scholarly journals Acquiring of Fine Land Covers Information by Using the Object Based Classification Method, and Examination of Reproducibility of Land Surface Temperature

2014 ◽  
Vol 70 (5) ◽  
pp. I_59-I_69
Author(s):  
Akio ONISHI ◽  
Ryuichi MAEZAKI
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Classification Method ◽  
Object Based ◽  
Land Covers

scholarly journals Evaluation of Landsat-8 TIRS data recalibrations and land surface temperature split-window algorithms over a homogeneous crop area with different phenological land covers

2021 ◽  
Vol 174 ◽  
pp. 237-253
Author(s):  
Raquel Niclòs ◽  
Jesús Puchades ◽  
César Coll ◽  
María J. Barberà ◽  
Lluís Pérez-Planells ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Land Covers ◽  
Crop Area

scholarly journals Microclimate Variation among Urban Land Covers: The Importance of Vertical and Horizontal Structure in Air and Land Surface Temperature Relationships

2017 ◽  
Vol 56 (9) ◽  
pp. 2531-2543 ◽  
Author(s):  
Steven M. Crum ◽  
G. Darrel Jenerette
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Land ◽  
Horizontal Structure ◽  
Surface Warming ◽  
Land Covers ◽  
Micrometeorological Conditions ◽  
Bare Surface

AbstractAir and land surface warming effects from urbanization are of increasing concern because of expanding heat-related impacts on human health. Many studies have investigated land-cover effects on air temperature Ta or land surface temperature (LST) individually, but relatively few studies have examined the relationships between these two heat indicators and other meteorological variables. The authors investigate how land cover influences local distributions of LST, Ta, and relative humidity (RH) and their interactions. During July 2016, 30 Ta and RH sensors were deployed at two heights above the ground (0.1 and 1.5 m) along with a thermal camera and an anemometer to quantify the influence of surface dynamics on atmospheric micrometeorological conditions. Sensors were distributed in Riverside, California, over five common urban land covers: asphalt, bare surface, turf grass, short trees, and tall trees. Stronger Ta–LST relationships were observed at 0.1 m for asphalt, bare surface, and grass and at 1.5 m for short and tall trees. Excluding grass, greater Ta–LST differences were found for daytime than for nighttime. To add to the complexity of Ta–LST relationships, increasing spatial variation in LST during the day for short- and tall-tree land covers were found. Furthermore, both wind velocity and LST were correlated with Ta vertical distributions. Higher RH and lower LST, Ta, and vapor pressure deficit were found in vegetated covers. Through the use of thermal imagery and meteorological measures, it was found that distinct land-cover influences on microclimate exist and that estimates of urban Ta using LST may improve with the use of land-cover-specific relationships.

scholarly journals Validation of Sentinel-3 SLSTR Land Surface Temperature Retrieved by the Operational Product and Comparison with Explicitly Emissivity-Dependent Algorithms

2021 ◽  
Vol 13 (11) ◽  
pp. 2228
Author(s):  
Lluís Pérez-Planells ◽  
Raquel Niclòs ◽  
Jesús Puchades ◽  
César Coll ◽  
Frank-M. Göttsche ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Systematic Uncertainty ◽  
Land Surface ◽  
Wide Band ◽  
Rice Paddy ◽  
Bare Soil ◽  
In Situ Data ◽  
Land Covers ◽  
Split Window Algorithm

Land surface temperature (LST) is an essential climate variable (ECV) for monitoring the Earth climate system. To ensure accurate retrieval from satellite data, it is important to validate satellite derived LSTs and ensure that they are within the required accuracy and precision thresholds. An emissivity-dependent split-window algorithm with viewing angle dependence and two dual-angle algorithms are proposed for the Sentinel-3 SLSTR sensor. Furthermore, these algorithms are validated together with the Sentinel-3 SLSTR operational LST product as well as several emissivity-dependent split-window algorithms with in-situ data from a rice paddy site. The LST retrieval algorithms were validated over three different land covers: flooded soil, bare soil, and full vegetation cover. Ground measurements were performed with a wide band thermal infrared radiometer at a permanent station. The coefficients of the proposed split-window algorithm were estimated using the Cloudless Land Atmosphere Radiosounding (CLAR) database: for the three surface types an overall systematic uncertainty (median) of –0.4 K and a precision (robust standard deviation) 1.1 K were obtained. For the Sentinel-3A SLSTR operational LST product, a systematic uncertainty of 1.3 K and a precision of 1.3 K were obtained. A first evaluation of the Sentinel-3B SLSTR operational LST product was also performed: systematic uncertainty was 1.5 K and precision 1.2 K. The results obtained over the three land covers found at the rice paddy site show that the emissivity-dependent split-window algorithms, i.e., the ones proposed here as well as previously proposed algorithms without angular dependence, provide more accurate and precise LSTs than the current version of the operational SLSTR product.

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 Assessing of Land Surface Temperature at the Seulawah Agam Volcano Area using the Landsat Series Imagery

2021 ◽  
Vol 1825 (1) ◽  
pp. 012021
Author(s):  
Nasrullah Zaini ◽  
Muhammad Yanis ◽  
Marwan ◽  
Muhammad Isa ◽  
Freek van der Meer
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface

scholarly journals The Gradient Effect on the Relationship between the Underlying Factor and Land Surface Temperature in Large Urbanized Region

Land ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 20
Author(s):  
Yixu Wang ◽  
Mingxue Xu ◽  
Jun Li ◽  
Nan Jiang ◽  
Dongchuan Wang ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landscape Planning ◽  
Potential Gradient ◽  
Surface Characteristics ◽  
Ordinary Least Squares ◽  
Urban Agglomeration ◽  
Spatial Gradient ◽  
Gradient Effect

Although research relating to the urban heat island (UHI) phenomenon has been significantly increasing in recent years, there is still a lack of a continuous and clear recognition of the potential gradient effect on the UHI—landscape relationship within large urbanized regions. In this study, we chose the Beijing-Tianjin-Hebei (BTH) region, which is a large scaled urban agglomeration in China, as the case study area. We examined the causal relationship between the LST variation and underlying surface characteristics using multi-temporal land cover and summer average land surface temperature (LST) data as the analyzed variables. This study then further discussed the modeling performance when quantifying their relationship from a spatial gradient perspective (the grid size ranged from 6 to 24 km), by comparing the ordinary least squares (OLS) and geographically weighted regression (GWR) methods. The results indicate that: (1) both the OLS and GWR analysis confirmed that the composition of built-up land contributes as an essential factor that is responsible for the UHI phenomenon in a large urban agglomeration region; (2) for the OLS, the modeled relationship between the LST and its drive factor showed a significant spatial gradient effect, changing with different spatial analysis grids; and, (3) in contrast, using the GWR model revealed a considerably robust and better performance for accommodating the spatial non-stationarity with a lower scale dependence than that of the OLS model. This study highlights the significant spatial heterogeneity that is related to the UHI effect in large-extent urban agglomeration areas, and it suggests that the potential gradient effect and uncertainty induced by different spatial scale and methodology usage should be considered when modeling the UHI effect with urbanization. This would supplement current UHI study and be beneficial for deepening the cognition and enlightenment of landscape planning for UHI regulation.

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