OMB Individually Reported

Global food-and-water security-support analysis data (GFSAD) project [2024 INV#WO0000000107073]

Low riskExact public inventory row

Description

1. Landsat-derived rainfed and irrigated area-product of Conterminous United States (LRIP30) 2. Landsat-derived global cropland extent product @ 30 m (LGCEP30) 3. Landsat-derived global rainfed and irrigated area product @ 30 m (LGRIP30)

Detailed example

Producing irrigated and rainfed cropland maps and statistics of United States of America (USA) and the world using Landsat and other similar satellites at 30 m or better spatial resolution. For example: https://www.usgs.gov/apps/croplands/app/map. Numerous datasets and scientific papers are published on this work. Please visit: www.usgs.gov/wgsc/gfsad30

AI / analytics pattern

Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.

Automation level / stage

c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.

Expected benefit

1. assessing Nation's irrigated and rainfed cropland areas 2. critical to assessing crop water use, crop water productivity, and crop water savings 3. providing information on global irrigated and rainfed cropland area maps and statistics

Controls / human review

ATO: No; PIA: Not published

Data needed

All data used in our AI models (ML\DL) are publicly available from sources such as U. S. Geological Survey (USGS), NASA, European Space Agency (ESA). These data are Landsat and Sentinel Satellites of USGS\NASA and ESA. We also use USDA Cropland Data Layer (CDL) for training and testing models. All these data are publicly available online.