Mapping and uncertainty analysis of crop residue cover using sequential gaussian cosimulation with quickbird images

Cha Chi Fan, Guangxing Wang, George Z. Gertner, Haibo Yao, Dana G. Sullivan, Mark Masters

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In the United States, about 30% of agricultural lands have been classified as highly erodible, contributing to continuous degradation of soil productivity. Conservation tillage is a well-known best management practice to conserve soil water resources. Crop residue reduces soil losses from water and wind erosion and increases sequestration of carbon in the soil. Crop residue retention is considered a soil conservation practice, and accurately estimating and mapping crop residue percentage cover is critical (Pacheco and McNairn 2010). Traditionally, ground survey-based methods are often used to estimate crop residue percentage cover (Bannari et al. 2006; Pacheco et al. 2006). However, this method is very time-consuming. Thus, developing a satellite-derived mapping algorithm to rapidly quantify crop residue percentage cover at field and landscape scales has become very important.

Original languageEnglish (US)
Title of host publicationRemote Sensing of Natural Resources
PublisherCRC Press
Pages353-372
Number of pages20
ISBN (Electronic)9781466556935
ISBN (Print)9781466556928
DOIs
StatePublished - Jan 1 2013

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Environmental Science(all)
  • Engineering(all)
  • Earth and Planetary Sciences(all)

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    Fan, C. C., Wang, G., Gertner, G. Z., Yao, H., Sullivan, D. G., & Masters, M. (2013). Mapping and uncertainty analysis of crop residue cover using sequential gaussian cosimulation with quickbird images. In Remote Sensing of Natural Resources (pp. 353-372). CRC Press. https://doi.org/10.1201/b15159