详细信息
基于GF-1和TM数据的金河林业局天然林保护成效评估研究 被引量:4
Study on the Evaluation of Natural Forest Protection in Jinhe Forestry Bureau Based on GF-1 and TM Data
文献类型:期刊文献
中文题名:基于GF-1和TM数据的金河林业局天然林保护成效评估研究
英文题名:Study on the Evaluation of Natural Forest Protection in Jinhe Forestry Bureau Based on GF-1 and TM Data
作者:胡鸿[1,2] 鞠洪波[1] 田昕[1] 杨雪清[2] 孙志超[2]
第一作者:胡鸿
机构:[1]中国林业科学研究院资源信息研究所;[2]国家林业局调查规划设计院
年份:2019
卷号:32
期号:1
起止页码:141-146
中文期刊名:林业科学研究
外文期刊名:Forest Research
收录:CSTPCD;;Scopus;北大核心:【北大核心2017】;CSCD:【CSCD2019_2020】;
基金:高分辨率遥感影像在天然林保护业务中的应用(发改办高技[2013]2140号)
语种:中文
中文关键词:天然林保护;GF-1;TM;地表覆盖类型;植被覆盖度
外文关键词:natural forest protection;GF-1;TM;surface cover type;vegetation coverage
分类号:S771.8
摘要:[目的]利用遥感影像的特点,将地表覆盖类型和植被覆盖度作为天然林保护成效评估的研究指标,提出一种评估天然林保护成效的方法。[方法]首先,分析GF-1遥感影像特点,结合TM影像特点,研究针对GF-1遥感影像的处理和分析技术;其次,选择评估天然林保护成效评估的指标;再次,选取内蒙古金河林业局作为试验区,对试验区的地表覆盖类型变化、植被覆盖度变化进行分析,结合现地调查数据进行验证,从而评估天然林保护成效。[结果]基于采用分类后比较法能够有效检测出地表覆盖类型变化,经验证检测精度能够达到90%以上;归一化植被指数结合像元二分模型能够用于复杂地表植被覆盖度的反演,经野外实测数据验证精度可达到83%。[结论]根据地表覆盖类型变化监测和植被覆盖度变化监测结果,金河林业局天然林保护工程实施以来实现了森林资源由过度消耗向恢复性增长转变。
[Objective] Based on the characteristics of remote sensing images, the surface cover types and vegetation coverage were used as indicators to evaluate the effectiveness of natural forest protection, and a method to evaluate the effectiveness of natural forest protection was put forward.[Method] The characteristics of GF-1 data in China were analyzed, and the processing and analysis techniques for GF-1 remote sensing images were studied in combination with the features of TM images. Then, in view of the performance evaluation of natural forest protection, the indicators for evaluating the effectiveness of natural forest protection were selected. The Jinhe Forestry Bureau was selected as a test area, where the changes of surface cover type changes and vegetation coverage were analyzed, and then verified with field survey data to assess the effectiveness of natural forest protection.[Result] The post-classification method can effectively detect the changes of land cover types based on proven detection, the accuracy are higher more than 90%. Two pixel normalized vegetation index model can be used for inversion of complex surface vegetation coverage, and the accuracy verified by the field data can reach 83%.[Conclusion] According to the results of monitoring the change of surface cover type and vegetation coverage, the natural forest protection project has achieved some achievements since the implementation of the natural forest protection project of the forest resources from excessive consumption to the restorative growth.
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