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Volume 13 | Issue 9 | Year 2026 | Article Id. IJCE-V13I9P115 | DOI : https://doi.org/10.14445/23488352/IJCE-V13I9P115

Remote Sensing-based Integration of Land Use/Land Cover, Vegetation Cover, and Land Surface Temperature with Hydrological Implications in Tikrit City, Iraq

Omar Taher Nafe’e, Dalia Shaker Mahdi, Lubna B. Mahmood, Asmaa Abdul Jabbar Jamel

Received Revised Accepted Published
15 Jul 2026 24 Aug 2026 03 Sep 2026 29 Sep 2026

Citation :

Omar Taher Nafe’e, Dalia Shaker Mahdi, Lubna B. Mahmood, Asmaa Abdul Jabbar Jamel, "Remote Sensing-based Integration of Land Use/Land Cover, Vegetation Cover, and Land Surface Temperature with Hydrological Implications in Tikrit City, Iraq," International Journal of Civil Engineering, vol. 13, no. 9, pp. 256-272, 2026. Crossref, https://doi.org/10.14445/23488352/IJCE-V13I9P115

Abstract

This study examines the integrated relationship among Land Use/Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST), with hydrological implications, in Tikrit City, Iraq, using Landsat data acquired in 2017 and 2025. LULC, NDVI, and LST layers were prepared using the same spatial boundary, and 4124 paired sample points were extracted from identical locations to support temporal and statistical comparison. The LULC results showed a clear reduction in Soil from 70.52% in 2017 to 49.88% in 2025, whereas Vegetation increased from 25.49% to 44.12%. Built Area also increased from 3.08% to 4.90%, indicating moderate urban expansion. The dominant land-cover transition was from Soil to Vegetation, covering 66,014.66 ha. Mean NDVI increased significantly from 0.061 to 0.075, while mean LST remained statistically stable, changing only from 41.992°C to 42.031°C. However, non-parametric tests indicated that the spatial distribution of LST changed significantly. The NDVI–LST relationship was positive in both years, with Pearson correlation increasing from 0.670 in 2017 to 0.709 in 2025. Regression analysis showed that NDVI explained 44.9% and 50.2% of LST variation in 2017 and 2025, respectively. Class-based analysis indicated that the dominant heat-contributing class shifted from Soil in 2017 to Built Area in 2025. These findings show that surface thermal behavior in Tikrit City cannot be explained by vegetation cover alone, but depends on land-cover composition, mixed pixels, agricultural activity, soil exposure, surface moisture, and seasonal conditions. From a hydrological perspective, the reduction of exposed soil, expansion of vegetation, and growth of built-up areas have implications for infiltration opportunity, runoff potential, evapotranspiration tendency, and surface moisture retention.

Keywords

Hydrological implications, Land Use/Land Cover, Vegetation index, Land surface temperature, Landsat, Remote sensing.

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