Global Cropland and Food Security Analysis Over Four Decades Using Landsat and MODIS Satellite Data Fusion
The overarching goal of the Global Food Security-Analysis Data at 30 m (GFSAD30) project is to map and monitor global croplands for ensuring sustainable water and food security in the twenty-first century. It is a NASA-funded, 5-year project in collaboration with the USGS, NASA GSFC, Northern Arizona University, University of New Hampshire, University of Wisconsin-Madison, Duke University, and ICRISAT. The currently available cropland products suffer from five major limitations:
(A) Absence of precise spatial location of the cropped areas
(B) Coarse resolution of map products with significant uncertainties in areas, locations, and detail
(C) Uncertainties in differentiating irrigated croplands from rain-fed croplands
(D) Absence of crop types and cropping intensities
(E) Absence of a dedicated web\data portal for the dissemination of cropland products
We are focusing on cropland mapping algorithm development, validation, and implementation at a global scale, and Landsat and MODIS satellite data fusion to improve the temporal resolution of the fine spatial resolution data. We are extremely happy to be able to leverage NAU’s new computing cluster Monsoon in this data-intensive geospatial analysis. As we move from coarse-resolution MODIS-based classification to finer-resolution Landsat-based classification, our dataset increases exponentially in size. We estimate that the Landsat-based classification in our lab can take up 5 years when performed on an average desktop computer. However, the same analysis would take 92 hours on Monsoon. Our lab is producing the following map products as a part of this project:
1. Cropland area extent
2. Classification 8 dominant crop types that occupy 70% of the global cropland areas
3. Classification of irrigated versus rain fed croplands
4. Classification of cropping intensity: single, double, triple, and continuous cropping
These final products will be made publicly available via a USGS web portal. The project team is also collaborating with Google Earth Engine.
You can read about the project and the entire team here: http://geography.wr.usgs.gov/science/croplands/index.html.