Paper
9 November 2004 Cropland change detection with SPOT-4 VEGETATION imagery in Inner Mongolia, China
Jiankun Guo, Jiyuan Liu, Guoman Huang, Dafang Zhuang, Zhiqiang Gao, Huimin Yan
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Abstract
The policy of ecological return of cultivated land has been carried out for several years in China and the cultivated land is decreasing. The objective of this study is to explore the potential and the methodology for the cropland change detection with Discrete Fourier Transform (DFT) approach using high temporal resolution imagery and some ancillary data. The data used in this study are 10-day composite SPOT-4 VEGETATION (VGT) Normalized Difference Vegetation Index (NDVI) over the period from April to November in 1998 and 2002 respectively, and the ancillary data include the existing land cover dataset derived from TM images and agricultural phonological calendar. The DFT method was applied to the NDVI data set on a per pixel basis. The magnitude of the difference of amplitudes in the first three harmonics was used to identify the areas where changes might occur, and then the unsupervised classification was used to determine the types of change. The methodology used in this study can minimize the influence of noise and phenology variance to the change detection. The result showed that the significant change of cropland and other land cover can be detected with this method.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiankun Guo, Jiyuan Liu, Guoman Huang, Dafang Zhuang, Zhiqiang Gao, and Huimin Yan "Cropland change detection with SPOT-4 VEGETATION imagery in Inner Mongolia, China", Proc. SPIE 5544, Remote Sensing and Modeling of Ecosystems for Sustainability, (9 November 2004); https://doi.org/10.1117/12.559420
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Cited by 1 scholarly publication.
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KEYWORDS
Vegetation

Composites

Clouds

Fourier transforms

Agriculture

Temporal resolution

Remote sensing

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