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Scientia Silvae Sinicae ›› 2017, Vol. 53 ›› Issue (7): 94-104.doi: 10.11707/j.1001-7488.20170710

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Forest Area Remote Sensing Monitoring Using the Multi-Level Sampling Interpretation Approach

Zhang Yuxing, Wang Xuejun, Huang Guosheng, Dang Yongfeng, Chen Xinyun   

  1. Academy of Forest Inventory and Planning, State Forestry Administration Beijing 100174
  • Received:2016-01-08 Revised:2016-06-29 Online:2017-07-25 Published:2017-08-23

Abstract: [Objective] It is the urgent requirement for forestry that forest resources data and changing information are quickly and effectively acquired by using remote sensing.[Method] This study built forest resource monitoring approach by combining three levels sampling of remote sensing imagery and field surveying. We chose Liaoning Province as study area to assess our method by using multi-source remote sensing data with high, medium and low spatial resolution from 2013 to 2014.[Result] Firstly, we obtained the forest area estimating model by combining separately filed measured plots and high, middle and low resolution remote sensing data. The performance of these three forest area regress model were evaluated and showed high precision(R2=0.99, 0.91, 0.70,respectively). Secondly, we estimated the forest area (590.83 million hectares) and forest coverage(40.54%) of Liaoning Province,respectively. The value of forest coverage is similar to that determined by forest resources inventory(40.49%), which proved that the proposed method in this study could obtain forest area with high precision(more than 99%). In addition, the forest distribution map of Liaoning Province was produced based on MODIS NDVI threshold value method. This study proposed a forest resource monitoring approach which can obtain annual forest area and distribution map of Liaoning Province.[Conclusion] This research explored the method of remote sensing monitoring indices as an available technique. It would be helpful to monitoring forest resource because of the shortening forest monitoring result output cycle. The forest resource monitoring approach proposed in this paper should have a bright future of application and dissemination, and would provide important support for building remote sensing monitoring system of national forest resource.

Key words: multi level sampling, remote sensing monitoring, interpretation division, forest area, annual monitoring

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