Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian land cover between 1981 and 2001

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.

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A COMPARATIVE STUDY OF LAND SURFACE TEMPERATURE WITH DIFFERENT INDICES ON HETEROGENEOUS LAND COVER USING LANDSAT 8 DATA

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

10.5194/isprs-archives-xlii-5-389-2018 ◽

2018 ◽

Vol XLII-5 ◽

pp. 389-394 ◽

Cited By ~ 4

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>

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THE GEO-SPATIAL APPROACH TO DETECT THE CHANGE IN VEGETATION AND LAND SURFACE TEMPERATURE (LST) AFTER FORMATION OF ROHINGYA SETTLEMENTS IN BANGLADESH

Journal of Civil Engineering Science and Technology ◽

10.33736/jcest.3986.2021 ◽

2021 ◽

Vol 12 (2) ◽

pp. 288-241

Author(s):

Mahdi Mansur Mahi ◽

Md. Shahriar Sharif ◽

Rhyme Rubayet Rudra ◽

Md. Nazmul Haque

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Land Surface Temperature ◽

Vegetation Cover ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Landsat 8 ◽

Vegetation Density ◽

Tree Plantation

The goal of this study is to examine the effects of Rohingya Influx specially on vegetation land cover and LST in Teknaf Peninsula, Cox’s Bazar, Bangladesh over time. For doing so, the research followed three steps. Firstly, the primary and secondary data were collected from prescribed sources like LANDSAT 8 images from Earth Explorer (USGS) and the Shapefiles were collected from secondary sources. Then, Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) functions are explored in geospatial environment to assess the effect of deforestation on the region. Finally, A correlation is shown between LST and NDVI for making a decision from the environmental perspective. The findings state that, the region around the Rohingya Camps progressively lost its vegetation density as a result of increasing deforestation. According to this analysis, there was 87.87 % vegetation cover in 2013, which gradually decreased before the Rohingya Invasion in 2017. After the incident in 2018, vegetation cover drops to 75.67 %. Similarly, area with no vegetation increased more rapidly than others. The outcome showed that the transition in land cover was quicker and more noticeable in recent time. As a result, the LST has been increasing over the years. According to the study, there were around 8.71 % of areas with high temperatures in 2013, which increased to 36.86 % in 2020. It indicates that a large quantity of vegetation has been lost as a result of deforestation, and the LST of this region has changed dramatically. Furthermore, data was examined by Union to assess the individual effect from 5 Rohingya camps, and it was discovered that the situation in Teknaf Union is terrible, while the situation in Baharchhara Union is comparably better. Finally, the results of the research encourage an extensive regional environmental policy to eradicate this problem. To recompense the loss of nature govt. and responsible department should take necessary steps like hill conservation or tree plantation.

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Land Surface Temperature Assessment in Central Sumatra, Indonesia

Indonesian Journal of Geography ◽

10.22146/ijg.51327 ◽

2020 ◽

Vol 52 (2) ◽

pp. 239

Author(s):

Tofan Agung Eka Prasetya ◽

Munawar Munawar ◽

Muhammad Rifki Taufik ◽

Sarawuth Chesoh ◽

Apiradee Lim ◽

...

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Regression Model ◽

Land Surface Temperature ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Multiple Linear Regression Model ◽

Moderate Resolution ◽

Moderate Resolution Imaging Spectroradiometer

Land Surface Temperature (LST) assessment can explain temperature variation, which may be influenced by factors such as elevation, land cover, and the normalized difference vegetation index (NDVI). In this study, a multiple linear regression model of LST variation was constructed based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Terra satellite, relating to the period, 2000-2018. The highest LST variation of nearly 1.3 °C/decade was found in savanna areas while the lowest variation was in the evergreen broadleaf forest and woody savanna, which experienced a decrease of 2.1 °C/decade. The overall mean change of LST was -0.4 °C/decade and the regression model with LST as the dependent variable and elevation, land cover type, and NVDI as independent variables produced an R square of 0.376. The variation in LST was different depending upon the NDVI.

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

Remote Sensing ◽

10.3390/rs13020323 ◽

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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Spatio-temporal analysis and simulation of land cover changes and their impacts on land surface temperature in urban agglomeration of Bisha Watershed, Saudi Arabia

Geocarto International ◽

10.1080/10106049.2021.1980616 ◽

2021 ◽

pp. 1-31

Author(s):

Javed Mallick ◽

Vijay P. Singh ◽

Mohammed K. Almesfer ◽

Swapan Talukdar ◽

Majed Alsubhi ◽

...

Keyword(s):

Saudi Arabia ◽

Land Cover ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Temporal Analysis ◽

Urban Agglomeration ◽

Land Cover Changes ◽

Spatio Temporal

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Dynamics of human-induced lakes and their impact on land surface temperature in Toshka Depression, Western Desert, Egypt

10.21203/rs.3.rs-229433/v1 ◽

2021 ◽

Author(s):

Rasha Abou Samra

Keyword(s):

Land Use ◽

Land Cover ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Vegetation Index ◽

Research Area ◽

Western Desert ◽

Severe Drought ◽

Land Use Land Cover

Abstract Land surface temperature (LST) is a significant environmental variable that is appreciably influenced by land use /land cover changes. The main goal of this research was to quantify the impacts of land use/land cover change (LULC) from the drying of Toshka Lakes on LST by remote sensing and GIS techniques. Landsat series TM and OLI satellite images were used to estimate LST from 2001 to 2019. Automated Water Extraction Index (AWEI) was applied to extract water bodies from the research area. Optimized Soil-Adjusted Vegetation Index (OSAVI) was utilized to predict the reclaimed land in the Toshka region until 2019. The results indicated a decrease in the lakes by about 1517.79 km2 with an average increase in LST by about 25.02 °C between 2001 and 2019. It was observed that the dried areas of the lakes were converted to bare soil and are covered by salt crusts. The results indicated that the land use change was a significant driver for the increased LST. The mean annual LST increased considerably by 0.6 °C/y between 2001 and 2019. A strong negative correlation between LST and Toshka Lakes area (R-square = 0.98) estimated from regression analysis implied that Toshka Lakes drying considerably affected the microclimate of the study area. Severe drought conditions, soil degradation, and many environmental issues were predicted due to the rise of LST in the research area. There is an urgent need to develop favorable strategies for sustainable environmental management in the Toshka region.

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The Effects of Land Use Zoning and Densification on Changes in Land Surface Temperature in Seoul

Sustainability ◽

10.3390/su11247056 ◽

2019 ◽

Vol 11 (24) ◽

pp. 7056 ◽

Cited By ~ 2

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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Evaluating the Temperature Difference Parameter in the SSEBop Model with Satellite-Observed Land Surface Temperature Data

Remote Sensing ◽

10.3390/rs11161947 ◽

2019 ◽

Vol 11 (16) ◽

pp. 1947 ◽

Cited By ~ 2

Author(s):

Lei Ji ◽

Gabriel B. Senay ◽

Naga M. Velpuri ◽

Stefanie Kagone

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Temperature Difference ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Weather Data ◽

Climate Data ◽

Modis Data ◽

South Central

The Operational Simplified Surface Energy Balance (SSEBop) model uses the principle of satellite psychrometry to produce spatially explicit actual evapotranspiration (ETa) with remotely sensed and weather data. The temperature difference (dT) in the model is a predefined parameter quantifying the difference between surface temperature at bare soil and air temperature at canopy level. Because dT is derived from the average-sky net radiation based primarily on climate data, validation of the dT estimation is critical for assuring a high-quality ETa product. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) data to evaluate the SSEBop dT estimation for the conterminous United States. MODIS data (2008–2017) were processed to compute the 10-year average land surface temperature (LST) and normalized difference vegetation index (NDVI) at 1 km resolution and 8-day interval. The observed dT (dTo) was computed from the LST difference between hot (NDVI < 0.25) and cold (NDVI > 0.7) pixels within each 2° × 2° sampling block. There were enough hot and cold pixels within each block to create dTo timeseries in the West Coast and South-Central regions. The comparison of dTo and modeled dT (dTm) showed high agreement, with a bias of 0.8 K and a correlation coefficient of 0.88 on average. This study concludes that the dTm estimation from the SSEBop model is reliable, which further assures the accuracy of the ETa estimation.

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