What does this research mean for the field?

MODIS 250m data is an effective generic indicator for mapping intensive broadleaf crop production but lacks sensitivity in areas of low agricultural intensification, suggesting that crop-specific approaches are preferable to aggregate global cropland mapping. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The aim is to evaluate the effectiveness of MODIS data for mapping global cropland extent across various regions.

July 21, 2010Remote SensingOpen Access

Estimating Global Cropland Extent with Multi-year MODIS Data

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The aim is to evaluate the effectiveness of MODIS data for mapping global cropland extent across various regions.
Utilized 250 m MODIS data with multi-year metrics incorporating land bands and NDVI.
Developed global classification tree models using a bagging methodology and sub-pixel training datasets.
Created a cropland/non-cropland indicator map using USDA-FAS data for regional evaluations.
MODIS data accurately reflected high probability areas for corn and soybean production.
Wheat region predictions had lower accuracy, while rice production areas showed the least confidence.
Regions without agricultural intensification, such as Africa, were poorly mapped compared to more intensive regions.

Authors

KPKyle PittmanWorld Resources Institute MHMatthew C. HansenUniversity of London IBInbal Becker‐ReshefMicrosoft (United States)

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Implication

Randomized trial assesses global cropland mapping with MODIS, indicating strengths and weaknesses in accuracy.

Cite This Study

Pittman et al. (2010) studied this question.

synapsesocial.com/papers/6a084f490df715653be8a747 https://doi.org/10.3390/rs2071844

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Estimating Global Cropland Extent with Multi-year MODIS Data

Key Points

Discussion

Implication

Cite This Study

Estimating Global Cropland Extent with Multi-year MODIS Data

Key Points

Discussion

Implication

Cite This Study