scholarly journals Index-based Approach in Relation to Built-up and LST Dynamics; A Study of Lahore, Pakistan

Author(s):  
Kanwal Javid ◽  
Muhammad Ameer Nawaz Akram ◽  
Shazia Pervaiz ◽  
Rumana Siddiqui ◽  
Nausheen Mazhar

In 21st century, cities outpaced in size and also in density due to development of economic sector. Consequently, the wide spread expansion of urban areas is resulting in the loss of productive green cover and water bodies. Therefore, realizing this alarming situation, the present study is aimed to investigate and evaluate the pattern of urban expansion by considering two major land cover types (i) built-up area (ii) other classes (vegetation, waterbody, soil etc.) during the last six years (2015-2020). For this study Sentinel imagery was acquired from USGS Earth Explorer, while Modis Terra images were acquired from World View NASA. New built-up area index (NBUI), normalized difference vegetation index (NDVI), worldview water index (WV-WI) and land surface temperature (LST) were calculated in order to analyze variations in Lahore’s major land cover types and its varying temperature patterns. Spatial analysis presented the obvious impacts of land development on Lahore. NBUI indicated that the built-up area has increased drastically from 34.0% in 2015 to 84.2% in 2020; NDVI analysis depicted a decline from 0.76% to 0.73%, in the green spaces of Lahore during the study period; WV-WI portrayed inconsistent values of water bodies, a gift of massive rise in the built-up area in Lahore. LST results presented that the temperature was 42.21°C in 2015, which simultaneously increased and recorded at 49.51°C in 2020. The increase in LST exhibited the alarming situation for urban environment and can become threat to increase the air pollution level in Lahore. Therefore, this study will serve as a snapshot for policy makers to control the menace of unplanned urbanization by formulating stringent policies to protect environment.


2013 ◽  
Vol 6 (2) ◽  
pp. 563-582 ◽  
Author(s):  
S. Faroux ◽  
A. T. Kaptué Tchuenté ◽  
J.-L. Roujean ◽  
V. Masson ◽  
E. Martin ◽  
...  

Abstract. The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1 km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and normalized difference vegetation index (NDVI) from SPOT/Vegetation (a global monitoring system of vegetation) yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 plant functional types (PFTs) representing generic vegetation types – principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land – as incorporated by the SVAT model ISBA (Interactions Surface Biosphere Atmosphere) developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land occupation nomenclatures.



Author(s):  
I. Ibrahim ◽  
A. Abu Samah ◽  
R. Fauzi ◽  
N. M. Noor

Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R<sup>2</sup> = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.



2021 ◽  
Author(s):  
Marzie Naserikia ◽  
Melissa Hart ◽  
Negin Nazarian

<p>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.</p>



2020 ◽  
Vol 12 (5) ◽  
pp. 837 ◽  
Author(s):  
Xiying Tang ◽  
Yaoping Cui ◽  
Nan Li ◽  
Yiming Fu ◽  
Xiaoyan Liu ◽  
...  

The impact of human activities on vegetation has been the focus of much research, but the impact on radiation energy through surface albedo associated with vegetation greenness and length of the growth season is still not well documented. Based on the land cover data for the years 2000 and 2015, this study first divided the land cover change in Beijing from 2000 to 2015 into five types according to the impact of human activities and vegetation resilience, namely, old urban areas (OU), urban expansion areas (UE), cropland (CP), mixed pixel areas (MP, which means the land covers other than urban expansion which had changed from 2000 to 2015), and the residual vegetation cover areas (pure pixels (PP), dominated by natural and seminatural vegetation, such as grassland, forest, and wetland). Then, we calculated the direct radiative forcing from the albedo change from 2000 to 2015 and analyzed the effect of vegetation on the albedo under different land cover types based on multi-resource Moderate Resolution Imaging Spectroradiometer (MODIS) products of vegetation, albedo, and solar radiation. The results showed that the most typical changes in land cover were from urban expansion. By comparing the PP with the four human-affected land cover types (OU, UE, MP, and CP), we confirmed that the radiative forcing increment between 2001–2003 and 2013–2015 in PP (0.01 W/m2) was much smaller than that in the four human-affected land cover types (the mean increment was 0.92 W/m2). This study highlights that human activities affected vegetation growth. This, in turn, brought changes in the albedo, thereby enhancing radiative forcing in Beijing during 2000–2015.



2012 ◽  
Vol 5 (4) ◽  
pp. 3573-3620 ◽  
Author(s):  
S. Faroux ◽  
A. T. Kaptué Tchuenté ◽  
J.-L. Roujean ◽  
V. Masson ◽  
E. Martin ◽  
...  

Abstract. The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1-km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and NDVI from SPOT/Vegetation yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 Plant Functional Types (PFTs) representing generic vegetation types – principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land – as incorporated by the SVAT model ISBA developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land occupation nomenclatures.



Author(s):  
I. Ibrahim ◽  
A. Abu Samah ◽  
R. Fauzi ◽  
N. M. Noor

Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p&lt;0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R<sup>2</sup> = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.



2021 ◽  
Vol 9 ◽  
Author(s):  
Merja H. Tölle ◽  
Evgenii Churiulin

Characterization of climate uncertainties due to different land cover maps in regional climate models is essential for adaptation strategies. The spatiotemporal heterogeneity in surface characteristics is considered to play a key role in terrestrial surface processes. Here, we quantified the sensitivity of model results to changes in land cover input data (GlobCover 2009, GLC 2000, CCI, and ECOCLIMAP) in the regional climate model (RCM) COSMO-CLM (v5.0_clm16). We investigated land cover changes due to the retrieval year, number, fraction and spatial distribution of land cover classes by performing convection-permitting simulations driven by ERA5 reanalysis data over Germany from 2002 to 2011. The role of the surface parameters on the surface turbulent fluxes and temperature is examined, which is related to the land cover classes. The bias of the annual temperature cycle of all the simulations compared with observations is larger than the differences between simulations. The latter is well within the uncertainty of the observations. The land cover class fractional differences are small among the land cover maps. However, some land cover types, such as croplands and urban areas, have greatly changed over the years. These distribution changes can be seen in the temperature differences. Simulations based on the CCI retrieved in 2000 and 2015 revealed no accreditable difference in the climate variables as the land cover changes that occurred between these years are marginal, and thus, the influence is small over Germany. Increasing the land cover types as in ECOCLIMAP leads to higher temperature variability. The largest differences among the simulations occur in maximum temperature and from spring to autumn, which is the main vegetation period. The temperature differences seen among the simulations relate to changes in the leaf area index, plant coverage, roughness length, latent and sensible heat fluxes due to differences in land cover types. The vegetation fraction was the main parameter affecting the seasonal evolution of the latent heat fluxes based on linear regression analysis, followed by roughness length and leaf area index. If the same natural vegetation (e.g. forest) or pasture grid cells changed into urban types in another land cover map, daily maximum temperatures increased accordingly. Similarly, differences in climate extreme indices are strongest for any land cover type change to urban areas. The uncertainties in regional temperature due to different land cover datasets were overall lower than the uncertainties associated with climate projections. Although the impact and their implications are different on different spatial and temporal scales as shown for urban area differences in the land cover maps. For future development, more attention should be given to land cover classification in complex areas, including more land cover types or single vegetation species and regional representative classification sample selection. Including more sophisticated urban and vegetation modules with synchronized input data in RCMs would improve the underestimation of the urban and vegetation effect on local climate.



2020 ◽  
Vol 3 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Abdulla Al Kafy ◽  
Abdullah Al-Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Md. Soumik Sikdar ◽  
Mohammad Hasib Hasan Khan ◽  
...  

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.



Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.



2021 ◽  
Vol 13 (3) ◽  
pp. 1099
Author(s):  
Yuhe Ma ◽  
Mudan Zhao ◽  
Jianbo Li ◽  
Jian Wang ◽  
Lifa Hu

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.



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