Evaluating Multiple Sensors for Mapping Cropped Area of Smallholder Farms in the Eastern Indo-Gangetic Plains

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dc.contributor.author Smith, Harrison
dc.contributor.advisor Jain, Meha
dc.date.accessioned 2019-05-06T18:01:13Z
dc.date.available NO_RESTRICTION en_US
dc.date.available 2019-05-06T18:01:13Z
dc.date.issued 2019-04
dc.date.submitted 2019-04
dc.identifier.uri http://hdl.handle.net/2027.42/149011
dc.description.abstract Accurate, fine-scale agricultural statistics are critical for understanding trends in crop production throughout the world. In many areas of the world, however, on-the-ground crop area estimates may be difficult to acquire or are only present at state or national scales. In these areas, remote sensing can offer a cost-effective alternative for gathering fine-scale agricultural statistics. Many methods exist for mapping cropped area using remote sensing, but the majority of these are done using moderate-to-coarse spatial resolution sensors such as MODIS or Landsat. Though often finer in scale than state-level data, these sensors may not accurately estimate cropped area in smallholder systems, where a typical agricultural plot can be smaller than a single image pixel. The purpose of this study was to examine the tradeoffs of using four different sensors—MODIS, Landsat 8, Sentinel-2, and PlanetScope—for mapping cropped area in the eastern Indo-Gangetic Plains (IGP) region of India. We used NDVI time series imagery from each sensor to map cropped area for the 2017-2018 winter growing season, and assessed accuracy using classified maps created using random forest classification. We compared each sensor in terms of accuracy, data availability, and ease of use. We find that Sentinel-2 and PlanetScope both show increased accuracies compared to more commonly used sensors such as MODIS and Landsat 8. This indicates that coarse and even moderate resolution sensors, such as MODIS and Landsat 8, may not be sufficient for mapping fine-scale cropped area in smallholder systems. Our results highlight the importance of appropriate sensor selection when mapping cropped area in smallholder systems. en_US
dc.language.iso en_US en_US
dc.subject remote sensing en_US
dc.subject crop areas en_US
dc.subject agriculture en_US
dc.subject India en_US
dc.title Evaluating Multiple Sensors for Mapping Cropped Area of Smallholder Farms in the Eastern Indo-Gangetic Plains en_US
dc.type Thesis en_US
dc.description.thesisdegreename Master of Science en_US
dc.description.thesisdegreediscipline School for Environment and Sustainability en_US
dc.description.thesisdegreegrantor University of Michigan en_US
dc.contributor.committeemember Bergen, Kathleen
dc.identifier.uniqname harsmi en_US
dc.description.bitstreamurl https://deepblue.lib.umich.edu/bitstream/2027.42/149011/1/Smith_Harrison_Thesis.pdf
dc.owningcollname Dissertations and Theses (Ph.D. and Master's)
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