scholarly journals Local Climate Zones and Thermal Characteristics in Riyadh City, Saudi Arabia

2021 ◽  
Vol 13 (22) ◽  
pp. 4526
Author(s):  
Ali S. Alghamdi ◽  
Ahmed Ibrahim Alzhrani ◽  
Humud Hadi Alanazi
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Thermal Characteristics ◽  
Arid Climate ◽  
Landsat 8 ◽  
Design Strategies ◽  
Local Climate ◽  
Riyadh City ◽  
Local Climate Zones

Using the local climate zone (LCZ) framework and multiple Earth observation input features, an LCZ classification was developed and established for Riyadh City in 2017. Four land-cover-type and four urban-type LCZs were identified in the city with an overall accuracy of 87%. The bare soil/sand (LCZ-F) class was found to be the largest LCZ class, which was within the nature of arid climate cities. Other land-cover LCZs had a lower coverage percentage (each class with <7%). The compact low-rise (LCZ-3) class was the largest urban type, as urban development in arid climate cities tends to extend horizontally. The daytime surface thermal characteristics of the developed LCZs were analyzed at seasonal timescales using land surface temperature (LST) estimated from multiple Landsat 8 satellite images (June 2017–May 2018). The highest daytime mean LST was found over large low-rise (LCZ-8) class areas throughout the year. This class was the only urban-type LCZ class that demonstrated a positive LST departure from the overall mean LST across seasons. Other urban-type LCZ classes showed lower LSTs and negative deviations from the overall mean LSTs. The overall thermal results suggested the presence of the surface urban heat island sink phenomenon as urban areas experienced lower LSTs than their surroundings. Thermal results demonstrated that the magnitudes of LST differences among LCZs were considerably dependent on the way the region of interest/analysis was defined. This was related to the types of LCZ classes presented in the study area and the spatial distribution and abundance of these LCZ classes. The developed LCZ classification and thermal results have several potential applications in different areas including planning and urban design strategies and urban health-related studies.

scholarly journals Impact of urban environment on land surface temperature in local climate zones

2021 ◽  
Vol 333 ◽  
pp. 02008
Author(s):  
Anna Gosteva ◽  
Sofia Ilina ◽  
Aleksandra Matuzko
Keyword(s):  
Surface Temperature ◽  
Urban Environment ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Landsat 8 ◽  
Local Climate ◽  
Spatial Coverage ◽  
Artificial Environment ◽  
Local Climate Zones

The replacement of the natural landscape by artificial environment has led to changes in the ecosystem and physical properties of the surface, such as heat storage capacity, and thermal conductivity properties. These changes increase the difficulty of heat transfer between urban areas and the environment. Land surface temperature (LST) images from various satellites are widely used to represent urban thermal environments, which are more convenient and intuitive way. LST maps provide full spatial coverage, which distinguishes them from air temperature data obtained from meteorological stations. The study of LST according to the Landsat 8 data of Krasnoyarsk city over the past 10 years allowed the authors to talk about the observation of constant seasonal urban heat islands (UHI). For a more detailed consideration of the urban environment, this study further considers urban landscapes, thus the idea of local climate zone (LCZ) is introduced to study these diverse impacts in addition to the traditional map of LST. And analysis of the interaction of UHI and LCZ.

scholarly journals GIS-BASED MAPPING OF LOCAL CLIMATE ZONES USING FUZZY LOGIC AND CELLULAR AUTOMATA

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 199-206
Author(s):  
I. Estacio ◽  
J. Babaan ◽  
N. J. Pecson ◽  
A. C. Blanco ◽  
J. E. Escoto ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Cellular Automata ◽  
Land Cover ◽  
Land Surface ◽  
Visual Inspection ◽  
View Factor ◽  
Landsat 8 ◽  
Local Climate ◽  
Surface Fraction ◽  
Local Climate Zones

Abstract. Because of the vague distinction between urban and rural areas, the Local Climate Zone (LCZ) scheme was developed to better analyze the effect of Urban Heat Island. To map the LCZs in a city, the World Urban Database and Portal Tool is used as conventional method. However, this requires the assignment of training areas for each LCZ, which entails local knowledge of the area and may introduce errors, as distinction between LCZ types through visual inspection is inconclusive. This paper aims to develop a methodology and GIS tool to enhance and automate the mapping of LCZs using seven LCZ properties (sky view factor, building surface fraction, pervious surface fraction, impervious surface fraction, building height, roughness length, and surface albedo), and apply it in Quezon City, Philippines which comprises varying land use and land cover. Fuzzy Logic was used to determine the membership percentage of 100 m cells to an LCZ type based on these properties. Cellular Automata was implemented using Python to derive the LCZ map from the fuzzy layers. Results show that seven out of ten built-up LCZs and five out of seven land cover LCZs were identified. Through visual inspection on a basemap, the mapped LCZs was confirmed to match with the features of the city. Land Surface Temperature (LST) derived from Landsat 8 showed that each LCZ type displayed temperatures consistent with those observed from literature. The developed methodology and tool is ready to be used in other cities as long as the input layers are generated.

Impact of Urban Land Cover Types on Surface Temperature

2021 ◽  
Author(s):  
Marzie Naserikia ◽  
Melissa Hart ◽  
Negin Nazarian
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Climatic Conditions ◽  
Landsat 8 ◽  
Local Climate ◽  
Land Cover Types ◽  
Cooling Effects

&lt;p&gt;The conversion of natural land to built-up surfaces has been widely documented as the main determinant of warming across urban areas. However, uncertainties remain regarding which primary land cover variables control urban heat in different climatic conditions at a global scale. While there is a very little understanding of how the cooling effects of vegetation cover vary over different cities, there is a deep knowledge gap in realizing how other land covers (such as soil, water, and built-up areas) are associated with urban warming and how this relationship is varied in different background climates. Accordingly, using a high spatial resolution dataset, a global synthetic investigation is needed to find the underlying factors influencing intra-urban temperature variability in various climates. To address this shortcoming, this study focuses on exploring the relationship between land surface temperature and land cover in different cities (using Landsat 8 imagery) and aims to investigate the effects of these land cover types on thermal environments in different climatic backgrounds. Preliminary analysis shows that different land cover types have different roles in different climate classes due to their various surface characteristics and in particular, the performance of green spaces to reduce LST is highly dependent on its background climate. For example, the efficiency of vegetation cover to reduce urban surface warming in temperate and tropical climates is more than that in arid and semi-arid areas. In this climate class, since baren soil is the main contributor to the intensity of LST, increasing the area of a green space presents an effective method to mitigate the adverse effects of local warming. Our findings provide helpful information for future urban climate-sensitive planning oriented at mitigating local climate warming in cities.&lt;/p&gt;

scholarly journals MODELING THE DEVELOPMENTS IN URBANISATION AND RELATIONSHIP WITH VEGETATION COVER IN ALANYA

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 291-297
Author(s):  
B. İşler ◽  
Z. Aslan
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Landsat 8 ◽  
World Population ◽  
Land Use Land Cover ◽  
Temperature And Precipitation ◽  
Atmospheric Variables

Abstract. The increase in the world population and the migration of people from rural to urban areas causes an increase in artificial surfaces and causes many negative effects on the ecosystem, regional climate variations and global diversity. Nowadays, as the effects of climate change are felt more and more, it has gained importance in researches on this subject. Therefore, the estimation of the change in the vegetation density for the coming years and the determination of the land use / land cover (LULC) change in cities are very essential for urban planning. In this study, the effects of regional urbanization on vegetation are examined by using satellite data and atmospheric variables. In the vegetation analysis, multi-time index values obtained from TERRA-MODIS satellite, EVI (Enhanced Vegetation Index) and LST (Land Surface Temperature) were taken into account between the years of 2005 and 2018 in Alanya, Turkey. Temperature and precipitation were selected as the atmospheric variables and expected variations in EVI value until 2030 were estimated. In the study employed a wavelet-transformed artificial neural network (WANN) model to generate long-term (12-year) EVI forecasts using LST, temperature and precipitation. The relationship between land use / land cover and urbanization is investigated with NDBI (Normalized Difference Built-up Index) data obtained from the Landsat 8 OLI / TIRS satellite sensor. The simulation results show that The EVI value, which was 0.30 in 2018, will decrease to 0.25 in 2030.

scholarly journals RETRIEVAL OF LOCAL CLIMATE ZONES AND THEIR LINKAGES TO LAND SURFACE TEMPERATURE USING REMOTE SENSING IN HARARE METROPOLITAN CITY, ZIMBABWE

2019 ◽  
Vol IV-2/W5 ◽  
pp. 513-517
Author(s):  
T. D. Mushore
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Google Earth ◽  
Support Vector ◽  
Landsat 8 ◽  
Climate Zones ◽  
Local Climate ◽  
Metropolitan City ◽  
Local Climate Zones

<p><strong>Abstract.</strong> This study sought to determine Local Climate Zones (LCZs) in Harare metropolitan City, using Landsat 8 multi-spectral and multi-temporal data. The World Urban Database and Access Portal Tool (WUDAPT) and Support Vector Machine classifiers were applied. Training datasets were extracted from Google Earth as prescribed by the WUDAPT procedure. Before image classification, we tested the separability of the LCZs, using the Transformed Divergence Separability Index (TDSI) based on the digitized training datasets and Landsat 8 data. Derived LCZs were then linked with Landsat 8 derived Land Surface Temperature (LST) for the cool and hot seasons. TDSI values greater 1.9 were obtained indicating that LCZs were highly separable. Comparatively, the WUDAPT method produced more accurate LCZs results (Overall accuracy = 95.69%) than the SVM classifier (Overall accuracy = 89.86%) based on seasonal Landsat 8 data. However, SVM derived accuracies were within the acceptable range of at least 80% (overall accuracy) in literature. Further, LST was observed to be high in LCZs with high built-up density and low vegetation proportion, when compared to other zones. Due to high proportion of vegetation, sparsely built areas were at least 1&amp;thinsp;&amp;deg;C cooler. Although LCZs are usually linked at 2&amp;thinsp;m air temperature, they also strongly explain LST distribution. This work provides insight into the importance of mapping LCZs in third world countries where such information remains scarce.</p>

scholarly journals A COMPARATIVE STUDY OF LAND SURFACE TEMPERATURE WITH DIFFERENT INDICES ON HETEROGENEOUS LAND COVER USING LANDSAT 8 DATA

2018 ◽  
Vol XLII-5 ◽  
pp. 389-394 ◽  
Author(s):  
R. Bala ◽  
R. Prasad ◽  
V. P. Yadav ◽  
J. Sharma
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Sensor Data ◽  
Landsat 8 ◽  
Temperature Relation

<p><strong>Abstract.</strong> The temperature rise in urban areas has become a major environmental concern. Hence, the study of Land surface temperature (LST) in urban areas is important to understand the behaviour of different land covers on temperature. Relation of LST with different indices is required to study LST in urban areas using satellite data. The present study focuses on the relation of LST with the selected indices based on different land cover using Landsat 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) data in Varanasi, India. A regression analysis was done between LST and Normalized Difference Vegetation index (NDVI), Normalized Difference Soil Index (NDSI), Normalized Difference Built-up Index (NDBI) and Normalized Difference Water Index (NDWI). The non-linear relations of LST with NDVI and NDWI were observed, whereas NDBI and NDSI were found to show positive linear relation with LST. The correlation of LST with NDSI was found better than NDBI. Further analysis was done by choosing 25 pure pixels from each land cover of water, vegetation, bare soil and urban areas to determine the behaviour of indices on LST for each land cover. The investigation shows that NDSI and NDBI can be effectively used for study of LST in urban areas. However, NDBI can explain urban LST in the better way for the regions without water body.</p>

scholarly journals EVALUATION OF THE SEASONAL NIGHTTIME LST-AIR TEMPERATURE DISCREPANCIES AND THEIR RELATION TO LOCAL CLIMATE ZONES (LCZ) IN STRASBOURG

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 391-398
Author(s):  
S. Del Pozo ◽  
T. Landes ◽  
F. Nerry ◽  
P. Kastendeuch ◽  
G. Najjar ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Air Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Research Work ◽  
Local Climate ◽  
Urban Climatology ◽  
Urban Energy Balance ◽  
Local Climate Zones ◽  
The City

Abstract. More and more uses and applications are being given to local climate zone (LCZ) maps, which describe the structure of the urban and semi-urban areas. Among others, it is worth highlighting its use in studies of urban heat islands (UHI), sustainability and urban energy balance. Even if the classes are well described in the literature, it is difficult to estimate the general precision of these classification maps because the classification is highly dependent of the urban typology of the city under study. However, LCZ maps represent a reference in the field of urban climatology. This research work aims to make use of these maps to explain the strong influence of LCZ classes on land surface temperature (LST) and, consequently, on air temperature (AT). This kind of investigations will help us to explain the outliers observed in previous work between LST and AT at specific locations in the city of Strasbourg for the period 2012–2019. The LST data were obtained from the thermal infrared data of both ASTER (with 90-m spatial resolution and 16-days temporal resolution) and MODIS satellite (with 1-km spatial resolution and daily revisit period). The reference ATs were obtained from different field measurement provided by a huge network of meteorological stations distributed in the city of Strasbourg. The comparison of measured ATs and remote LSTs provide the opportunity to thoroughly evaluate the relationship between these two parameters both during the day and night, for different land covers and for different times of the year. Finally, UHI maps of Strasbourg for every season are presented.

scholarly journals Mapping Local Climate Zones Using ArcGIS-Based Method and Exploring Land Surface Temperature Characteristics in Chenzhou, China

2020 ◽  
Vol 12 (7) ◽  
pp. 2974 ◽  
Author(s):  
Yaping Chen ◽  
Bohong Zheng ◽  
Yinze Hu
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Spatial Form ◽  
Climate Zones ◽  
Local Climate ◽  
Four Seasons ◽  
Local Climate Zones ◽  
Urban Heat

The local climate zone (LCZ) has become a new tool for urban heat island research. Taking Chenzhou as the research object, eight urban spatial form elements and land cover elements are calculated respectively through ArcGIS, Skyhelios and ENVI software. The calculation results are then rasterized and clustered in ArcGIS to obtain the LCZ map at a resolution of 200 m. Afterwards, the land surface temperature (LST) of different local climate zones in the four seasons from 2017 to 2018 is further analyzed using one-way ANOVA F-test and Student’s t-test. The results suggest that: (1) by adding localized LCZ classes and applying the semi-automatic algorithm on the Arc-GIS platform, the final overall accuracy reaches 69.54%, with a kappa value of 0.67, (2) the compact middle-rise buildings (LCZ-2′) and open low-rise buildings (LCZ-6) heavily contribute to the high LST of the downtown area, while the large low-rise buildings (LCZ-8) cause the high LST regions in the eastern part of the town, (3) obvious land surface temperature differences can be detected in four seasons among different LCZ classes, with high LST in summer and autumn. Built-up LCZ classes generally revealed higher LSTs than land cover LCZs in all seasons. The findings of this study provide better understandings of the relationship between LCZ and LST, as well as important insights for urban planners on urban heat mitigation.

scholarly journals Spatial Distribution of Surface Temperature and Land Cover: A Study Concerning Sardinia, Italy

2020 ◽  
Vol 12 (8) ◽  
pp. 3186 ◽  
Author(s):  
Sabrina Lai ◽  
Federica Leone ◽  
Corrado Zoppi
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Spatial Data ◽  
Land Surface ◽  
Urban Areas ◽  
Regional Scale ◽  
Landsat 8 ◽  
Policy Recommendations ◽  
Mediterranean Shrubs ◽  
Land Covers

Land surface temperature (LST) is a key climate variable that has been studied mainly at the urban scale and in the context of urban heat islands. By analyzing the connection between LST and land cover, this study shows the potential of LST to analyze the relation between urbanization and heating phenomena at the regional level. Land cover data, drawn from Copernicus, and LST, retrieved from Landsat 8 satellite images, are analyzed through a methodology that couples GIS and regression analysis. By looking at the Italian island of Sardinia as a case study, this research shows that urbanization and the spatial dynamics of heating phenomena are closely connected, and that intensively farmed areas behave quite similarly to urban areas, whereas forests are the most effective land covers in mitigating LST, followed by areas covered with Mediterranean shrubs. This leads to key policy recommendations that decision-makers could implement to mitigate LST at the regional scale and that can, in principle, be exported to regions with similar climate and land covers. The significance of this study can be summed up in its novel approach to analyzing the relationship between LST and land covers that uses freely available spatial data and, therefore, can easily be replicated in other regional contexts to derive appropriate policy recommendations.

scholarly journals Analysis of land surface temperatures in the "Local Climate Zones" of Novi Sad (Serbia)

2020 ◽  
Vol 100 (1) ◽  
pp. 41-50
Author(s):  
Stevan Savic ◽  
Jan Geletic ◽  
Dragan Milosevic ◽  
Michal Lehnert
Keyword(s):  
Land Surface ◽  
Landsat 8 ◽  
Similar Time ◽  
Climate Zones ◽  
Local Climate ◽  
Surface Temperatures ◽  
Local Climate Zones ◽  
Scattered Trees ◽  
Land Surface Temperatures ◽  
Novi Sad

In this study, the Local Climate Zones (LCZs) in Novi Sad, the second largest city in Serbia, are analysed as to surface temperature differences. The LCZs were delineated on the basis of the GIS-based method created by Geletic & Lehnert (2016). Land Surface Temperatures (LSTs) were derived from the satellites Terra, sensor ASTER, and LANDSAT-8. The thermal images were provided at a similar time (at about 9.30 AM) between 2002 and 2008 (ASTER) and between 2013 and 2017 (LANDSAT-8). Statistical analyses, including the analysis of variance (ANOVA) and Tukey-HSD test, were employed to reveal LST differences between the LCZs. The results indicate that in 84% of cases there were significant differences in LST between pairs of LCZs. Temperature differences between LCZs were the most pronounced in the summer season. In general, 8 (large low-rise), 10 (heavy industry), 2 (compact midrise) and 3 (compact low-rise) LCZs had the highest surface temperatures in Novi Sad. Contrary to this, LCZs A (dense trees), B (scattered trees) G (water bodies) were the coolest zones.

Sign in / Sign up

Export Citation Format

Share Document