scholarly journals SPATIAL AND TEMPORAL VARIABILITY OF SURFACE TEMPERATURE, LAND USE AND LAND COVER CHANGE: A CASE STUDY IN CAMPINAS, BRAZIL

2021 ◽  
Vol 28 ◽  
Author(s):  
Luiza Marchezan Bezerra ◽  
Ana Maria Heuminski de Avila
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface ◽  
Land Use Changes ◽  
Thermal Infrared ◽  
Climatic Conditions ◽  
Spatial And Temporal Variability ◽  
Landsat 8 ◽  
Climatic Data ◽  
Infrared Sensor

deteriorating climatic conditions in urban centers of Brazil is a real concern for human security and urban livelihood sustainability.  The city of Campinas in São Paulo state/Brazil is highly vulnerable to climatic disasters. The present paper analyses the relationship between land use changes and temperature in Campinas between 1989 and 2016. The 28-year period was chosen due to the variability of climatic data in three meteorological stations (University of Campinas, Agronomic Institute of Campinas and International Airport of Viracopos). Data from five sources were used for land use land changes (LULC), and land surface temperature (LST) analysis. The data sources were: i) Landsat 5 Thermometer Mapper (TM), ii) Landsat 5 Thermal Infrared Sensor (TIRS), iii) Thermal Infrared Sensor (ETM +) sensors from Landsat 5, iv) Landsat 8 Operational Land Imager (OLI), and v) Thermal Infrared Sensor (TIRS). The results indicate consistent relations between urbanized increase area and the elevation of air and surface temperature in Campinas. In the studied period, there was an increase of 23% in urbanized areas in Campinas and around the meteorological stations. Cepagri presented the highest growth, about 22%, as well as the station with the highest air temperature

scholarly journals Land Surface Temperature Retrieval from LANDSAT-8 Thermal Infrared Sensor Data and Validation with Infrared Thermometer Camera

2018 ◽  
Vol 7 (4.20) ◽  
pp. 608 ◽  
Author(s):  
Muhammad Mejbel Salih ◽  
Oday Zakariya Jasim ◽  
Khalid I. Hassoon ◽  
Aysar Jameel Abdalkadhum
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Infrared Sensor ◽  
Infrared Thermometer ◽  
Ground Truth Data ◽  
Land Cover Types

This paper illustrates a proposed method for the retrieval of land surface temperature (LST) from the two thermal bands of the LANDSAT-8 data. LANDSAT-8, the latest satellite from Landsat series, launched on 11 February 2013, using LANDSAT-8 Operational Line Imager and Thermal Infrared Sensor (OLI & TIRS) satellite data. LANDSAT-8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12 bits. In this search a trial has been made to estimate LST over Al-Hashimiya district, south of Babylon province, middle of Iraq. Two dates images acquired on 2nd &18th of March 2018 to retrieve LST and compare them with ground truth data from infrared thermometer camera (all the measurements contacted with target by using type-k thermocouple) at the same time of images capture. The results showed that the rivers had a higher LST which is different to the other land cover types, of less than 3.47 C ◦, and the LST different for vegetation and residential area were less than 0.4 C ◦ with correlation coefficient of the two bands 10 and 11 Rbnad10= 0.70, Rband11 = 0.89 respectively, for the imaged acquired on the 2nd of march 2018 and Rband10= 0.70 and Rband11 = 0.72 on the 18th of march 2018. These results confirm that the proposed approach is effective for the retrieval of LST from the LANDSAT-8 Thermal bands, and the IR thermometer camera data which is an effective way to validate and improve the performance of LST retrieval. Generally the results show that the closer measurement taken from the scene center time, a better quality to classify the land cover. The purpose of this study is to assess the use of LANDSAT-8 data to specify temperature differences in land cover and compare the relationship between land surface temperature and land cover types.   

scholarly journals An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data

2015 ◽  
Vol 7 (4) ◽  
pp. 4268-4289 ◽  
Author(s):  
Fei Wang ◽  
Zhihao Qin ◽  
Caiying Song ◽  
Lili Tu ◽  
Arnon Karnieli ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Infrared ◽  
Sensor Data ◽  
Landsat 8 ◽  
Infrared Sensor ◽  
Temperature Retrieval

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.

Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data

2014 ◽  
Vol 11 (10) ◽  
pp. 1840-1843 ◽  
Author(s):  
Juan C. Jimenez-Munoz ◽  
Jose A. Sobrino ◽  
Drazen Skokovic ◽  
Cristian Mattar ◽  
Jordi Cristobal
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Infrared ◽  
Sensor Data ◽  
Landsat 8 ◽  
Infrared Sensor ◽  
Temperature Retrieval

scholarly journals Heat distribution modeling of the subsurface of Wapsalit geothermal area based on land surface temperature from Landsat-8 thermal infrared sensor imagery

2019 ◽  
Vol 15 (2) ◽  
pp. 182-184
Author(s):  
Joko Sampurno ◽  
Apriansyah Apriansyah ◽  
Riza Adriat
Keyword(s):  
Heat Flow ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Infrared ◽  
Model Parameters ◽  
Landsat 8 ◽  
Heat Distribution ◽  
Geothermal Area ◽  
Infrared Sensor

In this research, models of heat distribution of the subsurface of the Wapsalit geothermal area were built, which their structures were known before, using finite different method. Rock thermal diffusivity was used as the model parameter, which controlled the heat flow. The result showed that the heat flow was adjusted the model parameters effectively. Land surface temperature (LST) as the result of the model was compared to LST from Landsat-8 Thermal Infrared Sensor Imagery and produced absolute error 6.8% and 3.6% for cross-section 1 and 2, respectively. This error percentage confirmed that the model was successfully depicted the actual heat distribution of the subsurface of the study area.

scholarly journals SPATIOTEMPORAL MULTI-SATELLITE BIOPHYSICAL DATA ANALYSIS OF THE EFFECT OF URBANIZATION ON LAND SURFACE AND AIR TEMPERATURE IN BAGUIO CITY, PHILIPPINES

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 47-54
Author(s):  
A. Baloloy ◽  
R. R. Sta. Ana ◽  
J. A. Cruz ◽  
A. C. Blanco ◽  
N. V. Lubrica ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Land Use Changes ◽  
High Rate ◽  
Landsat 8 ◽  
Landsat Images

Abstract. Urbanization can be observed through the occurrence of land-use changes as more land is being transformed and developed for urban use. One of the Philippine cities with high rate of urbanization is Baguio City, known for having a subtropical highland climate. To understand the spatiotemporal relationship between urbanization and temperature, this study aims to analyze the correlation of urban extent with land surface and air temperature in Baguio City using satellite-based built-up extents, land surface temperature (LST) maps, and weather station-recorded air temperature data. Built-up extent layers were derived from three satellite images: Landsat, RapidEye and PlanetScope. Land-use land cover (LULC) maps were generated from Landsat images using biophysical indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI); while RapidEye and PlanetScope built-up extent maps were generated by applying the visible green-based built-up index (VgNIR-BI). Mean LST values from 1988 to 2018 during the dry and wet seasons were calculated from the Landsat-retrieved surface temperature layers. The result of the study shows that the increase in the built-up extent significantly intensified the LST during the dry season which was observed in all satellite data-derived built-up maps: RapidEye+PlanetScope (2012–2018; r = 0.88), Landsat 8 (2012–2018; r = 0.63) and Landsat 5,7,8 (1988–2018; r = 0.61). The main LST hotspots were detected inside the Central Business District where it expanded gradually from year 1998 (43 ha) to 2011 (83 ha), but have increased extensively within the years 2014 to 2019 (305 ha). On average, 98.5% of the hotspots detected from 1995 to 2019 are within the equivalent built-up area.

scholarly journals PEMANFAATAN CITRA SATELIT LANDSAT 8 UNTUK MEMETAKAN SEBARAN TITIK PANASSEBAGAI INDIKASI PENINGKATAN SUHU PERMUKAAN TANAH DI KABUPATEN KUTAI TIMUR

2021 ◽  
Vol 46 (3) ◽  
pp. 383
Author(s):  
Donny Dhonanto ◽  
Nurul Puspita Palupi ◽  
Ghaisani Salsabila
Keyword(s):  
Land Use ◽  
Information System ◽  
Data Analysis ◽  
Geographic Information System ◽  
Surface Temperature ◽  
Land Surface ◽  
Maximum Temperature ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Area Distribution

 Transformation of land-use cause forest area decrease that will affect microclimate (weather tends heat), thus hotspot may possible to scattered in that area and raise the transformation of surface temperature. The objective of this research is to determine the indication of surface temperature in the East Kutai District. The advantage of this research is to give information about hotspot area distribution based on land use and relate between hotspots with surface temperature increase so it is supposed to be one of the consider to transform land use in East Kutai District. This research was held from April until May 2019 at the Laboratory of Carthography and Geographic Information System, Faculty of Agriculture, Mulawarman University. This research using calculation of Land Surface Temperature (LST) value to determine the transformation of surface temperature in East Kutai District by data analysis from Landsat-8 OLI/TIRS satellite. Hotspot area distribution adapted to map of land-use so we found the source of the hotspot. The result of the research shows there are about 6 hotspots in land-use of plantation in 2017 and the increase of the surface temperature is not static cause by depending of rainfall in East Kutai District. Increasing of surface temperature in East Kutai District in October 2013 become 22.35 oC (for minimum temperature), whereas in May 2017 become 37.24 oC (for maximum temperature). 

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.

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