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 Assessing and Simulating Impacts of Land Use Land Cover Changes on Land Surface Temperature in Mymensingh City, Bangladesh

2021 ◽  
Vol 20 (2) ◽  
pp. 1-19
Author(s):  
Tahmid Anam Chowdhury ◽  
◽  
Md. Saiful Islam ◽  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Bare Soil ◽  
Land Use Land Cover ◽  
Remarkable Change

Urban developments in the cities of Bangladesh are causing the depletion of natural land covers over the past several decades. One of the significant implications of the developments is a change in Land Surface Temperature (LST). Through LST distribution in different Land Use Land Cover (LULC) and a statistical association among LST and biophysical indices, i.e., Urban Index (UI), Bare Soil Index (BI), Normalized Difference Builtup Index (NDBI), Normalized Difference Bareness Index (NDBaI), Normalized Difference Vegetation Index (NDVI), and Modified Normalized Difference Water Index (MNDWI), this paper studied the implications of LULC change on the LST in Mymensingh city. Landsat TM and OLI/TIRS satellite images were used to study LULC through the maximum likelihood classification method and LSTs for 1989, 2004, and 2019. The accuracy of LULC classifications was 84.50, 89.50, and 91.00 for three sampling years, respectively. From 1989 to 2019, the area and average LST of the built-up category has been increased by 24.99% and 7.6ºC, respectively. Compared to vegetation and water bodies, built-up and barren soil regions have a greater LST each year. A different machine learning method was applied to simulate LULC and LST in 2034. A remarkable change in both LULC and LST was found through this simulation. If the current changing rate of LULC continues, the built-up area will be 59.42% of the total area, and LST will be 30.05ºC on average in 2034. The LST in 2034 will be more than 29ºC and 31ºC in 59.64% and 23.55% areas of the city, respectively.

scholarly journals Application of Geo-informatics Technology to Access the Surface Temperature Using LANDSAT 8 OLI/TIRS Satellite Data: A Case Study in Ampara District in Sri Lanka

2020 ◽  
Author(s):  
Ibra Lebbe Mohamed Zahir
Keyword(s):  
Sri Lanka ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Surface Emissivity ◽  
Land Surface Emissivity

Land Surface Temperature is a one of the key variable of Global climate changes and model which estimate radiating budget in heat balance as control of climate model. It is a major influenced factor by the ability of the surface emissivity. In this study, were used Landsat 8 satellite image that have Operational Land Imager and Thermal Infrared Sensor to calculate Land Surface Temperature through geospatial technology over Ampara district, Sri Lanka. The Land Surface Temperature was estimated with respect to Land Surface Emissivity and Normalized Difference Vegetation Index values determined from the Red and Near Infrared channels. Land Surface Emissivity was processed directly by the thermal Infrared bands. Pixels based calculation were used to effort at LANDSAT 8 images that thermal Band 10 various dates in this study. The results were achievable to compute Normalized Difference Vegetation Index, Land Surface Emissivity, and Land Surface Temperature with applicable manner to compare with land use/ land cover data. It determines and predicts the changes of surface temperature to favorable to decision making process for the society. Study area faces seasonal drought in Sri Lanka, the prediction method that how land can be efficiently used with the present condition. Therefore, the Land Surface Temperature estimation can prove whether new irrigation systems for agricultural activities or can transformed source of energy into useful form that introducing solar hubs for energy production in future.

scholarly journals Investigating Land Surface Temperature Changes Using Landsat Data in Konya, Turkey

2016 ◽  
Vol XLI-B8 ◽  
pp. 285-289 ◽  
Author(s):  
O. Orhan ◽  
M. Yakar
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Salt Lake ◽  
Meteorological Data ◽  
Landsat 8 ◽  
Remotely Sensed Data ◽  
Landsat 5 Tm

The main purpose of this paper is to investigate multi-temporal land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) changes of Konya in Turkey using remotely sensed data. Konya is located in the semi-arid central Anatolian region of Turkey and hosts many important wetland sites including Salt Lake. Six images taken by Landsat-5 TM and Landsat 8- OLI satellites were used as the basic data source. These raw images were taken in 1984, 2011 and 2014 intended as long-term and short-term. Firstly, those raw images was corrected radiometric and geometrically within the scope of project. Three mosaic images were obtained by using the full-frame images of Landsat-5 TM / 8- OLI which had been already transformed comparison each other. Then, Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) maps have been produced to determine the dimension of the drought. The obtained results showed that surface temperature rates in the basin increased about 5°C between 1984 and 2014 as long periods, increased about 2-3°C between 2011and 2014 as short periods. Meteorological data supports the increase in temperature.

scholarly journals ASSESSMENT OF RELATIONSHIP BETWEEN LAND SURFACE TEMPERATURE AND NORMALIZED DIFFERENT VEGETATION INDEX USING LANDSAT IMAGES IN SOME REGIONS OF DIYALA GOVERNORATE

2021 ◽  
Vol 52 (4) ◽  
pp. 793-801
Author(s):  
Al-Jbouri & Al-Timimi
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Conditions ◽  
Landsat 8 ◽  
Landsat Images ◽  
Remote Sensing Techniques ◽  
The Relationship

Agriculture is the most important and most dependent economic activity and influenced by climatic conditions as the climate elements represented by solar radiation, temperature, wind and relative humidity. Therefore, is necessary that analyze and understand the relationship between climate and agriculture. The aim of this study to assessment the relationship between land surface temperature (LST) and normalized difference vegetation index (NDVI) for three regions of Diyala Governorate in Iraq (Al Muqdadya, Baladrooz, and Baquba) by through using of remote sensing techniques and geographic information system (GIS).The Normalized difference vegetation index NDVI and land surface temperature (LST) were used in two of the Landsat-5 ETM + and Landsat-8 OLI satellite imagery during the years 1999 and 2019.  The results showed that increased in NDVI and decreased in LST for 2019, while for 1999 increased in LST and decreased in NDVI for the three regions. Finally, the regression was used to obtain that correlation between LST and NDVI. It was concluded that the correlation coefficient between NDVI and LST is negative, where the strongest correlation was 0.76 for Baquba and weakest correlation was 0.55 for Muqdadyia.

scholarly journals Multi-criteria modelling of drought: a study of Brandenburg Federal State, Germany

2021 ◽  
Author(s):  
Christopher Ihinegbu ◽  
Taiwo Ogunwumi
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Federal State ◽  
Landsat 8 ◽  
Gis And Remote Sensing ◽  
Drought Assessment

AbstractDrought is the absence or below-required supply of precipitation, runoff and or moisture for an extended time period. Modelling drought is relevant in assessing drought incidence and pattern. This study aimed to model the spatial variation and incidence of the 2018 drought in Brandenburg using GIS and remote sensing. To achieve this, we employed a Multi-Criteria Approach (MCA) by using three parameters including Precipitation, Land Surface Temperature and Normalized Difference Vegetation Index (NDVI). We acquired the precipitation data from Deutsche Wetterdienst, Land Surface Temperature and NDVI from Landsat 8 imageries on the USGS Earth Explorer. The datasets were analyzed using ArcGIS 10.7. The information from these three datasets was used as parameters in assessing drought prevalence using the MCA. The MCA was used in developing the drought model, ‘PLAN’, which was used to classify the study area into three levels/zones of drought prevalence: moderate, high and extreme drought. We went further to quantify the agricultural areas affected by drought in the study area by integrating the land use map. Results revealed that 92% of the study area was severely and highly affected by drought especially in districts of Oberhavel, Uckermark, Potsdam-Staedte, and Teltow-Flaeming. Finding also revealed that 77.54% of the total agricultural land falls within the high drought zones. We advocated for the application of drought models (such as ‘PLAN’), that incorporates flexibility (tailoring to study needs) and multi-criteria (robustness) in drought assessment. We also suggested that adaptive drought management should be championed using drought prevalence mapping.

ANALISIS SPASIAL KERAPATAN BANGUNAN DAN PENGARUHNYA TERHADAP SUHU Studi Kasus di Kabupaten Bogor

2019 ◽  
Vol 3 ◽  
pp. 529
Author(s):  
Mega Adeanti ◽  
Muhammad Chaidir Harist
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Level 1

Kabupaten Bogor merupakan salah satu kabupaten yang saat ini pembangunannya cukup berkembang. Pada tahun 2016 jumlah penduduk di Kabupaten Bogor berjumlah 5.715.009 jiwa. Bertambahnya penduduk menyebabkan berkurangnya lahan dengan tutupan vegetasi menjadi daerah yang terbangun, dari bertambahnya lahan terbangun meyebabkan meningkatnya suhu di Kabupaten Bogor. Dengan pemanfaatan Sistem Informasi Geografis (SIG) dapat diketahui peningkatan suhu akibat dari padatnya bangunan di Kabupaten Bogor. Melalui pengolahan Citra Landsat 8 OLI/TIRS C1 Level-1 dengan ukuran 30 x 30 m tahun 2018 digunakan metode Normalized Difference Vegetation Index (NDVI) untuk mengetahui indeks kerapatan vegetasi, Normalized Difference Built Index (NDBI) untuk mengetahui kerapatan bangunan, dan metode Land Surface Temperature (LST) untuk mengetahui suhu permukaan di Kabupaten Bogor. Hasil yang didapatkan dari penelitian ini adalah semakin rapatnya bangunan maka suhu semakin tinggi dan sebaliknya, begitu juga dengan luas dari wilayah yang mengalami kenaikan suhu.

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 Investigating Land Surface Temperature Changes Using Landsat Data in Konya, Turkey

2016 ◽  
Vol XLI-B8 ◽  
pp. 285-289 ◽  
Author(s):  
O. Orhan ◽  
M. Yakar
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Salt Lake ◽  
Meteorological Data ◽  
Landsat 8 ◽  
Remotely Sensed Data ◽  
Landsat 5 Tm

The main purpose of this paper is to investigate multi-temporal land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) changes of Konya in Turkey using remotely sensed data. Konya is located in the semi-arid central Anatolian region of Turkey and hosts many important wetland sites including Salt Lake. Six images taken by Landsat-5 TM and Landsat 8- OLI satellites were used as the basic data source. These raw images were taken in 1984, 2011 and 2014 intended as long-term and short-term. Firstly, those raw images was corrected radiometric and geometrically within the scope of project. Three mosaic images were obtained by using the full-frame images of Landsat-5 TM / 8- OLI which had been already transformed comparison each other. Then, Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) maps have been produced to determine the dimension of the drought. The obtained results showed that surface temperature rates in the basin increased about 5°C between 1984 and 2014 as long periods, increased about 2-3°C between 2011and 2014 as short periods. Meteorological data supports the increase in temperature.

scholarly journals Analisis Fenomena Pulau Panas Perkotaan Kota Bandung Menggunakan Google Earth Engine

2019 ◽  
Author(s):  
Muhammad Malik Ar-Rahiem ◽  
Muhamad Riza Fakhlevi
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Google Earth ◽  
Landsat 8 ◽  
Heat Island ◽  
Urban Heat ◽  
Google Earth Engine

Pulau Panas Perkotaan (Urban Heat Island) adalah fenomena antropogenik akibat pengaruh urbanisasi. Kawasan perkotaan yang terbangun memiliki temperatur yang lebih hangat dibandingkan kawasan sekitarnya. Fenomena Pulau Panas Perkotaan di Kota Bandung diteliti menggunakan data Suhu Permukaan Tanah (Land Surface Temperature) yang diakuisisi dari satelit Landsat 8. Lima tahun data satelit dianalisis menggunakan piranti daring Google Earth Engine untuk menganalisis variasi temporal Pulau Panas Perkotaan di Kota Bandung dan sekitarnya. Suhu yang diakuisisi dari satelit dikonversi menjadi estimasi suhu permukaan dengan mempertimbangkan nilai Normalized Difference Vegetation Index. Hasil dari penelitian ini adalah peta persebaran rata-rata dan median suhu permukaan di Cekungan Bandung tahun 2013-2018, serta grafik seri waktu suhu permukaan di 3 jenis tata guna lahan yang mewakili daerah kota (sekitar Jalan Sudirman), hutan kota (Hutan Babakan Siliwangi), dan hutan (Tamah Hutan Raya Djuanda). Suhu rata-rata Kota Bandung pada tahun 2013-2018 adalah 26,93 oC (median seluruh data) dan 25,57oC (rata-rata seluruh data). Sementara perbandingan berdasarkan tata guna lahan; daerah kota memiliki suhu permukaan rata-rata 27,30 oC, daerah hutan kota memiliki suhu 21,31oC, dan daerah hutan memiliki suhu 18,60oC. Peta persebaran suhu panas permukaan dari citra Landsat 8 menunjukkan bahwa daerah hutan secara konsisten memiliki suhu paling rendah, diikuti dengan hutan kota, dan kemudian daerah kota menjadi area yang paling panas dengan suhu maksimal hingga 33,73oC. Penggunaan Google Earth Engine yang berbasis komputasi awan sangat memudahkan pengolahan data citra satelit dalam jumlah besar yang selama ini tidak memungkinkan dilakukan dengan cara konvensional (mengunduh dan memproses di komputer).

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