The utilization of urban underground space(UUS)offers an effective solution to urban problems but may also negatively affect urban development.Therefore,UUS development needs better concerted guidelines to coordinate ...The utilization of urban underground space(UUS)offers an effective solution to urban problems but may also negatively affect urban development.Therefore,UUS development needs better concerted guidelines to coordinate various urban systems and the multiple components of the underground world.Sustainable Development Goals(SDGs),which should be viewed as important yardsticks for UUS development,do not explicitly mention urban underground space,although many of them are affected by both the positive and negative consequences of its development.To fill this gap,this review lays the foundations of relevant UUS concepts and uses exemplary cases to reveal that 11 out of 17 SDGs can be linked with UUS uses.These linkages also manifest that land administration,integrated planning,architectural design,and construction technology are critical dimensions for increasing the contributions of UUS to the realization of SDGs.To achieve multi-disciplinary synergies among these four critical dimensions,a collaborative approach framework based on spatial data infrastructure is required.Thus,this work provides academics and practitioners with a holistic view of sustainable UUS development.展开更多
One of the ubiquitous human behaviours observed in natural disasters and humanitarian crisis is irrational stock-piling(also known as hoarding or panic buying).Limited,distorted and exaggerated information during cris...One of the ubiquitous human behaviours observed in natural disasters and humanitarian crisis is irrational stock-piling(also known as hoarding or panic buying).Limited,distorted and exaggerated information during crisis disturbs people’s judgement and results in aberrant actions which can be explained with economics and psychol-ogy theories.The objective of this paper is to examine the perplexing stockpiling phenomena during disasters like COVID-19 pandemic and discuss its immediate and long-term impact on economy,society and local communities.展开更多
The detection of informal settlements is the first step in planning and upgrading deprived areas in order to leave no one behind in SDGs.Very High-Resolution satellite images(VHR),have been extensively used for this p...The detection of informal settlements is the first step in planning and upgrading deprived areas in order to leave no one behind in SDGs.Very High-Resolution satellite images(VHR),have been extensively used for this purpose.However,as a cost-prohibitive data source,VHR might not be available to all,particularly nations that are home to many informal settlements.This study examines the application of open and freely available data sources to detect the structure and pattern of informal settlements.Here,in a case study of Jakarta,Indonesia,Medium Resolution satellite imagery(MR)derived from Landsat 8(2020)was classified to detect these settlements.The classification was done using Random Forest(RF)classifier through two complementary approaches to develop the training set.In the first approach,available survey data sets(Jakarta’s informal settlements map for 2015)and visual interpreta-tion using High-Resolution Google Map imagery have been used to build the training set.Throughout the second round of classifica-tion,OpenStreetMap(OSM)layers were used as the complementary approach for training.Results from the validation test for the second round revealed better accuracy and precision in classi-fication.The proposed method provides an opportunity to use open data for informal settlements detection,when:1)more expen-sive high resolution data sources are not accessible;2)the area of interest is not larger than a city;and 3)the physical characteristics of the settlements differ significantly from their surrounding formal area.The method presents the application of globally accessible data to help the achievement of resilience and SDGs in informal settlements.展开更多
基金This work was supported by the National Key Technology R&D Program(No.2012BAJ01B04)the National Natural Science Foundation of China(Grant No.42071251)the China Scholarship Council(File No.201806260167)。
文摘The utilization of urban underground space(UUS)offers an effective solution to urban problems but may also negatively affect urban development.Therefore,UUS development needs better concerted guidelines to coordinate various urban systems and the multiple components of the underground world.Sustainable Development Goals(SDGs),which should be viewed as important yardsticks for UUS development,do not explicitly mention urban underground space,although many of them are affected by both the positive and negative consequences of its development.To fill this gap,this review lays the foundations of relevant UUS concepts and uses exemplary cases to reveal that 11 out of 17 SDGs can be linked with UUS uses.These linkages also manifest that land administration,integrated planning,architectural design,and construction technology are critical dimensions for increasing the contributions of UUS to the realization of SDGs.To achieve multi-disciplinary synergies among these four critical dimensions,a collaborative approach framework based on spatial data infrastructure is required.Thus,this work provides academics and practitioners with a holistic view of sustainable UUS development.
文摘One of the ubiquitous human behaviours observed in natural disasters and humanitarian crisis is irrational stock-piling(also known as hoarding or panic buying).Limited,distorted and exaggerated information during crisis disturbs people’s judgement and results in aberrant actions which can be explained with economics and psychol-ogy theories.The objective of this paper is to examine the perplexing stockpiling phenomena during disasters like COVID-19 pandemic and discuss its immediate and long-term impact on economy,society and local communities.
文摘The detection of informal settlements is the first step in planning and upgrading deprived areas in order to leave no one behind in SDGs.Very High-Resolution satellite images(VHR),have been extensively used for this purpose.However,as a cost-prohibitive data source,VHR might not be available to all,particularly nations that are home to many informal settlements.This study examines the application of open and freely available data sources to detect the structure and pattern of informal settlements.Here,in a case study of Jakarta,Indonesia,Medium Resolution satellite imagery(MR)derived from Landsat 8(2020)was classified to detect these settlements.The classification was done using Random Forest(RF)classifier through two complementary approaches to develop the training set.In the first approach,available survey data sets(Jakarta’s informal settlements map for 2015)and visual interpreta-tion using High-Resolution Google Map imagery have been used to build the training set.Throughout the second round of classifica-tion,OpenStreetMap(OSM)layers were used as the complementary approach for training.Results from the validation test for the second round revealed better accuracy and precision in classi-fication.The proposed method provides an opportunity to use open data for informal settlements detection,when:1)more expen-sive high resolution data sources are not accessible;2)the area of interest is not larger than a city;and 3)the physical characteristics of the settlements differ significantly from their surrounding formal area.The method presents the application of globally accessible data to help the achievement of resilience and SDGs in informal settlements.
