Crop Intensity

  • Released Monday, October 5, 2009
  • Updated Friday, February 2, 2018 at 7:01AM
  • ID: 3629

This visualization shows Crop Intensity data (regions that produce the most crops), followed by the MODIS croplands product, the 26 countries that produce 82% of the world's food, the population density in 2002 and finally the projected population in 2050.

The U.S. Department of Agriculture (USDA) and the National Aeronautics and Space Administration (NASA) signed a Memorandum of Understanding (MOU) to strengthen collaboration. In support of this collaboration, NASA and the USDA Foreign Agricultural Service (FAS) jointly funded a new project to assimilate NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data and products into an existing decision support system (DSS) operated by the International Production Assessment Division (IPAD) of FAS. To meet its objectives, FAS/IPAD uses satellite data and data products to monitor agriculture worldwide and to locate and keep track of natural disasters such as short and long term droughts, floods and persistent snow cover which impair agricultural productivity. FAS is the largest user of satellite imagery in the non-military sector of the U.S. government. For the last 20 years FAS has used a combination of Landsat and NOAA-AVHRR satellite data to monitor crop condition and report on episodic events.

To successfully monitor worldwide agricultural regions and provide accurate agricultural production assessments, it is important to understand the spatial distribution of croplands. To do this a global croplands mask to identify all sites used for crop production. Croplands are highly variable both temporally and spatially. Croplands vary from year to year due to events such as drought and fallow periods, and they vastly differ across the globe in accordance with characteristics such as cropping intensity and field size. A flexible crop likelihood mask is used to help depict these varying characteristics of global crop cover. Regions featuring intensive agro-industrial farming practices such as the Maize Triangle in South Africa will have higher confidence values in the crop mask as compared to less intensively farmed regions in parts of Sub-Saharan Africa where cropland identification is partly confounded with natural background vegetation phenologies. Thus, a customized threshold can be employed to examine areas of varying cropping intensification.

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This image shows crop intensity data. Areas that have the largest yield are colored in a saturated orange where as the lesser producers are in a pale yellow.

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The MODIS project has a landcover product that classifies the areas of the Earth into 17 categories. Here, the croplands category are colored yellow.

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Twenty six countries worldwide produce 82% of the world's wheat, grain, and cereals. These countries are shown in yellow.

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This image shows the world's largest producers of wheat, grain, and cereal in yellow versus the world's 2002 population density in red.

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The United Nations is projecting the cross-hatched areas in light red to double their population.

Yellow represents the countries that currently produce over 80% of the world's wheat, grain, and cereals.

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The United Nations is projecting the cross hatched areas to triple their population by 2050.

Yellow shows the countries that currently produce over 80% of the world's wheat, grain, and cereals.

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This image shows the biggest producers of wheat, grain versus the countries that are projected to double or triple their population by 2050. The red cross hatched areas are where significantly more food will be needed. Africa is in trouble.


Please give credit for this item to:
NASA/Goddard Space Flight Center


This visualization is related to the following missions:

Datasets used in this visualization

Terra and Aqua VI (A.K.A. Composite Vegetation Index) (Collected with the MODIS sensor)
Data Compilation | NASA
Crop Intensity (A.K.A. Crop Intensity 1KM)
USDA/FAS and University of South Dakota
Gridded Population of the World (Version 3 Beta)
Data Compilation | SEDAC
Terra and Aqua NDVI (A.K.A. Normalized Difference Vegetation Index (NDVI)) (Collected with the MODIS sensor)

Note: While we identify the data sets used in these visualizations, we do not store any further details nor the data sets themselves on our site.

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