LI Juan, ZHANG Yongfu, YU Tingting, et al. Assessment of Spatial-Temporal Changes of Ecological Environment Quality and Its Driving Force in Aksu Region Based on Remote Sensing Ecological Index[J]. 2023, 37(6): 333-340.
DOI:
LI Juan, ZHANG Yongfu, YU Tingting, et al. Assessment of Spatial-Temporal Changes of Ecological Environment Quality and Its Driving Force in Aksu Region Based on Remote Sensing Ecological Index[J]. 2023, 37(6): 333-340. DOI: 10.13870/j.cnki.stbcxb.2023.06.042.
Assessment of Spatial-Temporal Changes of Ecological Environment Quality and Its Driving Force in Aksu Region Based on Remote Sensing Ecological Index
In order to monitor the spatiotemporal variations of ecological environment quality in the Aksu region comprehensively and timely
this study utilized the Google Earth Engine (GEE) platform to construct a remote sensing ecological index (RSEI) based on MODIS multispectral sensor data from 2005
2010
2015
and 2020. Additionally
the Moran index and Geo-detector were employed to investigate the spatial and temporal evolution of ecological quality and identify impact factors in the Aksu region. The findings indicated that: (1) The RSEI in the Aksu area increased from 0.24 to 0.27 between 2005 and 2020
exhibiting a fluctuating upward trend in ecological environmental quality. The high RSEI values were predominantly observed in the northern edge and central oasis region
while the low values were concentrated in the desert and Gobi region. (2) Throughout 2005-2020
the overall Moran index of the RSEI ranged between 0.80 and 0.87
signifying a strong positive correlation in the Aksu region
with high-high (H-H) and low-low (L-L) clusters being dominant. (3) From 2005 to 2020
the explanatory power of various factors in spatial heterogeneity (q-value) varied to different extents
with land use and rainfall identified as key drivers. Furthermore
the influence of interaction detection surpassed that of individual factors. This research provides valuable data and methodological references for the protection of the local ecological environment.
Alcaraz-Segura D, Lomba A, Sousa-Silva R, et al. Potential of satellite-derived ecosystem functional attributes to anticipate species range shifts[J].International Journal of Applied Earth Observation and Geoinformation,2017,57:86-92.
Chen J, Shen M G, Zhu X L, et al. Indicator of flower status derived from in situ hyperspectral measurement in an alpine meadow on the Tibetan Plateau[J].Ecological Indicators,2009,9(4):818-823.
Mishra N B, Crews K A, Neeti N, et al. MODIS derived vegetation greenness trends in African Savanna: Deconstructing and localizing the role of changing moisture availability, fire regime and anthropogenic impact[J].Remote Sensing of Environment,2015,169:192-204.
Coutts A M, Harris R J, Phan T, et al. Thermal infrared remote sensing of urban heat: Hotspots, vegetation, and an assessment of techniques for use in urban planning[J].Remote Sensing of Environment,2016,186:637-651.
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.
Gorelick N, Hancher M, Dixon M, et al. Google earth engine: Planetary-scale geospatial analysis for everyone[J].Remote Sensing of Environment,2017,202:18-27.
Xiong Y, Xu W H, Lu N, et al. Assessment of spatial-temporal changes of ecological environment quality based on RSEI and GEE: A case study in Erhai Lake Basin, Yunnan Province, China[J].Ecological Indicators,2021,125:e107518.
Hwang T, Song C H, Bolstad P V, et al. Downscaling real-time vegetation dynamics by fusing multi-temporal MODIS and Landsat NDVI in topographically complex terrain[J].Remote Sensing of Environment,2011,115(10):2499-2512.
Lobser S E, Cohen W B. MODIS tasselled cap: Land cover characteristics expressed through transformed MODIS data[J].International Journal of Remote Sensing,2007,28(22):5079-5101.
Yuan B D, Fu L N, Zou Y A, et al.Spatiotemporal change detection of ecological quality and the associated affecting factors in Dongting Lake Basin, based on RSEI[J].Journal of Cleaner Production,2021,302:e126995.
Jing Y Q, Zhang F, He Y F, et al. Assessment of spatial and temporal variation of ecological environment quality in Ebinur Lake Wetland National Nature Reserve, Xinjiang, China[J].Ecological Indicators,2020,110:e105874.
Shan Y F, Dai X A, Li W L, et al. Detecting spatial-temporal changes of urban environment quality by remote sensing-based ecological indices: A case study in Panzhihua city, Sichuan Province, China[J].Remote Sensing,2022,14(17):e4137.
Geng J W, Yu K Y, Xie Z, et al. Analysis of spatiotemporal variation and drivers of ecological quality in Fuzhou based on RSEI[J].Remote Sensing,2022,14(19):e4900.
Yue H, Liu Y, Li Y, et al. Eco-environmental quality assessment in China’s 35 major cities based on remote sensing ecological index[J].IEEE Access,2019,7:51295-51311.
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