Urban Climate Mitigation through NDVI and Albedo Monitoring: A Case Study in Kendari, Indonesia
DOI:
https://doi.org/10.32832/astonjadro.v15i2.23060Keywords:
spatial analysis, land use, NDVI, forest, Kendari.Abstract
The objective of this research is to apply spatial analysis of the Normalized Difference Vegetation Index (NDVI), albedo, and air temperature in Kendari City to identify the types of land use change resulting from changes in the vegetation of the Nipa-Nipa-forest area, the air temperature trend over the last 10 years, and to map areas with high mitigation needs. The method used is the spatial analysis of Landsat satellite imagery through supervised classification supported by ground check points to test the accuracy of 10 land use types. Air temperature analysis, and NDVI and albedo analysis are extracted from surface reflectance data to evaluate vegetation conditions and surface energy changes. The results show that air temperature variability is influenced by the duration of sun exposure and altitude. The diurnal pattern indicates that the temperature peaks at two in the afternoon and decreases again toward evening. At an altitude of 21.7 meters, the temperature is relatively lower during the day and higher at night compared to other layers. The Nipa-Nipa Grand Forest still dominates with the highest NDVI values, but has decreased in some zones due to forest fragmentation. Meanwhile, built-up areas and open land have experienced a significant increase with low NDVI values and high albedo, which indicates a reduction in vegetation quality and an increased potential for the urban heat island effect. Albedo values in vegetated areas, such as forests and mangroves, decreased between 2017 and 2022, indicating ecosystem degradation. The classification accuracy test yielded an overall accuracy of 94% and a Kappa value of 0.92, which shows a very high level of reliability and consistency with international research standards. The contribution of this research is to provide a spatial data-based scientific foundation regarding ecological dynamics in tropical urban areas, especially the role of the Nipa-Nipa Grand Forest as a climate buffer. These findings can support sustainable spatial planning, conservation strategies, and climate change mitigation efforts in Kendari City and similar regions.
References
[1] Arsyad, M., Iswandi, M., Kadir, I., & Putra, A. A. (2024). Coastal Areas Settlement Development–a Sustainable Model in Kendari City-indonesia. Future Cities & Environment.
[2] Pandey, B., & Ghosh, A. (2023). Urban ecosystem services and climate change: a dynamic interplay. Frontiers in Sustainable Cities, 5, 1281430.
[3] Artikanur, S. D., & June, T. (2019). Surface temperature and heat fluxes: Comparison between natural forest and oil palm plantation in Jambi Province using Surface Energy Balance Algorithm for Land (SEBAL). Agromet, 33(2), 62-70.
[4] Barati, A. A., Zhoolideh, M., Azadi, H., Lee, J. H., & Scheffran, J. (2023). Interactions of land-use cover and climate change at global level: How to mitigate the environmental risks and warming effects. Ecological Indicators, 146, 109829.
[5] Boussetta, S., Balsamo, G., Dutra, E., Beljaars, A., & Albergel, C. (2015). Assimilation of surface albedo and vegetation states from satellite observations and their impact on numerical weather prediction. Remote Sensing of Environment, 163, 111-126.
[6] BMKG. (2024). Catatan Iklim dan Kualitas Udara Indonesia 2024. BMKG.
[7] Coutts, A. M., Harris, R. J., Phan, T., Livesley, S. J., Williams, N. S., & Tapper, N. J. (2016). Thermal infrared remote sensing of urban heat: Hotspots, vegetation, and an assessment of techniques for use in urban planning. Remote sensing of environment, 186, 637-651
[8] Chanpichaigosol, N., Chaichana, C., & Rinchumphu, D. (2025). Urban heat island classification through alternative normalized difference vegetation index. Global Journal of Environmental Science and Management, 11(1), 57-76.
[9] Das, S., Choudhury, M. R., Chatterjee, B., Das, P., Bagri, S., Paul, D., Bera, M., & Dutta, S. (2024). Unraveling the urban climate crisis: Exploring the nexus of urbanization, climate change, and their impacts on the environment and human well-being–A global perspective. AIMS Public Health, 11(3), 963.
[10] Effendy, D. S., Rara, S. T., Nur, S. A., Jafarudin, S. D. P., Safitra, S., Rahmawati, S., & Amir, S. P. (2025). Analysis of the Effect of Climate Change on Public Health in Coastal Areas in Lapulu Village, Abeli Subdistrict, Kendari City in 2024. Journal of Epidemiology and Health Science, 2(1), 99-106.
[11] Esfandeh, S., Danehkar, A., Salmanmahiny, A., Sadeghi, S. M. M., & Marcu, M. V. (2021). Climate change risk of urban growth and land use/land cover conversion: An in-depth review of the recent research in Iran. Sustainability, 14(1), 338.
[12] Faradilla, R. H. F., Fyka, S. A., Putri, N. P., & Padangaran, N. B. (Eds.). (2020). Prosiding Seminar Nasional Pertanian: Pembangunan Pertanian dan Pangan di Era Disrupsi—Kendari, 25–26 Agustus 2020. UHO EduPress.
[13] Faria, T. D. O., Rodrigues, T. R., Curado, L. F. A., Gaio, D. C., & Nogueira, J. D. S. (2018). Surface albedo in different land-use and cover types in Amazon forest region. Revista Ambiente & Água, 13(2), e2120.
[14] Fasabbih, T. D., Pramono, D. A., Fadlin, F., & AP, A. B. S. (2025). Pemetaan Perubahan Kerapatan Vegetasi Mangrove di Kabupaten Berau Tahun 2019–2023 dengan Metode Normalized Difference Vegetation Index (NDVI). Journal of Geomatics Engineering, Technology, and Science, 3(2), 55-60.
[15] Feizizadeh, B., Blaschke, T., Nazmfar, H., Akbari, E., & Kohbanani, H. R. (2013). Monitoring land surface temperature relationship to land use/land cover from satellite imagery in Maraqeh County, Iran. Journal of Environmental Planning and Management, 56(9), 1290-1315.
[16] Guo, T., He, T., Liang, S., Roujean, J. L., Zhou, Y., & Huang, X. (2022). Multi-decadal analysis of high-resolution albedo changes induced by urbanization over contrasted Chinese cities based on Landsat data. Remote Sensing of Environment, 269, 112832.
[17] Hidalgo García, D. (2023). Evaluation and analysis of the effectiveness of the main mitigation measures against surface urban heat Islands in different local climate zones through remote sensing. Sustainability, 15(13), 10410.
[18] Hoornweg, D., & Pope, K. (2017). Population predictions for the world’s largest cities in the 21st century. Environment and urbanization, 29(1), 195-216.
[19] I'zzuddiin, M., Alina, A. N., Mahardianti, M. A., Yahya, F., & Prabawa, S. E. (2025). Analisis Perubahan Indeks Kerapatan Vegetasi Mangrove Menggunakan Algoritma Normalized Difference Vegetation Index (NDVI) di Pantai Timur Surabaya Berbasis Sistem Informasi Geografis (SIG). Jurnal Geodesi Undip, 14(1), 21-32.
[20] Kustas, W. P., & Norman, J. M. (1996). Use of remote sensing for evapotranspiration monitoring over land surfaces. Hydrological Sciences Journal, 41(4), 495-516.
[21] Limi, M. A., Sara, L., Ola, L. T., & Yunus, L. (2017). Environmental changes and fisherman welfare in coastal area of Kendari Bay. Journal of Agriculture, Forestry and Fisheries, 6(1), 20-25.
[22] Mohan, M., & Kandya, A. (2015). Impact of urbanization and land-use/land-cover change on diurnal temperature range: A case study of tropical urban airshed of India using remote sensing data. Science of the Total Environment, 506, 453-465.
[23] Munawir, A., June, T., Kusmana, C., & Setiawan, Y. (2019). Dynamics factors that affect the land use change in the Lore Lindu National Park. Proceeding of SPIE 11372, Event : Sixth Internasional Symposium on LAPAN-IPB Satelite. Bogor Indonesia.
[24] Munawir, A., June, T., Kusmana, C., & Setiawan, Y. (2022). SEBAL Model to Estimate Biophysics and Energy Flux Variable: Availability of Evapotranspiration Distribution Using Remote Sensing in Lore Lindu National Park. In IOP Conference Series: Earth and Environmental Science (Vol. 950, No. 1, p. 012022). IOP Publishing.
[25] McGregor, S., Cromsigt, J. P. G. M., Te Beest, M., Chen, J., Roy, D. P., Hawkins, H. J., & Kerley, G. I. H. (2024). Grassland albedo as a nature-based climate prospect: the role of growth form and grazing. Environmental Research Letters, 19(12), 124004.
[26] Rijal, S., Barkey, R. A., Nasri, & Nursaputra, M. (2019). Profile, level of vulnerability and spatial pattern of deforestation in Sulawesi period of 1990 to 2018. Forests, 10(2), 191.
[27] Ruan, L., Yan, M., Zhang, L., Fan, X., & Yang, H. (2022). Spatial-temporal NDVI pattern of global mangroves: A growing trend during 2000–2018. Science of The Total Environment, 844, 157075.
[28] Rusdiyanto, E., & Munawir, A. (2023). New built land threat of martapura river–implementation of environmental sustainability in Banjarmasin City, South Kalimantan, Indonesia. Journal of Ecological Engineering, 24(5).
[29] Sabajo, C. R., Le Maire, G., June, T., Meijide, A., Roupsard, O., & Knohl, A. (2017). Expansion of oil palm and other cash crops causes an increase of the land surface temperature in the Jambi province in Indonesia. Biogeosciences, 14(20), 4619-4635.
[30] Sugara, A., Lukman, A. H., Rudiastuti, A. W., Anggoro, A., Hidayat, M. F., Nugroho, F., Muslih, A.M., Suci, A.N.N., Zulhendri, R., & Rahmania, M. (2022). Utilization of Sentinel-2 Imagery in Mapping the Distribution and Estimation of Mangroves' Carbon Stocks in Bengkulu City. Geosfera Indonesia, 7(3), 219-235.
[31] Tahooni, A., Kakroodi, A. A., & Kiavarz, M. (2023). Monitoring of land surface albedo and its impact on land surface temperature (LST) using time series of remote sensing data. Ecological Informatics, 75, 102118.
[32] Tang, R., Zhao, X., Zhou, T., Jiang, B., Wu, D., & Tang, B. (2018). Assessing the impacts of urbanization on albedo in Jing-Jin-Ji Region of China. Remote Sensing, 10(7), 1096. https://doi.org/10.3390/rs10071096
[33] Touchaei, A. G., & Akbari, H. (2015). Evaluation of the seasonal effect of increasing albedo on urban climate and energy consumption of buildings in Montreal. Urban Climate, 14, 278-289.
[34] Trlica, A., Hutyra, L. R., Schaaf, C. L., Erb, A., & Wang, J. A. (2017). Albedo, land cover, and daytime surface temperature variation across an urbanized landscape. Earth's Future, 5(11), 1084-1101.
[35] Vahmani, P., & Ban‐Weiss, G. A. (2016). Impact of remotely sensed albedo and vegetation fraction on simulation of urban climate in WRF‐urban canopy model: A case study of the urban heat island in Los Angeles. Journal of Geophysical Research: Atmospheres, 121(4), 1511-1531.
[36] Vogelmann, J. E., Xian, G., Homer, C., & Tolk, B. (2012). Monitoring gradual ecosystem change using Landsat time series analyses: Case studies in selected forest and rangeland ecosystems. Remote Sensing of Environment, 122, 92-105.
[37] Wu, H., Huang, B., Zheng, Z., Ma, Z., & Zeng, Y. (2022). Spatial heterogeneity and temporal variation in urban surface albedo detected by high-resolution satellite data. Remote Sensing, 14(23), 6166.
[38] Zhu, Q., Chen, J., Wu, L., Huang, Y., Shao, C., Dong, G., Xu, Z.,u & Li, X. (2024). Changes in albedo and its radiative forcing of grasslands in East Asia drylands. Ecological Processes, 13(1), 1-15.
[39] Trlica, A., Hutyra, L. R., Schaaf, C. L., Erb, A., & Wang, J. A. (2017). Albedo, land cover, and daytime surface temperature variation across an urbanized landscape. Earth's Future, 5(11), 1084-1101.
[40] Richter, R. (2011). Atmospheric correction methods for optical remote sensing imagery of land. Advances in Environmental Remote Sensing: Remote Sensing Applications, 161-172.
[41] Iziomon, M. G., & Mayer, H. (2002). On the variability and modelling of surface albedo and long-wave radiation components. Agricultural and Forest Meteorology, 111(2), 141-152.
[42] Seidlitz, H. K., Thiel, S., Krins, A., & Mayer, H. (2001). Solar radiation at the Earth's surface. Comprehensive series in photosciences, 3, 705-738.
[43] Traversa, G., Fugazza, D., Senese, A., & Frezzotti, M. (2021). Landsat 8 OLI broadband albedo validation in Antarctica and Greenland. Remote Sensing, 13(4), 799.
[44] Mtshawu, B. (2021). Spatial estimation of surface soil texture using Landsat 8 data (Doctoral dissertation, University of the Free State).
[45] Wang, D., & Liang, S. (2016). Estimating high-resolution top of atmosphere albedo from Moderate Resolution Imaging Spectroradiometer data. Remote Sensing of Environment, 178, 93-103.
[46] Wiwoho, B. S., Phinn, S., & McIntyre, N. (2023). Two decades of land-use dynamics in an urbanizing tropical watershed: understanding the patterns and drivers. ISPRS International Journal of Geo-Information, 12(3), 92.
[47] Wicke, B., Sikkema, R., Dornburg, V., & Faaij, A. (2011). Exploring land use changes and the role of palm oil production in Indonesia and Malaysia. Land use policy, 28(1), 193-206.
[48] Hailu, T., Assefa, E., & Zeleke, T. (2024). Urban expansion induced land use changes and its effect on ecosystem services in Addis Ababa, Ethiopia. Frontiers in Environmental Science, 12, 1454556.
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