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生态学杂志 ›› 2025, Vol. 44 ›› Issue (11): 3830-3840.doi: 10.13292/j.1000-4890.202511.020

• 技术与方法 • 上一篇    下一篇

黄河流域改进遥感生态指数的多模型对比分析

孟飞*,钱鑫彤,田浩   

  1. (山东建筑大学测绘地理信息学院, 济南 250101)
  • 出版日期:2025-11-10 发布日期:2025-11-14

Multi-model comparative analysis of improved remote sensing ecological index in the Yellow River Basin.

MENG Fei*, QIAN Xintong, TIAN Hao#br#

#br#
  

  1. (School of Surveying, Mapping and Geographic Information, Shandong Jianzhu University, Jinan 250101, China).

  • Online:2025-11-10 Published:2025-11-14

摘要: 黄河流域生态环境复杂且脆弱,传统的遥感生态指数(remote sensing ecological index,RSEI)模型无法全面考虑该区域的地形起伏和荒漠化特征,导致其在流域生态状况监测中具有一定的局限性。为更准确评估流域生态状况,本文以RSEI模型为基础,基于GEE(Google Earth Engine)构建引入坡度(SLOPE)的SRSEI、引入荒漠化指数(DI)的DRSEI和集成所有因子的CRSEI模型,并评估引入指标的具体效用及各模型的监测效果。结果表明:集成不同组合生态因子信息后,SRSEI、DRSEI和CRSEI平均相关度均高于0.73;DI对CRSEI和DRSEI的负面影响显著,相关系数分别为-0.89和-0.9;在区域A中,CRSEI的熵值最高,为2.02,区域B中,DRSEI和CRSEI的熵值均为2.07,区域C中,CRSEI的熵值为1.91,表明SLOPE和DI的引入提升了模型对生态纹理的表达能力,进一步增强了模型在黄河流域生态质量监测中的适用性,为该区域生态保护提供了科学支撑。


关键词: 黄河流域, 改进遥感生态指数, 荒漠化, 坡度, 生态环境

Abstract: The ecological environment of the Yellow River Basin is complex and fragile. The traditional Remote Sensing Ecological Index (RSEI) model fails to fully consider the topographic relief and desertification characteristics of the region, resulting in certain limitations in monitoring the ecological status of the basin. To more accurately assess the ecological status of the basin, we built SRSEI with SLOPE, DRSEI with desertification index (DI) and CRSEI with all factors integrated on the basis of RSEI model and GEE (Google Earth Engine), and evaluated the specific utility of the introduced indicators and the monitoring effect of each model. The results showed that the average correlation of SRSEI, DRSEI, and CRSEI was higher than 0.73 after integrating the information of different ecological factors. DI had a significant negative effect on CRSEI and DRSEI, and the correlation coefficients were -0.89 and -0.9, respectively. In region A, the entropy of CRSEI was the highest (2.02). In region B, the entropy of DRSEI and CRSEI was both 2.07. In region C, the entropy of CRSEI was 1.91. The introduction of SLOPE and DI improved the expression ability of the model for ecological texture. The results enhanced the applicability of the model in ecological quality monitoring in the Yellow River Basin and further provided the scientific support for ecological protection.


Key words: Yellow River basin, improved remote sensing ecological index, desertification, slope, ecological environment