scholarly journals Remote sensing inversion and spatial variation of land surface temperature over mining areas of Jixi, Heilongjiang, China

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10257
Author(s):  
Jia-shuo Cao ◽  
Zheng-yu Deng ◽  
Wen Li ◽  
Yuan-dong Hu
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Coal Mining ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Coverage ◽  
Landsat 8 ◽  
Mining Activities ◽  
Patch Area ◽  
Mining Areas

Background Jixi is a typical mining city in China that has undergone dramatic changes in its land-use pattern of mining areas over the development of its coal resources. The impacts of coal mining activities have greatly affected the regional land surface temperature and ecological system. Methods The Landsat 8 Operational Land Imager (OLI) data from 2015 and 2019 were used from the Jiguan, Didao, and Chengzihe District of Jixi in Heilongjiang, China as the study area. The calculations to determine the land-use classification, vegetation coverage, and land surface temperature (LST) were performed using ArcGIS10.5 and ENVI 5.3 software packages. A correlation analysis revealed the impact of land-use type, vegetation coverage, and coal mining activities on LSTs. Results The results show significant spatial differentiation in the LSTs of Jixi City. The LSTs for various land-use types were ranked from high to low as follows: mining land > construction land > grassland > cultivated land > forest land > water area. The LST was lower in areas with high vegetation coverage than in other areas. For every 0.1 increase in vegetation coverage, the LST is expected to drop by approximately 0.75 °C. An analysis of mining land patches indicates that the patch area of mining lands has a significant positive correlation with both the average and maximum patch temperatures. The average patch temperature shows a logarithmic increase with the growth of the patch area, and within 200,000 m2, the average patch temperature increases significantly. The maximum patch temperature shows a linear increase with the patch area growth, and for every 100,000 m2 increase in the patch area of mining lands, the maximum patch temperature increases by approximately 0.81 °C. The higher the average patch temperature of mining land, the higher the temperature in its buffer zone, and the greater its influence scope. This study provides a useful reference for exploring the warming effects caused by coal mining activities and the definition of its influence scope.

scholarly journals The Effects of Land Use Zoning and Densification on Changes in Land Surface Temperature in Seoul

2019 ◽  
Vol 11 (24) ◽  
pp. 7056 ◽  
Author(s):  
Jae-Ik Kim ◽  
Myung-Jin Jun ◽  
Chang-Hwan Yeo ◽  
Ki-Hyun Kwon ◽  
Jun Yong Hyun
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Descriptive Analysis ◽  
Landsat 8 ◽  
Land Use Type ◽  
Coverage Ratio

This study investigated how changes in land surface temperature (LST) during 2004 and 2014 were attributable to zoning-based land use type in Seoul in association with the building coverage ratio (BCR), floor area ratio (FAR), and a normalized difference vegetation index (NDVI). We retrieved LSTs and NDVI data from satellite images, Landsat TM 5 for 2004 and Landsat 8 TIRS for 2014 and combined them with parcel-based land use information, which contained data on BCR, FAR, and zoning-based land use type. The descriptive analysis results showed a rise in LST for the low- and medium-density residential land, whereas significant LST decreases were found in high-density residential, semi-residential, and commercial areas over the time period. Statistical results further supported these findings, yielding statistically significant negative coefficient values for all interaction variables between higher-density land use types and a year-based dummy variable. The findings appear to be related to residential densification involving the provision of more high-rise apartment complexes and government efforts to secure more parks and green spaces through urban redevelopment and renewal projects.

scholarly journals Deteksi Perubahan Suhu Permukaan Menggunakan Data Satelit Landsat Multi-Waktu Studi Kasus Cekungan Bandung

2018 ◽  
Vol 19 (2) ◽  
pp. 145 ◽  
Author(s):  
Widya Ningrum ◽  
Ida Narulita
Keyword(s):  
Land Use ◽  
Temperature Distribution ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Surface Temperature Distribution

ABSTRACTThe rapid population growth and development of infrastructure in the Bandung basin has triggered an uncontrolled land use changes. The changes of land use will impact on land surface temperature distribution. Finally, these changes will give influence on climate. Land surface temperature is one of the important climatic elements in the energy balance. Changes in land surface temperature variations will potentially change other elements of the climate. The purpose of this paper is to obtain and to analyze the changes of surface temperature distribution in Bandung basin using multi temporal satellite data processing that is Landsat 5 and Landsat 8 in 2004, 2009 and 2014. Near Infrared Channel (Near Infrared/NIR) and visible wave channels (Visible band) have used to obtain the value Normalized Difference Vegetation Index/NDVI index and Albedo. Land and vegetation emissivity value and thermal band have used to determine land surface temperature. The results showed that the surface temperature distribution of Bandung basin has been changes characterized by the presence of two hotspot characters i.e. hot areas in urban and hot areas in non-urban area. The area is characterized by decreasing vegetation index values, increasing albedo values and increasing on surface temperature.  Land Surface Temperatures average value increased by 1.3°C. Land surface temperature tends to rise supposed as a result of changes in vegetated area into open area and the build area  Keywords: land surface temperature, normalized difference vegetation index, albedoABSTRAKPesatnya pertumbuhan penduduk dan perkembangan infrastruktur di cekungan Bandung telah memicu perubahan tutupan lahan yang tidak terkendali. Perubahan tutupan lahan akan mempengaruhi distribusi suhu permukaan. Hal tersebut pada akhirnya nanti akan mempengaruhi iklim. Suhu permukaan merupakan salah satu unsur iklim yang penting dalam neraca energi. Perubahan variasi suhu permukaan berpotensi mengubah unsur unsur iklim yang lainnya. Tujuan makalah ini adalah untuk mengetahui dan menganalisis perubahan distribusi suhu permukaan di cekungan Bandung melalui pengolahan data satelit multi waktu yaitu Landsat 5 dan Landsat 8 tahun 2004, 2009, 2014 dan 2016. Kanal Inframerah Dekat (Near Infrared/NIR) dan kanal gelombang tampak (Visible band) digunakan untuk memperoleh nilai Indeks Kehijauan Vegetasi (Normalized Difference Vegetation Index/NDVI) dan Albedo. Nilai emisivitas dari tanah dan vegetasi serta Band termal digunakan untuk menentukan nilai Suhu Permukaan Tanah.Hasil penelitian menunjukkan bahwa di cekungan Bandung telah terjadi perubahan distribusi suhu permukaan yang dicirikan oleh adanya dua karakter hotspot yaitu daerah panas di daerah urban dan daerah panas di daerah non-urban. Daerah tersebut dicirikan menurunnya nilai indeks vegetasi, menurunnya nilai albedo dan meningkatnya nilai suhu permukaan tanah. Nilai rataan Suhu Permukaan Tanah tahun 2005 - 2014 meningkat sebesar 1.3°C. Kecenderungan naik ini diduga sebagai akibat adanya perubahan tutupan lahan bervegetasi menjadi daerah yang lebih terbuka dan daerah terbangun.Kata kunci: suhu permukaan, indeks kehijauan vegetasi, albedo 

scholarly journals STUDY OF LAND USE CHANGES AND ITS RELATIONSHIP WITH TEMPERATURE AND DENGUE FEVER IN 2003 AND 2016 OVER JAKARTA PROVINCE USING LANDSAT 7+ETM AND LANDSAT 8 OLI

2018 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Risya Lailarahma ◽  
I Wayan Sandi Adnyana
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Surface Temperature ◽  
Dengue Fever ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Land Use Changes ◽  
Water Infiltration ◽  
Landsat 8 ◽  
Temperature Changes

Land use changes over Jakarta caused by urbanization affected the increasing of infrastructure and decreasing vegetation from 2003 to 2016. This condition reduced water infiltration and caused inundation when heavy rainfall coming. Then Aedes aegypti would breed.and increased which brought dengue fever desease. This study was about analyzing the land use change in Jakarta Province using Landsat image, and its relationship with land surface temperature and dengue fever distribution. The effects of land use change also analysed by this study which including the effects from temperature and dengue fever that analysed by indices of land use in Jakarta at 2003 and 2016. The temperature analysis could be obtained by TIR band in Landsat and using some algortitma which calculated in band math of ENVI software. Vegetation index value’s average decreased from 0.652 in 2003 to 0.647 2016 in 2016. Built up index value’s average increased from -0.03 in 2003 to -0.02 in 2016. While Bareland index value’s average decreased from 0.16 in 2003 to -0.46 in 2016. Land surface temperature increased 3?C from 2003 to 2016. Vegetation area decreased 27.929 ha, bare land area decreased 6.012 ha, while built up area increased 34.278 ha from 2003 to 2016. Increasing of land surface temperature proportional to increasing dengue fever patients 1.187 patients. Increasing of land surface temperature increasing dengue fever cases 1.187 patients. To review and monitor more about the relationship between landuse changes and temperature changes required image with high resolution so that the results obtained more accurate. Complete data of dengue fever per subdistricts also required to analyse further more about relationship between landuse changes, temperature changes, and dengue fever.

scholarly journals DETERMINING THE IMPACTS OF LAND COVER/USE CATEGORIES ON LAND SURFACE TEMPERATURE USING LANDSAT8-OLI

2016 ◽  
Vol XLI-B8 ◽  
pp. 251-256 ◽  
Author(s):  
F. Bektas Balcik ◽  
E. M. Ergene
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Tasseled Cap ◽  
Tasseled Cap Transformation ◽  
The Impact ◽  
Use Categories

Due to unplanned and uncontrolled expansion of urban areas, rural land cover types have been replaced with artificial materials. As a result of these replacements, a wide range of negative environmental impacts seriously impacting human health, natural areas, ecosystems, climate, energy efficiency, and quality of living in town center. In this study, the impact of land surface temperature with respect to land cover and land use categories is investigated and evaluated for Istanbul, Turkey. Land surface temperature data was extracted from 21 October 2014 dated Landsat 8 OLI data using mono-window algorithm. In order to extract land use/cover information from remotely sensed data wetness, greenness and brightness components were derived using Tasseled Cap Transformation. The statistical relationship between land surface temperature and Tasseled Cap Transformation components in Istanbul was analyzed using the regression methods. Correlation between Land Surface Temperature and Meteorological Stations Temperature calculated %74.49.

scholarly journals Analysis of Land Use Land Cover Changes with Land Surface Temperature Using Spatial-Temporal Data for Nagpur City, India

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Farhan Khan ◽  
Bhumika Das ◽  
R. K. Mishra ◽  
Brijesh Patel
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Spatial Data ◽  
Land Surface ◽  
Water Bodies ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Barren Land

Abstract Remote sensing and Geographic Information System (GIS) are the most efficient tools for spatial data processing. This Spatial technique helps in generating data on natural resources such as land, forests, water, and their management with planning. The study focuses on assessing land change and surface temperature for Nagpur city, Maharashtra, for two decades. Land surface temperature and land use land cover (LULC) are determined using Landsat 8 and Landsat 7 imageries for the years 2000 and 2020. The supervised classification technique is used with a maximum likelihood algorithm for performing land classification. Four significant classes are determined for classification, i.e., barren land, built-up, vegetation and water bodies. Thermal bands are used for the calculation of land surface temperature. The land use land cover map reveals that the built-up and water bodies are increasing with a decrease in vegetation and barren land. Likewise, the land surface temperature map showed increased temperature for all classes from 2000 to 2020. The overall accuracy of classification is 98 %, and the kappa coefficients are 0.98 and 0.9 for the years 2000 and 2020, respectively. Due to urban sprawl and changes in land use patterns, the increase in land surface temperature is documented, which is a global issue that needs to be addressed.

scholarly journals DETERMINING THE IMPACTS OF LAND COVER/USE CATEGORIES ON LAND SURFACE TEMPERATURE USING LANDSAT8-OLI

2016 ◽  
Vol XLI-B8 ◽  
pp. 251-256
Author(s):  
F. Bektas Balcik ◽  
E. M. Ergene
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Tasseled Cap ◽  
Tasseled Cap Transformation ◽  
The Impact ◽  
Use Categories

Due to unplanned and uncontrolled expansion of urban areas, rural land cover types have been replaced with artificial materials. As a result of these replacements, a wide range of negative environmental impacts seriously impacting human health, natural areas, ecosystems, climate, energy efficiency, and quality of living in town center. In this study, the impact of land surface temperature with respect to land cover and land use categories is investigated and evaluated for Istanbul, Turkey. Land surface temperature data was extracted from 21 October 2014 dated Landsat 8 OLI data using mono-window algorithm. In order to extract land use/cover information from remotely sensed data wetness, greenness and brightness components were derived using Tasseled Cap Transformation. The statistical relationship between land surface temperature and Tasseled Cap Transformation components in Istanbul was analyzed using the regression methods. Correlation between Land Surface Temperature and Meteorological Stations Temperature calculated %74.49.

scholarly journals Land Use/Land Cover Changes and the Relationship with Land Surface Temperature Using Landsat and MODIS Imageries in Cameron Highlands, Malaysia

Land ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 372
Author(s):  
Darren How Jin Aik ◽  
Mohd Hasmadi Ismail ◽  
Farrah Melissa Muharam
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Cameron Highlands ◽  
The Impact

Mountainous regions are more sensitive to climatic condition changes and are susceptible to recent increases in temperature. Due to urbanization and land use/land cover (LULC) issues, Cameron Highlands has been impacted by rising land surface temperature (LST) variation. Thus, this study was carried out to explore the impact of the LULC change on LST in the Cameron Highlands from 2009 to 2019 using remote sensing images acquired from Landsat 7 ETM+, Landsat 8 Operational Land Imager (OLI/TIRS), and Moderate Resolution Imaging Spectroradiometer (MODIS) 11A Thermal sensors. A split-window algorithm was applied to Landsat 8 images (2013–2019) to derive the LST. Air temperature data of the study area were also obtained to cross-validate data sources. Based on the validation results, the accuracy of LULC and LST outputs were more than 94.6% and 80.0%, respectively. The results show that the current trend of urban growth continues at a rate of 0.16% per year, and the area experienced an LST increase of 2 °C between 2009 and 2019. This study is crucial for land planners and environmentalists to understand the impacts of LULC change on LST and to propose appropriate policy measures to control development in Cameron Highlands.

scholarly journals LAND USE ANALYSIS ON LAND SURFACE TEMPERATURE IN URBAN AREAS USING A GEOGRAPHICALLY WEIGHTED REGRESSION AND LANDSAT 8 IMAGERY, A CASE STUDY: TEHRAN, IRAN

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 117-122 ◽  
Author(s):  
A. Karimi ◽  
P. Pahlavani ◽  
B. Bigdeli
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Spatial Data ◽  
Geographically Weighted Regression ◽  
Land Surface ◽  
Urban Areas ◽  
Weighted Regression ◽  
Landsat 8 ◽  
Spatial Factors

Due to urbanization and changes in the urban thermal environment and because the land surface temperature (LST) in urban areas are a few degrees higher than in surrounding non-urbanized areas, identifying spatial factors affecting on LST in urban areas is very important. In this regard, due to the unique properties of spatial data, in this study, a geographically weighted regression (GWR) was used to identify effective spatial factors. The GWR is a suitable method for spatial regression issues, because it is compatible with two unique properties of spatial data, i.e. the spatial autocorrelation and spatial non-stationarity. In this study, the Landsat 8 satellite data on 18 August 2014 and Tehran land use data in 2006 was used for determining the land surface temperature and its effective factors. As a result, R<sup>2</sup> value of 0.765983 was obtained by taking the Gaussian kernel. The results showed that the industrial,military, transportation, and roads areas have the highest surface temperature.

scholarly journals Land Use/Land Cover Change With Impact On Land Surface Temperature: A Case Study Of Mkda Planning Area, West Bengal, India

2020 ◽  
Vol 13 (4) ◽  
pp. 43-53
Author(s):  
Samrin Fatema ◽  
Dr. Abhisek Chakrabarty
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Landsat 8 ◽  
Hard Material ◽  
Local Climate ◽  
Landsat 7 ◽  
Multi Temporal

The type of surface influences the temperature of a surface. If it is made of concrete or another hard material, the temperature will be higher. Hence it is essential to study the land surface temperature (LST) of urban areas. The LST is an important parameter in the estimation of radiation budgets and heat balance and is a controlling factor of dynamic climate changes. In this work, we made an effort to identify the LST of the Midnapore Kharagpur Development Authority planning region. Multi-temporal images acquired by Landsat 7 ETM+, Landsat 5 TM and Landsat 8 using OLI sensors on 3 May 2001, 7 May 2011 and 29 May 2019, respectively, were corrected for radiometric and geometric errors and processed to extract LULC classes and LST. Thermal remote sensing can be used to monitor the temperature and local climate of urban areas. This study has shown that the temperature varies across the surface according to land use. It was found that the urbanized area increased from 6.79% (40.39 sq. km) to 11.6% (69.2 sq. km) between 2001 and 2011 and from 11.6% (69.2 sq. km) to 17.22 % (102.79 sq. km) between 2011 and 2019. The LST study has shown that there has been a tremendous change in the spatial pattern of the temperature between 2001 and 2019. Whereas in 2001 the highest temperature did not exceed 34°C, by 2019 it had increased by nearly 8°C, reaching 41.29°C. So, the findings of this study are significant.

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