GEOGRAPHICAL RESEARCH ›› 2019, Vol. 38 ›› Issue (4): 831-843.doi: 10.11821/dlyj020180299

• Orginal Article • Previous Articles     Next Articles

Forest insect-disease monitoring and estimation based on satellite remote sensing data

Zhongwei GUO1,2(), Chaoyang WU2,3(), Xiaoyue WANG1,2   

  1. 1. The State Key Laboratory of Remote Sensing, Institute of Remote Sensing and Digital Earth, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049; China
    3. The Key Laboratory of Land Surface pattern and simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2018-04-01 Revised:2018-06-01 Online:2019-04-20 Published:2019-04-20

Abstract:

Forest insect has been known as the "Fire without Smoke" due to their major damages to forest resources. Therefore it is of great significance for research on ecosystem safety. Current remote sensing based monitoring of forest insect outbreak mainly focuses on its distributions, reasons and consequent influences on productivity. Using insect outbreak data acquired at British Colombia in Canada over 2002-2012, we here provide an analysis of the impacts of insect intensity on relationship between leaf area index (LAI) and the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). We showed that for pixels converting from light to moderate and from moderate to severe, correlations between LAI and NDVI became higher first, then lower evidently and correlations between LAI and EVI became higher consistently. Furthermore, for severely-affected regions, the correlation became stronger. Our results provide a good reference for the future assessment of insect damage on ecosystem function using remote sensing observations.

Key words: forest pests and diseases, Normalized Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), correlation