A5073617419- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Remote-Sensing Image Classification
- Remote Sensing and LiDAR Applications
- Data Management and Algorithms
- Urban Heat Island Mitigation
- Remote Sensing and Land Use
- Advanced Image and Video Retrieval Techniques
- Geographic Information Systems Studies
- Image Retrieval and Classification Techniques
- Semantic Web and Ontologies
- Wildlife Ecology and Conservation
- Impact of Light on Environment and Health
- Forest Management and Policy
- Species Distribution and Climate Change
- Rangeland Management and Livestock Ecology
- Cryospheric studies and observations
- Housing Market and Economics
- Fire effects on ecosystems
- Forest ecology and management
- Rangeland and Wildlife Management
- Spatial and Panel Data Analysis
- Constraint Satisfaction and Optimization
- Urban Stormwater Management Solutions
- Advanced Image Fusion Techniques
State University of New York
2014-2024
SUNY College of Environmental Science and Forestry
2014-2024
York University
2013-2023
Purchase College
2010-2022
University of Maine
2000-2014
Land-cover (LC) products, especially at the regional and global scales, comprise essential data for a wide range of environmental studies affecting biodiversity, climate, human health. This review builds on previous compartmentalized efforts by summarizing 23 41 LC products. Characteristics related to spatial resolution, overall accuracy, time acquisition, sensor used, classification scheme method, support change detection, download location, key corresponding references are provided....
Algae serves as a food source for wide range of aquatic species; however, high concentration inorganic nutrients under favorable conditions can result in the development harmful algal blooms (HABs). Many studies have addressed HAB detection and monitoring; no global scale meta-analysis has specifically explored remote sensing-based monitoring. Therefore, this manuscript elucidates visualizes spatiotemporal trends monitoring using sensing methods discusses future insights through 420 journal...
Understanding the factors that influence performance of classifications over urban areas is considerable importance to applications remote-sensing-derived products in design and planning. We examined impact training sample selection on a binary classification nonurban for Denver, Colorado, metropolitan area. Complete coverage reference data cover were available year 1997, which allowed us examine variability accuracy multiple repetitions process. Four sampling designs selecting evaluated....
Abstract Super-resolution mapping (SRM) is a recently developed research task in the field of remotely sensed information processing. It provides ability to obtain land-cover maps at finer scale using relatively low-resolution images. Existing algorithms based on indicator geostatistics and downscaling cokriging offer an SRM approach spatial structure models derived from real data. In this article, novel method sequentially produced with local variogram (SLIV) model. SLIV method, variograms...
Land cover land use (LCLU) products provide essential information for numerous environmental and human studies. Here, we assess the accuracy of eleven global regional over conterminous U.S. using 25,000 high-confidence randomly distributed samples. Results show that in general, National Cover Database (NLCD) Change Monitoring, Assessment Projection (LCMAP) outperform other multi-class products, both terms higher individual class with variability across classes. More specifically, F1...
Moose–vehicle collisions (MVCs) pose a serious safety and environmental concern in many regions of Europe North America. For example, the state Vermont, one‐third all reported MVCs resulted motorist injury or fatality while have increased from two 1982 to 164 2002. Our work used MVC dataset 1983 1999 Northeastern Highlands Vermont (four major roads) perform space, time spatiotemporal analyses guide future mitigation strategies. An adapted kernel density estimator was implemented for...
Beech bark disease (BBD) has affected the composition, structure, and function of forests containing a significant proportion American beech (Fagus grandifolia Ehrh.) across North America. BBD spread been investigated at landscape regional scales, but few studies have examined spatial patterns severity within stands where forest management mitigation measures can be implemented. We analyzed changes in composition between 1985 2009 fine-scale 2000 ∼2 ha northern hardwood stand Adirondack...
Population growth will result in a significant anthropogenic environmental change worldwide through increases developed land (DL) consumption. DL consumption is an important and socioeconomic process affecting humans ecosystems. Attention has been given to modeling inside highly populated cities. However, should expand non-metropolitan areas where arguably the consequences are more significant. Here, we study all counties within conterminous U.S. based on satellite-derived product (National...
Urbanization is an important issue concerning diverse scientific and policy communities. Computational models quantifying locations quantities of urban growth offer numerous environmental socioeconomic benefits. Traditional are based on a single-algorithm fitting procedure thus restricted their ability to capture spatial heterogeneity. Accordingly, GIS-based modeling framework titled multi-network urbanization (MuNU) model developed that integrates multiple neural networks. The MuNU enables...