EventsThe 6th International Electronic Conference on Remote Sensing
Published
This submission belongs to the session S3. Remote Sensing in Semi-Arid and Arid Areas of the event The 6th International Electronic Conference on Remote Sensing
Published date
14 Oct, 2026
Academic Editor
author-avatarTimo Balz
Contribution&Funding
Conceptualization,
[Naila Nabeel Alqadsi]
Methodology,
[Naila Nabeel Alqadsi]
Formal analysis,
[Naila Nabeel Alqadsi]
Data curation,
[Naila Nabeel Alqadsi]
Writing - original draft,
[Naila Nabeel Alqadsi]
Supervision,
[Xi Zheng]
Funding: --
Citation
Naila Nabeel Alqadsi, Xi Zheng, Nadera Nabeel Alqadsi, Mapping Urban Heat Drivers and Cooling Priorities in Topographically Enclosed Districts: A Remote Sensing Framework Applied to Crater District, Aden, Yemen, in Proceedings of The 6th International Electronic Conference on Remote Sensing, 19 October–21 October 2026, MDPI: Basel, Switzerland
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Mapping Urban Heat Drivers and Cooling Priorities in Topographically Enclosed Districts: A Remote Sensing Framework Applied to Crater District, Aden, Yemen

Naila Nabeel Alqadsi 1
Nadera Nabeel Alqadsi 1
1. Landscape Architecture , Beijing Forestry University , Beijing , 100083, China
Abstract

Topographically enclosed urban districts, set within valleys, basins, or volcanic craters inside larger cities, may experience intensified surface heat, as the surrounding terrain restricts ventilation and traps warm air. This intra-urban form remains poorly characterized in data-scarce semi-arid and arid regions. We present a remote sensing framework to diagnose surface urban heat drivers and map cooling-priority zones, applied to Crater District, Aden, Yemen, inside an extinct volcanic caldera in an arid coastal climate.

Cloud-free Landsat 8/9 thermal imagery for the 2023-2025 hot season (43 scenes) was processed in Google Earth Engine to retrieve land surface temperature (LST) data, using the single-channel method with NDVI-based emissivity. A topographic enclosure index was derived from SRTM elevation data, calculated as the difference between the mean elevation of a 500 m neighborhood and each pixel's elevation, representing relative terrain depression and vegetation cover from NDVI. Surface Urban Heat Island Intensity (SUHII) was computed relative to the periphery, and the influence of enclosure and vegetation on LST was assessed via pixel-wise correlation (n = 2967) and Getis-Ord Gi* hot-spot analysis. Hot spots were overlaid with high-enclosure, low-vegetation zones to generate a cooling-priority map.

The mean district-interior LST reached 46.5C, which is marginally below the periphery (46.7C; SUHII ~ -0.2C). This modest district-wide SUHII reflects that the surrounding periphery is itself a hot, arid landscape rather than a cool baseline. Within the district, LST correlated positively with topographic enclosure (r = 0.235, p < 0.001) and weakly with vegetation cover (r = 0.101, p < 0.001), showing that more enclosed sub-areas experience elevated surface heat independent of the district's overall SUHII. Hot-spot analysis identified significant heat clusters covering approximately 0.14 km2, concentrated in the most enclosed, least vegetated sectors; these were flagged as the highest-priority zones for cooling intervention (~0.11 km2).

These findings indicate that topographic enclosure is a statistically significant driver of intra-urban surface heat variation in arid urban settings. The framework translates these drivers into a spatial cooling-priority map, offering a low-cost, transferable planning tool for topographically constrained districts in semi-arid and arid cities where ground data are limited.

Keywords
Urban heat island
Land surface temperature
Remote sensing
Arid urban climate
Google Earth Engine
Topographic enclosure
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