scholarly journals Seasonal SUHI Analysis Using Local Climate Zone Classification: A Case Study of Wuhan, China

2021 ◽  
Vol 18 (14) ◽  
pp. 7242
Author(s):  
Lingfei Shi ◽  
Feng Ling ◽  
Giles M. Foody ◽  
Zhen Yang ◽  
Xixi Liu ◽  
...  
Keyword(s):  
Land Surface ◽  
Google Earth ◽  
Vegetation Density ◽  
Climate Zone ◽  
Local Climate ◽  
High Rise ◽  
Urban Rural ◽  
Scattered Trees ◽  
Autumn And Winter ◽  
Local Climate Zone

The surface urban heat island (SUHI) effect poses a significant threat to the urban environment and public health. This paper utilized the Local Climate Zone (LCZ) classification and land surface temperature (LST) data to analyze the seasonal dynamics of SUHI in Wuhan based on the Google Earth Engine platform. In addition, the SUHI intensity derived from the traditional urban–rural dichotomy was also calculated for comparison. Seasonal SUHI analysis showed that (1) both LCZ classification and the urban–rural dichotomy confirmed that Wuhan’s SHUI effect was the strongest in summer, followed by spring, autumn and winter; (2) the maximum SUHI intensity derived from LCZ classification reached 6.53 °C, which indicated that the SUHI effect was very significant in Wuhan; (3) LCZ 8 (i.e., large low-rise) had the maximum LST value and LCZ G (i.e., water) had the minimum LST value in all seasons; (4) the LST values of compact high-rise/midrise/low-rise (i.e., LCZ 1–3) were higher than those of open high-rise/midrise/low-rise (i.e., LCZ 4–6) in all seasons, which indicated that building density had a positive correlation with LST; (5) the LST values of dense trees (i.e., LCZ A) were less than those of scattered trees (i.e., LCZ B) in all seasons, which indicated that vegetation density had a negative correlation with LST. This paper provides some useful information for urban planning and contributes to the healthy and sustainable development of Wuhan.

scholarly journals Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China

2021 ◽  
Vol 13 (10) ◽  
pp. 1902
Author(s):  
Chaomin Chen ◽  
Hasi Bagan ◽  
Xuan Xie ◽  
Yune La ◽  
Yoshiki Yamagata
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Grid Cell ◽  
Classification Model ◽  
Textural Features ◽  
Climate Zone ◽  
Local Climate ◽  
Dual Polarized ◽  
Local Climate Zone ◽  
Sentinel 2

Local climate zone (LCZ) maps have been used widely to study urban structures and urban heat islands. Because remote sensing data enable automated LCZ mapping on a large scale, there is a need to evaluate how well remote sensing resources can produce fine LCZ maps to assess urban thermal environments. In this study, we combined Sentinel-2 multispectral imagery and dual-polarized (HH + HV) PALSAR-2 data to generate LCZ maps of Nanchang, China using a random forest classifier and a grid-cell-based method. We then used the classifier to evaluate the importance scores of different input features (Sentinel-2 bands, PALSAR-2 channels, and textural features) for the classification model and their contribution to each LCZ class. Finally, we investigated the relationship between LCZs and land surface temperatures (LSTs) derived from summer nighttime ASTER thermal imagery by spatial statistical analysis. The highest classification accuracy was 89.96% when all features were used, which highlighted the potential of Sentinel-2 and dual-polarized PALSAR-2 data. The most important input feature was the short-wave infrared-2 band of Sentinel-2. The spectral reflectance was more important than polarimetric and textural features in LCZ classification. PALSAR-2 data were beneficial for several land cover LCZ types when Sentinel-2 and PALSAR-2 were combined. Summer nighttime LSTs in most LCZs differed significantly from each other. Results also demonstrated that grid-cell processing provided more homogeneous LCZ maps than the usual resampling methods. This study provided a promising reference to further improve LCZ classification and quantitative analysis of local climate.

scholarly journals Local Climate Zone Mapping Using Multi-Source Free Available Datasets on Google Earth Engine Platform

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 454
Author(s):  
Lingfei Shi ◽  
Feng Ling
Keyword(s):  
Large Scale ◽  
Urban Climate ◽  
Google Earth ◽  
Positive Contribution ◽  
Climate Zone ◽  
Local Climate ◽  
Google Earth Engine ◽  
Occurrence Matrix ◽  
Local Climate Zone ◽  
Sentinel 2

As one of the widely concerned urban climate issues, urban heat island (UHI) has been studied using the local climate zone (LCZ) classification scheme in recent years. More and more effort has been focused on improving LCZ mapping accuracy. It has become a prevalent trend to take advantage of multi-source images in LCZ mapping. To this end, this paper tried to utilize multi-source freely available datasets: Sentinel-2 multispectral instrument (MSI), Sentinel-1 synthetic aperture radar (SAR), Luojia1-01 nighttime light (NTL), and Open Street Map (OSM) datasets to produce the 10 m LCZ classification result using Google Earth Engine (GEE) platform. Additionally, the derived datasets of Sentinel-2 MSI data were also exploited in LCZ classification, such as spectral indexes (SI) and gray-level co-occurrence matrix (GLCM) datasets. The different dataset combinations were designed to evaluate the particular dataset’s contribution to LCZ classification. It was found that: (1) The synergistic use of Sentinel-2 MSI and Sentinel-1 SAR data can improve the accuracy of LCZ classification; (2) The multi-seasonal information of Sentinel data also has a good contribution to LCZ classification; (3) OSM, GLCM, SI, and NTL datasets have some positive contribution to LCZ classification when individually adding them to the seasonal Sentinel-1 and Sentinel-2 datasets; (4) It is not an absolute right way to improve LCZ classification accuracy by combining as many datasets as possible. With the help of the GEE, this study provides the potential to generate more accurate LCZ mapping on a large scale, which is significant for urban development.

Inter-local climate zone differentiation of land surface temperatures for Management of Urban Heat in Nairobi City, Kenya

Urban Climate ◽  
2020 ◽  
Vol 31 ◽  
pp. 100540 ◽  
Author(s):  
Emmanuel Matsaba Ochola ◽  
Elham Fakharizadehshirazi ◽  
Aggrey Ochieng Adimo ◽  
John Bosco Mukundi ◽  
John Mwibanda Wesonga ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Zone ◽  
Local Climate ◽  
Surface Temperatures ◽  
Land Surface Temperatures ◽  
Urban Heat ◽  
Local Climate Zone

Mapping Local Climate Zone in China’s Major Cities

2020 ◽  
Author(s):  
Qian Ma ◽  
Yongwei Wang ◽  
Shiguang Miao
Keyword(s):  
Urban Morphology ◽  
Underlying Surface ◽  
General Tendency ◽  
Climate Zone ◽  
Local Climate ◽  
Building Height ◽  
Form And Function ◽  
High Rise ◽  
And Function ◽  
Local Climate Zone

<p>Progress in urban climate science is severely hindered by the lacuna of globally consistent and coherent information that describes aspects of the form and function of urban morphology at a detailed spatial resolution. The World Urban Database and Access Portal Tools (WUDAPT) project is proposed to solve the above problems, which has adopted the Local Climate Zone (LCZ) scheme as a basic and consistent description of form and function of cities at neighborhood scale. This study aims to develop a LCZ classification map and establish the urban morphology database for climate research and urban planning in China’s major cities<strong>. </strong>A simple workflow provided by WUDAPT project has been applied to perform this task.</p><p>The results from the quality assessments show that the LCZ maps of 63 cities in China are generally of good quality, i.e. 69–92% overall accuracy (OA). In particular, the acceptable accuracy (77-93%) is much higher when considering weights that take the morphological and climatic similarity of certain classes into account. The building height data from surveying of these cities, including of Beijing, shanghai, Changsha, Chongqing, Fuzhou, Qingdao, Lanzhou, Harbin and Lhasa，were used for testing, and a moderate accuracy (at building height) was of 51-68%. Most of buildings heights of LCZ types are in line with the surveying data, except for Compact high-rise (LCZ 1) and Open high-rise (LCZ 4), which is about 20.5±4.7 m, and has slightly lower than the LCZ standard value (>25 m). This is due to insufficient underlying input information on building height, and a general tendency to confuse these two classes with Compact mid-rise (LCZ 2) and Open mid-rise (LCZ 5).</p><p>Construction area is a very important type of underlying surface in developing countries like China. For example, in Beijing, Guangzhou and Chongqing, this type accounts for 21%, 9% and 9%, mainly distributed in suburban areas. This is an important urban underlying surface in China, but this underlying surface type has not been defined by Stewart and Oke. A follow-up study will try to define the underlying surface of construction area in LCZ classification system.</p>

scholarly journals An Assessment of Microclimates in Southern Ontario: the Application of the Local Climate Zone Method in Toronto and the Surrounding Region

2021 ◽  
Author(s):  
E. Jerome Price-Todd
Keyword(s):  
Population Growth ◽  
Heat Island ◽  
Urbanization Process ◽  
Zone Method ◽  
Southern Ontario ◽  
Climate Zone ◽  
Local Climate ◽  
Urban Rural ◽  
Urban Heat ◽  
Local Climate Zone

The Golden Horseshoe is a densely populated area in southern Ontario and the population is expected to grow to 11.5 million residents by 2031. The urbanization process will likely intensify due to the current and expected population growth. The urban heat island (UHI) effect at 19 meteorological stations in southern Ontario were assessed using climate normals from 1981-2010 and the local climate zone (LCZ) method. The stations were assigned an LCZ unit based upon their calculated impervious, pervious and building surface fractions. It was found that areas representing higher urban-centric zones had higher UHI intensities (LCZ 5 with 2 K) than areas that were less urban-centric (LCZ 9 with 1.12 K and LCZ 6 with 1.37 K) revealing a continuum of “urbanicity”. The LCZ method provided greater objectivity when calculating the UHI intensity than the simpler method of an urban / rural dichotomy. With expected warming and population growth in the area the detrimental human health, environmental and economic impacts associated with the UHI effect should be given consideration for any future planning and decision making.

scholarly journals An Assessment of Microclimates in Southern Ontario: the Application of the Local Climate Zone Method in Toronto and the Surrounding Region

2021 ◽  
Author(s):  
E. Jerome Price-Todd
Keyword(s):  
Population Growth ◽  
Heat Island ◽  
Urbanization Process ◽  
Zone Method ◽  
Southern Ontario ◽  
Climate Zone ◽  
Local Climate ◽  
Urban Rural ◽  
Urban Heat ◽  
Local Climate Zone

The Golden Horseshoe is a densely populated area in southern Ontario and the population is expected to grow to 11.5 million residents by 2031. The urbanization process will likely intensify due to the current and expected population growth. The urban heat island (UHI) effect at 19 meteorological stations in southern Ontario were assessed using climate normals from 1981-2010 and the local climate zone (LCZ) method. The stations were assigned an LCZ unit based upon their calculated impervious, pervious and building surface fractions. It was found that areas representing higher urban-centric zones had higher UHI intensities (LCZ 5 with 2 K) than areas that were less urban-centric (LCZ 9 with 1.12 K and LCZ 6 with 1.37 K) revealing a continuum of “urbanicity”. The LCZ method provided greater objectivity when calculating the UHI intensity than the simpler method of an urban / rural dichotomy. With expected warming and population growth in the area the detrimental human health, environmental and economic impacts associated with the UHI effect should be given consideration for any future planning and decision making.

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