Mapping Croplands in Morocco and Tunisia using MAGE
Abstract
Morocco and Tunisia are both net-wheat importing countries, which experience fluctuations in production due to drought. Knowledge of food supply is critical for the local governments' understanding of food security and to re-assure the population regarding food availability. Tunisia was the epicenter for the event known as the "Arab Spring." Although the Arab Spring had several societal components, chronic uncertainty in the governments' reliability raised concerns about food supply and food availability despite the government's policy responses. Due to its importance for geopolitical as well as market opportunity reasons, in March and April of 2017, analysts from the USDA Foreign Agricultural Service (FAS) traveled to Morocco and Tunisia to conduct crop assessment. Fieldwork data collection is necessary for us as crop analysts to use our convergence of evidence approach, which includes ground information, satellite imagery, meteorological information and reports from our offices abroad. During this trip, analysts used the new mobile application from the National Geospatial Intelligence Agency (NGA) called MAGE to collect fieldwork data for crop classification. Using the several thousand training data collected through the mobile application and by leveraging satellite data within Google Earth Engine, an in-season crop mask was created. The final product was delivered to the team just a few days after returning to USDA Washington and was used in the first wheat production estimate of the season released May 10, 2017. The final product helps analysts determine an experimental in-season area estimation and to focus our other remote sensing tools and products on our areas of interest. The US Department of Agriculture's International Production Assessment Division is responsible for publishing monthly production, area and yield estimates for 17 commodities in over 150 countries.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFMGC33A1056M
- Keywords:
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- 1632 Land cover change;
- GLOBAL CHANGE;
- 1640 Remote sensing;
- GLOBAL CHANGE;
- 1655 Water cycles;
- GLOBAL CHANGE;
- 6309 Decision making under uncertainty;
- POLICY SCIENCES