Abstract
This study aims to evaluate the effectiveness of Object-Based Image Analysis (OBIA) in classifying high-resolution satellite and drone imagery, and its application in mapping the distribution of Land Surface Temperature (LST) in Malang City parks. Malang was chosen because of its unique urban dynamics and the challenges faced in managing the urban heat island effect. Using data from thermal UAVs, this study provides a detailed analysis of urban microscale green spaces. OBIA is applied to classify areas based on surface material and vegetation, resulting in an accurate mapping of LST variations. The results show that areas with dense vegetation such as Merdeka Square Park have lower LST values, while areas with hard surfaces such as asphalt and concrete show higher LST values. This study reveals that 22.13% of the area has very low temperatures (31-36℃) and 30.05% with high temperatures (46-51℃). The implications of these results are very relevant for policy development, showing that increasing urban green space, planting wide canopy trees, using environmentally friendly materials, and adding water elements have a significant impact on reducing the urban heat island effect and increasing thermal comfort. These recommendations can be integrated into the urban planning strategy of Malang and other cities with similar characteristics to support the sustainability of the urban environment globally.
| Original language | English |
|---|---|
| Pages (from-to) | 1633-1644 |
| Number of pages | 12 |
| Journal | International Journal of Sustainable Development and Planning |
| Volume | 20 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Apr 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
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SDG 17 Partnerships for the Goals
Keywords
- climate mitigation
- LST
- OBIA
- remote sensing
- unmanned aerial vehicles (UAV)
- urban green spaces
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