The role of urban trees in reducing land surface temperatures in European cities

Urban trees influence temperatures in cities. However, their effectiveness at mitigating urban heat in different climatic contexts and in comparison to treeless urban green spaces has not yet been sufficiently explored. Here, we use high-resolution satellite land surface temperatures (LSTs) and land-cover data from 293 European cities to infer the potential of urban trees to reduce LSTs. We show that urban trees exhibit lower temperatures than urban fabric across most European cities in summer and during hot extremes. Compared to continuous urban fabric, LSTs observed for urban trees are on average 0-4 K lower in Southern European regions and 8-12 K lower in Central Europe. Treeless urban green spaces are overall less effective in reducing LSTs, and their cooling effect is approximately 2-4 times lower than the cooling induced by urban trees. By revealing continental-scale patterns in the effect of trees and treeless green spaces on urban LST our results highlight the importance of considering and further investigating the climate-dependent effectiveness of heat mitigation measures in cities

Evapotranspiration estimation using Landsat-8 data with a two-layer framework

This work was partially supported by the National Natural Science Foundation of China (41401042), National Key Basic Research Program of China (973 Program) (Grant No. 2015CB452701) and National Natural Science Foundation of China (Grant Nos. 41571019 and 41371043).Peer reviewedproo

Desertification sensitivity analysis using medalus model and gis: A case study of the oases of middle draa valley, morocco

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Oases can play a significant role in the sustainable economic development of arid and Saharan regions. The aim of this study was to map the desertification-sensitive areas in the Middle Draa Valley (MDV), which is in the southeast of Morocco. A total of 13 indices that affect desertification processes were identified and analyzed using a geographic information system. The Mediterranean desertification and land use approach; which has been widely used in the Mediterranean regions due to its simplicity; flexibility and rapid implementation strategy; was applied. All the indices were grouped into four main quality indices; i.e., soil quality; climate quality; vegetation quality and management quality indices. Each quality index was constructed by the combination of several sub-indicators. In turn; the geometric mean of the four quality index maps was used to construct a map of desertification-sensitive areas; which were classified into four classes (i.e., low; moderate; high and very high sensitivity). Results indicated that only 16.63% of the sites in the study were classified as least sensitive to desertification; and 50.34% were classified as highly and very highly sensitive areas. Findings also showed that climate and human pressure factors are the most important indicators affecting desertification sensitivity in the MDV. The framework used in this research provides suitable results and can be easily implemented in similar oasis arid areas

Impact of land use change on urban surface temperature and urban green space planning; case study of the island of Bali, Indonesia

Land use and surface temperature were monitored from 1995 to 2013 to examine green space development in Bali using Landsat and ASTER imageries. Urban areas were formed by conversion of vegetation and paddy fields. Heat islands with surface temperature of over 29 ºC were found and influenced by urban area types. High priority, low priority and not a priority zones for green space were resulted by weighted overlay of LST, NDVI and urban area types

The application of the surface energy balance system model to estimate evapotranspiration in South Africa

Includes abstract.Includes bibliographical references.In a water scarce country like South Africa with a number of large consumers of water, it is important to estimate evapotranspiration (ET) with a high degree of accuracy. This is especially important in the semi-arid regions where there is an increasing demand for water and a scarce supply thereof. ET varies regionally and seasonally, so knowledge about ET is fundamental to save and secure water for different uses, and to guarantee that water is distributed to water consumers in a sustainable manner. Models to estimate ET have been developed using a combination of meteorological and remote sensing data inputs. In this study, the pre-packaged Surface Energy Balance System (SEBS) model was used for the first time in the South African environment alongside MODerate Resolution Imaging Spectroradiometer (MODIS) satellite data and validated with eddy covariance data measured in a large apple orchard (11 ha), in the Piketberg area of the Western Cape. Due to the relative infancy of research in this field in South Africa, SEBS is an attractive model choice as it is available as open-source freeware. The model was found to underestimate the sensible heat flux through setting it at the wet limit. Daily ET measured by the eddy covariance system represented 55 to 96% of the SEBS estimate, an overestimation of daily ET. The consistent underestimation of the sensible heat flux was ascribed to sensitivities to the land surface air temperature gradient, the choice of fractional vegetation cover formula as well as the height of the vegetation canopy (3.2 m) relative to weather station reference height (2 m). The methodology was adapted based on the above findings and was applied to a second study area (quaternary catchment P10A, near Grahamstown, Eastern Cape) where two different approaches for deriving surface roughness are applied. It was again demonstrated that the sensible heat flux is sensitive to surface roughness in combination with land surface air temperature gradient and again, the overestimation of daily ET persisted (actual ET being greater than reference ET). It was concluded that in complex environments, at coarse resolution, it is not possible to adequately describe the remote sensing derived input parameters at the correct level of accuracy and at the spatial resolution required for the accurate estimation of the sensible heat flux

The Long-term Impact of Land Use Land Cover Change on Urban Climate: Evidence from the Phoenix Metropolitan Area, Arizona

abstract: This dissertation research studies long-term spatio-temporal patterns of surface urban heat island (SUHI) intensity, urban evapotranspiration (ET), and urban outdoor water use (OWU) using Phoenix metropolitan area (PMA), Arizona as the case study. This dissertation is composed of three chapters. The first chapter evaluates the SUHI intensity for PMA using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) product and a time-series trend analysis to discover areas that experienced significant changes of SUHI intensity between 2000 and 2017. The heating and cooling effects of different urban land use land cover (LULC) types was also examined using classified Landsat satellite images. The second chapter is focused on urban ET and the impacts of urban LULC change on ET. An empirical model of urban ET for PMA was built using flux tower data and MODIS land products using multivariate regression analysis. A time-series trend analysis was then performed to discover areas in PMA that experienced significant changes of ET between 2001 and 2015. The impact of urban LULC change on ET was examined using classified LULC maps. The third chapter models urban OWU in PMA using a surface energy balance model named METRIC (Mapping Evapotranspiration at high spatial Resolution with Internalized Calibration) and time-series Landsat Thematic Mapper 5 imagery for 2010. The relationship between urban LULC types and OWU was examined with the use of very high-resolution land cover classification data generated from the National Agriculture Imagery Program (NAIP) imagery and regression analysis. Socio-demographic variables were selected from census data at the census track level and analyzed against OWU to study their relationship using correlation analysis. This dissertation makes significant contributions and expands the knowledge of long-term urban climate dynamics for PMA and the influence of urban expansion and LULC change on regional climate. Research findings and results can be used to provide constructive suggestions to urban planners, decision-makers, and city managers to formulate new policies and regulations when planning new constructions for the purpose of sustainable development for a desert city.Dissertation/ThesisDoctoral Dissertation Geography 201

Remote sensing of energy and water fluxes over Volta Savannah catchments in West Africa

The deterioration of the West African savannah in the last three decades is believed to be closely linked with about 0.5 C rise in temperature leading to evaporation losses and declining levels of the Volta Lake in Ghana. Although hydrological models can be used to predict climate change impacts on the regional hydrology, spatially-observed ground data needed for this purpose are largely unavailable. This thesis seeks to address this problem by developing improved methods for estimating energy and water fluxes (e.g. latent heat [ET]) from remotely sensed data and to demonstrate how these may be used to parameterize hydrological models. The first part of the thesis examines the potential of the Penman-Monteith method to estimate local-scale ET using groundbased hydrometeorological observations, vegetation coefficients and environmental data. The model results were compared with pan observations, scintillometer (eddy correlation) measurements and the Thomthwaite empirical method. The Penman- Monteith model produced better evaporation estimates (~3.90 mm day(^-1) for the Tamale district) than its counterpart methods. The Thomthwaite, for example, overestimated predictions by 5.0-11.0 mm day(^-1). Up-scaling on a monthly time scale and parameterization of the Grindley soil moisture balance model with the Thomthwaite and Penman-Monteith data, however, produced similar estimates of actual evaporation and soil moisture, which correlated strongly (R(^2) = 0.95) with water balance estimates. To improve ET estimation at the regional-scale, the second part of the thesis develops spatial models through energy balance modelling and data up-scaling methods, driven by radiometric measurements from recent satellite sensors such as the Landsat ETM+, MODIS and ENVISAT-AATSR. The results were validated using estimates from the Penman-Monteith method, field observations, detailed satellite measurements and published data. It was realised that the MODIS sensor is a more useful source of energy and water balance parameters than AA TSR. For example, stronger correlations were found between MODIS estimates of ET and other energy balance variables such as NDVI, surface temperature and net radiation (R(^2) = 0.67-0.73) compared with AATSR estimates (R(^2) = 0.31-0.40). There was also a good spatial correlation between MODIS and Landsat ETM+ results (R(^2) = 0.71), but poor correlations were found between AATSR and Landsat data (R(^2) = 0.0-0.13), which may be explained by differences in instrument calibration. The results further showed that ET may be underestimated with deviations of ~2.0 mm day 1 when MODIS/AATSR measurements are validated against point observations because of spatial mismatch. The final part of the thesis demonstrates the application of the ET model for predicting runoff (Q) using a simplified version of the regional water balance equation. This is followed byanalysis of flow sensitivity to declining scenarios of biomass volume. The results showed the absence of Q for >90% of the study area during the dry season due largely to crude model approximation and lack of rainfall data, which makes model testing during the wet season important. Runoff prediction may be improved if spatial estimates of rainfall, ET and geographical data (e.g. land-use/cover maps, soil & geology maps and DEM) could be routinely derived from satellite imagery

Spatial Analysis of Post-Hurricane Katrina Thermal Pattern and Intensity in Greater New Orleans: Implications for Urban Heat Island Research

In 2005, Hurricane Katrina’s diverse impacts on the Greater New Orleans area included damaged and destroyed trees, and other despoiled vegetation, which also increased the exposure of artificial and bare surfaces, known factors that contribute to the climatic phenomenon known as the urban heat island (UHI). This is an investigation of UHI in the aftermath of Hurricane Katrina, which entails the analysis of pre and post-hurricane Katrina thermal imagery of the study area, including changes to surface heat patterns and vegetative cover. Imagery from Landsat TM was used to show changes to the pattern and intensity of the UHI effect, caused by an extreme weather event. Using remote sensing visualization methods, field data, and local knowledge, the author found there was a measurable change in the pattern and intensity of the New Orleans UHI effect, as well as concomitant changes to vegetative land cover. This finding may be relevant for urban planners and citizens, especially in the context of recovery from a large-scale disaster of a coastal city, regarding future weather events, and other natural and human impacts

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Current Insights and Trends

NASA or NOAA Earth-observing satellites are not the only space-based TIR platforms. The European Space Agency (ESA), the Chinese, and other countries have in orbit or plan to launch TIR remote sensing systems. Satellite remote sensing provides an excellent opportunity to study land-atmosphere energy exchanges at the regional scale. A predominant application of TIR data has been in inferring evaporation, evapotranspiration (ET), and soil moisture. In addition to using TIR data for ET and soil moisture analysis over vegetated surfaces, there is also a need for using these data for assessment of drought conditions. The concept of ecological thermodynamics provides a quantification of surface energy fluxes for landscape characterization in relation to the overall amount of energy input and output from specific land cover types