Spatial Distribution of Land Surface Temperatures in Kuwait: Urban Heat and Cool Islands.
ABSTRACT: The global rise of urbanization has led to the formation of surface urban heat islands and surface urban cool islands. Urban heat islands have been shown to increase thermal discomfort, which increases heat stress and heat-related diseases. In Kuwait, a hyper-arid desert climate, most of the population lives in urban and suburban areas. In this study, we characterized the spatial distribution of land surface temperatures and investigated the presence of urban heat and cool effects in Kuwait. We used historical Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra satellite 8-day composite land surface temperature (LST) from 2001 to 2017. We calculated the average LSTs of the urban/suburban governorates and compared them to the average LSTs of the rural and barren lands. We repeated the analysis for daytime and nighttime LST. During the day, the temperature difference (urban/suburban minus versus governorates) was -1.1 °C (95% CI; -1.2, -1.00, p < 0.001) indicating a daytime urban cool island. At night, the temperature difference (urban/suburban versus rural governorates) became 3.6 °C (95% CI; 3.5, 3.7, p < 0.001) indicating a nighttime urban heat island. In light of rising temperatures in Kuwait, this work can inform climate change adaptation efforts in the country including urban planning policies, but also has the potential to improve temperature exposure assessment for future population health studies.
Project description:Urban forms and functions have critical impacts on urban heat islands (UHIs). The concept of a "local climate zone" (LCZ) provides a standard and objective protocol for characterizing urban forms and functions, which has been used to link urban settings with UHIs. However, only a few structure types and surface cover properties are included under the same climate background or only one or two time scales are considered with a high spatial resolution. This study assesses multi-temporal land surface temperature (LST) characteristics across 18 different LCZ types in Beijing, China, from July 2017 to June 2018. A geographic information system-based method is employed to classify LCZs based on five morphological and coverage indicators derived from a city street map and Landsat images, and a spatiotemporal fusion model is adopted to generate hourly 100-m LSTs by blending Landsat, Moderate Resolution Imaging Spectroradiometer (MODIS), and FengYun-2F LSTs. Then, annual and diurnal cycle parameters and heat island and cool island (HI or CI) frequency are linked to LCZs at annual, seasonal, monthly, and diurnal scales. Results indicate that: (1) the warmest zones are compact and mid and low-rise built-up areas, while the coolest zones are water and vegetated types; (2) compact and open high-rise built-up areas and vegetated types have seasonal thermal patterns but with different causes; (3) diurnal temperature ranges are the highest for compact and large low-rise settings but the lowest for water and dense or scattered trees; and (4) HIs are the most frequent summertime and daytime events, while CIs occur primarily during winter days, making them more or less frequent for open or compact and high- or low-rise built-up areas. Overall, the distinguishable LSTs or UHIs between LCZs are closely associated with the structure and coverage properties. Factors such as geolocation, climate, and layout also interfere with the thermal behavior. This study provides comprehensive information on how different urban forms and functions are related to LST variations at different time scales, which supports urban thermal regulation through urban design.
Project description:In this study Yan'an City, a typical hilly valley city, was considered as the study area in order to explain the relationships between the surface urban heat island (SUHI) and land use/land cover (LULC) types, the landscape pattern metrics of LULC types and land surface temperature (LST) and remote sensing indexes were retrieved from Landsat data during 1990-2015, and to find factors contributed to the green space cool island intensity (GSCI) through field measurements of 34 green spaces. The results showed that during 1990-2015, because of local anthropogenic activities, SUHI was mainly located in lower vegetation cover areas. There was a significant suburban-urban gradient in the average LST, as well as its heterogeneity and fluctuations. Six landscape metrics comprising the fractal dimension index, percentage of landscape, aggregation index, division index, Shannon's diversity index, and expansion intensity of the classified LST spatiotemporal changes were paralleled to LULC changes, especially for construction land, during the past 25 years. In the urban area, an index-based built-up index was the key positive factor for explaining LST increases, whereas the normalized difference vegetation index and modified normalized difference water index were crucial factors for explaining LST decreases during the study periods. In terms of the heat mitigation performance of green spaces, mixed forest was better than pure forest, and the urban forest configuration had positive effects on GSCI. The results of this study provide insights into the importance of species choice and the spatial design of green spaces for cooling the environment.
Project description:Land surface temperature (LST) can reflect the land surface water-heat exchange process comprehensively, which is considerably significant to the study of environmental change. However, research about LST in karst mountain areas with complex topography is scarce. Therefore, we retrieved the LST in a karst mountain area from Landsat 8 data and explored its relationships with LUCC and NDVI. The results showed that LST of the study area was noticeably affected by altitude and underlying surface type. In summer, abnormal high-temperature zones were observed in the study area, perhaps due to karst rocky desertification. LSTs among different land use types significantly differed with the highest in construction land and the lowest in woodland. The spatial distributions of NDVI and LST exhibited opposite patterns. Under the spatial combination of different land use types, the LST-NDVI feature space showed an obtuse-angled triangle shape and showed a negative linear correlation after removing water body data. In summary, the LST can be retrieved well by the atmospheric correction model from Landsat 8 data. Moreover, the LST of the karst mountain area is controlled by altitude, underlying surface type and aspect. This study provides a reference for land use planning, ecological environment restoration in karst areas.
Project description:Widely scattered urban villages (UVs) and increasingly serious urban heat islands (UHIs) are common urban problems in highly urbanized regions, especially in the developing countries. However, the influences of UVs on UHIs remain little understood. In this study, different methodologies are performed to retrieve land surface temperature (LST) from thermal bands and the nearest object-oriented method with spectral, texture, shape metrics using ZY-3 high-resolution satellite imagery, and road network data are used to extract UVs and other land-use types in the Guangzhou?Foshan (GF) core areas of Pearl River Delta (PRD). Moreover, the relationship between LST and land-use types is then analyzed on the multiple scales. The results show that five land-use types (vegetation, normal construction land (NCL), UVs, water, and unused land) extracted by the object-oriented method were qualified for subsequent analysis because of satisfactory overall accuracy (0.887) and the Kappa coefficient (0.863). In the GF core areas presenting the most outstanding UHI effect across the PRD region, about 60.5% of the total area is covered by the impervious surfaces, including NCL (50.4%) and UVs (10.1%). The average LST of UVs was 1.89?2.97 °C lower than that of NCL. According to the average contribution index of thermal effect and the Pearson's correlation coefficients, UVs present a relatively lower contribution to UHI and a weaker warming effect than NCL, but possess a higher contribution to UHI and a stronger warming effect than other land-use types, resulting in some slightly lower LST-valleys in the UVs adjacent to the NCL and distinct LST-peaks of UVs close to vegetation and water on the surface temperature profile lines. This work increases our understanding of the relationship between increasingly serious UHIs and widely distributed UVs, and would be valuable for local authorities to monitor and improve urban environment in metropolitan regions.
Project description:The improvement and implementation of a colonoscopy technique has led to increased detection of laterally spreading tumors (LSTs), which are presumed to constitute an aggressive type of colonic neoplasm. Early diagnosis and treatment of LSTs is clinically challenging. To overcome this problem, we employed iTRAQ to identify LST-specific protein biomarkers potentially involved in LST progression. In this study, we identified 2,001 differentially expressed proteins in LSTs using iTRAQ-based proteomics technology. Lipocalin-2 (LCN-2) was the most up-regulated protein. LSTs expression levels of LCN-2 and matrix metallopeptidase-9 (MMP-9) showed positive correlation with worse pathological grading, and up-regulation of these proteins in LSTs was also reflected in serum. Furthermore, LCN-2 protein overexpression was positively correlated with MMP-9 protein up-regulation in the tumor tissue and serum of LST patients (former rs?=?0.631, P?=?0.000; latter rs?=?0.815, P?=?0.000). Our results suggest that LCN-2 constitutes a potential biomarker for LST disease progression and might be a novel therapeutic target in LSTs.
Project description:The complicity of long-term land surface temperature (LST) changes has been under investigated and less understood, hindering our understanding of the history and mechanism of terrestrial climate change. Here, we report the longest (800 thousand years) LSTs based on distributions of soil fossil bacterial glycerol dialkyl glycerol tetraethers preserved in well-dated loess-paleosol sequences at the center of the Chinese Loess Plateau. We have found a previously-unrecognized increasing early and prolonged warming pattern toward the northwestern plateau at the onset of the past seven deglaciations, corresponding to the decrease in vegetation coverage, suggesting underlying surface vegetation or lack of has played an important role in regulating LSTs, superimposed on the fundamental global glacial-interglacial changes. Our results support that LSTs in semi-humid and semi-arid regions with little vegetation will be more sensitive to the anticipated global temperature rise, while improving vegetation coverage would reduce LSTs and thus ecological impacts.
Project description:BACKGROUND:Evidence has shown that deep learning computer aided detection (CADe) system achieved high overall detection accuracy for polyp detection during colonoscopy. AIM:The detection performance of CADe system on non-polypoid laterally spreading tumors (LSTs) and sessile serrated adenomas/polyps (SSA/Ps), with higher risk for malignancy transformation and miss rate, has not been exclusively investigated. METHODS:A previously validated deep learning CADe system for polyp detection was tested exclusively on LSTs and SSA/Ps. 1451 LST images from 184 patients were collected between July 2015 and January 2019, 82 SSA/Ps videos from 26 patients were collected between September 2018 and January 2019. The per-frame sensitivity and per-lesion sensitivity were calculated. RESULTS:(1) For LSTs image dataset, the system achieved an overall per-image sensitivity and per-lesion sensitivity of 94.07% (1365/1451) and 98.99% (197/199) respectively. The per-frame sensitivity for LST-G(H), LST-G(M), LST-NG(F), LST-NG(PD) was 93.97% (343/365), 98.72% (692/701), 85.71% (324/378) and 85.71% (6/7) respectively. The per-lesion sensitivity of each subgroup was 100.00% (71/71), 100.00% (64/64), 98.31% (58/59) and 80.00% (4/5). (2) For SSA/Ps video dataset, the system achieved an overall per-frame sensitivity and per-lesion sensitivity of 84.10% (15883/18885) and 100.00% (42/42), respectively. CONCLUSIONS:This study demonstrated that a local-feature-prioritized automatic CADe system could detect LSTs and SSA/Ps with high sensitivity. The per-frame sensitivity for non-granular LSTs and small SSA/Ps should be further improved.
Project description:Cities are often hotter and drier compared with nearby undeveloped areas, but how organisms respond to these multifarious stressors associated with urban heat islands is largely unknown. Terrestrial isopods are especially susceptible to temperature and aridity stress as they have retained highly permeable gills from their aquatic ancestors. We performed a two temperature common garden experiment with urban and rural populations of the terrestrial isopod, <i>Oniscus asellus</i>, to uncover evidence for plastic and evolutionary responses to urban heat islands. We focused on physiological tolerance traits including tolerance of heat, cold, and desiccation. We also examined body size responses to urban heat islands, as size can modulate physiological tolerances. We found that different mechanisms underlie responses to urban heat islands. While evidence suggests urban isopods may have evolved higher heat tolerance, urban and rural isopods had statistically indistinguishable cold and desiccation tolerances. In both populations, plasticity to warmer rearing temperature diminished cold tolerance. Although field-collected urban and rural isopods were the same size, rearing temperature positively affected body size. Finally, larger size improved desiccation tolerance, which itself was influenced by rearing temperature. Our study demonstrates how multifarious changes associated with urban heat islands will not necessarily contribute to contemporary evolution in each of the corresponding physiological traits.
Project description:Downscaling microwave soil moisture (SM) with optical/thermal remote sensing data has considerable application potential. Spatial correlations between SM and land surface temperature (LST) or LST-derived SM indexes (SMIs) are vital to the current optical/thermal and microwave fusion downscaling methods. In this study, the spatial correlations were evaluated at the same spatial scale using SMAPVEX12 SM data and MODIS day/night LST products. LST-derived SMIs was calculated using NLDAS-2 gridded meteorological data with conventional trapezoid and two-stage trapezoid models. Results indicated that (1) SM agrees better with daytime LST than the nighttime or the day-night differential LST; (2) the daytime LSTs on Aqua and Terra present very similar spatial agreement with SM and they have very similar performances as downscaling factors in simulating SM; (3) decoupling effect among SM, LST, and LST-derived SMIs occurs not only in very wet but also in very dry condition; and (4) the decoupling effect degrades the performance of LST as a downscaling factor. The future downscaling algorithms should consider net surface radiation and soil type to tackle the decoupling effect.
Project description:Urban heat island (UHI) is one of the most focuses in urban climate study. The parameterization of the anthropogenic heat (AH) is crucial important in UHI study, but universal method to parameterize the spatial pattern of the AH is lacking now. This paper uses the NOAA DMSP/OLS nighttime light data to parameterize the spatial pattern of the AH. Two experiments were designed and performed to quantify the influences of the AH to land surface temperature (LST) in eastern China and 24 big cities. The annual mean heating caused by AH is up to 1 K in eastern China. This paper uses the relative LST differences rather than the absolute LST differences between the control run and contrast run of common land model (CoLM) to find the drivers. The heating effect of the anthropogenic footprint has less influence on relatively warm and wet cities.