Identification of low-carbon travel block based on GIS hotspot analysis using spatial distribution learning algorithm
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3447-8
Abstract: In the future, big data will become an efficient and useful means for improving urban planning, and machine learning can take city as a simplified and efficient system. We take full advantage of the benefits… read more here.
Keywords: block; carbon; low carbon; travel ... See more keywords
Urban residents' response to and evaluation of low-carbon travel policies: Evidence from a survey of five eastern cities in China.
Sign Up to like & getrecommendations! Published in 2018 at "Journal of environmental management"
DOI: 10.1016/j.jenvman.2018.03.091
Abstract: To address the problems of excessive energy consumption and global climate change, the Chinese government has issued numerous policies to guide urban residents' low-carbon travel behavior. To evaluate the validity of these policies from the… read more here.
Keywords: response; low carbon; urban residents; response evaluation ... See more keywords
EFFECTS OF LAND USE FEATURES IN BLOCKS ON THE SELECTION OF LOW-CARBON TRAVEL BY URBAN RESIDENTS
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DOI: 10.15666/aeer/1704_93779389
Abstract: This paper attempts to disclose the effects of land use pattern on the selection of low-carbon travel by urban residents. Targeting 19 blocks in north western China’s Xi’an, the author collected data from various sources,… read more here.
Keywords: use features; use; low carbon; carbon travel ... See more keywords