Research and application of an improved ecological assessment index model integrating multi-source spatio-temporal data

doi:10.13474/j.cnki.11-2246.2025.1225

Abstract

Abstract: To address the limitations of existing ecological indices that often neglect water bodies and are inadequate for comprehensive regional assessment.This study develops an improved remote sensing ecological index (MRSEI)by integrated multi-source spatio-temporal data.The model incorporates five indicators—NDVI,NDBSI,TVDI,EWI,and TWI—to evaluate ecological conditions from four dimensions: greenness,dryness,wetness,and water.An empirical analysis is conducted using 2023 Landsat-8 imagery in Peixian county,Jiangsu province.The results indicate that the ecological environment in the study area had generally improved,with significant enhancements observed in three western towns and eastern lakeside regions.Compared to the traditional RSEI,the MRSEI demonstrates higher accuracy in evaluating water bodies (with a approximately 12% increase in correlation coefficient),owing to its incorporation of water-related indicators and optimized weighting.This study provides an effective tool for accurate ecological quality assessment and sustainable management at the county level,and more suitable for precise monitoring of large-scale land-water composite ecosystems.

Key words: MRSEI, spatio-temporal big data, remote sensing inversion, PCA

CLC Number:

P237

PAN Lei, ZHOU Song, LI Yanan, RAO Jiawang. Research and application of an improved ecological assessment index model integrating multi-source spatio-temporal data[J]. Bulletin of Surveying and Mapping, 2025, 0(12): 144-149,177.

References

［1］[ZK(#]徐涵秋.区域生态环境变化的遥感评价指数［J］.中国环境科学, 2013, 33(5):889-897.
［2］[JP4]罗镕基, 王宏涛, 王成.基于改进遥感生态指数的甘肃省古浪县生态质量评价［J］.干旱区地理, [JP3]2023, 46(4):539-549.[JP]
［3］[JP2]王波, 黄津辉, 郭宏伟, 等.基于遥感的内陆水体水质监测研究进展[JP3]［J］.水资源保护, 2022, 38(3):117-124.[JP]
［4］杨屹, 梁晨雪.黄河流域水资源生态系统服务价值时空变化及驱动分析:以关中平原城市群为例［J］.技术经济, 2023, 42(5):189-200.［5］[ZK(#]王晓红, 辛守英, 张薇, 等.基于主成分分析下贝叶斯优化卷积神经网络模型人工林树种识别的研究［J］.森林工程, 2025, 41(2):298-311.
［6］郭宇龙, 李云梅, 吕恒, 等. 基于主成分降维的总悬浮物浓度遥感估算模型适用性分析［J］. 湖泊科学, 2013, 25(6): 892-899.
［7］TUCKER C J.Red and photographic infrared linear combinations for monitoring vegetation［J］.Remote Sensing of Environment, 1979, 8(2): 127-150.
［8］ZHA Y, GAO J, NI S.Use of normalized difference built-up index in automatically mapping urban areas from TM imagery［J］.International Journal of Remote Sensing, 2003, 24(3): 583-594.
［9］李振轩, 黄敏儿, 高飞, 等.基于U-Net、U-Net++和Attention-U-Net网络的遥感影像水体提取［J］.测绘通报, 2024(8): 26-30.
［10］ SANDHOLT I, RASMUSSEN K, ANDERSEN J.A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status［J］.Remote Sensing of Environment, 2002, 79(2/3): 213-224.
［11］刘宪锋, 朱秀芳, 潘耀忠, 等. 近54年华北平原干旱时空变化特征及其影响因素［J］. 北京师范大学学报(自然科学版), 2015, 51(S1): 1-7.
［12］ JOLLIFFE I T, CADIMA J.Principal component analysis: a review and recent developments［J］.Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2016, 374(2065): 20150202.
［13］王静, 王佳, 徐江琪, 等. 改进遥感生态指数的典型海岸带城市生态环境质量评价: 以湛江市为例［J］. 自然资源遥感, 2023, 35(3): 43-52.
［14］孙彩霞, 杨帆, 胡晋.基于遥感数据的新生态环境指数评价［J］.测绘通报, 2021(11): 12-15.
［15］李树涛, 李聪妤, 康旭东. 多源遥感图像融合发展现状与未来展望［J］. 遥感学报, 2021, 25(1):148-166.

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