Laser & Optoelectronics Progress, Volume. 57, Issue 16, 162802(2020)

Land Use Change Detection Based on GF-1 Satellite Remote Sensing Images

Qing Fu1,2,3, Chen Guo1,2、*, and Wenlang Luo1,2
Author Affiliations
  • 1School of Electronics and Information Engineering, Jinggangshan University, Ji'an, Jiang xi 343009, China
  • 2Jiangxi Engineering Laboratory of IoT Technologies for Crop Growth, Ji'an, Jiang xi 343009, China
  • 3College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China
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    Land use change detection is crucial in land resource management and monitoring. Herein, GF-1 multi-spectral remote sensing images, which were captured in Nanchang city of Jiangxi province in 2013—2017, are classified using the image classification method based on support vector machine. Moreover, land use change maps of the study area in those five years are generated, and land use change characteristics are analyzed. Results show that the types of land in the study area are mainly forest land, grassland, water, and building land. In the five years, the vegetation changed the most with a decrease of 54.74 km 2, followed by the water area with an increase of 22.12 km 2, then land building area with an increase of 19.45 km 2, and bare land area with an increase of 5.17 km 2.

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    Qing Fu, Chen Guo, Wenlang Luo. Land Use Change Detection Based on GF-1 Satellite Remote Sensing Images[J]. Laser & Optoelectronics Progress, 2020, 57(16): 162802

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Nov. 18, 2019

    Accepted: Jan. 15, 2020

    Published Online: Aug. 5, 2020

    The Author Email: Guo Chen (fvqing@163.com)

    DOI:10.3788/LOP57.162802

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