Multitemporal Analysis of Land Surface Dynamics in Petroșani Municipality Using NDVI, NDWI, NBR and SAVI Spectral Indices During the 2020–2025 Period
References
- Foley J.A., DeFries R., Asner G.P., Barford C., Bonan G., Carpenter S.R., Chapin F.S., Coe M.T., Daily G.C., Gibbs H.K., Helkowski J.H., Holloway T., Howard E.A., Kucharik C.J., Monfreda C., Patz J.A., Prentice I.C., Ramankutty N., Snyder P.K., 2005 Global consequences of land use. Science, 309(5734): 570–574. https://doi.org/10.1126/science.1111772
- Turner B.L., Lambin E.F., Reenberg A., 2007 The emergence of land change science for global environmental change and sustainability, Proceedings of the National Academy of Sciences, 104(52): 20666–20671. https://doi.org/10.1073/pnas.070411910
- Verburg P.H., Neumann K., Nol L., 2011 Challenges in using land use and land cover data for global change studies, Global Change Biology, 17(2): 974–989. https://doi.org/10.1111/j.1365-2486.2010.02307.x
- Drusch M., Del Bello U., Carlier S., Colin O., Fernandez V., Gascon F., Hoersch B., Isola C., Laberinti P., Martimort P., Meygret A., Spoto F., Sy O., Marchese F., Bargellini P., 2012 Sentinel-2: ESA’s optical high-resolution mission for GMES operational services. Remote Sensing of Environment, 120: 25–36. https://doi.org/10.1016/j.rse.11.026
- Wulder M.A., Loveland T.R., Roy D.P., Crawford C.J., Masek J.G., Woodcock C.E., Allen R.G., Anderson M.C., Belward A.S., Cohen W.B., Dwyer J., Erb A., Gao F., Griffiths P., Helder D., Hermosilla T., Hipple J.D., Hostert P., Hughes M.J., Huntington J., Johnson D.M., Kennedy R., Kilic A., Li Z., Lymburner L., McCorkel J., Pahlevan N., Scambos T.A., Schaaf C., Schott J.R., Sheng Y., Storey J., Vermote E., Vogelmann J., Whitte J.C., Wynne R.H., Zhu Z., 2019 Current status of Landsat program, science, and applications. Remote Sensing of Environment, 225: 127–147. https://doi.org/10.1016/j.rse.02.015
- Delegido J., Verrelst J., Alonso L., Moreno J., 2011 Evaluation of Sentinel-2 red-edge bands for empirical estimation of green LAI and chlorophyll content, Sensors, 11(7): 7063–7081. https://doi.org/10.3390/s110707063
- Verrelst J., Camps-Valls G., Muñoz-Marí J., Rivera-Caicedo J.P., Moreno J., van der Tol C., 2019 Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties – A review. ISPRS Journal of Photogrammetry and Remote Sensing, 152: 90–113. https://doi.org/10.1016/j.isprsjprs.05.005
- Xue J., Su B., 2017 Significant remote sensing vegetation indices: A review of developments and applications, Journal of Sensors, 2017: 1353691. https://doi.org/10.1155/2017/1353691
- Rouse J.W., Haas R.H., Schell J.A., Deering D.W., 1974 Monitoring vegetation systems in the Great Plains with ERTS, NASA SP-351.
- Tucker C.J., 1979 Red and photographic infrared linear combinations for monitoring vegetation, Remote Sensing of Environment, 8(2): 127–150. Doi. 10.1016/0034-4257(79)90013-0
- Pettorelli N., Vik J.O., Mysterud A., Gaillard J.M., Tucker C.J., Stenseth N.C., 2005 Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology & Evolution, 20(9): 503–510. https://doi.org/10.1016/j.tree.05.011
- Huete A.R., 1988 A soil-adjusted vegetation index (SAVI), Remote Sensing of Environment, 25(3): 295–309. https://doi.org/10.1016/0034-4257(88)90106-X
- McFeeters S.K., 1996 The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features, International Journal of Remote Sensing, 17(7): 1425–1432. https://doi.org/10.1080/01431169608948714
- Gao B.-C., 1996 NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space, Remote Sensing of Environment, 58(3): 257–266. https://doi.org/10.1016/S0034-4257(96)00067-3
- Key C.H., Benson N.C., 2006 Landscape assessment: Ground measure of severity, the Composite Burn Index, and remote sensing of severity, the Normalized Burn Ratio, USDA Forest Service, Rocky Mountain Research Station.
- Telesca L., Lovallo M., Cardettini G., Aromando A., Abate N., Proto M., Loperte A., Masini N., Lasaponara R., 2023 Urban and peri-urban vegetation monitoring using satellite MODIS NDVI time series, singular spectrum analysis, and fisher–shannon statistical method. Sustainability, 15(14): 11039. https://doi.org/10.3390/su151411039
- Fairbairn A.J., Katholnigg S., Leichtle T., Merkens L., Schroll L., Weisser W.W., Meyer S.T., 2025 NDVI and vegetation volume as predictors of urban bird diversity. Scientific Reports, 15(1): 12863. https://doi.org/10.1038/s41598-025-96098-0
- Shang H., Zhan H.-Z., Ni W.-K., Liu Y., Gan Z.-H., Liu S.-H., 2022 Surface environmental evolution monitoring in coal mining subsidence area based on multi-source remote sensing data, Frontiers in Earth Science, 10: 790737. doi: 10.3389/feart.2022.790737
- Hong F., He G., Wang G., Zhang Z., Peng Y., 2023 Monitoring of land cover and vegetation changes in juhugeng coal mining area based on multi-source remote sensing data, Remote Sensing, 15(13): 3439; https://doi.org/10.3390/rs15133439
- Wang X., Liang Y., Geng Y., Huang K., 2026 Predicting carbon storage changes in coal mining regions: a remote sensing approach based on the PIM-PLUS-INVEST model, Scientific Reports, 16: 3568. https://doi.org/10.1038/s41598-025-33572-9
- Zhu Z., Wang S., Woodcock C.E., 2015 Improvement and expansion of the Fmask algorithm: Cloud, cloud shadow, and snow detection for Landsats 4–8 and Sentinel-2 imagery, Remote Sensing of Environment, 159: 269–277. doi. 10.1016/j.rse.2014.12.014
- Kennedy R.E., Yang Z., Braaten J., Copass C., Antonova N., Jordan C., Nelson P., 2018 Attribution of disturbance change agent from Landsat time-series in support of habitat monitoring, Remote Sensing of Environment, 221: 479–490. Doi. 10.1016/j.rse.2015.05.005
- Gorelick N., Hancher M., Dixon M., Ilyushchenko S., Thau D., Moore R., 2017 Google Earth Engine: Planetary-scale geospatial analysis for everyone, Remote Sensing of Environment, 202: 18–27. https://doi.org/10.1016/j.rse.2017.06.031
- Claverie M., Ju J., Masek J.G., Dungan J.L., Vermote E.F., Roger J.-C., Skakun S.V., Justice C., 2018 The Harmonized Landsat and Sentinel-2 surface reflectance data set. Remote Sensing of Environment, 219: 145–161. https://doi.org/10.1016/j.rse.09.002
- Phiri D., Simwanda M., Salekin S., Nyirenda V.R., Murayama Y., Ranagalage M., 2020 Sentinel-2 data for land cover/use mapping: A review, Remote Sensing, 12(14): 2291. https://doi.org/10.3390/rs12142291
- Nimară C., Tofan G.B., 2015 The impact of mining activities on the west of Petroșani Depression and identification of affected geomorphological resources, Case study: Aninoasa–Vulcan–Lupeni sector. Studia Universitatis Babeș-Bolyai Geographia, 60(2): 27–34.
- Faur F., Marchiș D., Nistor C., 2017 Evolution of the coal mining sector in Jiu Valley in terms of sustainable development and current socio-economic implications, Research Journal of Agricultural Science, 49(4): 110–117.
- Faur F., Apostu I.-M., 2019 The impact and the risk of abandoned buildings from Petroșani City on the urban environment, Studia Universitatis Babeș-Bolyai Ambientum, 64(2): 11–30. Doi. 10.24193/subbambientum.2019.2.02.
- Negoe L., Apostu I.-M., Faur F., Lazăr M., 2019 Assessment of the urban landscape of Petroșani Municipality and the impact of abandoned buildings on it, Research Journal of Agricultural Science, 51(4): 104–114.
- Vorovencii I., 2021 Changes detected in the extent of surface mining and reclamation using multitemporal Landsat imagery: A case study of Jiu Valley, Romania, Environmental Monitoring and Assessment, 193(1): 30. Doi. 10.1007/s10661-020-08834-w.
- Vorovencii I., 2024 Long-term land cover changes assessment in the Jiului Valley mining basin in Romania, Frontiers in Environmental Science, 12: 1320009. https://doi.org/10.3389/fenvs.2024.1320009
- Veto I., Avădanei M., Țârle Burescu F., Vușcan A., Sala F., Herbei M.V., 2025 Characterization of the Jiu Valley Mining Basin, Romania, using remote sensing techniques in relation to land use categories and relief parameters, Life Science and Sustainable Development, 6(2): 111–121. https://doi.org/10.58509/1ngsg630
- Google., Google Maps., 2026 Map and satellite imagery of Petroșani Municipality, Hunedoara County, Romania, Google LLC. Available online: Google Maps (accessed on 29 August 2026).
- Agenția Națională de Cadastru și Publicitate Imobiliară (ANCPI)., 2024 Geoportal ANCPI – Administrative boundaries [Geospatial dataset], National Agency for Cadastre and Land Registration, Bucharest, Romania. (Accessed 15 July, 2026).
- Hammer Ø., Harper D.A.T., Ryan P.D., 2001 PAST: Paleontological Statistics software package for education and data analysis, Palaeontologia Electronica, 2001, 4(1): 1-9.
- JASP Team., 2022 JASP (Version 0.16.2) [Computer software]
- Wolfram Research I., 2024 Mathematica, Version 14.2, Champaign, IL
Language: English
Page range: 33 - 47
Submitted on: Aug 10, 2026
Accepted on: Sep 10, 2026
Published on: Oct 6, 2026
Published by: University of Petrosani
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
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© 2026 Mihai Valentin Herbei, Roxana Claudia Herbei, Florin Sala, published by University of Petrosani
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