MAPPING VEGETATION DENSITY (NDVI) AND LAND SURFACE TEMPERATURE (LST) TO SUPPORT URBAN PLANNING ADAPTATION TO CLIMATE CHANGE IN SEMARANG CITY
Keywords:
NDVI, LST, Climate Change, Urban Planning, Semarang CityAbstract
Climate change is a global issue with significant implications for urban planning. This study examines Vegetation Density (NDVI) and Land Surface Temperature (LST) in Semarang City to support climate-adaptive urban planning. Using Landsat 8 imagery data from 2015 and 2023, analyzed through a Geographic Information System (GIS) approach, the findings reveal a substantial decline in vegetated areas. The moderately dense vegetation category decreased by 1,085.13 hectares (10.82%), while non-vegetated areas expanded by 1,988.64 hectares (30.05%). Additionally, there was a significant rise in surface temperature, from a maximum of 28.445°C in 2015 to 35.730°C in 2023. A strong negative correlation between NDVI and LST indicates that vegetation loss contributes to increased temperatures. To mitigate these effects, this study recommends adaptation strategies such as enhancing urban vegetation, expanding green open spaces, and implementing sustainable water management. These measures are expected to assist policymakers in developing strategies to enhance urban resilience to climate change.
Downloads
References
Aldrian, E., Pengkajian, B., & Teknologi, P. (2011). Adaptasi dan Mitigasi Perubahan Iklim di Indonesia. http://www.bmkg.go.id
Hatipah Yasmine, W., Jauhari, A., & Rina Muhayah Noor Pitri Program Studi Kehutanan, dan. (2022). Analisis Korelasi Nilai Normalized Difference Vegetation Index (Ndvi) Dengan Suhu Permukaan Tanah Di Khdtk Universitas Lambung Mangkurat. Jurnal Sylva Scienteae (Vol. 05, Issue 5).
Intergovernmental Panel on Climate Change (IPCC). (2023). Short-lived Climate Forcers. In Climate Change 2021 – The Physical Science Basis (pp. 817–922). Cambridge University Press. https://doi.org/10.1017/9781009157896.008
Ode Alwi, L., Gandri, L., Hidayat, H., Rahmatiah Tuwu, E., Bana, S., Fitriani, V., Indriyani, L. (2022). Analisis Spasial Fenomena Urban Heat Island Kota Kendari Menggunakan Algoritma Land Surface Temperature. Jurnal Meteorologi Dan Geofisika, 23(2), 109 - 118.
Oke, T. R. (1982). The energetic basis of the urban heat island. In Quart. J. R. Met. Soc (Vol. 108, Issue 455).
Boer, R. (2013). Penyusunan Rencana Aksi Daerah Adaptasi Perubahan Iklim. Laporan Kemajuan. DKI Jakarta
Wang, F., Qin, Z., Song, C., Tu, L., Karnieli, A., & Zhao, S. (2015). An improved mono-window algorithm for land surface temperature retrieval from landsat 8 thermal infrared sensor data. Remote Sensing, 7(4), 4268–4289. https://doi.org/10.3390/rs70404268
Yang, Y. Z., Cai, W. H., & Yang, J. (2017). Evaluation of MODIS land surface temperature data to estimate near-surface air temperature in Northeast China. Remote Sensing, 9(5). https://doi.org/10.3390/rs9050410
Esri Indonesia. (2022).Argis Pro. Diakses 1 Agustus 2024 dari https://esriindonesia.co.id/id/arcgis-pro
USGS (1879). EarthExplorer. Diakses 2 Agustus 2024 dari https://earthexplorer.usgs.gov/
NASA. (2013). Landsat 8. Diakses 5 Agustus 2024 dari https://landsat.gsfc.nasa.gov/satellites/landsat-8/
Badan Informasi Geospasial (2024). Data RBI Perwilayah. Diakses 1 Agustus 2024 dari https://tanahair.indonesia.go.id/
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Angga Kris Sahara, Vita Elysia
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
By Submitting your manuscript to our journal, your are following Copyright & License
.jpg)
