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Assessment of tornado disaster in rubber plantation in western Hainan using Landsat and Sentinel-2 time series images

  • role： First author第一作者
  • Affiliation：

    Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS)/Danzhou Investigation & Experiment Station of Tropical Cops, Ministry of Agriculture and Rural/ State Key Laboratory Incubation Base for Cultivation & Physiology of Tropical Crops, Haikou 571101, China

  • Email：chbq40@163.com
  • Introduction：陈帮乾，1982年生,男，副研究员，研究方向为热带农林遥感。E-mail:chbq40@163.com
CHEN Bangqian1,  
  • Affiliation：

    School of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China

YUN Ting2,  
  • Affiliation：

    Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS)/Danzhou Investigation & Experiment Station of Tropical Cops, Ministry of Agriculture and Rural/ State Key Laboratory Incubation Base for Cultivation & Physiology of Tropical Crops, Haikou 571101, China

AN Feng1,  
  • Affiliation：

    College of Big Data and Intelligence Engineering, Southwest Forestry University, Kunming 650224, China

KOU Weili3,  
  • Affiliation：

    Institute of Scientific and Technical Information, CATAS, Haikou 571101, China

LI Hailiang4,  
  • Affiliation：

    Institute of Scientific and Technical Information, CATAS, Haikou 571101, China

LUO Hongxia4,  
  • Affiliation：

    Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS)/Danzhou Investigation & Experiment Station of Tropical Cops, Ministry of Agriculture and Rural/ State Key Laboratory Incubation Base for Cultivation & Physiology of Tropical Crops, Haikou 571101, China

YANG Chuan1,  
  • Affiliation：

    Tropical Crops Genetic Resources Institute, CATAS, Haikou 571101, China

WANG Qinfei5,  
  • Affiliation：

    Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS)/Danzhou Investigation & Experiment Station of Tropical Cops, Ministry of Agriculture and Rural/ State Key Laboratory Incubation Base for Cultivation & Physiology of Tropical Crops, Haikou 571101, China

SUN Rui1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS)/Danzhou Investigation & Experiment Station of Tropical Cops, Ministry of Agriculture and Rural/ State Key Laboratory Incubation Base for Cultivation & Physiology of Tropical Crops, Haikou 571101, China

  • Email：wzxrri@163.com
  • Introduction：吴志祥，1970年生，男，研究员，研究方向为橡胶林碳循环等。E-mail:wzxrri@163.com
WU Zhixiang1*

реферат

Wind damage is one of the most serious natural disasters affecting the development of China’s natural rubber industry. It caused huge physical damage (e.g., a large number of fallen leaves, branches and trunk breakage) to rubber plantation in a short period of time, which seriously affected the subsequent growth and latex production. Although traditional ground surveys have high accuracy, they are time-consuming, labor-intensive, and economical. The rapid assessment using remote sensing is of great significance for guiding post-disaster production recovery, insurance compensation, and scientific research.Taking the tornado induced by tropical storm Yangliu in 2019 in western Hainan Island as a case study, this study explores the potential of combining Landsat and Sentinel-2 time series images to assess tornado damage of rubber plantations from the perspectives of data availability, image composite methods, and disaster assessment indicators. The image difference method was used to detect differences before and after the tornado.The results showed that: (1) cloudless Landsat 7/8 and Sentinel-2 images can cover more than 90% of the study area at least once within 20 days before and after the disaster, and almost cover the whole area within 30 days. The average coverage at the pixel scale is three times in 30 days and six times in 60 days. (2) The image difference generated by the maximum value composite of images acquired before tornado and the medium value composite of image acquired after tornado is the most significant and stable. (3) In term of time window, the monitoring effect from images acquired within 40 days before and after tornado tends to be stable, and there is no significant difference when compared with the results generated from a 90-days time window. It is conservatively recommended to use images in a 60-day window before and after the tornado for disaster assessment. (4) The EVI of the damaged rubber plantation before and after the tornado changed the most, followed by NBR, LSWI, NDVI, near infrared (NIR), and shortwave infrared (SWIR1 and SWIR2) bands. In terms of percentage changes, LSWI and SWIR2 showed the highest changes after the tornado, followed by NBR, EVI, NIR, and SWIR1. However, the spatial variation of LSWI was significantly lower than that of SWIR2. (5) The tornado completely destroyed about 645 ha of rubber plantation in western Hainan Island. As a crop with a 30-years economic life cycle, the loss is very serious.This study demonstrates the great potential of combining Landsat and Sentinel-2 images to access tornado damage of rubber plantation, and provides important insights for timely evaluating typhoon disaster of rubber plantations and other crops in future.

ключеви́че слова́

rubber plantation;long time series images;image composite method;time window;damage assessment index

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