We developed a novel framework to map boro rice at peak season using Sentinel images. These Boro rice maps in Bangladesh showed high classification accuracy (mean of 87.90%). There was no requirement of sample data collection for training the classification model. Multi-Otsu effectively maps rice in low-data areas, outperforming other ML methods and provides stakeholders rice area statistics to support food security management.
Satellite as well as reanalysis-based datasets are widely available and useful in detecting spatial and temporal variability of rainfall at a finer resolution. These products have been widely used in weather forecasting and hydrological and climate …
People and the environment rely on water to exist and thrive, especially water on the Earth's surface because that is the easiest place to get it. The amount of surface water and where it is located is changing with the climate and changes in people's water use, and our need for it is increasing. To plan ahead for future water needs, we need to better understand how the climate and people are changing surface water patterns both separately and together. To help improve our understanding of these changes, we modeled the amount of surface water in three different ways. First, we modeled based on climate data (like temperature and precipitation); second, based on human data (like land use and population); and third, based on both climate and human data together. We found that we could best model the amount of surface water if we used both climate and human data together, and that human data can explain a lot of the changes in the amount of surface water. These results mean that we can work to control changes in the amount of surface water by controlling human actions through planning and policies.
Spatiotemporal quantification of surface water and flooding is essential given that floods are among the largest natural hazards. Effective disaster response management requires near real-time information on flood extent. Satellite remote sensing is …
Fresh water stored by on-farm reservoirs (OFRs) is an important component of surface hydrology and is critical for meeting global irrigation needs. Farmers use OFRs to store water during the wet season and for crop irrigation during the dry season, …
Unprecedented amounts of analysis-ready Earth Observation (EO) data, combined with increasing computational power and new algorithms, offer novel opportunities for analysing ecosystem dynamics across large geographic extents, and to support …
Basemap and Planet Fusion—derived from PlanetScope imagery—represent the next generation of analysis ready datasets that minimize the effects of the presence of clouds. These datasets have high spatial (3 m) and temporal (daily) resolution, which …
On-farm reservoirs (OFRs)—artificial water impoundments that retain water from rainfall and run-off—enable farmers to store water during the wet season to be used for crop irrigation during the dry season. However, monitoring the inter- and intra-annual change of these water bodies remains a challenging task because they are typically small (
Floods, defined as water that temporarily submerges land for over 72 hours or longer, are the largest natural hazard in terms of life loss and economic damage. Effective and immediate disaster response management can reduce the impact of floods but it requires near real-time information on flood occurrence, typically derived based on Earth Observation data.
Water stress is a global concern as a changing climate leads to variations in weather patterns and agricultural and urban areas continue to use water-intensive practices. Understanding spatial and temporal factors of surface water dynamics is key to better managing our resources and limiting the effects of water stress