The impact of tree cover loss on land surface temperature: A case study of central Massachusetts using Landsat Thematic Mapper thermal data

Rogan, John; Ziemer, Martha; Martin, Deborah; Ratick, Samuel J.; Cuba, Nicholas; DeLauer, Verna

doi:10.1016/j.apgeog.2013.07.004

Cited by 69 publications

(36 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Therefore, the LST outcomes of this study may disagree with previous studies [6,53,54] which show higher LST values in urban areas than in the areas surrounding and outside cities. In the period studied, Duhok City showed a lower LST in urban areas than in the suburbs ( Figure 8); this is due to the sun's heat in surrounding areas being absorbed directly into the ground, causing it to heat up faster than in other land cover categories.…”

Section: Relationship Between Land Surface Temperature and Different contrasting

confidence: 55%

Urban Land Use Land Cover Changes and Their Effect on Land Surface Temperature: Case Study Using Dohuk City in the Kurdistan Region of Iraq

Ibrahim

2017

Climate

155

View full text Add to dashboard Cite

Abstract:The growth of urban areas has a significant impact on land use by replacing areas of vegetation with residential and commercial areas and their related infrastructure; this escalates the land surface temperature (LST). Rapid urban growth has occurred in Duhok City due to enhanced political and economic growth during the period of this study. The objective is to investigate the effect of land use changes on LST; this study depends on data from three Landsat images (two Landsat 5-TM and Landsat OLI_TIRS-8) from 1990, 2000 and 2016. Supervised classification was used to compute land use/cover categories, and to generate the land surface temperature (LST) maps the Mono-window algorithm was used. Images were also used to create the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference bareness index (NDBAI) and normalized difference water index (NDWI) maps. Linear regression analysis was used to generate relationships between LST with NDVI, NDBI, NDBAI and NDWI. The study outcome proves that the changes in land use/cover have a significant role in the escalation of land surface temperatures. The highest temperatures are associated with barren land and built-up areas, ranging from 47 • C, 50 • C, 56 • C while lower temperatures are related to water bodies and forests, ranging from 25 • C, 26 • C, 29 • C respectively, in 1990, 2000 and 2016. This study also proves that NDVI and NDWI correlate negatively with low temperatures while NDBI and NDBAI correlate positively with high temperatures.

show abstract

Section: Relationship Between Land Surface Temperature and Different contrasting

confidence: 55%

Urban Land Use Land Cover Changes and Their Effect on Land Surface Temperature: Case Study Using Dohuk City in the Kurdistan Region of Iraq

Ibrahim

2017

Climate

155

View full text Add to dashboard Cite

show abstract

“…Recently, LST data from Landsat were used for urban energy flux estimation [3]. Landsat-derived LST is also used for monitoring the forested areas, such as the correlation of LST with tree loss or the detection of changes in tropical forest cover [14,15]. The land cover/use changes affect LST as well, as has been demonstrated in different studies, using different types of satellite data [16].…”

Section: Introductionmentioning

confidence: 99%

Online Global Land Surface Temperature Estimation from Landsat

et al. 2017

View full text Add to dashboard Cite

This study explores the estimation of land surface temperature (LST) for the globe from Landsat 5, 7 and 8 thermal infrared sensors, using different surface emissivity sources. A single channel algorithm is used for consistency among the estimated LST products, whereas the option of using emissivity from different sources provides flexibility for the algorithm's implementation to any area of interest. The Google Earth Engine (GEE), an advanced earth science data and analysis platform, allows the estimation of LST products for the globe, covering the time period from 1984 to present. To evaluate the method, the estimated LST products were compared against two reference datasets: (a) LST products derived from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), as higher-level products based on the temperature-emissivity separation approach; (b) Landsat LST data that have been independently produced, using different approaches. An overall RMSE (root mean square error) of 1.52 • C was observed and it was confirmed that the accuracy of the LST product is dependent on the emissivity; different emissivity sources provided different LST accuracies, depending on the surface cover. The LST products, for the full Landsat 5, 7 and 8 archives, are estimated "on-the-fly" and are available on-line via a web application.

show abstract

“…where LST is the Land Surface Temperature in degree Kelvin, multiplied by 273.15 to convert Kelvin to Celsius [52]; C 0 to C 6 represent the Split-Window Coefficient values (Table 2), as illustrated by Skokovic et al [53] in their research; TB 10 and TB 11 are the Brightness Temperatures for Bands 10 and 11 in Kelvin; ε is the mean LSE of the TIR bands; W is the Atmospheric Water Vapor content; and ∆ε is the difference in the LSE. …”

Section: Discussionmentioning

confidence: 99%

Analysis of Climate and Topography Impacts on the Spatial Distribution of Vegetation in the Virunga Volcanoes Massif of East-Central Africa

et al. 2017

View full text Add to dashboard Cite

This paper aimed to investigate the influence of climatic and topographic factors on the distribution of vegetation in the Virunga Volcanoes Massif using GIS and remote sensing techniques. The climatic variables considered were precipitation, Land Surface Temperature (LST), and evapotranspiration (ET), whereas the topographic factors considered were elevation and aspect. The dataset consisted of MODIS NDVI data, satellite-delivered precipitation, ET, and the LST. A 2014 Landsat 8 OLI image was used to produce a vegetation map of the study area, while DEM was used to derive the elevation attributes and to calculate the aspect angles. Moran's I and Geographically Weighted Regression (GWR) Model was used to analyze the relationships between the climatic factors and NDVI changes over elevation and aspect. The results indicated that among the nine vegetation types inventoried in the area, the Mean NDVI varied from 0.33 to 0.59 and the optimal vegetation growth was found at an elevation between 2000 and 3900 m, with mean NDVI values larger than 0.50. The peak mean NDVI value of 0.59 was found at the elevation from 2100 to 2800 m. Vegetation growth was found to be more sensitive to elevation, as NDVI values were more varied at a lower elevation (<4000 m) than at a higher elevation (>4000 m). Considering the aspect, the greater vegetation growth was found in SE (132 • , 148 • ), SW (182 • , 186 • ), and NW (309.5 • -337.5 • ), with mean NDVI values larger than 0.56. This indicated that vegetation was susceptible to better growth conditions in the lower elevation ranges and in shady areas. The vegetation NDVI in this study area was mostly uncorrelated with precipitation (R 2 = 0.34), but was strongly correlated with LST (R 2 = 0.99) and ET (R 2 = 98). LST (≥18 • C) and ET (1286 mm/year −1 ) were found to provide optimal conditions for vegetation growth in the Virunga Volcanoes Massif. Empirically, the results concluded that elevation, aspect, LST, and ET are the main factors controlling the spatial distribution and vegetation growth in this area. This information is significantly helpful for biodiversity conservation and constitutes a valuable input to environmental and ecological research.

show abstract

The impact of tree cover loss on land surface temperature: A case study of central Massachusetts using Landsat Thematic Mapper thermal data

Cited by 69 publications

References 30 publications

Urban Land Use Land Cover Changes and Their Effect on Land Surface Temperature: Case Study Using Dohuk City in the Kurdistan Region of Iraq

Urban Land Use Land Cover Changes and Their Effect on Land Surface Temperature: Case Study Using Dohuk City in the Kurdistan Region of Iraq

Online Global Land Surface Temperature Estimation from Landsat

Analysis of Climate and Topography Impacts on the Spatial Distribution of Vegetation in the Virunga Volcanoes Massif of East-Central Africa

Contact Info

Product

Resources

About