A5081338017- Remote Sensing in Agriculture
- Flood Risk Assessment and Management
- Climate change impacts on agriculture
- Remote Sensing and LiDAR Applications
- Land Use and Ecosystem Services
- Hydrology and Drought Analysis
- Remote Sensing and Land Use
- Remote-Sensing Image Classification
- Urban Green Space and Health
- Leaf Properties and Growth Measurement
- Geographic Information Systems Studies
- Soil Geostatistics and Mapping
- Astronomical Observations and Instrumentation
- Soil Moisture and Remote Sensing
- Water resources management and optimization
- Advanced Measurement and Detection Methods
- Soil and Land Suitability Analysis
- Environmental and Agricultural Sciences
- Image and Object Detection Techniques
- Urban Heat Island Mitigation
- Advanced Image and Video Retrieval Techniques
- Simulation and Modeling Applications
- Environmental Monitoring and Data Management
- Satellite Image Processing and Photogrammetry
- Smart Agriculture and AI
George Mason University
2018-2023
Taiyuan Institute of Technology
2009
Wuhan University
2007
Abstract Accurate crop-specific damage assessment immediately after flood events is crucial for grain pricing, food policy, and agricultural trade. The main goal of this research to estimate the that occurs by using a newly developed Disaster Vegetation Damage Index (DVDI). By incorporating DVDI along with information on crop types inundation extents, assessed three case-study events: Iowa Severe Storms Flooding (DR 4386), Nebraska 4387), Texas 4272). Crop qualitative scale reported at...
Land use and land cover (LULC) classification using satellite images is an important approach to monitor changes on earth. To produce LULC maps, supervised methods are often used. For many algorithms, independence of features implied assumption. However, this assumption rarely tested. classification, all bands as input models the default approach. some may be highly correlated, which cause model performances unstable. In research, correlations multicollinearity among multi-spectral analyzed...
Inland aquaculture in Bangladesh has been growing fast the last decade. The underlying land use/land cover (LULC) change is an important indicator of socioeconomic and food structure Bangladesh, fishpond mapping essential to understand such LULC change. Previous research often used water indexes (WI), as Normalized Difference Water Index (NDWI) Modified (MNDWI), enhance bodies use shape-based metrics assist classification individual features, coastal ponds. However, inland fishponds are...
Bangladesh is one of the most vulnerable countries to sea level rise due climate change. Soil salinity potential threat coastal ecosystem and agriculture which might hinder country's future food security. Conventional field-based soil monitoring over vast region may not be cost time efficient. Satellite remote sensing offering an efficient way monitor via different indices. This study monitors in five years interval from 1990 2015 using a regression equation developed tested same...
Mapping rice area is a critical resource planning task in many South Asia countries where the primary crop. Remote sensing-based methods typically rely on domain knowledge, such as crop calendar and phenology, supervised classification with ground truth samples. Applying Google Earth Engine (GEE) has been proven effective especially at large scale owing to comprehensive up-to-date data catalog massive server-side processing power. However, writing scripts through code editor requires users...
Rapid urbanization has been an important social and economic phenomenon in the last 50 years. Our study analyzes spatial–temporal landscape pattern National Capital Region (NCR) of Delhi, one most rapid areas world. Delhi metropolitan area its surrounding satellite cities exhibit a soaring rate change during two decades. A set metrics with supplementary ecological meaning was chosen to changes NCR. The results indicate that brought enormous NCR, consequently, substantial impacts on pattern....
Land use and land cover maps are essential to study how the earth surface change over time human activities interact with environments. The growing amount of available remote sensing images, especially well archived Landsat images 30 meters resolution, have been used conduct supervised classification for maps. However, achieve high accuracy, ground truth samples fine quality large quantity required. Collecting is both time-consuming expensive sometimes even unviable when needed past years....
Cyberinfrastructure plays an important role in the collection, management, and dissemination of drought information agricultural activities, especially when activities involve a variety facilities, data sources, communities. The challenge coordinating tremendous sources systems becomes paramount. Some key questions require additional attention if analyzing large social-environmental context: preprocessing observation into analysis-ready format, integrate vegetation/soil observations across...
GIS data layer on crop field boundary has many applications in agricultural research, ecosystem study, monitoring, and land management. Crop mapping through survey is not time cost effective for vast agriculture areas. Onscreen digitization fine-resolution satellite image also labor-intensive error-prone. The recent development segmentation based their spectral characteristics promising cropland detection. However, processing of large volume multi-band images often required high-performance...
Cropland Data Layer (CDL) is an annual crop-specific land use map produced by the U.S. Department of Agricultural (USDA) National Statistics Service (NASS). The CDL products are officially hosted on CropScape website which provides capabilities geospatial data visualization, retrieval, processing, and statistics based open Web services. This study utilizes cloud computing technology to improve performance application A cloud-based prototype implemented tested. experiment results show...
Quick prediction and forecasting of crop yield during the growing season before harvest are important value in supporting decision makers agriculture food security at large. Indices derived from remote sensing have been approved rapid approach monitoring detecting growth conditions. The correlation between vegetation indices has well recognized applied many estimation study. High temporal resolution time series index maps generated up to daily coverage using multiple source data different...
To effectively disseminate location-linked information despite the existence of digital walls across institutions, this study developed a cross-institution mobile App, named GeoFairy2, to overcome virtual gaps among multi-source datasets and aid general users make thorough accurate in-situ decisions. The app provides one-stop service with relevant assist instant decision making. It was tested proven be capable on-demand coupling delivering location-based from multiple sources. can help crack...
WaterSmart project is an NSF funded projected seeks water consumption reduction using satellite observations. In order to fit the fine temporal resolution requirement, satellites are required have a high revisit cycle. MODIS ideal platform for monitoring ground thanks its daily coverage while spatial too coarse. Research has demonstrated possibility improve of Landsat 8 images. This research aimed establish workflow adapt data fusion algorithm achieve automatically processing at real-time in...