Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1209-1214, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1209-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1209-1214, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1209-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

SUGARCANE CROP EXTRACTION USING OBJECT-ORIENTED METHOD FROM ZY-3 HIGH RESOLUTION SATELLITE TLC IMAGE

H. Luo1,2,3, Z. Y. Ling1,2,3, G. Z. Shao1,2,3, Y. Huang1,2,3, Y. Q. He1, W. Y. Ning1,2,3, and Z. Zhong1,2,3 H. Luo et al.
  • 1Geomatic Center of Guangxi, Nanning 530023, China
  • 2Guangxi Branch of Satellite Surveying and Mapping Application Center, Nanning 530023, China
  • 3Guangxi Data and Application Center of High Resolution Earth Observation System, Nanning 530023, China

Keywords: Sugarcane Crop, Extraction, Object-oriented, ZY-3, Three Line Camera (TLC), Texture, Digital Surface Model (DSM)

Abstract. Sugarcane is one of the most important crops in Guangxi, China. As the development of satellite remote sensing technology, more remotely sensed images can be used for monitoring sugarcane crop. With the help of Three Line Camera (TLC) images, wide coverage and stereoscopic mapping ability, Chinese ZY-3 high resolution stereoscopic mapping satellite is useful in attaining more information for sugarcane crop monitoring, such as spectral, shape, texture difference between forward, nadir and backward images. Digital surface model (DSM) derived from ZY-3 TLC images are also able to provide height information for sugarcane crop. In this study, we make attempt to extract sugarcane crop from ZY-3 images, which are acquired in harvest period. Ortho-rectified TLC images, fused image, DSM are processed for our extraction. Then Object-oriented method is used in image segmentation, example collection, and feature extraction. The results of our study show that with the help of ZY-3 TLC image, the information of sugarcane crop in harvest time can be automatic extracted, with an overall accuracy of about 85.3 %.