Geography

Title

A generalized computer vision approach to mapping crop fields in heterogeneous agricultural landscapes

Document Type

Article

Abstract

Smallholder farms dominate in many parts of the world, particularly Sub-Saharan Africa. These systems are characterized by small, heterogeneous, and often indistinct field patterns, requiring a specialized methodology to map agricultural land cover. Using a variety of sites in South Africa, we present a new approach to mapping agricultural fields, based on efficient extraction of a vast set of simple, highly correlated, and interdependent features, followed by a random forest classifier. We achieved similar high performance across agricultural types, including the spectrally indistinct smallholder fields as well as the more easily distinguishable commercial fields, and demonstrated the ability to generalize performance across large geographic areas. In sensitivity analyses, we determined multi-temporal information provided greater gains in performance than the addition of multi-spectral bands available in DigitalGlobe Worldview-2 imagery.

Publication Title

Remote Sensing of Environment

Publication Date

6-15-2016

Volume

179

First Page

210

Last Page

221

ISSN

0034-4257

DOI

10.1016/j.rse.2016.03.010

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