Remote Sensing (Oct 2021)

Evaluating the Farmland Use Intensity and Its Patterns in a Farming—Pastoral Ecotone of Northern China

  • Xin Chen,
  • Guoliang Zhang,
  • Yuling Jin,
  • Sicheng Mao,
  • Kati Laakso,
  • Arturo Sanchez-Azofeifa,
  • Li Jiang,
  • Yi Zhou,
  • Haile Zhao,
  • Le Yu,
  • Rui Jiang,
  • Zhihua Pan,
  • Pingli An

DOI
https://doi.org/10.3390/rs13214304
Journal volume & issue
Vol. 13, no. 21
p. 4304

Abstract

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The growing population and northward shifts in the center of grain production collectively contribute to the arising farmland use intensity of the farming–pastoral ecotone of Northern China (FPENC). Consequently, it poses a great threat to the vulnerable ecosystem of FPENC. Thus, farmland use intensity monitoring is a top priority to practice sustainable farming. In this study, we establish an indicator system designed to evaluate farmland use intensity in Ulanqab, located in the central part of FPENC. This system includes three single-year indicators (the degree of coupling between effective rainfall and crop water requirement (Dcrr), irrigation intensity (Iri) and crop duration (Cd)) and two multi-year indicators (the frequency of adopting the green-depressing cropping system (Gf) and rotation frequency (Rf)). We mapped five farmland use intensity indicators in Ulanqab from 2010 to 2019 using satellite imagery and other ancillary data. Then, the farmland use patterns were recognized by applying the self-organizing map algorithm. Our results suggest that the mapping results of crop types, center pivot irrigation (CPI), and irrigated areas are reasonably accurate. Iri, Cd, and Rf experienced an increase of 31 m3/hm2, 1 day, and 0.06 in Ulanqab from 2010 to 2019, respectively, while Dcrr and Gf witnessed a decrease of 0.002 and 0.004, respectively. That is, farmers are progressively inclined to higher farmland use intensity. Moreover, spatial heterogeneity analysis shows that Northern Ulanqab owned higher Dcrr, Iri, Cd, and Rf, and lower Gf than the southern part. We conclude the paper by discussing the implications of the results for areas with different farmland use intensity patterns.

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