scholarly journals Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China

Land ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 14
Author(s):  
Maomao Zhang ◽  
Cheng Zhang ◽  
Abdulla-Al Kafy ◽  
Shukui Tan
Keyword(s):  
Land Use ◽  
Development Strategy ◽  
Thermal Environment ◽  
Image Data ◽  
Machine Learning Algorithms ◽  
Rapid Expansion ◽  
Green Development ◽  
Urban Heat ◽  
Vegetation Water ◽  
Artificial Neural Network Ann

The changes of land use/land cover (LULC) are important factor affecting the intensity of the urban heat island (UHI) effect. Based on Landsat image data of Wuhan, this paper uses cellular automata (CA) and artificial neural network (ANN) to predict future changes in LULC and LST. The results show that the built-up area of Wuhan has expanded, reaching 511.51 and 545.28 km2, while the area of vegetation, water bodies and bare land will decrease to varying degrees in 2030 and 2040. If the built-up area continues to expand rapidly, the proportion of 30~35 °C will rise to 52.925% and 55.219%, and the affected area with the temperature >35 °C will expand to 15.264 and 33.612 km2, respectively. The direction of the expansion range of the LST temperature range is obviously similar to the expansion of the built-up area. In order to control and alleviate UHI, the rapid expansion of impervious layers (built-up areas) should be avoided to the greatest extent, and the city’s “green development” strategy should be implemented.

scholarly journals Characterizing the Hourly Variation of Urban Heat Islands in a Snowy Climate City during Summer

2019 ◽  
Vol 16 (14) ◽  
pp. 2467 ◽  
Author(s):  
Chaobin Yang ◽  
Ranghu Wang ◽  
Shuwen Zhang ◽  
Caoxiang Ji ◽  
Xie Fu
Keyword(s):  
Land Use ◽  
Urban Area ◽  
Air Temperature ◽  
Temporal Variability ◽  
Spatial Information ◽  
Thermal Environment ◽  
Thermal Characteristics ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat

Temporal variation of urban heat island (UHI) intensity is one of the most important themes in UHI studies. However, fine-scale temporal variability of UHI with explicit spatial information is sparse in the literature. Based on the hourly air temperature from 195 meteorological stations during August 2015 in Changchun, China, hourly spatiotemporal patterns of UHI were mapped to explore the temporal variability and the effects of land use on the thermal environment using time series analysis, air temperature profiling, and spatial analysis. The results showed that: (1) high air temperature does not indicate strong UHI intensity. The nighttime UHI intensity (1.51 °C) was much stronger than that in the daytime (0.49 °C). (2) The urban area was the hottest during most of the day except the period from late morning to around 13:00 when there was about a 40% possibility for an “inverse UHI intensity” to appear. Paddy land was the coolest in the daytime, while woodland had the lowest temperature during the nighttime. (3) The rural area had higher warming and cooling rates than the urban area after sunrise and sunset. It appeared that 23 °C was the threshold at which the thermal characteristics of different land use types changed significantly.

Impact of Land Use Pattern on Urban Thermal Environment in Wuhan, China

2013 ◽  
Vol 361-363 ◽  
pp. 529-532
Author(s):  
Lu Ping Ye ◽  
Zhi Ping Cheng ◽  
Nan Sheng You ◽  
Qiang Wang ◽  
Xiu Qin Tian
Keyword(s):  
Land Use ◽  
Environmental Effects ◽  
Thermal Environment ◽  
Fractal Theory ◽  
Quantitative Description ◽  
Urban Land ◽  
Urban Land Use ◽  
Bare Land ◽  
Urban Heat ◽  
Urban Thermal Environment

Traditionally, assessing impacts of urban land use on thermal environment is mainly depended on statistical analysis, which cannot exactly express the internal spatial correlation fundamental between urban land use and thermal environmental effects. This study introduces fractal theory to build radius dimension, and makes a quantitative description of the characteristics change from the center of the urban heat island effect on land use spatial pattern to the surrounding. The results suggested that those radius dimensions of five typical land use types are ranked in descending order: cropland, forest, water, bare land and built-up. It is indicated that built-up has positive effect on the performance of urban thermal environment, while forest, cropland and water have negative effect on urban thermal environment. The effect of bare land is not obvious. It is demonstrated that the radius dimension can effectively distinguish the gathered or mitigated effects from various land use spatial structure on urban heat environmental effects, which scientifically guides government to mitigate the UHI extant and degree by urban land use planning.

Land-Use/Land-Cover Changes and Their Influence on Urban Thermal Environment in Zhengzhou City During the Period of 1986 to 2026

2020 ◽  
Author(s):  
Pei Liu ◽  
Ruimei Han ◽  
Leiku Yang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Thermal Environment ◽  
Dynamic Change ◽  
Urban Sustainability ◽  
Land Cover Changes ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
High Level ◽  
The Impact

<p>Rapid urbanization has become a major urban sustainability concern due to environmental impacts, such as development of urban heat island (UHI) and the reduction of urban security states. To date, most research on urban sustainability development has focus on dynamic change monitoring or UHI state characterization. While there is little literature on UHI change analysis. In addition, there has been little research on the impact of land use and land cover changes (LULCCs) on UHI, especially simulates future trend of LULCCs, UHI change, and dynamic relationship of LULCCs and UHI. The purpose of this research is to design a remote sensing based framework that investigates and analysis that how the LULCCs in the process of urbanization affected thermal environment. In order to assesses and predicts impact of LULCCs on urban heat environment, multi-temporal remotely sensed data from 1986 to 2016 were selected as source data, and Geographic Information System (GIS) methods such as CA-Markov model were employed to construct the proposed framework. The results shown that (1) there has been a substantial strength of urban expansion during the 40 years study period; (2) the most far distance urban center of gravity movement from north-northeast (NEE) to west-southwest (WSW) direction; (3) the dominate temperature were middle level, sub-high level and high level in the research area; (4) there was a higher changing frequency and range from east to west; (5) there was significant negative correlation between land surface temperature and vegetation, and significant positive correlation between temperature and human settlement.</p>

Monitoring the Spatiotemporal Dynamics of Urban Green Space and Its Impacts on Thermal Environment in Shenzhen City from 1978 to 2018 with Remote Sensing Data

2021 ◽  
Vol 87 (2) ◽  
pp. 81-89
Author(s):  
Yue Liu ◽  
Hui Li ◽  
Peng Gao ◽  
Cheng Zhong
Keyword(s):  
Urban Heat Island ◽  
Green Space ◽  
Temporal Dynamics ◽  
Thermal Environment ◽  
Urban Green Space ◽  
Rapid Expansion ◽  
Heat Island ◽  
Urban Green ◽  
Shenzhen City ◽  
Urban Heat

In a developing city, urban green space (UGS) plays an increasingly significant role in improving the urban environment and beautifying the urban landscape. In the meantime, UGS has been substantially and frequently interfered with by human activities. Taking Shenzhen city (a great metropolis of China) as an example, this study investigated the spatio-temporal dynamics of UGS and its influence on the urban thermal environment with Landsat images. From 1978 to 2018, all croplands and more than 50% of water bodies disappeared, while the built-up area increased more than 6 times. The rapid expansion of impervious surface and loss of UGS led to the spread of a surface urban heat island. The study shows that UGS has a significantly mitigating impact on urban land surface temperature, with cold islands mainly located at city parks. The results will be of great significance for improving UGS management, alleviating the urban heat island effect, and establishing a sustainable eco-environment.

Remote Sensing for Land Use Mapping, Case of The Study Area: Urban Commune of Saada, Morocco

2021 ◽  
Vol 2 (1) ◽  
pp. 36-43
Author(s):  
Abdelouhed Farah ◽  
Ahmed Algouti ◽  
Abdellah Algouti ◽  
Essaadia Adaze ◽  
Mohammed Ifkirne
Keyword(s):  
Land Use ◽  
Urban Area ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Satellite Image ◽  
Image Data ◽  
Machine Learning Algorithms ◽  
Exponential Population Growth ◽  
Landsat Satellite ◽  
The City

The phenomenon of urban planning in favor of agricultural land on the outskirts of the city of Marrakech is in full expansion. The study of land use changes is of pivotal interest for the knowledge, management, monitoring, surveillance, and evaluation of our environment. Indeed, the city of Marrakech has been experiencing exponential population growth for several decades. This phenomenon has led to a dynamic urban characterized by the increase and densification of urbanized areas (e.g. buildings and infrastructures) which leads to the occupation of natural spaces. To this end, this study aims at highlighting the mapping and evolution of land use in the city of Marrakech from Landsat satellite image data (1989, 2005 and 2020) through the application of the Image classification using Machine Learning algorithms with the QGis Orfeo Toolbox, which facilitate the production of land use maps at three dates as well as an evolution map of the conurbation and also to quantify the obtained results. The directions of extension of the urban area were defined and thus demonstrate its impact on the agricultural land located in the peri-urban area.

Metro Station Surrounding Land-Use Development Strategy

2014 ◽  
Vol 543-547 ◽  
pp. 4066-4068
Author(s):  
Zhi Qiang Xue ◽  
Sheng Yong Yao ◽  
Jin Jie Chen
Keyword(s):  
Land Use ◽  
Survey Data ◽  
Development Strategy ◽  
Satellite Image ◽  
Image Data ◽  
Rail Transit ◽  
Metro Station ◽  
The Development Strategy ◽  
Satellite Image Data ◽  
Land Use Development

With the construction of Shijiazhuangs rail transit, how to improve the efficiency of metro station surrounding land use has become a serious problem. In this paper ,Shijiazhuang metro station surrounding land use is intended to research object by using satellite image data and travel questionnaire. This paper analyzes the land use characteristics of surrounding Shijiazhuangs metro station, and come up with the development strategy of metro station surrounding land use through the analysis of survey data.

scholarly journals Comprehensive Measurement and Regional Imbalance of China’s Green Development Performance

2021 ◽  
Vol 13 (3) ◽  
pp. 1409
Author(s):  
Shengyun Wang ◽  
Yaxin Zhang ◽  
Huwei Wen
Keyword(s):  
Development Strategy ◽  
Regional Differences ◽  
Environmental Governance ◽  
Primary Source ◽  
Scientific Basis ◽  
Coordinated Development ◽  
Green Development ◽  
Southwest Region ◽  
Development Levels ◽  
Regional Imbalance

This study adopted the two-stage super-efficiency network slack-based model (SBM) to measure the green development performance index (GDPI) of 30 provinces in China. The Dagum Gini coefficient decomposition was used to analyze the regional differences and their sources in China’s green development performance. The results are as follows: first, the green development performance showed a declining trend from 1997 to 2017. The improvement of environmental governance efficiency was the key to achieving green development progress. The green development levels of coastal areas were significantly higher than those of inland provinces. Second, the regional imbalance in China’s green development performance was gradually worsening. The inter-regional differences were the primary source of the overall differences. The intra-regional difference of green development within the northwest was the largest. Third, among the eight regions, only the southwest region had σ convergence in green development performance; in addition, absolute β convergence and conditional β convergence were divergent, thereby confirming the regional imbalance of the widening regional differences in China’s green development performance. This study aimed to provide a scientific basis and effective reference for further advancing China’s regional coordinated development strategy.

scholarly journals Assessment and Spatial-Temporal Evolution Analysis of Urban Land Use Efficiency under Green Development Orientation: Case of the Yangtze River Delta Urban Agglomerations

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 715
Author(s):  
Yingkai Tang ◽  
Kun Wang ◽  
Xuanming Ji ◽  
He Xu ◽  
Yangqing Xiao
Keyword(s):  
Land Use ◽  
Urban Development ◽  
Evaluation System ◽  
Yangtze River Delta ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Efficiency ◽  
Green Development ◽  
Use Efficiency ◽  
Development Orientation

Rapid urbanization has provided a strong impetus for the economic growth of China, but it has also caused many problems such as inefficient urban land use and environmental pollution. With the popularization of the concept of green and sustainable development, the Environmental-Social-Governance (ESG) assessment concept is widely accepted. The government and residents are paying more and more attention to environmental issues in urban development, and environmental protection has formed an important part of urban development. In this context, this study takes 26 cities in the Yangtze River Delta as examples to build an evaluation system for urban land-use efficiency under green development orientation. The evaluation system takes into account the inputs of land, capital, labor, and energy factors in the process of urban development. Based on emphasizing economic output, the social benefits and undesired outputs brought about by urban development are taken into account. This paper measures urban land use efficiency by the super-efficiency SBM model, and on this basis, analyses the spatial-temporal evolution characteristics of urban land-use efficiency. Further, this paper measures urban land use efficiency without considering undesired outputs and compares the two evaluation methods. Again, the comparison illustrates the rationality of urban land use efficiency evaluation system under green development orientation.

scholarly journals Analyzing the Patterns, Trends and Dynamics of the Land-Use Changes in Azores Region: From 1990 to 2018

2021 ◽  
Vol 13 (10) ◽  
pp. 5433
Author(s):  
Rui Alexandre Castanho ◽  
José Manuel Naranjo Gómez ◽  
Gualter Couto ◽  
Pedro Pimentel ◽  
Áurea Sousa ◽  
...  
Keyword(s):  
Land Use ◽  
Development Strategy ◽  
Land Use Changes ◽  
Regional Government ◽  
Land Uses ◽  
Comprehensive Planning ◽  
Sustainability Planning ◽  
The Enlightenment ◽  
Planning Strategies ◽  
Agricultural Areas

The remarkable richness and singularity of the Azorean Region (located 38° North) and its landscapes require a sharp, well-defined, and comprehensive planning policy. Bearing in mind the significance of this issue in the enlightenment of sustainability, planning strategies should be based and supported by different studies and thematic domains to understand the problem thoroughly. Using GIS (Geographic Information Systems), the present article enables us to identify the dynamics and patterns of the evolution of the Land-Use Changes in the Azores Region from 1990 to 2018. In aggregate, the Azores islands showed growth in artificial surfaces and forest and seminatural land-uses by essentially decreasing agricultural areas—most resulting from the economic and social development strategy pursued by several Azorean governments. Moreover, this study permits us to reinforce that the Azores Archipelago’s land-uses has undergone multiple changes—marked by increasing and decreasing periods. In fact, some of these reducing dynamics are disturbing. They require closer monitorization by regional government actors to give protection, preservation, and conservation to these incomparable ultra-peripheral landscapes, environments, ecosystems, and the region as a whole.

scholarly journals Prediction of Healing Performance of Autogenous Healing Concrete Using Machine Learning

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4068
Author(s):  
Xu Huang ◽  
Mirna Wasouf ◽  
Jessada Sresakoolchai ◽  
Sakdirat Kaewunruen
Keyword(s):  
Machine Learning ◽  
Search Algorithm ◽  
Weather Conditions ◽  
Prediction Performance ◽  
Machine Learning Algorithms ◽  
Coefficient Of Determination ◽  
Gradient Boosting ◽  
Support Vector ◽  
Self Healing ◽  
Artificial Neural Network Ann

Cracks typically develop in concrete due to shrinkage, loading actions, and weather conditions; and may occur anytime in its life span. Autogenous healing concrete is a type of self-healing concrete that can automatically heal cracks based on physical or chemical reactions in concrete matrix. It is imperative to investigate the healing performance that autogenous healing concrete possesses, to assess the extent of the cracking and to predict the extent of healing. In the research of self-healing concrete, testing the healing performance of concrete in a laboratory is costly, and a mass of instances may be needed to explore reliable concrete design. This study is thus the world’s first to establish six types of machine learning algorithms, which are capable of predicting the healing performance (HP) of self-healing concrete. These algorithms involve an artificial neural network (ANN), a k-nearest neighbours (kNN), a gradient boosting regression (GBR), a decision tree regression (DTR), a support vector regression (SVR) and a random forest (RF). Parameters of these algorithms are tuned utilising grid search algorithm (GSA) and genetic algorithm (GA). The prediction performance indicated by coefficient of determination (R2) and root mean square error (RMSE) measures of these algorithms are evaluated on the basis of 1417 data sets from the open literature. The results show that GSA-GBR performs higher prediction performance (R2GSA-GBR = 0.958) and stronger robustness (RMSEGSA-GBR = 0.202) than the other five types of algorithms employed to predict the healing performance of autogenous healing concrete. Therefore, reliable prediction accuracy of the healing performance and efficient assistance on the design of autogenous healing concrete can be achieved.

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