scholarly journals Assessment of the land surface temperature dynamics in the city of Sofia using Landsat satellite data

2018 ◽  
Author(s):  
Ivan Yanev ◽  
Lachezar Filchev
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Temperature Dynamics ◽  
Landsat Satellite ◽  
The City

scholarly journals Spatiotemporal analysis of the land surface temperature distribution over the territory of Novosibirsk city based on Landsat data

2020 ◽  
Vol 223 ◽  
pp. 03011
Author(s):  
Elena A. Mamash ◽  
Igor A. Pestunov ◽  
Dmitri L. Chubarov
Keyword(s):  
Temperature Distribution ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Spatiotemporal Analysis ◽  
Landsat 8 ◽  
Surface Temperature Distribution ◽  
Development Analysis ◽  
The City

The paper discusses the applicability of Landsat 8 data for analyzing the land surface temperature distribution over the territory of Novosibirsk. The satellite data is compared with the data from ground meteorological stations. Using cloud-based systems and methods for processing time series of satellite data, a composite image of the temperature field for the territory of Novosibirsk is built; trends and anomalies in the temperature distribution in the urban area are studied. The results could be applied in urban development analysis and management of the city territory.

scholarly journals Estimation of land surface temperature using Landsat satellite data: A case study of Mueang Maha Sarakham District, Maha Sarakham Province, Thailand for the years 2006 and 2015

2019 ◽  
Vol 27 (4) ◽  
pp. 401-409
Author(s):  
Tanutdech Rotjanakusol ◽  
Teerawong Laosuwan
Keyword(s):  
Data Analysis ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Statistical Correlation ◽  
Climatic Conditions ◽  
Infrared Band ◽  
Landsat Satellite ◽  
High Level

At present, the climate has constantly been changing, especially the increase in global average temperature that results in the risk of severe climatic conditions such as heat wave, drought and flood. The objective of this study is to estimate land surface temperature (LST) by applying Landsat satellite data in Mueang Maha Sarakham District, Maha Sarakham Province, Thailand. The study focuses on investigating the temperature changes for the years 2006 and 2015. The research was conducted by analyzing the satellite data in the thermal infrared band with a geo-informatics package software mutually with mathematical models. The operation results indicated that the average LST was at 26.28°C in 2006 and 27.15°C in 2015. In order to verify the accuracy of the data in this study, the results of the annual satellite data analysis were brought to find out a statistical correlation with the LST data from the Meteorological Station of Thai Meteorological Department (TMD). The results indicated that there was a correlation of the data at a high level in 2006 and 2015. The results of this study indicated that the satellite data analysis method is reliable and can be used to analyze, track, and verify data to predict surface temperatures effectively.

scholarly journals Assessment of thermal conditions in Krasnoyarsk urban area with use of different satellite data and geographic information system

2019 ◽  
Vol 23 (Suppl. 2) ◽  
pp. 615-621 ◽  
Author(s):  
Alexandra Matuzko ◽  
Oleg Yakubailik
Keyword(s):  
Surface Temperature ◽  
Urban Area ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Temperature Anomalies ◽  
The City

Satellite data in the thermal infrared range are a powerful source of information for the analysis and determination of city urban area temperature anomalies. The article presents a technique for monitoring the land surface temperature on the basis of combination of ?Landsat 8? satellite thermal infrared data with PlanetScope satellite constellation high resolution data. Such combination of satellite data from several spacecrafts increase the detalization of temperature maps to the level of individual city blocks. Determination of the nature and boundaries of temperature anomalies will help to understand the causes of the unfavorable environmental situation in Krasnoyarsk, where, in addition to high industrial emissions, their influence and atmospheric processes, leading to the fact that impurities are delayed and concentrated over the city. The results shows that the temperature in the places of thermal anomalies is 5?-8? higher than the average land surface temperature of the city. Based on the results of the analysis of summer thermal multi-temporal space images, several thermal zones of different nature were outlined on the territory under consideration. This information can be used in planning the development of the city, the design of new urban neighborhoods.

scholarly journals SOIL MOISTURE ANALYSIS USING MULTISPECTRAL DATA IN NORTH CENTRAL PART OF MONGOLIA

2019 ◽  
Vol IV-2/W5 ◽  
pp. 485-491
Author(s):  
E. Natsagdorj ◽  
T. Renchin ◽  
P. De Maeyer ◽  
B. Tseveen ◽  
C. Dari ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Regional Scale ◽  
Research Work ◽  
Agricultural Area ◽  
Forest Steppe ◽  
Landsat Satellite

<p><strong>Abstract.</strong> Soil moisture (SM) content is one of the most important environmental variables in relation to land surface climatology, hydrology, and ecology. Long-term SM data-sets on a regional scale provide reasonable information about climate change and global warming specific regions. The aim of this research work is to develop an integrated methodology for SM of kastanozems soils using multispectral satellite data. The study area is Tuv (48°40′30″N and 106°15′55″E) province in the forest steppe zones in Mongolia. In addition to this, land surface temperature (LST) and normalized difference vegetation index (NDVI) from Landsat satellite images were integrated for the assessment. Furthermore, we used a digital elevation model (DEM) from ASTER satellite image with 30-m resolution. Aspect and slope maps were derived from this DEM. The soil moisture index (SMI) was obtained using spectral information from Landsat satellite data. We used regression analysis to develop the model. The model shows how SMI from satellite depends on LST, NDVI, DEM, Slope, and Aspect in the agricultural area. The results of the model were correlated with the ground SM data in Tuv province. The results indicate that there is a good agreement between output SM and SM of ground truth for agricultural area. Further research is focused on moisture mapping for different natural zones in Mongolia. The innovative part of this research is to estimate SM using drivers which are vegetation, land surface temperature, elevation, aspect, and slope in the forested steppe area. This integrative methodology can be applied for different regions with forest and desert steppe zones.</p>

Spatial Hotspot Analysis of Bucharest’s Urban Heat Island (UHI) Using Modis Data

2018 ◽  
Vol 18 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Georgiana Grigoraș ◽  
Bogdan Urițescu
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Hot Spots ◽  
Land Surface ◽  
Hot Spot ◽  
Monitoring Network ◽  
Residential Areas ◽  
Hotspot Analysis ◽  
The City

Abstract The aim of the study is to find the relationship between the land surface temperature and air temperature and to determine the hot spots in the urban area of Bucharest, the capital of Romania. The analysis was based on images from both moderate-resolution imaging spectroradiometer (MODIS), located on both Terra and Aqua platforms, as well as on data recorded by the four automatic weather stations existing in the endowment of The National Air Quality Monitoring Network, from the summer of 2017. Correlation coefficients between land surface temperature and air temperature were higher at night (0.8-0.87) and slightly lower during the day (0.71-0.77). After the validation of satellite data with in-situ temperature measurements, the hot spots in the metropolitan area of Bucharest were identified using Getis-Ord spatial statistics analysis. It has been achieved that the “very hot” areas are grouped in the center of the city and along the main traffic streets and dense residential areas. During the day the "very hot spots” represent 33.2% of the city's surface, and during the night 31.6%. The area where the mentioned spots persist, falls into the "very hot spot" category both day and night, it represents 27.1% of the city’s surface and it is mainly represented by the city center.

scholarly journals Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

2021 ◽  
Vol 13 (2) ◽  
pp. 323
Author(s):  
Liang Chen ◽  
Xuelei Wang ◽  
Xiaobin Cai ◽  
Chao Yang ◽  
Xiaorong Lu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Maximum Temperature ◽  
Maximum Temperature Difference ◽  
Rapid Urbanization ◽  
The Impact ◽  
The City

Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

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