A5024812064- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Remote Sensing and Land Use
- Remote Sensing and LiDAR Applications
- Conservation, Biodiversity, and Resource Management
- Remote-Sensing Image Classification
- Environmental and Agricultural Sciences
- Environmental Changes in China
- Geographic Information Systems Studies
- Mining and Resource Management
- Fire effects on ecosystems
- Forest ecology and management
- Oil Palm Production and Sustainability
- Rangeland Management and Livestock Ecology
- Geochemistry and Geologic Mapping
- Microbial Community Ecology and Physiology
- Environmental DNA in Biodiversity Studies
- Mineral Processing and Grinding
- Fish Ecology and Management Studies
- Urban Agriculture and Sustainability
- Urban Green Space and Health
- Species Distribution and Climate Change
- Freshwater macroinvertebrate diversity and ecology
- Ginkgo biloba and Cashew Applications
- Plant Water Relations and Carbon Dynamics
University of Alabama in Huntsville
2023
Marshall Space Flight Center
2023
Amazon (United States)
2019
RedCastle Resources (United States)
2018
US Forest Service
2016
Remote sensing landscape monitoring approaches frequently benefit from a dense time series of observations. To enhance these series, data multiple satellite systems need to be integrated. Landsat image is valuable 30-meter resolution source spatial information assess forest conditions over time. Together both operational satellites—7 and 8—provide revisit frequency 8 days at the equator. This moderate temporal provides essential detect annual large area abrupt land cover changes. However,...
Forests in Southeast Asia are experiencing some of the highest rates deforestation and degradation world, with natural forest species being replaced by cropland plantation monoculture. In this work, we have developed an innovative method to accurately map rubber palm oil plantations using fusion Landsat-8, Sentinel 1 2. We applied cloud shadow masking, bidirectional reflectance distribution function (BRDF), atmospheric topographic corrections optical imagery a speckle filter harmonics for...
Land cover monitoring efforts are important for resource planning and ecosystem services in many countries. Collect Earth Online (CEO) is a new, free open source user-friendly software tool land monitoring. It the product of collaborative effort between NASA, Food Agriculture Organization United Nations (FAO), US Forest Service Google. This paper provides full overview CEO's structure functionality. Based on cloud, supports simultaneous data entry by multiple users. No desktop installation...
Spatially and temporally consistent vegetation structure time-series have great potential to improve the capacity for national land cover monitoring, reduce latency cost of international reporting, harmonize regional characterizations. Here we present a semi-automatic, operational algorithm mapping monitoring woody canopy height at scale using freely available Landsat data. The presented employs automatic data processing set lidar-based prediction models. Changes in are detected separately...
Land cover maps play an integral role in environmental management. However, countries and institutes encounter many challenges with producing timely, efficient, temporally harmonized updates to their land maps. To address these issues we present a modular Regional Cover Monitoring System (RLCMS) architecture that is easily customized create products using primitive map layers. Primitive layers are suite of biophysical end member maps, primitives representing the raw information needed make...
Land cover maps are a critical component to make informed policy, development, planning, and resource management decisions. However, technical, capacity, institutional challenges inhibit the creation of consistent relevant land for use in developing regions. Many regions lack coordinated infrastructure, technologies produce robust monitoring system that meets needs. Local capacity may be replaced by external consultants or methods which long-term sustainability. In this study, we...
During the last few decades, a large number of people have migrated to Kathmandu city from all parts Nepal, resulting in rapid expansion city. The unplanned and accelerated growth is causing many environmental population management issues. To manage urban efficiently, authorities need means be able monitor regularly. In this study, we introduced novel approach automatically detect by leveraging state-of-the-art cloud computing technologies using Google Earth Engine (GEE) platform. We...
Time series land cover data statistics often fluctuate abruptly due to seasonal impact and other noise in the input image. Temporal smoothing techniques are used reduce time mapping. The effects of may vary based on method category. In this study, we compared performance Fourier transformation smoothing, Whittaker smoother Linear-Fit averaging Landsat 5, 7 8 yearly composites classify Province No. 1 Nepal. each was tested whether it applied image or primitives generated using random forest...
Monitoring is essential to ensure that environmental goals are being achieved, including those of sustainable agriculture. Growing interest in monitoring provides an opportunity improve practices. Approaches directly monitor land cover change and biodiversity annually by coupling the wall-to-wall coverage from remote sensing site-specific community composition DNA (eDNA) can provide timely, relevant results for parties interested success agricultural To measured impacts due projects not...
Air pollution from burning sugarcane is an important environmental issue in Thailand. Knowing the location and extent of plantations would help formulating effective strategies to reduce burning. High resolution satellite imagery combined with deep-learning technologies can be map high precision. However, land cover mapping using data computationally intensive networks costly. In this study, we used Planet that has been made available public through Norway's International Climate Forest...
Supporting successful global mangrove conservation and policy requires accurate identification of anthropogenic biophysical drivers extent, yet such studies are scarce. We apply a hybrid methodology, combining existing remote sensing maps with local expert knowledge vegetation land use dynamics. conducted stratified random sampling in eight subregions, experts visually interpreted over 20,900 plots using high-resolution imagery Collect Earth Online. Similar to previous estimates, we found...
Satellite-based forest alert systems are an important tool for ecosystem monitoring, planning conservation, and increasing public awareness of cover change. Continuous monitoring in tropical regions, such as those experiencing pronounced monsoon seasons, can be complicated by spatially extensive persistent cloud cover. One solution is to use Synthetic Aperture Radar (SAR) imagery acquired the European Space Agency’s Sentinel-1A B satellites. The Sentinel 1A satellites acquire C-band radar...
Land cover change and its impact on food security is a topic that has major implications for development in population-dense Southeast Asia. The main drivers of forest loss include the expansion agriculture plantation estates, growth urban centers, extraction natural resources, water infrastructure development. design implementation appropriate land use policies requires accurate timely information dynamics to account potential political, economical, agricultural consequences. Therefore,...
Understanding land cover change dynamics and potential pathways of is critical importance for sustainable resource management, to promote food security resilience on a range spatial scales. Data scarcity key concern, however, with the availability free Earth Observation (EO) data, such challenges can be suitably addressed. In this research we have developed robust machine learning (random forest) approach utilizing EO Geographic Information System (GIS) which enables an innovative means our...
While deforestation has traditionally been the focus for forest canopy disturbance detection, degradation must not be overlooked. Both and influence carbon loss greenhouse gas emissions thus included in activity data reporting estimates, such as Reduced Emissions from Deforestation Degradation (REDD+) program. Here, we report on efforts to develop mapping capacity Nepal based a pilot project country’s Terai region, an ecologically complex physiographic area. To strengthen Nepal’s estimates...
Historical forest management practices in the southwestern US have left forests prone to high-severity, stand-replacement fires. Reducing cost of forest-fire and reintroducing fire landscape without negative impact depends on detailed knowledge stand composition, particular, above-ground biomass (AGB). Lidar-based modeling techniques provide opportunities increase ability managers monitor AGB other metrics at reduced cost. We developed a regional lidar-based statistical model estimate for...
Cambodia's agricultural landscape is rapidly transforming, particularly in the cashew sector. Despite country's rapid emergence and ambition to become largest producer, comprehensive data on plantation areas environmental impacts of this expansion are lacking. This study addresses gap detailed land use for plantations Cambodia assesses implications advancements. We collected over 80,000 training polygons across train a convolutional neural network using high-resolution optical SAR satellite...
Savannas, characterised by a continuous grass layer and discontinuous tree layer, are widespread globally highly flammable during dry seasons, contributing to 90% of annual global burned areas significant emissions. Asian savannas, often mismanaged owing structural variability misclassification as ‘poor forests’, face excessive or insufficient fire regimes. Addressing trans-boundary haze climate mitigation requires improved understanding sustainable management. This paper addresses savanna...
Palm oil production has been identified as one of the major drivers deforestation for tropical countries. To meet supply chain objectives, commodity producers and other stakeholders need timely information land cover dynamics in their shed. However, such data are difficult to obtain from suppliers who may lack digital geographic representations sheds locations. Here we present a "community model," machine learning model trained on pooled sourced many different stakeholders, develop specific...