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Mapping Asian Cropping Intensity With MODIS

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Title Mapping Asian Cropping Intensity With MODIS
 
Creator Gray, Joshua
 
Contributor Friedl, Mark
Frolking, Steve
Ramankutty, Navin
Nelson, Andrew
Gumma, Murali Krishna
 
Subject time series
cropping intensity
 
Description Agricultural systems are geographically extensive,
have profound significance to society, and affect regional energy,
climate, and water cycles. Since most suitable lands worldwide
have been cultivated, there is a growing pressure to increase yields
on existing agricultural lands. In tropical and subtropical regions,
multicropping is widely used to increase food production, but
regional-to-global information related to multicropping practices
is poor. The high temporal resolution and moderate spatial resolution
of the MODIS sensors provide an ideal source of information
for characterizing cropping practices over large areas.
Relative to studies that document agricultural extensification,
however, systematic assessment of agricultural intensification via
multicropping has received relatively little attention. The goal of
this work was to help close this information gap by developing
methods that use multitemporal remote sensing to map multicropping
systems in Asia. Image time-series analysis is especially
challenging in this part of the world because atmospheric conditions
including clouds and aerosols lead to high frequencies of
missing or low-quality observations, especially during the Asian
Monsoon. The methodology that we developed builds upon the
algorithm used to produce the MODIS Land Cover Dynamics
product (MCD12Q2), but uses an improved methodology optimized
for crops. We assessed our results at the aggregate scale
using state, district, and provincial level inventory statistics reporting
total cropped and harvested areas, and at the field scale
using survey results for 191 field sites in Bangladesh. While the
algorithm highlighted the dominant continental-scale patterns in
agricultural practices throughout Asia, and produced reasonable
estimates of state and provincial level total harvested areas, fieldscale
assessment revealed significant challenges in mapping high
cropping intensity due to abundant missing data.
 
Date 2014-08-31
2017-01-09T21:34:08Z
2017-01-09T21:34:08Z
 
Type Journal Article
 
Identifier http://oar.icrisat.org/id/eprint/9185
https://mel.cgiar.org/reporting/download/hash/bAc9w6Jv
Joshua Gray, Mark Friedl, Steve Frolking, Navin Ramankutty, Andrew Nelson, Murali Krishna Gumma. (31/8/2014). Mapping Asian Cropping Intensity With MODIS. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(8), pp. 3373-3379.
https://hdl.handle.net/20.500.11766/5397
Limited access
 
Language en
 
Rights CC-BY-NC-4.0
 
Format PDF
 
Publisher Institute of Electrical and Electronics Engineers (IEEE)
 
Source IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;7,(2014) Pagination 3373,3379