سابِق|تال

Terrestrial change detection integrating the Dynamic Ratio and the Max-difference Algorithm

  • role： First author第一作者
  • Affiliation：

    Shandong Key Laboratory of Eco-Environmental Science for Yellow River Delta, Binzhou University, Binzhou 256603, China

    Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China

  • Email：xiaodonglee@126.com
  • Introduction：李晓东，男，1977年生，助理研究员，研究方向为遥感应用。E-mail：xiaodonglee@126.com
LI Xiaodong12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China

  • Email：songks@iga.ac.cn
  • Introduction：宋开山，男，1974年生，研究员，研究方向为湿地水环境遥感。E-mail：songks@iga.ac.cn
SONG Kaishan2*

ملخص

The dynamic variation of the ecological environment, as the material basis of human breeding, directly affects people’s quality of life. The terrestrial ecosystem continuously evolves with the developing human society. The rapid and accurate extraction of land-cover change information is conducive to ecological environment protection, the scientific management of natural resources, and the maintaining the human-earth relationship.The objective of this paper is to determine how to construct the dynamic ratio method with the unified threshold to quantitatively measure the change direction, the changed region, and the change type of wetland.On the basis of remote sensing ecological index (i.e., MNDWI, NDVI, and NDSI), the change detection method was proposed to extract the max-difference in the growing season (2018) and the inter-annual dynamic change rate, respectively. The Landsat images data in 2006 and 2018 were used. The main goal is the annual significant assessment of ecological change in land-cover, the determination of the ecological change direction of land-cover, and the analysis of the transformation types of land cover. Principal component analysis was used to extract the first principal component of the monthly max-difference and inter-annual dynamic change rate. Finally, 5626 samples were collected by using visual interpretation. Accuracy assessment was subsequently conducted on the result of the annual and inter-annual change detection.(1) The dynamic ratio method is suitable for the inter-annual change detection in the study area and has higher change detection accuracy and greater stability than single-index (or band) change detection. The overall accuracy of the method is 93.8%, and the Kappa coefficient is 0.876. (2) The monthly max-difference of the ecological indexes (i.e., MNDWI, NDVI, and NDSI) was used to quantitatively measure the annual ecological variation in the study area. Finally, the first principal component retained 83.04% change information. Moreover, land vegetation and water have a positive contribution to the surface ecological change in the study area. The normalized difference soil index contributed negative effects to land ecological change. The dynamic change detection method does not need to set the dynamic threshold, and is more suitable for the efficient updating of land-cover types on a global scale.The quick extracting method of change information with single-phase remote sensing image between two different times enriches remote sensing monitoring technology. Such enhancement is salient especially in the evaluation of land surface ecological factors. It also provides updated data with support for natural resource inventory at the global scale.

مفهوم

the change detection;the Dynamic Ratio method;remote sensing land cover;Songnen plain;Northeast China

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