scholarly journals Response of Spatio-Temporal Differentiation Characteristics of Habitat Quality to Land Surface Temperature in a Fast Urbanized City

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1668
Author(s):  
Yongge Hu ◽  
Enkai Xu ◽  
Gunwoo Kim ◽  
Chang Liu ◽  
Guohang Tian
Keyword(s):  
Surface Temperature ◽  
Habitat Quality ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Northern Region ◽  
Urban Heat Islands ◽  
Urban Habitat ◽  
Rural Settlements ◽  
Quality Model ◽  
High Type

The degradation and loss of global urban habitat and biodiversity have been extensively studied as a global issue. Urban heat islands caused by abnormal land surface temperature (LST) have been shown to be the main reason for this problem. With the accelerated urbanization process and the increasing possibility of abnormal temperatures in Zhengzhou, China, more and more creatures cannot adapt and survive in urban habitats, including humans; therefore, Zhengzhou was selected as the study area. The purpose of this study is to explore the response of urban habitat quality to LST, which provides a basis for the scientific protection of urban habitat and biodiversity in Zhengzhou from the perspective of alleviating heat island effect. We used the InVEST-Habitat Quality model to calculate the urban habitat quality, combined with GIS spatial statistics and bivariate spatial autocorrelation analysis, to explore the response of habitat quality to LST. The results show the following: (1) From 2000 to 2015, the mean value of urban habitat quality gradually decreased from 0.361 to 0.304, showing a downward trend as a whole. (2) There was an obvious gradient effect between habitat quality and LST. Habitat quality’s high values were distributed in the central and northern built-up area and low values were distributed in the high-altitude western forest habitat and northern water habitat. However, the distribution of LST gradient values were opposite to the habitat quality to a great extent. (3) There were four agglomeration types between LST and habitat quality at specific spatial locations: the high-high type was scattered mainly in the western part of the study area and in the northern region; the high-low type was mainly distributed in the densely populated and actively constructed central areas; the low-low type was mainly distributed in the urban-rural intersections and small and medium-sized rural settlements; and the low-high type was mainly distributed in the western mountainous hills and the northern waters.

scholarly journals A Review of Reconstructing Remotely Sensed Land Surface Temperature under Cloudy Conditions

2021 ◽  
Vol 13 (14) ◽  
pp. 2838
Author(s):  
Yaping Mo ◽  
Yongming Xu ◽  
Huijuan Chen ◽  
Shanyou Zhu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Spatial Scales ◽  
Remotely Sensed ◽  
Urban Heat Islands ◽  
Reconstruction Algorithms ◽  
Gap Filling ◽  
Practical Applications ◽  
Data Gaps

Land surface temperature (LST) is an important environmental parameter in climate change, urban heat islands, drought, public health, and other fields. Thermal infrared (TIR) remote sensing is the main method used to obtain LST information over large spatial scales. However, cloud cover results in many data gaps in remotely sensed LST datasets, greatly limiting their practical applications. Many studies have sought to fill these data gaps and reconstruct cloud-free LST datasets over the last few decades. This paper reviews the progress of LST reconstruction research. A bibliometric analysis is conducted to provide a brief overview of the papers published in this field. The existing reconstruction algorithms can be grouped into five categories: spatial gap-filling methods, temporal gap-filling methods, spatiotemporal gap-filling methods, multi-source fusion-based gap-filling methods, and surface energy balance-based gap-filling methods. The principles, advantages, and limitations of these methods are described and discussed. The applications of these methods are also outlined. In addition, the validation of filled LST values’ cloudy pixels is an important concern in LST reconstruction. The different validation methods applied for reconstructed LST datasets are also reviewed herein. Finally, prospects for future developments in LST reconstruction are provided.

scholarly journals Normalized Method for Land Surface Temperature Monitoring on Coastal Reclaimed Areas

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4836 ◽  
Author(s):  
Bahaa Mohamadi ◽  
Shuisen Chen ◽  
Timo Balz ◽  
Khansa Gulshad ◽  
Stephen C. McClure
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Temporal Change ◽  
Southern China ◽  
Open Water ◽  
Temporal Analysis ◽  
Urban Heat Islands ◽  
Data Availability ◽  
Robust Detection

The temporal analysis of land surface temperature (LST) has generally been studied using data from the same season, as temperature varies greatly over time. However, the cloud cover in thermal remotely sensed images and the coarse resolution of passive sensor system significantly limits data availability of same season for comparative temporal analysis in many parts of the world. To address this problem, we propose a new method for temporal monitoring of surface temperature based on LST normalization (LSTn); deploying the average open water temperature to normalize LST when monitoring temporal change in the surface temperature of newly coastal reclaimed areas. This method was applied in the Lingding Bay area, Guangdong Province, Southern China. Original LST and LSTn values were calculated for years 1987, 1997, 2007, and 2017. In contrast to the original LST, results show that LSTn can reduce seasonal variability when monitoring temporal change in surface temperatures. Additionally, LSTn revealed pronounced differences between the temperature of impervious surfaces and other land cover types. This method offers more robust detection of surface urban heat islands than original LST in newly developed coastal areas.

scholarly journals Multi-Temporal Land Surface Temperature and Vegetation Greenness in Urban Green Spaces of Puebla, Mexico

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 155
Author(s):  
Filoteo Gomez-Martinez ◽  
Kirsten M. de Beurs ◽  
Jennifer Koch ◽  
Jeffrey Widener
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Population Expansion ◽  
Urban Heat Islands ◽  
Green Spaces ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Urban Heat

The urban heat island (UHI) effect is a global problem that is likely to grow as a result of urban population expansion. Multiple studies conclude that green spaces and waterbodies can reduce urban heat islands. However, previous studies often treat urban green spaces (UGSs) as static or limit the number of green spaces investigated within a city. Cognizant of these shortcomings, Landsat derived vegetation and land surface temperature (LST) metrics for 80 urban green spaces in Puebla, Mexico, over a 34-year (1986–2019) and a 20-year (2000–2019) period were studied. To create a photo library, 73 of these green spaces were visited and the available land cover types were recorded. Green spaces with Indian laurel were found to be much greener and vegetation index values remained relatively stable compared to green spaces with mixed vegetation cover. Similarly, green spaces with large waterbodies were cooler than those without water. These results show that larger green spaces were significantly cooler (p < 0.01) and that size can explain almost 30% of temperature variability. Furthermore, green spaces with higher vegetation index values were significantly cooler (p < 0.01), and the relationship between greenness and temperature strengthened over time.

scholarly journals The Response of Land Surface Temperature to the Changing Land-Use Land-Cover in a Mountainous Landscape under the Influence of Urbanization: Gilgit City as a case study in the Hindu Kush Himalayan Region of Pakistan

2019 ◽  
Vol 10 (3) ◽  
pp. 40-49
Author(s):  
Aftab Ahmed Khan ◽  
Syed Najam ul Hassan ◽  
Saranjam Baig ◽  
Muhammad Zafar Khan ◽  
Amin Muhammad
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Linear Regression Analysis ◽  
Northern Region ◽  
Google Earth ◽  
Landsat Images

With growing urbanization in mountainous landscapes, the built-up areas dominate other land use classesresulting in increased land surface temperature (LST). Gilgit city in northern Pakistan has witnessed tremendousurban growth in the recent past decades. It is anticipated that this growth will exponentially increase in the nearfuture because of the China-Pakistan Economic Corridor (CPEC) initiatives, as this city happens to be thecommercial hub of the northern region of Pakistan. The objective of present study is to explore the influence ofland use and land cover variations on LST and to evaluate the relationship between LST with normalizeddifference vegetation index (NDVI), normalized difference water index (NDWI), and normalized difference built -up index (NDBI) values. This study is carried out on data from Google earth and three Landsat images (Landsat 5-TM, Landsat 7-ETM, and Landsat OLI_TIRS-8) during the period from 1992, 2004 and 2016. Land use/coverclasses are determined through supervised classification and LST maps are created using the Mono -windowalgorithm. The accuracy assessment of land use/cover classes is carried out comparing Google Earth digitizedvector for the periods of 2004 and 2016 with Landsat classified images. Further, NDVI, NDBI, and NDWI mapsare computed from images for years 1992, 2004, and 2016. The relationships of LST with NDVI, NDBI, andNDWI are computed using Linear Regression analysis. The results reveal that the variations in land use and landcover play a substantial role in LST variability. The maximum temperatures are connected with built -up areas andbarren land, ranging from 48.4°C, 50.7°C, 51.6°C, in 1992, 2004, and 2016, respectively. Inversely, minimumtemperatures are linked to forests and water bodies, ranging from 15.1°C, 16°C, 21.6°C, in 1992, 2004, and 2016respectively. This paper also results that NDBI correlates positively with high temperatures, whereas NDVI andNDWI associate negatively with lesser temperatures. The study will support to policymakers and urban planners tostrategize the initiatives for eco-friendly and climate-resilient urban development in fragile mountainouslandscapes.

scholarly journals The Response of Land Surface Temperature to the Changing Land-Use Land-Cover in a Mountainous Landscape under the Influence of Urbanization: Gilgit City as a case study in the Hindu Kush Himalayan Region of Pakistan

2019 ◽  
Vol 10 (3) ◽  
pp. 40-49
Author(s):  
Aftab Ahmed Khan ◽  
Syed Najam ul Hassan ◽  
Saranjam Baig ◽  
Muhammad Zafar Khan ◽  
Amin Muhammad
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Linear Regression Analysis ◽  
Northern Region ◽  
Google Earth ◽  
Landsat Images

With growing urbanization in mountainous landscapes, the built-up areas dominate other land use classesresulting in increased land surface temperature (LST). Gilgit city in northern Pakistan has witnessed tremendousurban growth in the recent past decades. It is anticipated that this growth will exponentially increase in the nearfuture because of the China-Pakistan Economic Corridor (CPEC) initiatives, as this city happens to be thecommercial hub of the northern region of Pakistan. The objective of present study is to explore the influence ofland use and land cover variations on LST and to evaluate the relationship between LST with normalizeddifference vegetation index (NDVI), normalized difference water index (NDWI), and normalized difference built -up index (NDBI) values. This study is carried out on data from Google earth and three Landsat images (Landsat 5-TM, Landsat 7-ETM, and Landsat OLI_TIRS-8) during the period from 1992, 2004 and 2016. Land use/coverclasses are determined through supervised classification and LST maps are created using the Mono -windowalgorithm. The accuracy assessment of land use/cover classes is carried out comparing Google Earth digitizedvector for the periods of 2004 and 2016 with Landsat classified images. Further, NDVI, NDBI, and NDWI mapsare computed from images for years 1992, 2004, and 2016. The relationships of LST with NDVI, NDBI, andNDWI are computed using Linear Regression analysis. The results reveal that the variations in land use and landcover play a substantial role in LST variability. The maximum temperatures are connected with built -up areas andbarren land, ranging from 48.4°C, 50.7°C, 51.6°C, in 1992, 2004, and 2016, respectively. Inversely, minimumtemperatures are linked to forests and water bodies, ranging from 15.1°C, 16°C, 21.6°C, in 1992, 2004, and 2016respectively. This paper also results that NDBI correlates positively with high temperatures, whereas NDVI andNDWI associate negatively with lesser temperatures. The study will support to policymakers and urban planners tostrategize the initiatives for eco-friendly and climate-resilient urban development in fragile mountainouslandscapes.

scholarly journals Study of the Parameters of Urban Heat Islands on the Irkutsk Region Territory According to Remote Sensing Data

2020 ◽  
Vol 34 ◽  
pp. 131-140
Author(s):  
E. N. Sutyrina ◽  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Dimensional Structure ◽  
Heat Islands ◽  
Irkutsk Region ◽  
Urban Heat ◽  
The Difference ◽  
The City

The investigation is aimed to determine the boundaries and intensity of urban heat islands in the Irkutsk region and assess the change in these parameters over a long-term period. The formation of an urban heat island is an example of anthropogenic influence on the urban climate. Land surface temperature and its spatial and temporal variations can be used to study urban heat islands, since the difference between the land surface temperature within the city and its surroundings is the result of the transformation of the underlying surface, heat capacity and three-dimensional structure of urban buildings in the process of urbanization. In order to study the phenomenon of urban heat islands of cities of the Irkutsk region, the land surface temperature data reconstructed from AVHRR-based thermal infrared imagery for 1998-2019 was used. As a result of the study, multi-temporal maps showing the urban heat islands of the agglomeration of Irkutsk-Angarsk-Shelekhov and the city of Bratsk were obtained. The investigated heat islands are characterized by a significant diurnal dynamic, so the difference in temperature values between the city and the suburbs in summer daytime reached 8-10 °C, in the evening and at night in summer this parameter decreases to 3-5 °C. The dimensions of the urban heat islands of the cities under investigation in the daytime exceed the dimensions of these heat anomalies in the evening and at night. Interannual variability in the intensity of urban heat islands did not show statistically significant trends from 1998 to 2019, the areas of urban heat islands increased significantly over the study period. The observed increase in area was probably associated with the development of the cities under study, with the transformation of landscapes and a decrease in the density of vegetation in the suburbs. In order to assess the contribution of the lack of vegetation to the formation of the urban heat islands in summer daytime, the values of the land surface temperature were compared with the values of the vegetation index NDVI. An analysis of the relationships between these parameters found that daytime land surface temperature was in close inverse relationship with the NDVI value, while this relationship was less pronounced at night and in the evening.

scholarly journals Assessment of Urban Heat Islands Based on the Relationship Between Land Surface Temperature and Land Use/Land Cover in Greater Doha

2020 ◽  
Author(s):  
Simil Amir Siddiqui
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Land Use Land Cover ◽  
Heat Islands ◽  
Urban Heat ◽  
The City

Urban heat islands (UHI) are areas with elevated temperatures occurring in cities compared to surrounding rural areas. This study realizes the lack of research regarding the trends of UHIs in desert countries and focuses on Doha. The research includes twelve months of two-time periods; 2000-2019. ArcGIS software was used to compute the land surface temperature (LST) of the city using Landsat images. Land use/land cover (LULC) maps were computed to show how the city has evolved in 19 years. 30 field samples were used to verify the accuracy of the LULC. Results showed UHI in Doha did not display similar pattern to that of cities in subtropical and temperate regions. Higher temperatures were prevalent in out-skirts comprising of barren and built-up areas with high population and no vegetation. Comparatively, the main downtown with artificially planted vegetation and shade from skyscrapers created cooler microclimates. The overall LST of greater Doha has increased by 0.7°C from 2000 to 2019. Furthermore %LULC of built up, vegetation, barren land, marsh land and water body were 29%, 4.5%, 58.6%, 2.8% and 5% in 2000 and 56.5 %, 8.2%, 33.2 %, 0% and 2.1% in 2019 respectively. Overall, there was an increase in built-up and vegetation decrease in water and barren areas and complete loss of marshland. Highest temperatures were recorded for marshland area in year 2000 and barren and built in year 2019. Transect profiles showed positive correlation between NDBI and LST and a negative correlation between NDVI and LST.

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