High resolution crop type maps are an important tool for improving food security, and remote sensing is increasingly used to create such maps in regions that possess ground truth labels for model...
Crop type mapping at the field level is critical for a variety of applications in agricultural monitoring, and satellite imagery is becoming an increasingly abundant and useful raw input from...
Crop productivity is potentially affected by several air pollutants, although these are usually studied in isolation. A significant challenge to understanding the effects of multiple pollutants in...
Quantification of the sector-specific financial impacts of historical global warming represents a critical gap in climate change impacts assessment. The multiple decades of county-level data...
The sustainability of aquaculture has been debated intensely since 2000, when a review on the net contribution of aquaculture to world fish supplies was published in Nature. This paper...
Recent years have witnessed rapid growth in satellite-based approaches to quantifying aspects of land use, especially those monitoring the outcomes of sustainable development programs. Burke et al...
Crop yield maps estimated from satellite data increasingly are used to understand drivers of yield trends and variability, yet satellite-derived regional maps are rarely compared with location-...
The increasing availability of satellite data at higher spatial, temporal and spectral resolutions is enabling new applications in agriculture and economic development, including agricultural...
As climate change leads to increased frequency and severity of drought in many agricultural regions, a prominent adaptation goal is to reduce the drought sensitivity of crop yields.
High resolution satellite imagery and modern machine learning methods hold the potential to fill existing data gaps in where crops are grown around the world at a sub-field level.
Researchers including David Lobell analyze how human-caused climate change has impacted a water deficit in Southern Africa and might contribute to a rising food security crisis in the region.
Accurate automated segmentation of remote sensing data could benefit applications from land cover mapping and agricultural monitoring to urban development surveyal and disaster damage assessment....
The advent of multiple satellite systems capable of resolving smallholder agricultural plots raises possibilities for significant advances in measuring and understanding agricultural productivity...
Machine learning and satellite data of crops shows that farms that till the soil less can increase yields of corn and soybeans and improve the health of the soil.
Irrigation has been pivotal in wheat’s rise as a major crop in India and is likely to be increasingly important as an adaptation response to climate change.
Rosamond L. NaylorSenior FellowWilliam Wrigley Professor of Earth System Science, Senior Fellow, Stanford Woods Institute and Freeman Spogli Institute for International Studies, Senior Fellow and Founding Director, Center on Food Security and the Environment
Timothy E. JoslingSenior Fellow, by courtesyProfessor, Food Research Institute, Emeritus, 1940-2018
Steven GorelickCyrus F. Tolman Professor and Senior Fellow, Stanford Woods Institute for the Environment
Hemant PullabhotlaPostdoctoral Scholar, Center on Food Security and the Environment, Department of Earth System Science