Deep learning and earth observation to support the sustainable development goals: Current approaches, open challenges, and future opportunities
The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …
promises significant advances to support the Sustainable Development Goals (SDGs). New …
[HTML][HTML] Optical remotely sensed time series data for land cover classification: A review
Accurate land cover information is required for science, monitoring, and reporting. Land
cover changes naturally over time, as well as a result of anthropogenic activities. Monitoring …
cover changes naturally over time, as well as a result of anthropogenic activities. Monitoring …
Environmental outcomes of the US renewable fuel standard
The Renewable Fuel Standard (RFS) specifies the use of biofuels in the United States and
thereby guides nearly half of all global biofuel production, yet outcomes of this keystone …
thereby guides nearly half of all global biofuel production, yet outcomes of this keystone …
Current status of Landsat program, science, and applications
Formal planning and development of what became the first Landsat satellite commenced
over 50 years ago in 1967. Now, having collected earth observation data for well over four …
over 50 years ago in 1967. Now, having collected earth observation data for well over four …
Fmask 4.0: Improved cloud and cloud shadow detection in Landsats 4–8 and Sentinel-2 imagery
We developed the Function of mask (Fmask) 4.0 algorithm for automated cloud and cloud
shadow detection in Landsats 4–8 and Sentinel-2 images. Three major innovative …
shadow detection in Landsats 4–8 and Sentinel-2 images. Three major innovative …
[HTML][HTML] Sentinel-2 cropland map** using pixel-based and object-based time-weighted dynamic time war** analysis
Efficient methodologies for map** croplands are an essential condition for the
implementation of sustainable agricultural practices and for monitoring crops periodically …
implementation of sustainable agricultural practices and for monitoring crops periodically …
[HTML][HTML] Near real-time agriculture monitoring at national scale at parcel resolution: Performance assessment of the Sen2-Agri automated system in various crop** …
The convergence of new EO data flows, new methodological developments and cloud
computing infrastructure calls for a paradigm shift in operational agriculture monitoring. The …
computing infrastructure calls for a paradigm shift in operational agriculture monitoring. The …
Automated cropland map** of continental Africa using Google Earth Engine cloud computing
J ** using satellite-derived remotely sensed data
remains a challenge in Africa because of the heterogeneous and fragmental landscape …
remains a challenge in Africa because of the heterogeneous and fragmental landscape …
Exploring Google Earth Engine platform for big data processing: Classification of multi-temporal satellite imagery for crop map**
Many applied problems arising in agricultural monitoring and food security require reliable
crop maps at national or global scale. Large scale crop map** requires processing and …
crop maps at national or global scale. Large scale crop map** requires processing and …
Improving agricultural field parcel delineation with a dual branch spatiotemporal fusion network by integrating multimodal satellite data
Accurate spatial information for agricultural field parcels is important for agricultural
production management and understanding agro-industrialization and intensification …
production management and understanding agro-industrialization and intensification …