The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLIII-B3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 247–252, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-247-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 247–252, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-247-2020

  21 Aug 2020

21 Aug 2020

EXTRACTION OF THE INDIVIDUAL TREE INFECTED BY PINE WILT DISEASE USING UNMANNED AERIAL VEHICLE OPTICAL IMAGERY

X. Zhou, L. Liao, D. Cheng, X. Chen, and Q. Huang X. Zhou et al.
  • Technology Service Center of Surveying and Mapping, Sichuan Bureau of Surveying, Mapping and Geoinformation, Chengdu, China

Keywords: Pine Wilt Disease, Unmanned Aerial Vehicle, Vegetation Indices, Threshold Image Segmentation, Individual Tree

Abstract. For eliminating pine trees infected pine wilt disease in southern China based on remote sensing technique, it is important to ensure the provision of timely information about individual diseased tree. It is not easy to detect and extract the diseased pine trees from conventional remote sensing techniques. This paper proposes a new approach for extracting information about individual diseased tree, without the use of satellite images and aerial hyperspectral images. Field measurements in different leaf infected stages indicates the possibility of extracting diseased trees by using only the three regular bands, red, green and blue. VEG was selected and proved to be the optimal index in 12 vegetation indices from the three visible bands. Using the adaptive local threshold selection methods, VEG grayscale image pixels could be automatically segmented into the diseased trees region. Based on mathematical morphology, the accuracy of individual tree information extraction reached 90%.