贾坤等：Crop classification using HJ satellite multispectral data in the North China Plain

Crop classification using HJ satellite multispectral data in the North China Plain

Author(s): Jia, K (Jia, Kun)[ 1,2,5 ] ; Wu, BF (Wu, Bingfang)[ 1,2,3,4 ] ; Li, QZ (Li, Qiangzi)[ 1,2,4 ]

Source: JOURNAL OF APPLIED REMOTE SENSING  Volume: 7     Article Number: 073576   DOI: 10.1117/1.JRS.7.073576   Published: APR 12 2013

Abstract: The HJ satellite constellation is designed for environment and disaster monitoring by the Chinese government. This paper investigates the performance of multitemporal multispectral charge-coupled device (CCD) data on board HJ-1-A and HJ-1-B for crop classification in the North China Plain. Support vector machine classifier is selected for the classification using different combinations of multitemporal HJ multispectral data. The results indicate that multitemporal HJ CCD data could effectively identify wheat fields with an overall classification accuracy of 91.7%. Considering only single temporal data, 88.2% is the best classification accuracy achieved using the data acquired at the flowering time of wheat. The performance of the combination of two temporal data acquired at the jointing and flowering times of wheat is almost as well as using all three temporal data, indicating that two appropriate temporal data are enough for wheat classification, and much more data have little effect on improving the classification accuracy. Moreover, two temporal data acquired over a larger time interval achieves better results than that over a smaller interval. However, the field borders and smaller cotton fields cannot be identified effectively by HJ multispectral data, and misclassification phenomenon exists because of the relatively coarse spatial resolution. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE) [DOI: 10.1117/1.JRS.7.073576]

Author Keywords: HJ satellite; multispectral; multitemporal; crop; classification

KeyWords Plus: SUPPORT VECTOR MACHINES; ACREAGE ESTIMATION; TIME-SERIES; PERFORMANCE; NETWORKS; LANDSAT; IMAGES

Reprint Address: Jia, K (reprint author)

         Beijing Normal Univ, Beijing 100875, Peoples R China.

Addresses:

         [ 1 ] Beijing Normal Univ, Beijing 100875, Peoples R China

         [ 2 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

         [ 3 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China

         [ 4 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China

         [ 5 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China

E-mail Addresses: wubf@irsa.ac.cn