Skip to content
DraconiticResearch
Search Sources API
203,203 studies31 sourcesUpdated 5 min ago
Peer-reviewedCC BYGeocarto International

A remote sensing-based surface thermal stress index for assessing urban heat dynamics in Greater Cairo

  • Nesren Khairy1
  • Mona S. Ramadan2
  • Abdallah Bakhit Saleh3
  • Amany A. Elemam4
  • Mayada Abd el kader5
  • Ismail Y. Ismail4
  • Hossam Khedr2
  • Rasha H. Ramadan5
5 affiliations
  1. 1Environmental Studies Department, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt
  2. 2Geography and Urban Sustainability Department, College of Humanities & Social Sciences, UAE University, Al Ain, UAE
  3. 3Department of Geography, Faculty of Humanities and Social Sciences, University of N'Djamena, N'Djamena, Chad
  4. 4Department of Geography, Faculty of Art, Menoufia University, Shibin Al Kawm, Egypt
  5. 5Department of Geographic Information Systems, Remote Sensing, and Surveying, Faculty of Humanities, Egyptian Chinese University (ECU), Cairo, Egypt
Read full textDOICite

Abstract

Rapid urban growth has reshaped surface thermal conditions in Greater Cairo. This study applies a Surface Thermal Stress Index (STSI) integrating normalised land surface temperature (LST), NDVI, and NDBI from Landsat 8 annual composites processed in Google Earth Engine for 2015 and 2025. Higher STSI values indicate more favourable surface conditions rather than physiological thermal comfort. Using common spatial support, fixed pooled normalisation bounds, and weights of 0.35/0.30/0.35, mean LST decreased from 33.61 to 31.62 °C, while mean STSI increased from 0.44646 to 0.48248. The lowest score class, defined by a fixed 2015 quintile cutoff, contracted from 20.00% to 5.23% of the area. Alternative-weight maps remained strongly correlated with the baseline (r = 0.984–0.999), although priority-area boundaries varied. Year-matched population overlays, MODIS comparisons, and Landsat land-cover transitions provide demographic, thermal, and land-surface context. STSI offers a reproducible framework for preliminary daytime surface screening alongside component maps and sensitivity results.

Related

  1. Decadal dynamics of surface water extent and quality in Fujian Province, China: An integrated optical-SAR remote sensing analysis using Landsat and Sentinel-1 time series (2015–2024)
    Muhammad Irfan Ahamad, Yuping Su, Zabih Ullah +3
    Ecological IndicatorsPeer-reviewedCC BYFull textEnvironmental science & pollutionDOAJ
  2. TEPI: A transferable street-level framework for assessing urban thermal equity under data constraints
    Yanhuo Luo, Jiayi Luo
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textEnvironmental science & pollutionCrossref
  3. Assessing Dynamical Contributions to SWOT Sea Surface Height in an Internal Tide Hotspot
    Arne Bendinger, Clement Vic, Michel Tchilibou +2
    Geophysical Research LettersPeer-reviewedCC BY1 citedOceanography & cryosphereHAL
  4. Assessing SWOT capabilities for monitoring floodplain water dynamics in the Paraná Basin
    Edward Salameh, Lucas Sengsourinho, Cassandra Normandin +2
    Scientific ReportsPeer-reviewedCC BY 4.0Full text2 citedClimate scienceEnvironmental science & pollutionHAL
  5. Unraveling nonlinear ecosystem water use efficiency dynamics and environmental drivers across Iran using remote sensing and XGBoost-SHAP
    Majid Kazemzadeh
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textClimate scienceCrossref

Cite

BibTeXRIS
BibTeX
@article{khairy2026remote,
  title = {{A remote sensing-based surface thermal stress index for assessing urban heat dynamics in Greater Cairo}},
  author = {Nesren Khairy and Mona S. Ramadan and Abdallah Bakhit Saleh and Amany A. Elemam and Mayada Abd el kader and Ismail Y. Ismail and Hossam Khedr and Rasha H. Ramadan},
  journal = {Geocarto International},
  year = {2026},
  month = oct,
  doi = {10.1080/10106049.2026.2756834},
  url = {https://doi.org/10.1080/10106049.2026.2756834},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - A remote sensing-based surface thermal stress index for assessing urban heat dynamics in Greater Cairo
AU  - Nesren Khairy
AU  - Mona S. Ramadan
AU  - Abdallah Bakhit Saleh
AU  - Amany A. Elemam
AU  - Mayada Abd el kader
AU  - Ismail Y. Ismail
AU  - Hossam Khedr
AU  - Rasha H. Ramadan
PY  - 2026
DA  - 2026/10/31
JO  - Geocarto International
DO  - 10.1080/10106049.2026.2756834
UR  - https://doi.org/10.1080/10106049.2026.2756834
AB  - Rapid urban growth has reshaped surface thermal conditions in Greater Cairo. This study applies a Surface Thermal Stress Index (STSI) integrating normalised land surface temperature (LST), NDVI, and NDBI from Landsat 8 annual composites processed in Google Earth Engine for 2015 and 2025. Higher STSI values indicate more favourable surface conditions rather than physiological thermal comfort. Using common spatial support, fixed pooled normalisation bounds, and weights of 0.35/0.30/0.35, mean LST decreased from 33.61 to 31.62 °C, while mean STSI increased from 0.44646 to 0.48248. The lowest score class, defined by a fixed 2015 quintile cutoff, contracted from 20.00% to 5.23% of the area. Alternative-weight maps remained strongly correlated with the baseline (r = 0.984–0.999), although priority-area boundaries varied. Year-matched population overlays, MODIS comparisons, and Landsat land-cover transitions provide demographic, thermal, and land-surface context. STSI offers a reproducible framework for preliminary daytime surface screening alongside component maps and sensitivity results.
SN  - 1752-0762
SN  - 1010-6049
ER  -