry out ecological protection. To understand the changes in the distribution of vegetation NPP in China and the influence of climate factors...

Introduction Urbanization converts vegetated lands into impervious surfaces and often degrades vegetation carbon sequestration in urban ecosystems. At the same time, the impact on urban vegetation growth from urban expansion could be spatially diverse given different natural environments and urban management practices. Methods Here we applied time...

Green vegetation plays a vital role in energy flows and matter cycles in terrestrial ecosystems, and vegetation phenology may not only be influenced by, but also impose active feedback on, climate changes. The phenological events of vegetation such as the start of season (SOS), end of season (EOS), and length of season (LOS) can respond to climate...

In order to solve a series of problems in the current feeding process, such as inaccuracy, unevenness and high labour costs, a precision feeding system for largemouth bass was developed by integrating feeding management model, water quality monitoring system, fish feeding activity sensor, automatic feeding machine and software platform. Based on th...

Net primary productivity (NPP) plays a vital role in the globe carbon cycle. Quantitative assessment of the effects of climate changes and human activities on net primary productivity dynamics is vital for understanding the driving mechanisms of vegetation change and sustainable development of ecosystems. This study investigates the contributions o...

Precise feeding is an effective guarantee to improve the welfare of aquatic animals, increase culture efficiency and reduce environmental pollution, whereas internet of things (IoT) technology is an important means to promote the development of informatization and intelligence of aquaculture. In order to improve the precision, informatization and i...

In order to reveal the spatial variation characteristics and influencing factors of grassland net primary productivity (NPP) in China, this paper uses remote sensing data, land use data and meteorological data to simulate and estimate China’s grassland net primary productivity from 2001 to 2019 using the Carnegie-Ames-Stanford Approach (CASA). The...

Rapid urbanization has threatened sustainable urban development in many cities across the globe, causing green space loss and vegetation cover degradation which reduce carbon sequestration. Optimal land management practices (LMPs) in an urban context are known as ways capable of promoting urban vegetation growth and contributing to carbon sequestra...

Forests play a vital role in sequestering carbon dioxide from the atmosphere. Vegetation phenology is sensitive to climate changes and natural environments. Exploring the patterns in phenological events of the forests can provide useful insights for understanding the dynamics of vegetation growth and their responses to climate variations. Deciduous...

Pollution from tailings areas often introduces serious animal- and plant-associated ecological disasters and can even endanger human health. Communication-navigation-remote sensing (CNR)-integrated monitoring is expected to play a key role in the assessment of ecological environments in tailings areas, but CNR integration has long been a challenge...

Excessive emissions of greenhouse gases — of which carbon dioxide is the most significant component, are regarded as the primary reason for increased concentration of atmospheric carbon dioxide and global warming. Terrestrial vegetation sequesters 112–169 PgC (1PgC = 10¹⁵g carbon) each year, which plays a vital role in global carbon recycling. Vege...

With advances in remote sensing, massive amounts of remotely sensed data can be harnessed to support land use/land cover (LULC) change studies over larger scales and longer terms. However, a big challenge is missing data as a result of poor weather conditions and possible sensor malfunctions during image data collection. In this study, cloud-based...

The latest vision transformer (ViT) has stronger contextual feature representation capability than the existing convolutional neural networks and thus has the potential to depict the remote sensing scenes, which usually have more complicated object distribution and spatial arrangement than ground image scenes. However, recent researches reflect tha...

Green vegetation plays a vital role in urban ecosystem services. Rapid urbanization often tends to induce urban vegetation cover fragmentation (UVCF) in cities and suburbs. Mapping the changes in the structure (aggregation) and abundance of urban vegetation cover helps to make improved policies for sustainable urban development. In this paper, a ne...

This paper proposed a geoscience model service integrated workflow-based rainstorm waterlogging analysis method to overcome the defects of conventional waterlogging analysis systems. In this research, we studied a general OGC WPS service invoking strategy, an automatic asynchronous invoking mechanism of WPS services in the BPEL workflow, and a dist...

Urban greenness plays a vital role in supporting the ecosystem services of a city. Exploring the dynamics of urban greenness space and their driving forces can provide valuable information for making solid urban planning policies. This study aims to investigate the dynamics of urban greenness space patterns through landscape indices and to apply ge...

Featured Application The study assessed the reduced carbon uptake (RCU) due to human activities and highlighted the patterns of the impact on RCU from human-related driving forces so that optimized grassland management policies could be implemented to achieve more carbon sequestration from vegetation. Abstract The ever-rising concentration of atmo...

The global temperature could increase over 1.5 or even 2 °C by the middle of 21st century due to massive emissions of greenhouse gases (GHGs) — of which carbon dioxide (CO2) is the largest component1. Human activities emit more than 10 PgC (1PgC=1015gC) per year into the atmosphere1, which is regarded as the primary reason for increased atmospheric...

Google Earth Engine (GEE) has been increasingly used in environmental and urban studies due to its cloud-based geospatial processing capability and accessibility to a large collection of geospatial datasets like Landsat, Modis, etc. However, at present, ecological and urban modeling efforts based on GEE are facing three grave challenges: current il...

Urban green space and urban landscape patterns are of great significance to the sustainable development for urban ecosystems. Spatial statistics such as Moran’s I indicator can only reveal the spatial autocorrelation of urban green space or urban landscape itself, while the dynamic changes of urban green space and urban landscape in spatial correla...

The uncertainty of carbon fluxes of the terrestrial ecosystem is the highest among all flux components, calling for more accurate and efficient means to monitor land sinks. Gross primary productivity (GPP) is a key index to estimate the terrestrial ecosystem carbon flux, which describes the total amount of organic carbon fixed by green plants throu...

Significant land cover change (SLCC) in grassland ecosystem includes both conversions in land cover types and critical modifications to specific land cover properties without land cover conversions. A statistics-based framework, known as spatiotemporal outlier analysis (STOA), was proposed to detect SLCC from time-series remote sensing data conside...

Aims Remote sensing technology has been proved useful in mapping grassland vegetation properties. Spectral features of vegetation cover can be recorded by optical sensors on board of different platforms. With increasing popularity of applying unmanned aerial vehicle (UAV) to mapping plant cover, the study aims to investigate the possible applicatio...

The land type cover information has significantly important role to understand land type change and earth activities. Despite the availability of numerous high-resolution satellite data, very minimal number of land type change researches are available up till now due to the computational limitations. This study provides land type change mapping bas...

Vegetation plays an irreplaceable role for urban ecosystem services. Urban greenness represents all vegetation cover in and around cities. Understanding spatiotemporal patterns of the changes in urban greenness (CUG) provides fundamental clues for urban planning. The impact on CUG can be roughly categorized as being climate-induced and human-induce...

Grassland ecosystems worldwide are confronted with degradation. It is of great importance to understand long-term trajectory patterns of grassland vegetation by advanced analytical models. This study proposes a new approach called a binary logistic regression model with neighborhood interactions, or BLR-NIs, which is based on binary logistic regres...

Vegetation Net Primary Productivity (NPP) is an important indicator for agriculture production. Understanding spatio-temporal dynamics of NPP and their driving factors have attracted much attention from both academic field and practical applications. In this paper, we coupled spatial statistics and a new approach called accumulated density map anal...

The cause-effect associations between geographical phenomena are an important focus in ecological research. Recent studies in structural equation modeling (SEM) demonstrated the potential for analyzing such associations. We applied the variance-based partial least squares SEM (PLS-SEM) and geographically-weighted regression (GWR) modeling to assess...

To optimize the efficiency of the geospatial service in the flood response decision making system, a Parallel Agent-as-a-Service (P-AaaS) method is proposed and implemented in the cloud. The prototype system and comparisons demonstrate the advantages of our approach over existing methods. The P-AaaS method includes both parallel architecture and a...

An Agent-as-a-Service (AaaS)-based geospatial service aggregation is proposed to build a more efficient, robust and intelligent geospatial service system in the Cloud for flood emergency response. It involves an AaaS infrastructure, encompassing the mechanisms and algorithms for geospatial Web Processing Service (WPS) generation, geoprocessing and...

Spatio-temporal variations of vegetation phenology, e.g. start of green-up season (SOS) and end of vegetation season (EOS), serve as important indicators of ecosystems. Routinely processed products from remotely sensed imagery, such as the normalized difference vegetation index (NDVI), can be used to map such variations. A remote sensing approach t...

This paper explored the spatio-temporal patterns of vegetation productivity based on MODIS-NDVI and spatial auto-correlation analysis in the grassland of Inner Mongolia, China during 2011–2013. Two statistics indices, i.e., spatial auto-correlation and semi variance function, were applied in the analysis. The results showed that: (1) at regional sc...

Since the Open Geospatial Consortium (OGC) proposed the geospatial Web Processing Service (WPS), standard OGC Web Service (OWS)-based geospatial processing has become the major type of distributed geospatial application. However, improving the performance and sustainability of the distributed geospatial applications has become the dominant challeng...

More intelligent construction of geospatial service chains and more efficient execution of such service chains remain major challenges in distributed geospatial analysis. This study addresses these challenges using a Cloud- and agent-based approach for automatic and intelligent construction of a geospatial service chain in the Cloud environment. A...

Spatial heterogeneity exists widely in geographical space. We here suggest that spatial association mining should consider spatial variations when designing knowledge-discovering models and applying the models in geographical studies. A Quadtree-based framework was proposed to mine localized spatial associations. Unlike many other approaches, the n...

Techniques for mapping and monitoring vegetation status under human disturbance (e.g., grazing livestock) can contribute to sustainable development of grasslands. The main objective of this paper is to investigate whether the effects of differences in grazing intensity (measured by stocking rate (SR)) could be discriminated using in situ spectral d...

It is well known that the application of Spatial Information Service has a problem of computation intensive. In traditional solution, it is almost impossible to estimate the computing resources of the application and thus either waste or shortage of resources will appear at last. Aimed at it, this paper combines the cloud computing features and pre...

Support Vector Machine (SVM) has been used to classify data and extensively explored in various fields. Instead of using original data as model inputs, we proposed here SVM modeling based on a nonlinear-mapping approach. Such a nonlinear data mapping for the SVM increased the hyperplane margin space, decreased the structural risk minimization (SRM)...

Modeling Distance and Direction Relationships (DDR) is a key issue in spatial analysis and spatial reasoning. Various fields such as geology, hydrology, ecology, etc. apply DDR models to help digging out valuable patterns hidden in geoscientific dataset. This paper proposed two quantitative models through a raster-based approach for computing Eucli...

This paper analyzed and discussed the effect of three similarity measure modes, i.e., spatial distance measure (SDM), non-spatial attribute similarity measure (NSASM) and their hybrid (SDM+NSASM), on interpolation accuracy by inverse distance weighting algorithm (IDW). The newly proposed approach differed from the traditional IDW one in that it als...

Grasslands occupy a great part of area in the global terrestrial landscapes and are important resources from both agronomic and ecological perspectives. Understanding vegetation dynamics is critical to make informed decisions for grassland management. Remote sensing technique has been widely applied in long-term grassland vegetation mapping. In thi...

Spatial association rules mining is a process of acquiring information and knowledge from large databases. Due to the nature of geographic space and the complexity of spatial objects and relations, the classical association rule mining methods are not suitable for the spatial association rule mining. Classical association rule mining treats all inp...

We investigated whether vegetation characteristics under different grazing intensities (measured by stocking rates, or SRs) could be discriminated using ASD field spectrometer data ranging from 350nm to 2,500 nm (a total of 2,151 wavelengths). Canopy spectral measurements and above-ground biomass under four different stocking rates (SR-0 sheep/ha,...

The dynamics of vegetation cover plays an important role in global environment evaluation. Due to the spatial, spectral and radiometric differences among different remote sensing platforms, building long-term and consistent vegetation index (VI) time series is desired to derive comparable vegetation health. In this paper, an approach called Min_Max...

Current literature suggests that grassland degradation occurs in areas with poor soil conditions or noticeable environmental changes and is often a result of overgrazing or human disturbances. However, these views are questioned in our analyses. Based on the analysis of satellite vegetation maps from 1984, 1998, and 2004 for the Xilin River Basin,...

Association rules may exist in many transaction datasets. It is valuable if those rules can be extracted. During the extraction process, efficiency and effectiveness are the main concerns. This paper proposed the concept of association rule discovery from dataset containing predetermined decision itemset (PDI) and rare transaction. PDI is a set of...

An optimized producing environment is a key issue in bio-chemical industry production. Due to the complex mechanism of bio-chemical production, understanding the favorable environment is very difficult. On the other hand, a great amount of data has been accumulated through industry production over years. It is possible to find out valuable rules th...

This paper proposed a model and algorithm to mine local association rules from existing spatial dataset while fully taking the fact that spatial heterogeneity may widely exist in reality. The essential part of the model is the calculation localized measure of association strength (LMAS) which is used to quantify local association patterns. Spatial...

Available information and analytical models are often critical to making scientific decisions for site-specific crop management. Expert, or domain knowledge, is an intelligent source that also helps this process. This paper discusses the integration of domain knowledge and modelling in site-specific crop management decision making. A web-based spat...

Large and growing archives of orbital imagery of the earth’s surface collected over the past 40 years provide an important resource for documenting past and current land cover and environmental changes. However uses of these data are limited by the lack of coincident ground information with which either to establish discrete land cover classes or t...

In this paper we propose a service-oriented architecture for spatial data integration (SOA-SDI) in the context of a large number of available spatial data sources that are physically sitting at different places, and develop web-based GIS systems based on SOA-SDI, allowing client applications to pull in, analyze and present spatial data from those a...

Spatial heterogeneity widely exists in the nature. Traditional spatial association data mining assumes that the area on which the mining algorithm performs is evenly distributed, which leads to the mismatch between the mined knowledge and the reality. We suggest that spatial association mining should consider this spatial heterogeneity when designi...

Two models, artificial neural network (ANN) and multiple linear regression (MLR), were developed to estimate typical grassland aboveground dry biomass in Xilingol River Basin, Inner Mongolia, China. The normalized difference vegetation index (NDVI) and topographic variables (elevation, aspect, and slope) were combined with atmospherically corrected...

People are more willing to use visual experience to help their routine work nowadays. The great success of Google map has raised user expectations about geovisualization. In this paper, we presented a web-based architecture for integrating geospatial web services with Pictometry® imagery flown by Pictometry International Corporation (Inc.). Pictome...

Aims Mapping vegetation through remotely sensed images involves various considerations, processes and techniques. Increasing availability of remotely sensed images due to the rapid advancement of remote sensing technology expands the horizon of our choices of imagery sources. Various sources of imagery are known for their differences in spectral, s...

Community ecologists and vegetation scientists in grassland research have a strong interest in quantifying biotic communities in detail. However, a satisfactory classification with fine biotic details has been challenged by the coarse resolutions of Landsat images, although they are easily accessible. In this paper, a hybrid fuzzy classifier (HFC)...

A web-based decision support system, GZ-AgriGIS, was developed to assist local farmers in the region of Guangzhou, China make field-based crop management decisions, e.g. fertilizer applications (replacement) and irrigation. The system was aimed to share available site-specific agricultural domain knowledge and analytical models with the local farme...

This paper proposes the concept, structure and principle of GIS intelligent agent (GIS-IA). GIS-IA is the basic unit that can realize GIS intelligent analysis, and the frame of intelligent analysis based on GIS-IAs is an effective way to realize intelligent spatial decisionmaking.

This paper introduces some definitions and defines a set of calculating indexes to facilitate the research, and then presents an algorithm to complete the spatial clustering result comparison between different clustering themes. The research shows that some valuable spatial correlation patterns can be further found from the clustering result compar...

Spatial decision support is an important research area of spatial information science and should be an integrated function offered by GIS (Geographical Information System) software. It has been proved that many spatial problems are semi- or ill-structured and cannot be solved by traditional GIS that has no domain knowledge support. It is highly des...

This paper proposes the principle of comprehensive knowledge discovery. Unlike most of the current knowledge discovery methods, the comprehensive knowledge discovery considers both the spatial relations and attributes of spatial entities or objects. We introduce the theory of spatial knowledge expression system and some concepts including comprehen...

The principle of comprehensive knowledge discovery is proposed in this article. Unlike most of the current knowledge discovery methods, comprehensive knowledge discovery considers both the spatial relations and attributes of spatial entities or objects. We first introduce the theory if spatial knowledge expression system and some concepts that are...

In this paper, the entity-relation data model for integrating spatio-temporal data is designed. In the design, spatio-temporal data can be effectively stored and spatiao-temporal analysis can be easily realized.

A main task in agriculture production is field management of water and fertilizer. Excessive fertilizer and water application not only waste resource but also pollute the environment. The traditional principle of digital agriculture can only apply in flat or plain place where a large field usually should be partitioned evenly into many little grids...