Hui, Jiawei and Bai, Zhongke and Ye, Baoying (2021) Eco-Environment Evaluation of Grassland Based on Remote Sensing Ecological Index: A Case in Hulunbuir Area, China. Journal of Computer and Communications, 09 (06). pp. 203-213. ISSN 2327-5219
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Abstract
This research is based on Landsat5 TM, Landsat8 OLI/TIRS remote sensing data using RSEI model to analyze and monitor the ecological environment and its temporal and spatial changes in the forest-grass transition zone in Northeast China from 2004 to 2019. The change characteristics of the ecological environment of different types of land cover types are monitored by RSEI method, and the response of different land cover types to natural factors such as precipitation and temperature is analyzed at the same time. The distribution of RSEI in the study area presents the characteristics of high in the east and low in the west. The eastern mountainous area is densely covered with woodland, which is the area with the best ecological environment quality in the study area. The grassland in the western plain and the saline-alkali land around the river are the areas with poor ecological environment in the study area. Climate, precipitation, topography and other natural elements work together to form the quality of the ecological environment in the study area roughly bounded by 120?E. In years with poor natural conditions, this dividing line will have a clear eastward shifting trend, especially in the northern part of the study area. The spatial distribution of RSEI in the study area has a high degree of spatial autocorrelation, and Global Moran’s I has been above 0.8 over the years. In terms of temporal changes in ecological conditions, the ecological environment in the study area was basically stable from 2004 to 2008, with a slight deterioration; it improved significantly from 2008 to 2011; however, it deteriorated significantly from 2011 to 2019. According to the results of partial correlation analysis, the ecological environment of the former is highly correlated with natural elements such as climate and precipitation, while the latter is mainly affected by human factors.
Item Type: | Article |
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Subjects: | Science Global Plos > Computer Science |
Depositing User: | Unnamed user with email support@science.globalplos.com |
Date Deposited: | 15 May 2023 07:06 |
Last Modified: | 30 Jan 2024 06:44 |
URI: | http://ebooks.manu2sent.com/id/eprint/872 |