首页|Ecological quality assessment of large-scale regions using RSEI improved with YTT temperature rectification
Ecological quality assessment of large-scale regions using RSEI improved with YTT temperature rectification
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NETL
NSTL
Taylor & Francis
ABSTRACT The remote sensing based ecological index (RSEI), with its inherent advantages and without subjective intervention, has gained widespread usage as an ecological assessment model. However, the traditional RSEI has many restrictions (e.g. for assessing the ecological quality of large-scale regions, the heat component will be invalid). This paper presents Yesterday-Today-Tomorrow (YTT) temperature rectification model that can address the critical stitching problem caused by temporal disparities in image acquisition over large-scale regions (i.e. apply the heat component to large-scale regions for ecological quality assessment). The improved RSEI is named as L-RSEI (RSEI for Large-scale region). Furthermore, L-RSEI adopts an Enhanced Normalized Difference Vegetation Index (ENDVI) that leverages land cover/use information to enhance assessment accuracy. Applying L-RESI for the Guangxi section of the Xijiang River, the statistical results indicate that (1) The YTT model significantly enhances stitching accuracy compared to raw data, showing improvements of 62.85% in 2000, 58.97% in 2005, 66.12% in 2010, 31.96% in 2015, and 64.12% in 2020. These results affirm its superior performance for large areas. (2) The analysis of ENDVI demonstrates significant improvements over traditional NDVI. Specifically, the percentage of the D class (NDVI value in the range of 0.6–0.8) increases from 15.61% to 29.62%, while the E class (NDVI value in the range of 0.8–1.0) decreases from 60.56% to 47.82%. These findings highlight the finer segmentation achieved through ENDVI; (3) The proportion of middle-to-upper classes (a combination of Normal, Good, and Very Good classes) ranges from 91.88% in 2000 to 92.56% in 2020. Temporal analysis using L-RSEI reveals an initial deterioration followed by recovery in the eco-logical quality of the region, due to technological advancements, government interventions, and the shift in human-nature relationships. All of the aforementioned evidence demonstrates that our L-RSEI method is effective for assessing and monitoring ecological quality in large-scale regions.
Ecological quality assessmentenhanced NDVIYTT temperature rectificationimage stitchingL-RSEI
NETL
NSTL
Taylor & Francis
