THE LAND SURFACE TEMPERATURE IMPACT TO LAND COVER TYPES

Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R<sup>2</sup> = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.

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THE LAND SURFACE TEMPERATURE IMPACT TO LAND COVER TYPES

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b3-871-2016 ◽

2016 ◽

Vol XLI-B3 ◽

pp. 871-876 ◽

Cited By ~ 1

Author(s):

I. Ibrahim ◽

A. Abu Samah ◽

R. Fauzi ◽

N. M. Noor

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Temperature Variation ◽

Land Surface Temperature ◽

Land Surface ◽

Water Bodies ◽

Land Cover Types ◽

Tukey Test ◽

Bare Land ◽

Post Hoc

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Cooling Effect of Different Land Cover Types: A Case Study in Xi’an and Xianyang, China

Sustainability ◽

10.3390/su13031099 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1099

Author(s):

Yuhe Ma ◽

Mudan Zhao ◽

Jianbo Li ◽

Jian Wang ◽

Lifa Hu

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Urban Heat Island ◽

Land Surface Temperature ◽

Land Surface ◽

Cooling Effect ◽

Heat Island ◽

Land Cover Types ◽

Island Effect ◽

Urban Heat

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.

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

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.20.27402 ◽

2018 ◽

Vol 7 (4.20) ◽

pp. 608 ◽

Cited By ~ 3

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.

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Eight-Day Daytime Land Surface Temperature Pattern over Peninsular Malaysia

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.d9911.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 11949-11955

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Peninsular Malaysia ◽

Series Data ◽

Temperature Pattern ◽

Land Cover Types ◽

North East ◽

South West Monsoon

The monitoring of land surface temperature (LST) can assist scientists to better understand the possible effect of climate change on land cover types and in conducting appropriate analysis. The earth's annual temperature has moved up and down a few degrees Celsius, including Malaysia, over the past few million years. The location of Malaysia near the equator line and experiences tropical monsoon season were important to take into consideration to the LST changes. In this paper, the eight-day LST time series data for 14-year period (Jan 2003 – Dec 2016) was downloaded from Moderate Resolution Imaging Spectroradiometer (MODIS) website with two types of satellites which are Terra and Aqua. This study focused on two gridded areas in Peninsular Malaysia; the first one which is exposed to North East monsoon, namely super region 21 and another one to South West monsoon, which is super region 26. These two areas are selected due to they being the largest land area covered within the grid relative to other grids. The objective of this study is to compare the eight- day daytime LST pattern between two monsoons with different land cover types for both satellites. Analysis such as cubic spline function with the annual periodic boundary condition and weighted least square (WLS) regression were performed to extract annual seasonal trend for the areas covered. The results of LST showed most of the gridded areas experience similar seasonal pattern for each year but different pattern were discovered when both monsoons were considered. Moreover, the LST trends also changed according to the land cover types over the study period

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ANALYZING THE EFFECTS OF LAND COVER CHANGE ON SURFACE TEMPERATURE IN MOUNT MAKILING FOREST RESERVE (MMFR) AND ITS NEIGHBORING MUNICIPALITIES USING LANDSAT DATA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w19-165-2019 ◽

2019 ◽

Vol XLII-4/W19 ◽

pp. 165-172

Author(s):

V. K. M. Del Mundo ◽

C. L. Tiburan Jr.

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Land Cover Change ◽

Land Surface Temperature ◽

Land Surface ◽

Urban Centers ◽

Forest Reserve ◽

Land Cover Types ◽

Rapid Economic Growth ◽

Supervised Image Classification

Abstract. Land Surface Temperature (LST) is said to be affected by frequent changes in the land cover. Over the years, the immediate environs of Mount Makiling Forest Reserve (MMFR) have experienced such kind of change due to rapid economic growth of the area that also led to the expansion of urban centers. The study utilized Landsat imageries to determine the possible effects of land cover change on surface temperature using the integration of remote sensing and GIS technologies. Initially, the multispectral bands were radiometrically corrected using Dark Object Subtraction (DOS) while the thermal bands were corrected using Land Surface Emissivity (LSE). After these corrections were applied, the images were classified using supervised image classification technique where seven land cover types have been identified. The classified images were then validated using 200 reference data and this revealed an overall accuracy of 87.5% and 86.0% for the May 2003 and July 2015 images, respectively. Results showed that changes in land cover resulted to a significant change in Land Surface Temperature (LST). The LST in 2003 (16.49°C – 40.44°C) was found higher than that of 2015 which was observed between 13.35°C and 33.83°C only. The reason behind this is the increase in green spaces from 2003 to 2015. Among the major land cover types, forest lands exhibited the lowest mean surface temperature for both years having 27.27°C in 2003 and 21.35°C in 2015 while built-up areas had the highest surface temperature having 32.60°C in 2003 and 26.00°C in 2015.

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

Journal of Landscape Ecology ◽

10.2478/jlecol-2021-0017 ◽

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.

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Reconstruction of the Daily MODIS Land Surface Temperature Product Using the Two-Step Improved Similar Pixels Method

Remote Sensing ◽

10.3390/rs13091671 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1671

Author(s):

Junlei Tan ◽

Tao Che ◽

Jian Wang ◽

Ji Liang ◽

Yang Zhang ◽

...

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Water Cycle ◽

Ancillary Data ◽

Land Cover Types ◽

Modis Land Surface Temperature ◽

Yearly Average

The MODIS land surface temperature (LST) product is one of the most widely used data sources to study the climate and energy-water cycle at a global scale. However, the large number of invalid values caused by cloud cover limits the wide application of the MODIS LST. In this study, a two-step improved similar pixels (TISP) method was proposed for cloudy sky LST reconstruction. The TISP method was validated using a temperature-based method over various land cover types. The ground measurements were collected at fifteen stations from 2013 to 2018 during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) field campaign in China. The estimated theoretical clear-sky temperature indicates that clouds cool the land surface during the daytime and warm it at nighttime. For bare land, the surface temperature shows a clear seasonal trend and very similar across stations, with a cooling amplitude of 4.14 K in the daytime and a warming amplitude of 3.99 K at nighttime, as a yearly average. The validation result showed that the reconstructed LST is highly consistent with in situ measurements and comparable with MODIS LST validation accuracy, with a mean bias of 0.15 K at night (−0.43 K in the day), mean RMSE of 2.91 K at night (4.41 K in the day), and mean R2 of 0.93 at night (0.90 in the day). The developed method maximizes the potential of obtaining quality MODIS LST retrievals, ancillary data, and in situ observations, and the results show high accuracy for most land cover types.

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Impact of land cover change on land surface temperature over Greater Beirut Area – Lebanon

Journal of Geoinformatics & Environmental Research ◽

10.38094/jgier2121 ◽

2021 ◽

Vol 2 (1) ◽

pp. 14-27

Author(s):

Ali Khyami

Keyword(s):

Remote Sensing ◽

Twentieth Century ◽

Land Cover ◽

Surface Temperature ◽

Land Cover Change ◽

Land Surface Temperature ◽

Urban Growth ◽

Land Surface ◽

Bare Land ◽

The City

Remote sensing (RS) technology has been used together with geographic information systems (GIS) to determine the LC types, retrieve LST, and analyze their relationships. The term Greater Beirut Area (GBA) is used to refer to the city of Beirut and its suburbs which witnessed rapid urban growth, after the end of the civil war, in the last decade of the twentieth century, due to the increase in the number of its inhabitants, and the prosperity and development of sectors such as; industrial, trade, tourism, and construction. These factors led to a wide change in the land cover (LC) types and increased land surface temperature LST. The results showed an increase in built-up areas by 29.1%, and agricultural lands by 6%, while bare land, forests, and seawater decreased by 28.5%, 4.9%, and 1.9%, respectively. These changes caused large differences in the LST between built-up areas and other LC types. The highest LST recorded was in built-up areas (33.03°C in 1985, and 34.01°C in 2020), followed by bare lands (32.61 °C in 1985 and 33.49°C in 2020), cropland (31.23°C in 1985 and 32.17°C in 2020), forest (30.08°C in 1985 and 30.47°C in 2020), and water (24.97°C in 1985 and 28.15°C in 2020). Consequently, converting different LC types into built-up areas led to increases in LST and changed microclimate.

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Variations of Land Surface Temperature and Its Relationship with Land Cover and Changes in IPB Campus, Dramaga Bogor 2013-2018

E3S Web of Conferences ◽

10.1051/e3sconf/201912501004 ◽

2019 ◽

Vol 125 ◽

pp. 01004

Author(s):

Nafiriair Yufan Madakarah ◽

Supriatna ◽

Adi Wibowo ◽

Masita Dwi Mandini Manessa ◽

Yoanna Ristya

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Spatial Pattern ◽

Temperature Variation ◽

Land Surface Temperature ◽

Land Surface ◽

Northern Region ◽

Landsat 8 ◽

Vegetation Density ◽

Surface Temperature Variation

At the present time university can be called "small cities" due to their size of area, population and various kinds of activities. Bogor Agricultural University is a campus that can represent a city in smaller scope with a high variety of land cover. Further, the variation of land cover will affect the surface temperature variation. This study aims to determine spatial pattern of land surface temperature variation and relationship with land cover and also the changes. The data used in this study generated from Landsat 8 imagery and field surveys, then analyze using spatial and statistical analysis tools. The results show temperature has a spatial pattern associated with the land cover. Where the highest temperature tends to be located in the central region in the form of a built-up area and the lowest temperature tends to be located in northern region in the form of forest area. The highest increase in temperature tends to appear in the area that shows changes from vegetation to built-up area. Moreover, this study also found that this phenomenon only appears with temperature value were 7ºC greater than the increase in temperature on a similar land cover. Finally, this study proves that the higher vegetation density will create a lower temperature of land surface, while the higher building density creates a higher land surface temperature.

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