Statistical analysis of land surface temperature–vegetation indexes relationship through thermal remote sensing

Kumar, Deepak; Shekhar, Sulochana

doi:10.1016/j.ecoenv.2015.07.004

Cited by 152 publications

(79 citation statements)

References 15 publications

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“…This observation is very consistent with those reported by a number of previous studies (Zhang et al, 2009;Liu and Zhang, 2011;Ogashawara and Bastos, 2012;Kumar and Shekhar, 2015;Guo et al, 2015). The negative NDVI coefficient and positive NDBI coefficient from the three dates imply that within the study area, vegetation contributes to a decrease in the UHI effect while the built-up area strengthens the UHI effect.…”

Section: Ndvi Is Normalized Difference Vegetation Indexsupporting

confidence: 82%

Characterizing the relationship between land use land cover change and land surface temperature

Tran

Pla

Carmona

et al. 2017

ISPRS Journal of Photogrammetry and Remote Sensing

482

187

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Exploring changes in land use land cover (LULC) to understand the urban heat island (UHI) effect is valuable for both communities and local governments in cities in developing countries, where urbanization and industrialization often take place rapidly but where coherent planning and control policies have not been applied. This work aims at determining and analyzing the relationship between LULC change and land surface temperature (LST) patterns in the context of urbanization. We first explore the relationship between LST and vegetation, man-made features, and cropland using normalized vegetation, and built-up indices within each LULC type. Afterwards, we assess the impacts of LULC change and urbanization in UHI using hot spot analysis (Getis-Ord Gi* statistics) and urban landscape analysis. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted land cover and land use change. Results from this work provide an effective methodology for UHI characterization, showing that (a) LST depends on a nonlinear way of LULC types; (b) hotspot analysis using Getis Ord Gi* statistics allows to analyze the LST pattern change through time; (c) UHI is influenced by both urban landscape and urban development type; (d) LST pattern forecast and UHI effect examination can be done by the proposed model using nonlinear regression and simulated LULC change scenarios. We chose an inner city area of Hanoi as a case-study, a small and flat plain area where LULC change is significant due to urbanization and industrialization. The methodology presented in this paper can be broadly applied in other cities which exhibit a similar dynamic growth. Our findings can represent an useful tool for policy makers and the community awareness by providing a scientific basis for sustainable urban planning and management.

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Section: Ndvi Is Normalized Difference Vegetation Indexsupporting

confidence: 82%

Characterizing the relationship between land use land cover change and land surface temperature

Tran

Pla

Carmona

et al. 2017

ISPRS Journal of Photogrammetry and Remote Sensing

482

187

View full text Add to dashboard Cite

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“…Changes in vegetation cover are a response resulting from both environmental and biological conditions. Several authors have reported significant relationships between temperature and vegetation indices (Zhang et al, 2004; Kumar and Shekhar, 2015; Wang et al, 2015). Moreover, soil temperature influences soil moisture levels and microbial function and productivity (Lukewille and Wright, 1997; Pregitzer and King, 2005).…”

Section: Introductionmentioning

confidence: 99%

Temperature Effects on Biomass and Regeneration of Vegetation in a Geothermal Area

et al. 2017

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Understanding the effects of increasing temperature is central in explaining the effects of climate change on vegetation. Here, we investigate how warming affects vegetation regeneration and root biomass and if there is an interactive effect of warming with other environmental variables. We also examine if geothermal warming effects on vegetation regeneration and root biomass can be used in climate change experiments. Monitoring plots were arranged in a grid across the study area to cover a range of soil temperatures. The plots were cleared of vegetation and root-free ingrowth cores were installed to assess above and below-ground regeneration rates. Temperature sensors were buried in the plots for continued soil temperature monitoring. Soil moisture, pH, and soil chemistry of the plots were also recorded. Data were analyzed using least absolute shrinkage and selection operator and linear regression to identify the environmental variable with the greatest influence on vegetation regeneration and root biomass. There was lower root biomass and slower vegetation regeneration in high temperature plots. Soil temperature was positively correlated with soil moisture and negatively correlated with soil pH. Iron and sulfate were present in the soil in the highest quantities compared to other measured soil chemicals and had a strong positive relationship with soil temperature. Our findings suggest that soil temperature had a major impact on root biomass and vegetation regeneration. In geothermal fields, vegetation establishment and growth can be restricted by low soil moisture, low soil pH, and an imbalance in soil chemistry. The correlation between soil moisture, pH, chemistry, and plant regeneration was chiefly driven by soil temperature. Soil temperature was negatively correlated to the distance from the geothermal features. Apart from characterizing plant regeneration on geothermal soils, this study further demonstrates a novel approach to global warming experiments, which could be particularly useful in low heat flow geothermal systems that more realistically mimic soil warming.

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“…Under these circumstances, in the last years, many researchers in diff erent fi elds such as climatology, urban planning or remote sensing, focused on urban heat environment and UHI (Li, J. et al 2009;Unger, J. et al 2010;Kumar, D. and Shekhar, S. 2015). The urban environment is a complex system, involving concentrated human activities and integrated ecosystem vulnerabilities that could be seriously aff ected by the intensity increase of the UHI (Cohen, B.…”

Section: Detection Of Atmospheric Urban Heat Island Through Direct Mementioning

confidence: 99%

Detection of atmospheric urban heat island through direct measurements in Cluj-Napoca city, Romania

et al. 2016

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In the last decades, cities worldwide have experienced accelerated development, so that continuous urbanization and its impact is presently one of the most important topics in diff erent fi elds of research. The main aim of this study is to identify the intensity of the atmospheric urban heat island in Cluj-Napoca city, through direct observations campaigns by using fi xed points and transect measurements. The data has been collected over a period of 6 months (May-October 2015). The measurements have been performed mainly in anti-cyclonic weather condition, during the night, between 23:00 and 03:00. The profi les trajectories followed the main roads of the city on directions North-South, East-West, and Northwest-Southeast. 8 fi xed points have been chosen in order to highlight best the temperature patt erns in diff erent Local Climate Zones (LCZs). The main fi ndings of the study are the followings: the direct observations performed in three seasons (spring, summer and autumn) revealed the existence of an atmospheric urban heat island in Cluj-Napoca city; the warmest areas are compact high-rise and compact midrise, located in the eastern half of the city, where the temperature increases by more than 2.0 °C, as average value for all campaigns, but the maximum values, recorded in the summer are higher than 3.0 °C; the coolest areas are sparsely built areas and the large low-rise/water areas, where the temperature is quite similar to that recorded in the nearby rural areas (diff erence of 0.0-0.1 °C, as average values); local factors, such as mountain breeze and topography have a great impact on the atmospheric urban heat island confi guration.

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Statistical analysis of land surface temperature–vegetation indexes relationship through thermal remote sensing

Cited by 152 publications

References 15 publications

Characterizing the relationship between land use land cover change and land surface temperature

Characterizing the relationship between land use land cover change and land surface temperature

Temperature Effects on Biomass and Regeneration of Vegetation in a Geothermal Area

Detection of atmospheric urban heat island through direct measurements in Cluj-Napoca city, Romania

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