Research Papers

Classifying cropping area of middle Heihe River Basin in China using multitemporal Normalized Difference Vegetation Index data

[+] Author Affiliations
Huibang Han

The Weather Modification Office of Qinghai Province, Xining 810001, China

Mingguo Ma

Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Heihe Remote Sensing Experimental Research Station, Lanzhou 730000, China

Xufeng Wang

Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Heihe Remote Sensing Experimental Research Station, Lanzhou 730000, China

Shoucun Ma

Meteorological Service Center of Qinghai Province, Xining 810001, China

J. Appl. Remote Sens. 8(1), 083654 (Apr 02, 2014). doi:10.1117/1.JRS.8.083654
History: Received November 27, 2013; Revised March 3, 2014; Accepted March 5, 2014
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Abstract.  Accurate information regarding the structure of crops is critical for the improvement and optimization of land surface models. Multitemporal remote sensing imagery is more effective to determine the crop structure than the single-temporal images because they contain phenological information. Crop structure was extracted based on time series of moderate-resolution imaging spectroradiometer (MODIS) data in the middle Heihe River Basin. A time series of Normalized Difference Vegetation Index (NDVI) data with a 3-day temporal resolution was composed based on daily MODIS reflectance products (MOD 09) from January to December 2011. A total of 120 scenes of composited imagery were integrated into an image data cube of NDVI time series, which was used to extract crop structure for the study area. The spectral curves of corn, wheat, rape, vegetables, and other crops are based on both in situ measurements and visual interpretation. The major crop types were classified by using the adaptive boosting (Adaboost) and support vector machine (SVM) algorithms. The results show that the classification accuracy of Adaboost and SVM was 86.01% and 70.28%, respectively, with Kappa coefficients of 0.8351 and 0.6438, respectively. Summarizing the classification methods used in this study effectively characterize the spatial distribution of the main crops.

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Citation

Huibang Han ; Mingguo Ma ; Xufeng Wang and Shoucun Ma
"Classifying cropping area of middle Heihe River Basin in China using multitemporal Normalized Difference Vegetation Index data", J. Appl. Remote Sens. 8(1), 083654 (Apr 02, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083654


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