1. An M., Xie P., He W., et al. Spatiotemporal change of ecologic environment quality and human interaction factors in three gorges ecologic economic corridor, based on RSEI // Ecological Indicators. — 2022. — Vol. 141. — P. 109090. — https://doi.org/10.1016/j.ecolind.2022.109090 EDN: https://elibrary.ru/HHZNDH
2. Chen N., Cheng G., Yang J., et al. Evaluation of urban ecological environment quality based on improved RSEI and driving factors analysis // Sustainability. — 2023. — Vol. 15, no. 11. — P. 8464. — https://doi.org/10.3390/su15118464 EDN: https://elibrary.ru/ZPRRBW
3. Chernysh A. F. and Chervan A. N. Erosion-prone agrolandscapes of Belarus: soil erosion control and territorial land-use planning // Erosion and Channel Processes. Collection of Scientific Papers. Issue 7. — Moscow : Moscow State University Publ., 2020. — P. 338–356. — (In Russian).
4. Chervan A. N. and Romanova M. L. Territorial planning of the use of meadow ecosystems on the example of the Pripyatsky Polesie using materials of multi-temporal space imaging // Regional systems of complex remote sensing of agrolandscapes: Proceedings of the III All-Russian Scientific and Practical Seminar. — Krasnoyarsk, 2021. — P. 26–31. — https://doi.org/10.52686/9785604524923_26 — (In Russian).
5. Dubianok S. A., Kulakou A. Y. and Kononchuk T. P. Methodology for developing and ranking the environmental development of the regions of the Republic of Belarus // Journal of the Belarusian State University. Ecology. — 2022. — No. 1. — P. 14–24. — https://doi.org/10.46646/2521-683x/2022-1-14-24 — (In Russian).
6. Gan X., Du X., Duan C., et al. Evaluation of ecological environment quality and analysis of influencing factors in Wuhan City based on RSEI // Sustainability. — 2024. — Vol. 16, no. 13. — P. 5809. — https://doi.org/10.3390/su16135809 EDN: https://elibrary.ru/LKGOCZ
7. Gao P., Kasimu A., Zhao Y., et al. Evaluation of the temporal and spatial changes of ecological quality in the Hami Oasis based on RSEI // Sustainability. — 2020. — Vol. 12, no. 18. — P. 7716. — https://doi.org/10.3390/su12187716 EDN: https://elibrary.ru/ETGEYT
8. Geng J., Yu K., Xie Z., et al. Analysis of spatiotemporal variation and drivers of ecological quality in Fuzhou based on RSEI // Remote Sensing. — 2022. — Vol. 14, no. 19. — P. 4900. — https://doi.org/10.3390/rs14194900 EDN: https://elibrary.ru/IURGEU
9. Gong C., Lyu F. and Wang Y. Spatiotemporal change and drivers of ecosystem quality in the Loess Plateau based on RSEI: A case study of Shanxi, China // Ecological Indicators. — 2023. — Vol. 155. — P. 111060. — https://doi.org/10.1016/j.ecolind.2023.111060 EDN: https://elibrary.ru/KXUFJQ
10. Kolmykov A. V. and Avdeev A. N. Assessment of anthropogenic load on the territory of the Minsk Region of the Republic of Belarus // International Journal of Applied Sciences and Technology Integral. — 2020. — https://doi.org/10.24411/2658-3569-2020-10075 — (In Russian).
11. Kolmykov A. V. and Avdeev A. N. Production and soil-agroclimatic potential of agricultural organizations in Minsk Region // Bulletin of the Belarusian State Agricultural Academy. — 2021. — No. 3. — P. 191–200. — (In Russian). EDN: https://elibrary.ru/XNSSJV
12. Land Resources Register of the Republic of Belarus. — 2025. — URL: https://gki.gov.by/ru/activity_branches-landreestr/ (visited on 01/01/2026).
13. Liu Y., Dang C., Yue H., et al. Comparison between modified remote sensing ecological index and RSEI // National Remote Sensing Bulletin. — 2022. — Vol. 26, no. 4. — P. 683–697. — https://doi.org/10.11834/jrs.20229338 EDN: https://elibrary.ru/RNBGEL
14. Liu Y., Xu W., Hong Z., et al. Integrating three-dimensional greenness into RSEI improved the scientificity of ecological environment quality assessment for forest // Ecological Indicators. — 2023. — Vol. 156. — P. 111092. — https://doi.org/10.1016/j.ecolind.2023.111092 EDN: https://elibrary.ru/XBNXLV
15. Loginov V. F. and Struk M. I. Environmental problems of regional development in Belarus // Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya. — 2009. — No. 3. — P. 24–36. — (In Russian). EDN: https://elibrary.ru/KMLTED
16. Luo Z., Chai B. and Wang W. An improved RSEI-based evaluation for effective forest area by integrating forest structure and quality // Frontiers in Environmental Science. — 2025. — Vol. 13. — P. 1580169. — https://doi.org/10.3389/fenvs.2025.1580169 EDN: https://elibrary.ru/SYYFVU
17. Maimaitituersun A., Yang H., Aobuliaisan N., et al. Assessing subtle changes in arid land river basin ecological quality: A study utilizing the PIE engine platform and RSEI // Ecological Indicators. — 2025. — Vol. 170. — P. 113035. — https://doi.org/10.1016/j.ecolind.2024.113035 EDN: https://elibrary.ru/JRWGOS
18. Ning L., Jiayao W. and Fen Q. The improvement of ecological environment index model RSEI // Arabian Journal of Geosciences. — 2020. — Vol. 13, no. 11. — P. 403. — https://doi.org/10.1007/s12517-020-05414-7 EDN: https://elibrary.ru/BZOPHR
19. Pirozhnik I. I., Martsinkevich G. I., Vlasov B. P., et al. Integrated geographical research for ensuring sustainable development of Belarus // Bulletin of Belarusian State University. Series 2: Chemistry. Biology. Geography. — 2009. — No. 3. — P. 53–57. — (In Russian).
20. Sokolov A. S. Regional features of natural environment transformation of Belarus and geoecological zoning of it // Scientific Notes of V. I. Vernadsky Crimean Federal University. Geography. Geology. — 2017. — Vol. 3(69), no. 3–1. — P. 228–239. — (In Russian).
21. Vitchenko A. N., Vlasov B. P. and Martsinkevich G. I. Landscape-ecological research as an implementation of the sustainable development strategy of Belarus // Bulletin of Belarusian State University. Series 2: Chemistry. Biology. Geography. — 2009. — No. 1. — P. 81–88. — (In Russian).
22. Wang Z., Chen T., Zhu D., et al. RSEIFE: A new remote sensing ecological index for simulating the land surface ecoenvironment // Journal of Environmental Management. — 2023. — Vol. 326. — P. 116851. — https://doi.org/10.1016/j.jenvman.2022.116851 EDN: https://elibrary.ru/DASURW
23. Xiong Y., Xu W., 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 // Ecological Indicators. — 2021. — Vol. 125. — P. 107518. — https://doi.org/10.1016/j.ecolind.2021.107518 EDN: https://elibrary.ru/LXPYDD
24. Xu H., Wang Y., Guan H., et al. Prediction of ecological effects of potential population and impervious surface increases using a remote sensing based ecological index (RSEI) // Ecological Indicators. — 2018. — Vol. 93. — P. 730–740. — https://doi.org/10.1016/j.ecolind.2018.05.055
25. Xu H., Wang Y., Guan H., et al. Detecting ecological changes with a remote sensing based ecological index (RSEI) produced time series and change vector analysis // Remote Sensing. — 2019. — Vol. 11, no. 20. — P. 2345. — https://doi.org/10.3390/rs11202345
26. Yang W., Zhou Y. and Li C. Assessment of Ecological Environment Quality in Rare Earth Mining Areas Based on Improved RSEI // Sustainability. — 2023. — Vol. 15, no. 4. — P. 2964. — https://doi.org/10.3390/su15042964 EDN: https://elibrary.ru/HIRIDA
27. Yang X., Meng F., Fu P., et al. Time-frequency optimization of RSEI: A case study of Yangtze River Basin // Ecological Indicators. — 2022. — Vol. 141. — P. 109080. — https://doi.org/10.1016/j.ecolind.2022.109080 EDN: https://elibrary.ru/WYNNWQ
28. Yuan B., Fu L., Zou Y., et al. Spatiotemporal change detection of ecological quality and the associated affecting factors in Dongting Lake Basin, based on RSEI // Journal of Cleaner Production. — 2021. — Vol. 302. — P. 126995. — https://doi.org/10.1016/j.jclepro.2021.126995 EDN: https://elibrary.ru/FUEDKK
29. Zhang Y., She J., Long X., et al. Spatio-temporal evolution and driving factors of eco-environmental quality based on RSEI in Chang-Zhu-Tan metropolitan circle, central China // Ecological Indicators. — 2022. — Vol. 144. — P. 109436. — https://doi.org/10.1016/j.ecolind.2022.109436 EDN: https://elibrary.ru/QOYIRG
30. Zheng Z., Wu Z., Chen Y., et al. Instability of remote sensing based ecological index (RSEI) and its improvement for time series analysis // Science of The Total Environment. — 2022. — Vol. 814. — P. 152595. — https://doi.org/10.1016/j.scitotenv.2021.152595 EDN: https://elibrary.ru/EEMAQF



