Irrigation cooling effect on land surface temperature across China based on satellite observations

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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Mapping urban greenery to create the optimal cooling effect model against solar radiation under the conditions of a smart city

Abstracts of the ICA ◽

10.5194/ica-abs-1-326-2019 ◽

2019 ◽

Vol 1 ◽

pp. 1-2

Author(s):

Vladimír Sedlák ◽

Katarína Onačillová ◽

Michal Gallay ◽

Jaroslav Hofierka ◽

Ján Kaňuk ◽

...

Keyword(s):

Solar Radiation ◽

Surface Temperature ◽

Urban Environment ◽

Land Surface Temperature ◽

Land Surface ◽

Smart City ◽

Research Study ◽

Cooling Effect ◽

Urban Greenery ◽

Sentinel 2

Abstract. Current climate changes on a global scale require an optimal estimate of heat transfer in a complex urban environment as a part of the requirements for optimal urban planning in the conditions of a smart city. Urban greenery has a considerable impact on the cooling of the urban environment during thermal waves. Sentinel-2 as an Earth observation mission developed by the European Space Agency as part of the Copernicus Programme to perform terrestrial observations in support of various services could become a potential means also for quantified assessment of different urban scenarios where vegetation plays an essential role. The Sentinel-2 data provide higher spatial and temporal resolution than other similar missions allow.The presented research study is aimed at exploiting the potential of Sentinel-2 in simulating the cooling effect of urban greenery as part of smart city mapping in assessing the quality of life of its inhabitants. The main objective of the research study is to define a methodical approach for spatial surface temperature modelling in selected urban areas based on the solar radiation modelling and parameterization of the land cover properties from the Sentinel-2 data. While solar irradiation can be accurately calculated at a fine scale using virtual 3D city models, it is difficult to find other important parameters for ground surface modelling such as surface thermal emissivity, broadband albedo and evapotranspiration. The research study was tested and verified in 4&thinsp;sq.&thinsp;km urban area in the selected central parts of the city of Košice in Slovakia (Figure 1). For a detailed survey, four sites (site 1 &ndash; Moyzesova Street, site 2 &ndash; Historical centre, site 3 &ndash; City park, site 4 &ndash; Hvozdíkov park) were chosen in the central city area. The virtual 3D urban model was created from the airborne LiDAR (Light Detection And Ranging, hereinafter referred to as the lidar) and photogrammetric data obtained in a single mission.The aim of the research study was to assess the feasibility of using virtual 3D city models and multispectral satellite images to approximate surface temperature dynamics by modelling of the spatial distribution of solar radiation and land surface characteristics in a complex urban environment. A time-series of the Sentinel-2 data was collected for comparison with the reference time series of the terrestrial lidar (TLS &ndash; Terrestrial Laser Scanning) data on urban greenery on four selected urban areas of the city of Košice. Between the vegetation metrics, the statistical linear relationship derived from the Sentinel-2 and TLS data was defined. Based on terrain mapping, a geobotanic database of urban trees was created. The algorithmic structure of a toolbox for the land surface temperature modelling in the open-source GRASS GIS was developed based on the Stefan-Boltzmann law and Kirchhoff rule.This research study has highlighted how the Sentinel-2 data can be used to estimate of the broad-band albedo, surface emission, and solar transmittance to the vegetation of urban greenery. The main benefit of the research study is the developed algorithm for estimation of the land surface temperature in a GIS environment that provides a unique platform for integrating different types of data-sets to become usable in urban planning and for exploitation of the Sentinel-2 data in mitigation of a negative impact of the urban extreme heat islands on the quality of life of inhabitants. The resulting LST (Land Surface Temperature) was calculated for four scenarios using the detail of the study area of the site 1 (Figure 2) and whole study are (Figure 3) demonstrate. These figures also show the cooling effect of urban trees and shrubs.

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Land Surface Temperature Retrieval from Passive Microwave Satellite Observations: State-of-the-Art and Future Directions

Remote Sensing ◽

10.3390/rs12162573 ◽

2020 ◽

Vol 12 (16) ◽

pp. 2573

Author(s):

Si-Bo Duan ◽

Xiao-Jing Han ◽

Cheng Huang ◽

Zhao-Liang Li ◽

Hua Wu ◽

...

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Important Variable ◽

Satellite Observations ◽

Passive Microwave ◽

Empirical Methods ◽

Physically Based ◽

Temperature Retrieval ◽

Semi Empirical

Land surface temperature (LST) is an important variable in the physics of land–surface processes controlling the heat and water fluxes over the interface between the Earth’s surface and the atmosphere. Space-borne remote sensing provides the only feasible way for acquiring high-precision LST at temporal and spatial domain over the entire globe. Passive microwave (PMW) satellite observations have the capability to penetrate through clouds and can provide data under both clear and cloud conditions. Nonetheless, compared with thermal infrared data, PMW data suffer from lower spatial resolution and LST retrieval accuracy. Various methods for estimating LST from PMW satellite observations were proposed in the past few decades. This paper provides an extensive overview of these methods. We first present the theoretical basis for retrieving LST from PMW observations and then review the existing LST retrieval methods. These methods are mainly categorized into four types, i.e., empirical methods, semi-empirical methods, physically-based methods, and neural network methods. Advantages, limitations, and assumptions associated with each method are discussed. Prospects for future development to improve the performance of LST retrieval methods from PMW satellite observations are also recommended.

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