The Spatial Patterns of Land Surface Temperature and Its Impact Factors: Spatial Non-Stationarity and Scale Effects Based on a Geographically-Weighted Regression Model

Zhao, Hongbo; Ren, Zhibin; Tan, Juntao

doi:10.3390/su10072242

Cited by 40 publications

(18 citation statements)

References 63 publications

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“…Concerning the investigation of UHI characteristics and changes in large-scale, these studies mainly focus on: (1) The spatial distribution of UHI; (2) the methods of satellite image inversion;(3) the relationship between land use land cover (LULC) and LST [13]. Furthermore, landscape pattern analysis in a regional scale was also proved to be a proper method in UHI research [14].However, in small-scale UHI studies, the UHI is mainly characterized by the actual measured air temperature [15][16][17]. These kinds of studies mainly focused on the temperature difference between the green space and other land types, and the method of characterizing UHI intensity.…”

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confidence: 99%

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Mapping and Analyzing the Park Cooling Effect on Urban Heat Island in an Expanding City: A Case Study in Zhengzhou City, China

Wang

Tian

et al. 2020

Land

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The Urban Heat Island (UHI) effect has been extensively studied as a global issue. The urbanization process has been proved to be the main reason for this phenomenon. Over the past 20 years, the built-up area of Zhengzhou city has grown five times larger, and the UHI effect has become increasingly pressing for the city's inhabitants. Therefore, mitigating the UHI effect is an important research focus of the expanding capital city of the Henan province. In this study, the Landsat 8 image of July 2019 was selected from Landsat collection to obtain Land Surface Temperature (LST) by using Radiative Transfer Equation (RTE) method, and present land cover information by using spectral indices. Additionally, high-resolution Google Earth images were used to select 123 parks, grouped in five categories, to explore the impact factors on park cooling effect. Park Cooling Intensity (PCI) has been chosen as an indicator of the park cooling effect which will quantify its relation to park patch metrics. The results show that: (1) Among the five studied park types, the theme park category has the largest cooling effect while the linear park category has the lowest cooling effect; (2) The mean park LST and PCI of the samples are positively correlated with the Fractional Vegetation Cover (FVC) and with Normalized Difference Water Index (NDWI), but these are negatively correlated with the Normalized Difference Impervious Surface Index (NDISI). We can suppose that the increase of vegetation cover rate within water areas as well as the decrease of impervious surface in landscape planning and design will make future parks colder. (3) There is a correlation between the PCI and the park characteristics. The UHI effect could be mitigated by increasing of park size and reducing park fractal dimension (Frac_Dim) and perimeter-area ratio (Patario). (4) The PCI is influenced by the park itself and its surrounding area. These results will provide an important reference for future urban planning and urban park design to mitigate the urban heat island effect.Land 2020, 9, 57 2 of 17 countries and their rapid urban growth towards becoming a developed nation. Taking China as an example, according to the National Bureau of Statistics of China, the urbanization rate in China was 59.58% in 2018. This number is 12.58% higher than in 2008. This high-speed urbanization had led to widespread UHI problems in China [6]. With this rapid increase in urbanization has come an increase in energy consumption, with individuals attempting to reduce these adverse temperature effects (e.g., air conditioning, private vehicle usage). As a consequence, higher energy consumption based on coal power plants may result in air pollution, water pollution, and additional climate changes. More specifically, UHI compromised the health and life quality of citizens [7].Generally speaking, UHI can be measured by two methods: one of them is Surface UHI (SUHI); the other one is atmospheric UHI. Atmospheric UHI is defined into two different types: canopy layer UHI and boundary layer ...

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confidence: 99%

“…(3) the relationship between land use land cover (LULC) and LST [13]. Furthermore, landscape pattern analysis in a regional scale was also proved to be a proper method in UHI research [14].…”

mentioning

confidence: 99%

Mapping and Analyzing the Park Cooling Effect on Urban Heat Island in an Expanding City: A Case Study in Zhengzhou City, China

Wang

Tian

et al. 2020

Land

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“…For a statistically significant positive Z-score, the larger the Z-score is, the more intense is the clustering of high values (hot spot). For a statistically significant negative Z-score, the smaller the Z-score is, the more intense is the clustering of low values (cold spot) [35][36][37].…”

Section: Hot Spot Analysismentioning

confidence: 99%

Village Regrouping in the Eastern Plains of China: A Perspective on Home-Field Distance

Liu

Chen

et al. 2019

Sustainability

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Rural decline caused by rapid urbanization is a global issue, and village regrouping is an effective way to revitalize the countryside. The eastern plains of China (EPC) were the first regions to implement the policy of village regrouping in China. Despite being one of the most critical factors in village regrouping, home-field distances (HFDs) in these areas have received little attention. In this study, we selected 240 sample points in the EPC through spatial stratified sampling, each of which is a square of 10 × 10 km2. Based on high-resolution remote sensing images, the inter-regional differences of rural settlements and home-field straight-line distances (HFLDs) in the EPC were systematically analyzed. Based on the central place theory (CPT), the influencing mechanism of the HFLD, the maximum HFLD acceptable to farmers, and the reasonable number, distribution pattern, and service scope of central villages in the EPC were further explored. The results indicate that HFLDs in the EPC have significant latitude zonality and spatial autocorrelation. In the northeastern China plain (NECP), north China plain (NCP), and middle and lower reaches plain of the Yangtze River (MLPYR), the ranges of the maximum HFLD are 1000–4000 m, 500–2200 m, and 500–1500 m, respectively. The distribution pattern of rural settlements, the traffic conditions, and the vehicles used by farmers during periods of land development directly impact the HFLD. HFLDs in the EPC should not exceed 3.6–4.2 km (NECP can use the higher standard-4.2 km, NCP and MLPYR can use the lower standard-3.6 km), the service range of each rural settlement should not exceed 33.6–45.8 km2, and the number of rural settlements per 100 km2 should be greater than three. The rural settlements should be discretely distributed so that each piece of farmland can be tended. The MLPYR demonstrates the greatest potential for village regrouping, and the Chinese government should invest more funds in village regrouping and central village construction in the MLPYR. This study can provide a case study for developing countries in the urbanization phase, so as to improve the rationality of village regrouping planning.

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“…Spectral indices, such as the Normalized Difference Vegetation index (NDVI), detect vegetated (values > 0) and non-vegetated (values < 0) surfaces (Rouse et al, 1974;Guha et al, 2018). NDVI allows monitoring the health of the vegetation (Huete et al, 2002) and can also be used to delimit wet and dry periods (Zhao et al, 2018), diagnose LULC (Fu and Weng, 2016;Guha et al, 2018), and evaluate changes in spectral patterns of preserved environments (Mancino et al, 2014). For the analysis of urban development based on built-up areas, several researchers (Varhney, 2013, García andPérez, 2016;Guha et al, 2018) have used the Normalized Difference Built-up Index (NDBI), which clearly distinguishes urbanized areas from gardens and xerophilic vegetation across built-up urban environments.…”

Section: Introductionmentioning

confidence: 99%

Application of Spatial Modeling of Biophysical Variables in an Urbanized Area in the Amazon: The Case of the Metropolitan Area of Belém-Pará

Silva

Margalho

Serrão

et al. 2021

Rev. bras. meteorol.

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The type of land use and land cover plays a decisive role in land surface temperature (LST). As cities are composed of varied covers, including vegetation, built-up areas, buildings, roads and areas without vegetation, understanding LST patterns in complex urban spaces is becoming increasingly important. The present study investigated the relationship between LST and albedo, NDVI, NDWI, NDBI and NDBaI in the period between 1994 and 2017. Images from Thematic Mapper (TM) and Thermal Infrared Sensor (TIRS) onboard the Landsat 5 and 8 satellites, respectively, were used in the study. The images were processed, resampled (spatial resolution of 120 m) in the environment of the QGIS 3.0 software and, finally, centroids were extracted resulting in a total of 1252 points. A classical regression (CR) model was applied to the variables, followed by spatial autoregressive (SARM) and spatial error (SEM) models, and the results were compared using accuracy indices. The results showed that the highest correlation coefficient was found between albedo and NDBaI (r = 0.88). The relationship between albedo and LST (r = 0.7) was also positive and significant at р < 0.05. The global Moran's I index showed spatial dependence and non-stationarity of the LST (I = 0.44). The SEM presented the best accuracy metrics (AIC = 3307.15 and R2 = 0.65) for the metropolitan region of Belém, explaining considerably more variations in the relationship between explanatory factors and LST when compared to conventional CR models.

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The Spatial Patterns of Land Surface Temperature and Its Impact Factors: Spatial Non-Stationarity and Scale Effects Based on a Geographically-Weighted Regression Model

Cited by 40 publications

References 63 publications

Mapping and Analyzing the Park Cooling Effect on Urban Heat Island in an Expanding City: A Case Study in Zhengzhou City, China

Mapping and Analyzing the Park Cooling Effect on Urban Heat Island in an Expanding City: A Case Study in Zhengzhou City, China

Village Regrouping in the Eastern Plains of China: A Perspective on Home-Field Distance

Application of Spatial Modeling of Biophysical Variables in an Urbanized Area in the Amazon: The Case of the Metropolitan Area of Belém-Pará

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