Identification of Land Use, Land Cover Change, and Land Surface Temperature (LST) in Ethiopia using Landsat and MODIS Data, East Africa
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This study investigated land use and land cover (LULC) dynamics and their influence on land surface temperature (LST) using multi-temporal Landsat and MODIS satellite imagery. Supervised classification employing the Maximum Likelihood Algorithm was applied to classify LULC patterns, and classification accuracy was assessed following standard validation procedures to ensure reliability for environmental monitoring, water resource management, and climate change assessment. Trend and change detection analyses were conducted to evaluate the spatial and temporal variability of LULC and LST within the study area. The results identified 15 major LULC classes and revealed substantial expansion and contraction among different land cover types over time, accompanied by significant variations in LST. Grassland was the dominant land cover category, accounting for more than 36.53% of the total area. In contrast, the evergreen needle-leaf forest was the least extensive class, covering less than 0.0014% of the study area. The observed changes in LULC and associated thermal characteristics are primarily attributed to both anthropogenic activities and natural environmental processes, which directly influence hydrological conditions, including precipitation, evaporation, streamflow, and water quality dynamics. The findings highlight the strong interrelationship between land-cover transformation and surface thermal responses, emphasising the implications of uncontrolled land-use changes for hydrological balance and ecosystem sustainability. Therefore, the study recommends continuous monitoring and effective management of LULC changes, particularly settlement expansion and deforestation, to mitigate potential environmental degradation and hydrological imbalance within the catchment.
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Ayele, A., Tarekegn, K. (2020). The impact of urbanisation expansion on agricultural land in Ethiopia: A review. Environ. Socio-Econ. Stud. 8, 73–80. DOI: https://doi.org/10.2478/environ-2020-0024
Samal, D.R., Gedam, S. (2021). Assessing the Impacts of Land Use and Land Cover Change on Water Resources in the Upper Bhima River Basin, India. Environ. Chall. 5, 100251.DOI: https://doi.org/10.1016/j.envc.2021.100251
Calicioglu, O., Flammini, A., Bracco, S., Bellù, L., Sims, R. (2019). The Future Challenges of Food and Agriculture: An Integrated Analysis of Trends and Solutions. Sustainability 11, 222.DOI: https://doi.org/10.3390/su11010222
Zabihi, M., Moradi, H., Gholamalifard, M., Khaledi Darvishan, A., Fürst, C. (2020). Landscape Management through Change Processes Monitoring in Iran—Sustainability 12, 1753. DOI: https://doi.org/10.3390/su12051753
Das, S., Sarkar, R. (2019). Predicting the land use and land cover change using Markov model: a catchment level analysis of the Bhagirathi-Hugli River, Spatial Inf. Res. 27 (2019) 439e452, DOI: https://doi.org/10.1007/s41324-019-00251-7.
Tan, J., Yu, D., Li, Q., Tan, X., Zhou, W. (2020). Spatial relationship between land-use/ land-cover change and land surface temperature in the Dongting Lake area, China, Sci. Rep. 10 (2020) 1e9, DOI: https://doi.org/10.1038/s41598-020-66168-6.
Zoungrana, B.J.B., Conrad, C., Amekudzi, L.K., Thiel, M., Da, E.D., Forkuor, G., Low, F. (2015). Multi-temporal Landsat images and ancillary data for land-use/land-cover change (LULCC) detection in southwestern Burkina Faso, West Africa, Rem. Sens. 7 (2015) 12076e12102, DOI: https://doi.org/10.3390/rs70912076.
Cai, M., Ren, C., Xu, Y., Lau, K.K.L., Wang, R. (2018). Investigating the relationship between local climate
zone and land surface temperature
using an improved WUDAPT methodology - a case study of the Yangtze River Delta, China, Urban Clim. 24 (2018) 485e502, DOI: https://doi.org/10.1016/j.uclim.2017.05.010.
Khan, M.S., Ullah, S., Sun, T., Rehman, A.U., Chen, L. (2020). Land-use/land-cover changes and their contribution to urban heat Island: a case study of Islamabad, Pakistan, Sustainability 12 (2020), DOI: https://doi.org/10.3390/su12093861
Ayele, G.T., Tebeje, A.K., Demissie, S.S., Belete, M.A., Jemberrie, M.A., Teshome, W.M., Mengistu, D.T., Teshale, E.Z. (2018). Time-series land-cover mapping and change-detection analysis using a geographic information system and remote sensing, Northern Ethiopia, Air Soil. Water Res. 11 (2018), DOI: https://doi.org/10.1177/1178622117751603.
Mondal, I., Thakur, S., Ghosh, P., De, T.K., Bandyopadhyay, J. (2019). Land Use/Land Cover Modelling of Sagar Island, India Using Remote Sensing and GIS Techniques, Springer Singapore, DOI: https://doi.org/10.1007/978-981-13-1951-8_69.
Thakur, S., Maity, D., Mondal, I., Basumatary, G., Ghosh, P.B., Das, P., De, T.K. (2021). Assessment of Changes in Land Use, Land Cover, and Land Surface Temperature in the Mangrove Forest of Sundarbans, Northeast Coast of India, Environ. Dev. Sustain. 23 (2021) 1917e1943, DOI: https://doi.org/10.1007/s10668-020-00656-7.
Saleem, M.S., Ahmad, S.R., Shafiq-Ur-Rehman, Javed, M.A. (2020). Impact assessment of urban development patterns on land surface temperature using remote sensing techniques: a case study of Lahore, Faisalabad, and Multan districts, Environ. Sci. Pollut. Control Ser. 27 (2020) 39865e39878, DOI: https://doi.org/10.1007/s11356-020-10050-5.
Pepin, N., Deng, H., Zhang, H., Zhang, F., Kang, S., Yao, T. (2019). An Examination of temperature trends at high Elevations across the Tibetan plateau: the use of MODIS LST to understand patterns of Elevation-Dependent Warming, J. Geophys. Res. Atmos. 124 (2019) 5738e5756, DOI: https://doi.org/10.1029/2018JD029798.
Prakash, S., Norouzi, H. (2020). Land surface temperature variability across India: a remote sensing satellite perspective, Theor. Appl. Climatol. 139 (2020) 773e784, DOI: https://doi.org/10.1007/s00704-019-03010-8.
John, J., Bindu, G., Srimuruganandam, B., Wadhwa, A., Rajan, P. (2020). Land use/land cover and land surface temperature analysis in Wayanad district, India, using satellite imagery, Spatial Sci. 26 (2020) 343e360, DOI: https://doi.org/10.1080/19475683.2020.1733662.
Bayissa, Y., Tadesse, T., Demisse, G., & Shiferaw, A. (2017). Evaluation of Satellite-Based Rainfall Estimates and Application to Monitor Meteorological Drought for the Upper Blue Nile Basin, Ethiopia. Remote Sensing, 9(7), 669. DOI: https://doi.org/10.3390/rs9070669
Lemma, E., Upadhyaya, S., and Ramsankaran, R. (2022). Meteorological drought monitoring across the main river basins of Ethiopia using satellite rainfall products. Environmental Systems Research, 2–15. DOI: http://doi.org/10.1186/s40068-022-00251-x.
Yoshe, A.K. (2024). Water availability identification from GRACE dataset and GLDAS hydrological model over data-scarce river basins of Ethiopia, Hydrological Sciences Journal, 69:6, 721-745, DOI: http://doi.org/10.1080/02626667.2024.2333852
Ramachandran, R.M., Reddy, C.S. (2017). Monitoring of deforestation and land-use changes (1925–2012) in Idukki district, Kerala, India, using remote sensing and GIS, J. Indian Soc. Remote Sens. 45 (1) 163–170, DOI: https://doi.org/10.1007/s12524-015-0521-x.
Basukala, A.K., Oldenburg, C., Schellberg, J., Sultanov, M., Dubovyk, O. (2017). Towards improved land use mapping of irrigated croplands: performance assessment of different image classification algorithms and approaches, Eur. J. Remote Sens. 50 (1) 187–201, DOI: https://doi.org/10.1080/22797254.2017.1308235
Dibaba, W.T., Demissie, T.A., Miegel, K. (2020). Drivers and Implications of Land Use/Land Cover Dynamics in Finchaa Catchment, Northwestern Ethiopia. Land, 9, 113.DOI: https://doi.org/10.3390/land9040113
Minta, M., Kibret, K., Thorne, P., Nigussie, T., Nigatu, L. (2018). Land Use and Land Cover Dynamics in Dendi-Jeldu Hilly-Mountainous Areas in the Central Ethiopian Highlands. Geoderma 2018, 314, 27–36.DOI: https://doi.org/10.1016/j.geoderma.2017.10.035
Yoshe, A.K. 2025. Land use land cover detections using MODIS MCD12Q1 V6.1 and ESRI Sentinel-2 datasets in the Lake Chamo catchment. H2Open Journal (2025) 8 (1): 20–41, DOI: https://doi.org/10.2166/h2oj.2024.038.
Srivastava, A., Kumari, N. & Maza, M. (2020) Hydrological response to agricultural land use heterogeneity using variable infiltration capacity model, Water Resour. Manag., 34, 3779–3794.DOI: https://doi.org/10.1007/s11269-020-02630-4
Yesuph, A. Y. & Dagnew, A. B. (2019). Land Use/Cover spatiotemporal dynamics, driving forces, and implications in the Beshillo catchment of the Blue Nile basin, northeastern highlands of Ethiopia, Environ. Syst. Res., 8, 21. DOI: https://doi.org/10.1186/s40068-019-0148-y
Li, X., Zhou, Y., Asrar, G.R., Zhu, Z. (2018). Creating a seamless 1 km resolution daily land surface temperature dataset for urban and surrounding areas in the conterminous United States, Remote Sens. Environ. 206 (2018) 84e97, DOI: https://doi.org/10.1016/j.rse.2017.12.010.
Mal, S., Rani, S., Maharana, P. (2021). Estimation of spatio-temporal variability in land surface temperature over the Ganga River Basin using MODIS data. Estimation of spatio-temporal variability in land surface temperature over the Ganga River Basin using MODIS data, Geocarto Int. 1e23, DOI: https://doi.org/10.1080/10106049.2020.1869331.
Aliani, H., Malmir, M., Sourodi, M., Kafaky, S.B. (2019). Change detection and prediction of urban land-use changes using the CA–Markov model (case study: Talesh County). Environ. Earth Sci. 78, 546. DOI: https://doi.org/10.1007/s12665-019-8557-9
da Cunha, E.R., Santos, C.A.G., da Silva, R.M., Bacani, V.M., Teodoro, P.E., Panachuki, E., de Souza Oliveira, N. (2020). Mapping LULC types in the Cerrado-Atlantic Forest ecotone region using a Landsat time series and object-based image approach: A case study of the Prata River Basin, Mato Grosso do Sul, Brazil. Environ. Monit. Assess. 192, 136.DOI: https://doi.org/10.1007/s10661-020-8093-9
Rimal, B., Zhang, L., Keshtkar, H., Haack, B.N., Rijal, S., Zhang, P. (2018). Land Use/Land Cover Dynamics and Modelling of Urban Land Expansion by the Integration of Cellular Automata and Markov Chain. ISPRS Int. J. Geo-Inf. 7, 154. DOI: https://doi.org/10.3390/ijgi7040154
Mirchooli, F., Mahboobeh Kiani-Harchegani, Abdulvahed Khaledi Darvishan, Samereh Falahatkar, Seyed Hamidreza Sadeghi, Spatial distribution dependency of soil organic carbon content to important environmental variables, Ecological Indicators, Volume 116, 2020, 106473, DOI: https://doi.org/10.1016/j.ecolind.2020.106473.
Chen, X., and Zhang, Y. (2017). “Impacts of Urban Surface Characteristics on Spatiotemporal Pattern of Land Surface Temperature in Kunming, China.”Sustainable Cities and Society 32: 87–99.DOI: http://doi.org/10.1016/j.scs.2017.03.013.
Guha, S., and H. Govil. (2021). “An Assessment on the Relationship between Land Surface Temperature and Normalised Difference Vegetation Index.” Environment, Development and Sustainability 23 (2): 1944–1963. DOI: http://doi.org/10.1007/s10668-020-00657-6
Roşca, C. F., Harpa, G. V., Croitoru, A. E., Herbel, I., Imbroane, A. M. and Burada, D. C. (2017). “The Impact of Climatic and Non-climatic Factors on Land Surface Temperature in Southwestern Romania.” Theoretical and Applied Climatology 130: 775–790. DOI: http://doi.org/10.1007/s00704-016-1923-6.
Ali, J. M., Marsh, S. H. and Smith, M. J. (2017). “A Comparison between London and Baghdad Surface Urban Heat Islands and Possible Engineering Mitigation Solutions.”Sustainable Cities and Society 29: 159–168. DOI: http://doi.org/10.1016/j.scs.2016.12.010.
Madanian, M., Soffianian, A. R., Koupai, S. S., Pourmanafi, S., and Momeni, M. (2018). “The Study of Thermal Pattern Changes Using Landsat-derived Land Surface Temperature in the Central Part of Isfahan Province.” Sustainable Cities and Society 39: 650–661. DOI: http://doi.org/10.1016/j.scs.2018.03.018.
Pal, S., and Ziaul, S. (2017). “Detection of Land Use and Land Cover Change and Land Surface Temperature in EnglishBazar Urban Centre.” The Egyptian Journal of Remote Sensing and Space Sciences 20: 125–145. DOI: http://doi.org/10.1016/j.ejrs.2016.11.003.
Zhang, F., Kung, H., Johnson, V. C., LaGrone, B. I. andWang, J.(2017). “Change Detection of Land Surface Temperature (LST) and Some Related Parameters Using Landsat Image: A Case Study of the Ebinur Lake Watershed, Xinjiang, China.” Wetlands 1–16. DOI: http://doi.org/10.1007/s13157-017-0957-6.
Tayyebi, A., H. Shafizadeh-Moghadam, and Tayyebi, A. H. (2018). “Analysing Long-term Spatio-temporal Patterns of Land Surface Temperature in Response to Rapid Urbanisation in the Mega-city of Tehran.” Land Use Policy 71: 459–469. S. H. SADEGHI ET AL.DOI: https://doi.org/10.1016/j.landusepol.2017.11.023.14
Jafari, R., and Hasheminasab, S. (2017). “Assessing the Effects ofDam Building on Land Degradation in Central Iran with Landsat LST and LULC Time Series.” Environmental Monitoring and Assessment 189: 74. DOI: http://doi.org/10.1007/s10661-017-5792-y.
Tan, J., Yu, D., Li, Q., Tan, X.and Zhou, W. (2020). “Spatial Relationship between Land-use/land-cover Change and Land Surface Temperature in the Dongting Lake Area, China.” Scientific Reports 10 (1): 1–9. DOI: http://doi.org/10.1038/s41598-019-56847-4.
Mustafa, E. K., Liu, G., El-Hamid, A., Hazem, T. and Kaloop, M. R. (2021). “Simulation of Land Use Dynamics and Impact on Land Surface Temperature Using Satellite Data.” GeoJournal 86 (3):1089–1107. DOI: http://doi.org/10.1007/s10708-019-10115-0.
Monteiro, L., Sentelhas, P. & Pedraa, G. U. (2018) Assessment of NASA/POWER satellite-based weather system for Brazilian conditions and its impact on sugarcane yield simulation, Int. J. Climatol., 38,
–1581. DOI: https://doi.org/10.1002/joc.5282
Hoylman, Z. H., Jencso, K. G., Hu, J., Martin, J. T., Holden, Z. A., Seielstad, C. A., & Rowell, E. M. (2018). Hillslope topography mediates spatial patterns of ecosystem sensitivity to climate, J. Geophys. Res.: Biogeosci., 123, 353–371. DOI: https://doi.org/10. 1002/2017JG004108.
Chen, X., Jiang, L., Zhang, G., Meng, L., Pan, Z., Lun, F., & An, P. (2021). Green-depressing cropping system: a referential land use practice for fallow to ensure a harmonious human-land relationship in the farming-pastoral ecotone of northern China, Land Use Policy, 100, 104917. DOI: https://doi.org/10.1016/j.landusepol.2020.104917.
Guo, Y., Fang, G., Xu, Y. P., Tian, X. & Xie, J. (2020). Identifying how future climate and land use/cover changes impact streamflow in Xinanjiang Basin, East China. Sci. Total Environ., 710 (2020), Article 136275. DOI: https://doi.org/10.1016/j.scitotenv.2019.136275