Work

Evaluation of Ecological Environment Quality Using an Improved Remote Sensing Ecological Index Model

Year: 2024

Type: article

Abstract: The Remote Sensing Ecological Index (RSEI) model is widely used for large-scale, rapid Ecological Environment Quality (EEQ) assessment. However, both the RSEI and its improved models have limitations in explaining the EEQ with only two-dimensional (2D) factors, resulting in inaccurate evaluation results. Incorporating more comprehensive, three-dimensional (3D) ecological information poses challenges for maintaining stability in large-scale monitoring, using traditional weighting methods like the Principal Component Analysis (PCA). This study introduces an Improved Remote Sensing Ecological Index (IRSEI) model that integrates 2D (normalized difference vegetation factor, normalized difference built-up and soil factor, heat factor, wetness, difference factor for air quality) and 3D (comprehensive vegetation factor) ecological factors for enhanced EEQ monitoring. The model employs a combined subjective–objective weighting approach, utilizing principal components and hierarchical analysis under minimum entropy theory. A comparative analysis of IRSEI and RSEI in Miyun, a representative study area, reveals a strong correlation and consistent monitoring trends. By incorporating air quality and 3D ecological factors, IRSEI provides a more accurate and detailed EEQ assessment, better aligning with ground truth observations from Google Earth satellite imagery.

Source: Remote Sensing

DOI: 10.3390/rs16183485

Authors: Yanan Liu, Wanlin Xiang, Pingbo Hu, Peng Gao, Ai Zhang

Institution: Beijing University of Civil Engineering and Architecture

Language: English

Topic: Environmental Quality and Pollution

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDG: Life on land

Open Access status: gold

Estimated APC paid: $3,069