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ORIGINAL RESEARCH
Spatiotemporal Changes and Trends
in Ecological Quality Based on the GEE:
A Case Study of Chengdu City, China
1
Sichuan Guolanzhongtian Environment Technology Group Limited, Chengdu, P.R. China
2
University of Electronic Science and Technology of China, Chengdu, P.R. China
Submission date: 2024-03-25
Final revision date: 2024-06-12
Acceptance date: 2024-09-09
Online publication date: 2024-11-14
Publication date: 2025-11-04
Corresponding author
Pol. J. Environ. Stud. 2025;34(6):7373-7390
KEYWORDS
TOPICS
ABSTRACT
As a new first-tier city, Chengdu serves as a crucial ecological demonstration area in the upper
reaches of the Yangtze River. Assessing and monitoring the quality of the ecological environment
within this region are fundamental tasks for advancing the construction of an ecological civilization.
Our analysis revealed that from 2013 to 2022, the average RSEI ranged between 0.4 and 0.6, indicating
a gradual improvement in the quality of the ecological environment. Notably, between 2017 and 2022,
areas exhibiting excellent ecological quality expanded, while those exhibiting poor quality decreased.
Additionally, regions of medium-grade quality remained relatively stable and dominant. Over the past
decade, the global Moran’s I values ranged from 0.914 to 0.960, indicating a positive spatial correlation for
the ecological quality of Chengdu, albeit with a decreasing degree of clustering. Further analysis of the local
spatial autocorrelation of the RSEI revealed ‘high-high’ (H-H) concentrations primarily in the western
mountainous areas, attributed to lower urbanization rates and superior ecological conditions. Conversely,
‘low-low’ (L-L) clusters predominantly appeared in central urban zones characterized by intensive social
and industrial activities. In addition, the future trend of Chengdu RSEI showed a strong sustainability,
reflecting the continuous improvement of the overall ecological environment of Chengdu.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
REFERENCES (52)
1.
WU G.Y., SUN M.M., FENG Y.C. How does the new environmental protection law affect the environmental social responsibility of enterprises in Chinese heavily polluting industries? Humanities & Social Sciences Communications. 11 (1), 168, 2024. https://doi.org/10.1057/s41599....
2.
WU G.Y., GAO Y., FENG Y.C. Assessing the environmental effects of the supporting policies for mineral resource-exhausted cities in China. Resources Policy. 85, 103939, 2023. https://doi.org/10.1016/j.reso....
3.
FENG Y.C., CHENG C., HU S.L., CAO A.Q. Campaign-style governance of air pollution in China? A comprehensive analysis of the central environmental protection inspection. Frontiers in Public Health. 11, 1081573, 2023. https://doi.org/10.3389/fpubh.....
4.
FENG Y.C., HU J., AFSHAN S., IRFAN M., HU M.J., ABBAS S. Bridging resource disparities for sustainable development: A comparative analysis of resource-rich and resource-scarce countries. Resources Policy. 85, 103981, 2023. https://doi.org/10.1016/j.reso....
5.
BADRELDIN N., GOOSSENS R. A satellite-based disturbance index algorithm for monitoring mitigation strategies effects on desertification change in an arid environment. Mitigation and Adaptation Strategies for Global Change. 20, 263, 2015. https://doi.org/10.1007/s11027....
6.
MA Q., HE C.Y., FANG X.N. A rapid method for quantifying landscape-scale vegetation disturbances by surface coal mining in arid and semiarid regions. Landscape Ecology. 33, 2061, 2018. https://doi.org/10.1007/s10980....
7.
LING X., LUO Z.W., FENG Y.C., LIU X., GAO Y. How does digital transformation relieve the employment pressure in China? Empirical evidence from the national smart city pilot policy. Humanities & Social Sciences Communications. 10 (1), 617, 2023. https://doi.org/10.1057/s41599....
8.
VICENTE-SERRANO S.M., CAMARERO J.J., OLANO J.M. Diverse relationships between forest growth and the Normalized Difference Vegetation Index at a global scale. Remote Sensing of Environment. 187, 14, 2016. https://doi.org/10.1016/j.rse.....
9.
VIJITH H., DODGE-WAN D. Applicability of MODIS land cover and Enhanced Vegetation Index (EVI) for the assessment of spatial and temporal changes in strength of vegetation in tropical rainforest region of Borneo. Remote Sensing Applications: Society and Environment. 18, 100311, 2020. https://doi.org/10.1016/j.rsas....
10.
LI F., ZENG Y., LUO J.H. Modeling grassland above ground biomass using a pure vegetation index. Ecological Indicators. 62, 279, 2016. https://doi.org/10.1016/j.ecol....
11.
RUKEYA S., ASIYA M., LI H., NIJAT K., ZHENG F.L., LI X.S., RENA A., YASIN K. Spatio-temporal changes of grassland ecosystem service values in Urumqi City based on the R.S. and GIS. Acta Ecologica Sinica. 40, 522, 2020. https://doi.org/10.5846/stxb20....
12.
XIE R.F., SHEN Y.M., LAO H. Dynamic changes and responses of coastal wetland landscape pattern based on human disturbance degree in Yancheng, Jiangsu Province, China. Chinese Journal of Ecology. 41 (2), 351, 2022.
13.
XU H.Q. A remote sensing urban ecological index and its application. Acta Ecologica Sinica. 33 (24), 7853, 2013.
14.
XIONG Y., XU W.H., LU N., HUANG S.D., WU C., WANG L.G., DAI F., KOU W.L. Assessment of spatial-temporal changes of ecological environment quality based on RSEI and GEE: a case study in Erhai lake basin, Yunnan Province, China. Ecological Indicators. 125, 107518, 2021. https://doi.org/10.1016/j.ecol....
15.
ZHANG Y.Q., JIANG F. Developing a remote sensing-based ecological index based on improved biophysical features. Journal of Applied Remote Sensing. 16 (1), 012008, 2021. https://doi.org/10.1117/1.JRS.....
16.
LI N., WANG J.Y., QIN F. The improvement of ecological environment index model RSEI. Arabian Journal of Geosciences. 13, 1, 2020. https://doi.org/10.1007/s12517....
17.
ZHANG H., SONG J.Y., LI M., HAN W.H. Eco-environmental quality assessment and cause analysis of Qilian Mountain National Park based on GEE. Chinese Journal of Ecology. 40 (6), 1883, 2021.
18.
GORELICK N., HANCHER M., DIXON M., ILYUSHCHENKO S., THAU D., MOORE R. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sensing of Environment. 202, 18, 2017. https://doi.org/10.1016/j.rse.....
19.
JIA S., WANG C., LI Y., ZHANG F., LIU W. The urbanization efficiency in Chengdu: an estimation based on a three-stage DEA model. Physics and Chemistry of the Earth, Parts A/B/C. 101, 59, 2017. https://doi.org/10.1016/j.pce.....
20.
FENG Y.C., SHOAIB M., AKRAM R., ALNAFRAH I., AI F.Y., IRFAN M. Assessing and prioritizing biogas energy barriers: A sustainable roadmap for energy security. Renewable Energy. 223, 120053, 2024. https://doi.org/10.1016/j.rene....
21.
SHEN Q., PAN Y.X., MENG X.X., LING X., HU S.L., FENG Y.C. How does the transition policy of mineral resource-exhausted cities affect the process of industrial upgrading? New empirical evidence from China. Resources Policy. 86, 104226, 2023. https://doi.org/10.1016/j.reso....
22.
SUR K., DAVE R., CHAUHAN P. Spatio-Temporal changes in NDVI and rainfall over Western Rajasthan and Gujarat region of India. Journal of Agrometeorology. 20 (3), 189, 2018. https://doi.org/10.54386/jam.v....
23.
CRIST E.P. A TM Tasseled Cap equivalent transformation for reflectance factor data. Remote Sensing of Environment. 17 (3), 301, 1985. https://doi.org/10.1016/0034-4....
24.
NICHOL J. Remote sensing of urban heat islands by day and night. Photogrammetric Engineering & Remote Sensing. 71 (5), 613, 2005. https://doi.org/10.14358/PERS.....
25.
LIU Y., MENG Q., ZHANG L., WU C. NDBSI: A normalized difference bare soil index for remote sensing to improve bare soil mapping accuracy in urban and rural areas. Catena. 214, 106265, 2022. https://doi.org/10.1016/j.cate....
26.
HU X., XU H.Q. A new remote sensing index for assessing the spatial heterogeneity in urban ecological quality: A case from Fuzhou City, China. Ecological Indicators. 89, 11, 2018. https://doi.org/10.1016/j.ecol....
27.
LU X., PENG S., YIN Y. Evaluation of Ecological Environment in Futuanhe Nature Reserve Based on Remote Sensing Ecological Index. 2022 IEEE 6th Information Technology and Mechatronics Engineering Conference, Chongqing, China. 6, 1351, 2022. https://doi.org/10.1109/ITOEC5....
28.
ZENG Y., HAO D., HUETE A., DECHANT B., BERRY J., CHEN J.M., JOINER J., FRANKENBERG C., BOND-LAMBERTY B., CHEN J.M., CHEN M. Optical vegetation indices for monitoring terrestrial ecosystems globally. Nature Reviews Earth & Environment. 3 (7), 477, 2022. https://doi.org/10.1038/s43017....
29.
FERCHICHI A., BEN ABBES A., BARRA V., FARAH I.R. Forecasting vegetation indices from spatio-temporal remotely sensed data using deep learning-based approaches: A systematic literature review. Ecological Informatics. 68, 101552, 2022. https://doi.org/10.1016/j.ecoi....
30.
SAMS B., BRAMLEY R.G., SANCHEZ L., DOKOOZLIAN N., FORD C., PAGAY V. Remote Sensing, Yield, Physical Characteristics, and Fruit Composition Variability in Cabernet Sauvignon Vineyards. American Journal of Enology and Viticulture. 73 (2), 93, 2022. https://doi.org/10.5344/ajev.2....
31.
CHENG M., JIAO X., LIU Y., SHAO M., YU X., BAI Y., WANG Z., WANG S., TUOHUTI N., LIU S. Estimation of soil moisture content under high maize canopy coverage from UAV multimodal data and machine learning. Agricultural Water Management. 264, 107530, 2022. https://doi.org/10.1016/j.agwa....
32.
SCHLÜTER S., LEUTHER F., ALBRECHT L., HOESCHEN C., KILIAN R., SUREY R., MIKUTTA R., KAISER K., MUELLER C.W., VOGEL H.J. Microscale carbon distribution around pores and particulate organic matter varies with soil moisture regime. Nature Communications. 13 (1), 2098, 2022. https://doi.org/10.1038/s41467....
33.
CHEN C., CHEN H., LIANG J., HUANG W., XU W., LI B., WANG J. Extraction of Water Body Information from Remote Sensing Imagery While Considering Greenness and Wetness Based on Tasseled Cap Transformation. Remote Sensing. 14 (13), 3001, 2022. https://doi.org/10.3390/rs1413....
34.
LUO H., MING D., XU L. Time series calculation of remote sensing ecological index based on GEE. Remote Sensing. Remote Sensing for Natural Resources. 34 (2), 271, 2022.
35.
AWAD M., ALDAOOD A., ALKIKI I. Development of a Compressibility Prediction Model Based on Soil Index Properties and Area Under/Bounded by Consolidation and Rebound Curves. Geotechnical and Geological Engineering. 40 (9), 4787, 2022. https://doi.org/10.1007/s10706....
36.
PERMATASARI A.D., PRASETYO S.Y.J. Identifikasi Wilayah Resiko Kerusakan Lahan Terbangun Sebagai Dampak Tsunami Berdasarkan Analisis Building Indices. Jurnal Transformatika. 20 (1), 13, 2022. https://doi.org/10.26623/trans....
37.
LUO M., ZHANG S., HUANG L., LIU Z., YANG L., LI R., LIN X. Temporal and Spatial Changes of Ecological Environment Quality Based on RSEI: A Case Study in Ulan Mulun River Basin, China. Sustainability. 14 (20), 13232, 2022. https://doi.org/10.3390/su1420....
38.
SEDDON A.W.R., MACIAS-FAURIA M., LONG P.R., BENZ D., WILLIS K.J. Sensitivity of global terrestrial ecosystems to climate variability. Nature. 531 (7593), 229, 2016. https://doi.org/10.1038/nature....
39.
BOORI M.S., CHOUDHARY K., PARINGER R., KUPRIYANOV A. Eco-environmental quality assessment based on pressure-state-response framework by remote sensing and GIS. Remote Sensing Applications: Society and Environment. 23, 100530, 2021. https://doi.org/10.1016/j.rsas....
40.
GAO W., ZHANG S., RAO X., LIN X., LI R. Landsat TM/OLI-Based Ecological and Environmental Quality Survey of Yellow River Basin, Inner Mongolia Section. Remote Sensing. 13 (21), 4477, 2021. https://doi.org/10.3390/rs1321....
41.
GONG C., LYU F., WANG Y. Spatiotemporal change and drivers of ecosystem quality in the Loess Plateau based on RSEI: A case study of Shanxi, China. Ecological Indicators. 155, 111060, 2023. https://doi.org/10.1016/j.ecol....
42.
LU C., ZHOU H., ZHANG F., DONG G., FU J. Land spatial transformation analysis in Shandong province based on Geo-information map. Transactions of the Chinese Society for Agricultural Machinery. 52 (7), 222, 2021.
43.
YANG A., ZHU L., CHEN S.H., J H., XIA X. Geoinformatic spectrum analysis of land use change in the Manas River Basin, China during 1975–2015. Chinese Journal of Applied Ecology. 30 (11), 3863, 2019.
44.
LE K.G., LIU P., LIN L.T. Traffic accident hotspot identification by integrating kernel density estimation and spatial autocorrelation analysis: A case study. International Journal of Crashworthiness. 27 (2), 543, 2022. https://doi.org/10.1080/135882....
45.
JING Y., ZHANG F., HE Y., KUNG H.T., JOHNSON V.C., ARIKENA M. Assessment of spatial and temporal variation of ecological environment quality in Ebinur Lake Wetland National Nature Reserve, Xinjiang, China. Ecological Indicators. 110, 105874, 2019. https://doi.org/10.1016/j.ecol....
46.
LI F.F., CAI J.P., LIAO Z.C. Comprehensive Evaluation and Analysis of Spatial Dynamic Transition of Air Pollution. IOP Conference Series: Earth and Environmental Science. 676 (1), 012009, 2021. https://doi.org/10.1088/1755-1....
47.
WANG F., LI W.H., LIN Y., NAN X., HU Z.R. Spatiotemporal pattern and driving force analysis of ecological environmental quality in typical ecological areas of the Yellow River Basin from 1990 to 2020. Environmental Science. 44 (5), 2518, 2023.
48.
ZHANG W., DU P.J., GUO S.C., LIN C., ZHENG H.R., FU P.J. Enhanced remote sensing ecological index and ecological environment evaluation in arid area. National Remote Sensing Bulletin. 27, 299, 2023.
49.
CHEN Y., SHEN H., WANG X.H., ZHAO W., PAN Z., WANG J., LI S., HAN D. Assessment method for urban energy carbon emission peak based on Mann-Kendall trend test. Journal of Shanghai Jiaotong University. 57 (7), 928, 2023.
50.
MANDELBROT B.B., WALLIS J.R. Robustness of the rescaled range R/S in the measurement of noncyclic long run statistical dependence. Water Resources Research. 5 (5), 967, 1969. https://doi.org/10.1029/WR005i....
51.
PARKER D.E. Urban heat island effects on estimates of observed climate change. Wiley Interdisciplinary Reviews: Climate Change. 1 (1), 123, 2010. https://doi.org/10.1002/wcc.21.
52.
FENG Y.C., HU S.L. The Effect of Smart City Policy on Urban Haze Pollution in China: Empirical Evidence from a Quasi-Natural Experiment. Polish Journal of Environmental Studies. 31 (3), 2083, 2022. https://doi.org/10.15244/pjoes....
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