Paper
3 November 2010 Study on object-oriented information extraction technology and its application to LUCC in the northern coast of Hainan Island
Congju Zhao, Pengshan Li, Xiang Li
Author Affiliations +
Proceedings Volume 7858, Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment; 785814 (2010) https://doi.org/10.1117/12.869409
Event: SPIE Asia-Pacific Remote Sensing, 2010, Incheon, Korea, Republic of
Abstract
The northern coast of Hainan Island was selected as the study area. The object-oriented information extraction technology was used to process the remote sensing data of 1991, 2001, 2008, and processing results were put to the test of the coefficient of Kappa. The results show that: (1) Methods based on object-oriented information extraction technology can turn remote sensing data to integrated geographic information accurately and efficiently. (2) Kappa indexes, used to test the accuracy of classification results, were 0.7984(in 1991), 0.8331(in 2001), and 0.8571(in 2008) and the overall accuracies were 85.2, 88.86 and 89.14, respectively, which indicated the classification technology was more effective. (3) From 1991 to 2008, the area of construction land and water area increased in the study area. The number of construction land significantly increased, rose by 12083.33 hm2, an average annual growth of 1.09 percent over the past 18 years. But the area of arable land, forest land, wetland and unused land decreased, among of which the decreasing tendency of arable land was significantly, the area dropped by 8124.75 hm2, about 0.73 percent annually on average. (4) During the period, 71.34% of the increased construction land was converted from arable land, which indicated that urbanization has caused a great loss to agricultural land.
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Congju Zhao, Pengshan Li, and Xiang Li "Study on object-oriented information extraction technology and its application to LUCC in the northern coast of Hainan Island", Proc. SPIE 7858, Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment, 785814 (3 November 2010); https://doi.org/10.1117/12.869409
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KEYWORDS
Remote sensing

Information technology

Image classification

Image segmentation

Feature extraction

Image enhancement

Agriculture

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