中国地理科学 ›› 2019, Vol. 20 ›› Issue (3): 405-416.doi: 10.1007/s11769-019-1041-3

• 论文 • 上一篇    下一篇

Evaluation of Forest Damaged Area and Severity Caused by Ice-snow Frozen Disasters over Southern China with Remote Sensing

WANG Xuecheng1,2, YANG Fei1,3, GAO Xing1, WANG Wei1, ZHA Xinjie1,2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, State Key Laboratory of Resources and Environmental Information System, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
  • 收稿日期:2018-06-07 出版日期:2019-06-27 发布日期:2019-05-06
  • 通讯作者: YANG Fei. E-mail:yangfei@igsnrr.ac.cn E-mail:yangfei@igsnrr.ac.cn
  • 基金资助:

    Under the auspices of National Key Research and Development Program of China (No. 2017YFA0604804), Advanced Scientific Research Projects of Chinese Academy of Sciences (No. QYZDY-SSW-DQC007-34), National Natural Science Foundation of China (No. 41301607), Innovation Project of LREIS (State Key Laboratory of Resources and Environmental Information System) of Chinese Academy of Sciences (No. O88RAA02YA)

Evaluation of Forest Damaged Area and Severity Caused by Ice-snow Frozen Disasters over Southern China with Remote Sensing

WANG Xuecheng1,2, YANG Fei1,3, GAO Xing1, WANG Wei1, ZHA Xinjie1,2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, State Key Laboratory of Resources and Environmental Information System, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
  • Received:2018-06-07 Online:2019-06-27 Published:2019-05-06
  • Contact: YANG Fei. E-mail:yangfei@igsnrr.ac.cn E-mail:yangfei@igsnrr.ac.cn
  • Supported by:

    Under the auspices of National Key Research and Development Program of China (No. 2017YFA0604804), Advanced Scientific Research Projects of Chinese Academy of Sciences (No. QYZDY-SSW-DQC007-34), National Natural Science Foundation of China (No. 41301607), Innovation Project of LREIS (State Key Laboratory of Resources and Environmental Information System) of Chinese Academy of Sciences (No. O88RAA02YA)

摘要:

The accurate assessment of forest damage is important basis for the forest post-disaster recovery process and ecosystem management. This study evaluates the spatial distribution of damaged forest and its damaged severity caused by ice-snow disaster that occurred in southern China during January 10 to February 2 in 2008. The moderate-resolution imaging spectroradiometer (MODIS) 13Q1 products are used, which include two vegetation indices data of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index). Furtherly, after Quality Screening (QS) and Savizky-Golay (S-G) filtering of MODIS 13Q1 data, four evaluation indices are obtained, which are NDVI with QS (QSNDVI), EVI with QS (QSEVI), NDVI with S-G filtering (SGNDVI) and EVI with S-G filtering (SGEVI). The study provides a new way of firstly determining the threshold for each image pixel for damaged forest evaluation, by computing the pre-disaster reference value and change threshold with vegetation index from remote sensing data. Results show obvious improvement with the new way for forest damage evaluation, evaluation result of forest damage is much close to the field survey data with standard error of only 0.95 and 1/3 less than the result that evaluated from other threshold method. Comparatively, the QSNDVI shows better performance than other three indices on evaluating forest damages. The evaluated result with QSNDVI shows that the severe, moderate, mild damaged rates of Southern China forests are 47.33%, 34.15%, 18.52%, respectively. By analyzing the influence of topographic and meteorological factors on forest-vegetation damage, we found that the precipitation on freezing days has greater impact on forest-vegetation damage, which is regarded as the most important factor. This study could be a scientific and reliable reference for evaluating the forest damages from ice-snow frozen disasters.

关键词: ice-snow disaster, vegetation index, forest, remote sensing, southern China

Abstract:

The accurate assessment of forest damage is important basis for the forest post-disaster recovery process and ecosystem management. This study evaluates the spatial distribution of damaged forest and its damaged severity caused by ice-snow disaster that occurred in southern China during January 10 to February 2 in 2008. The moderate-resolution imaging spectroradiometer (MODIS) 13Q1 products are used, which include two vegetation indices data of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index). Furtherly, after Quality Screening (QS) and Savizky-Golay (S-G) filtering of MODIS 13Q1 data, four evaluation indices are obtained, which are NDVI with QS (QSNDVI), EVI with QS (QSEVI), NDVI with S-G filtering (SGNDVI) and EVI with S-G filtering (SGEVI). The study provides a new way of firstly determining the threshold for each image pixel for damaged forest evaluation, by computing the pre-disaster reference value and change threshold with vegetation index from remote sensing data. Results show obvious improvement with the new way for forest damage evaluation, evaluation result of forest damage is much close to the field survey data with standard error of only 0.95 and 1/3 less than the result that evaluated from other threshold method. Comparatively, the QSNDVI shows better performance than other three indices on evaluating forest damages. The evaluated result with QSNDVI shows that the severe, moderate, mild damaged rates of Southern China forests are 47.33%, 34.15%, 18.52%, respectively. By analyzing the influence of topographic and meteorological factors on forest-vegetation damage, we found that the precipitation on freezing days has greater impact on forest-vegetation damage, which is regarded as the most important factor. This study could be a scientific and reliable reference for evaluating the forest damages from ice-snow frozen disasters.

Key words: ice-snow disaster, vegetation index, forest, remote sensing, southern China