A5035785614- Remote Sensing in Agriculture
- Smart Agriculture and AI
- Leaf Properties and Growth Measurement
- Spectroscopy and Chemometric Analyses
- Remote Sensing and LiDAR Applications
- Remote Sensing and Land Use
- Remote-Sensing Image Classification
- Hydrology and Watershed Management Studies
- Asian Geopolitics and Ethnography
- Soybean genetics and cultivation
- Rangeland Management and Livestock Ecology
- Impact of Light on Environment and Health
- Hydrology and Sediment Transport Processes
- Urban Transport and Accessibility
- Traffic and Road Safety
- Cambodian History and Society
- Urban Heat Island Mitigation
- Flood Risk Assessment and Management
- Soil erosion and sediment transport
Saint Louis University
2020-2024
Taylor Geospatial Institute
2023
Bexley Hall
2023
Bayer (United States)
2023
Southern Illinois University Carbondale
2021
Khulna University of Engineering and Technology
2015
Early detection of grapevine viral diseases is critical for early interventions in order to prevent the disease from spreading entire vineyard. Hyperspectral remote sensing can potentially detect and quantify a nondestructive manner. This study utilized hyperspectral imagery at plant level identify classify grapevines inoculated with newly discovered DNA virus vein-clearing (GVCV) asymptomatic stages. An experiment was set up test site South Farm Research Center, Columbia, MO, USA (38.92 N,...
Accurate and efficient estimation of crop biophysical traits, such as leaf chlorophyll concentrations (LCC) average angle (ALA), is an important bridge between intelligent breeding precision agriculture. While Unmanned Aerial Vehicle (UAV)-based hyperspectral sensors advanced machine learning models offer high-throughput solutions, collecting sufficient ground truth data for training can be challenging, leading to that lack generalizability practical uses. This study proposes a transfer...
Recent advances in unmanned aerial vehicles (UAV), mini and mobile sensors, GeoAI (a blend of geospatial artificial intelligence (AI) research) are the main highlights among agricultural innovations to improve crop productivity thus secure vulnerable food systems. This study investigated versatility UAV-borne multisensory data fusion within a framework multi-task deep learning for high-throughput phenotyping maize. UAVs equipped with set miniaturized sensors including hyperspectral, thermal,...
Leaf chlorophyll concentration (LCC) is an important indicator of plant health, vigor, physiological status, productivity, and nutrient deficiencies. Hyperspectral spectroscopy at leaf level has been widely used to estimate LCC accurately non-destructively. This study utilized leaf-level hyperspectral data with derivative calculus machine learning sorghum. We calculated fractional (FD) orders starting from 0.2 2.0 order increments. Additionally, 43 common vegetation indices (VIs) were...
Abstract Crop yield prediction from UAV images has significant potential in accelerating and revolutionizing crop breeding pipelines. Although convolutional neural networks (CNN) provide easy, accurate efficient solutions over traditional machine learning models computer vision applications, a CNN training requires large number of ground truth data, which is often difficult to collect the agricultural context. The major objective this study was develope an end-to-end 3D model for plot-scale...
Near-earth hyperspectral big data present both huge opportunities and challenges for spurring developments in agriculture high-throughput plant phenotyping breeding. In this article, we data-driven approaches to address the calibration utilizing near-earth agriculture. A data-driven, fully automated workflow that includes a suite of robust algorithms radiometric calibration, bidirectional reflectance distribution function (BRDF) correction normalization, soil shadow masking, image quality...
Soybean is a pivotal agricultural commodity around the world, primarily because of its high seed protein and oil concentration. Therefore, farmers, breeders end-users are highly interested in understanding predicting soybean composition traits from individual field level or agroecosystem. Seed proportions different chemical physical makeup seeds. Frequent daily coverage PlanetScope (PS) satellite provides unique opportunity estimating due to ability track crop growth development with...
The potential of artificial intelligence (AI) and machine learning (ML) in agriculture for improving crop yields reducing the use water, fertilizers, pesticides remains a challenge. goal this work was to introduce Hyperfidelis, geospatial software package that provides comprehensive workflow includes imagery visualization, feature extraction, zonal statistics, modeling key agricultural traits including chlorophyll content, yield, leaf area index ML framework can be used improve food...
Abstract Delineating accurate flowlines using digital elevation models is a critical step for overland flow modeling. However, extracting surface from high‐resolution (HRDEMs) can be biased, partly due to the absence of information on locations anthropogenic drainage structures (ADS) such as bridges and culverts. Without ADS, roads may act “digital dams” that prevent delineation flowlines. it unclear what variables terrain‐based hydrologic modeling used mitigate effect dams.” This study...
Abstract. Canopy cover is a key agronomic variable for understanding plant growth and crop development status. Estimation of canopy rapidly accurately through fully automated manner significant with respect to high throughput phenotyping. In this work, we propose simple, robust approach, namely rule-based method, that leverages the unique spectral pattern green vegetation at visible (VIS) near-infrared red (NIR) spectra regions distinguish from background (i.e., soil, residue,...
Walking acts as an authentic link for intermodal transfer in major activity centers and helps to fulfil recreational utilitarian trips a city. To assess the condition pattern of walking, walkability assessment is primary option. In last decade large number literatures urban planning, public health transportation have analyzed role built environment on physical activity, typically walking. This study first approach measuring neighborhood Khulna City which third largest city Bangladesh....
Abstract. Calculating solar-sensor zenith and azimuth angles for hyperspectral images collected by UAVs are important in terms of conducting bi-directional reflectance function (BRDF) correction or radiative transfer modeling-based applications remote sensing. These even more necessary to perform high-throughput phenotyping precision agriculture tasks. This study demonstrates an automated Python framework that can calculate the a push-broom camera equipped UAV. First, were radiometrically...
Soybean is an essential crop to fight global food insecurity and of great economic importance around the world. Along with genetic improvements aimed at boosting yield, soybean seed composition also changed. Since conditions during growth development influences nutrient accumulation in seeds, remote sensing offers a unique opportunity estimate traits from standing crops. Capturing phenological developments that influence requires frequent satellite observations higher spatial spectral...
Nitrogen fertilizers are one of the top expenses for corn farmers in North America, and highest cost any input over a growing season. The success developing better strategies nitrogen-use efficiency, such as improved varieties biologics, depends on an efficient way measuring in-planta nitrogen content. We testing reflectance-based UAV hyperspectral approach transmittance-based handheld called LeafSpec to estimate from images. is high throughput but with relatively low spatial resolution has...
Earth and Space Science Open Archive Presented WorkOpen AccessYou are viewing the latest version by default [v1]Extraction of PROSAIL-simulated Spectra from Multi-angular UAV Observations: Application for Leaf Angle EstimationAuthorsSouravBhadraiDVasitSaganAndreaEvelandToddMocklerSee all authors Sourav BhadraiD• Submitting AuthorGeospatial Institute, Saint Louis University, Louis, MO 63108, USADepartment Atmospheric Sciences, USAiDhttps://orcid.org/0000-0002-5832-4695view email addressThe...