One of the essential anthropogenic influences on urban climate is land-use/land-cover (LULC) change due to urbanization, which has a direct impact on land surface temperature (LST). However, LULC changes affect LST, and further, urban heat island (UHI) still needs to be investigated. In this study, we estimated changes in LULC from 1993 to 2018, its warming (positive) and cooling (negative) effect, and their contribution to relative LST (RLST) in the city of Islamabad using satellite remote-sensing data. The LULC was classified using a random forest (RF) classifier, and LST was retrieved by a standardized radiative transfer equation (RTE). Our results reveal that the impervious surfaces has increased by 11.9% on the cost of declining barren land, forest land, grass/agriculture land, and water bodies in the last 26 years. LULC conversion contributed warming effects such as forest land, water bodies, and grass/agriculture land transformed into impervious surfaces, inducing a warming contribution of 1.52 °C. In contrast, the replacement of barren land and impervious surfaces by forest land and water bodies may have a cooling contribution of −0.85 °C to RLST. Furthermore, based on the standardized scale (10%) of LULC changes, the conversion of forest land into impervious surfaces contributed 1% compared to back conversion by −0.2%. The positive contribution to UHI due to the transformation of a natural surface to the human-made surface was found higher than the negative (cooler) contribution due to continued anthropogenic activities. The information will be useful for urban managers and decision makers in land-use planning to control the soaring surface temperature for a comfortable living environment and sustainable cities.

The credible urban heat island (UHI) trend is crucial for assessing the effects of urbanization on climate. Land surface temperature (LST) and near surface air temperature (SAT) have been extensively used to obtain UHI intensities. However, the consistency of UHI trend between LST and SAT has rarely been discussed. This paper quantified the temporal stability and trend consistency between Moderate Resolution Imaging Spectroradiometer (MODIS) LST and in situ SAT. Linear regressions, temporal trends and coefficients of variations (CV) were analyzed based on the yearly mean, maximum and minimum temperatures. The findings in this study were: (1) Good statistical consistency (R² = 0.794) and the same trends were found only in mean temperature between LST-UHI and SAT-UHI. There are 54% of cities that showed opposite temporal trends between LST-UHI and SAT-UHI for minimum temperature while the percentage was 38% for maximum temperature. (2) The high discrepancies in temporal trends were observed for all cities, which indicated the inadequacy of LST for obtaining reliable UHI trends especially when using the maximum and minimum temperatures. (3) The larger uncertainties of LST-UHI were probably due to high inter-annual fluctuations of LST. The topography was the predominant factor that affected the UHI variations for both LST and SAT. Therefore, we suggested that SAT should be combined with LST to ensure the dependable temporal series of UHI. This paper provided references for understanding the UHI effects on various surfaces.

As a major crop type in the global agroecosystem, paddy rice fields contribute to global greenhouse gas emissions. Surface albedo plays a vital role in estimating carbon emissions. However, it is difficult to find a broadband albedo estimation over paddy rice fields. The objective of this study was to derive an applicable method to improve albedo estimation over a paddy rice field. Field multiangle reflectance and surface albedo were collected throughout the growing season. A physically based model (AMBRALS) was utilized to reconstruct the directional reflectance into the spectral albedo. Multiple spectral albedos (at the wavelengths of 470, 550, 660, 850, 1243, 1640 and 2151 nm) were calculated, and new narrowband to broadband conversion coefficients were derived between the observed spectral albedo and broadband albedo. The conversion schemes showed high consistency with the field albedo observations in the shortwave (285–3000 nm), infrared (700–3000 nm), and visible (400–700 nm) bands. This method can help improve albedo estimation in partially submerged environments.