Despite its tiny territory,Macao boasts a large volume of tourist activities,which serves as the pillar of its economy.Environment and natural resources are the cornerstone of tourism,but are also subject to the negat...Despite its tiny territory,Macao boasts a large volume of tourist activities,which serves as the pillar of its economy.Environment and natural resources are the cornerstone of tourism,but are also subject to the negative impact of tourism.Based on the theory and methodology of ecological footprint analysis,this paper calculated the touristic ecological footprint and deficit of Macao in 2009,in an effort to bring to light the current status of excessive consumption of resources by tourism.As the findings show,the non-transferable touristic ecological footprint and touristic ecological deficit of Macao in 2009 are respectively 18 300.891 gha and 12 737.584 gha,and the former is 3.29 times as large as the touristic ecological carrying capacity.Touristic ecological footprint of Macao is highly efficient in economic sense but currently tourism is developing in an unsustainable manner,so appropriate initiatives are in need to strike a balance between tourism development and resource conservation and to promote the sustainability of tourism industry of Macao.展开更多
To facilitate the travel preparation process to a city, a lot of work has been done to recommend a POI or a sequence of POIs automatically to satisfy users＇ needs. How- ever, most of the existing work ignores the iss...To facilitate the travel preparation process to a city, a lot of work has been done to recommend a POI or a sequence of POIs automatically to satisfy users＇ needs. How- ever, most of the existing work ignores the issue of planning the detailed travel routes between POIs, leaving the task to online map services or commercial GPS navigators. Such a service or navigator in terms of suggesting the shortest travel distance or time, which cannot meet the diverse requirements of users. For instance, in the case of traveling by driving for leisure purpose, the scenic view along the travel routes would be of great importance to users, and a good planning ser- vice should put the sceneries of the route in higher priority rather than the distance or time taken. To this end, in this paper, we propose a novel framework called ScenicPlanner for route recommendation, leveraging a combination of get- tagged image and check-in digital footprints from location- based social networks （LBSNs）. First, we enrich the road net- work and assign a proper scenic view score to each road seg- ment to model the scenic road network, by extracting relevant information from get-tagged images and check-ins. Then, we apply heuristic algorithms to iteratively add road segment and determine the travelling order of added road segments with the objective of maximizing the total scenic view score while satisfying the user-specified constraints （i.e., origin, desti- nation and the total travel distance）. Finally, to validate the efficiency and effectiveness of the proposed framework, we conduct extensive experiments on three real-world data sets from the Bay Area in the city of San Francisco, which con- tain a road network crawled from OpenStreetMap, more than 31 000 geo-tagged images generated by 1 571 Flickr users in one year, and 110 214 check-ins left by 15 680 Foursquare users in six months.展开更多
Mobile internet and wireless communication technologies have produced unprecedented location-aware data.Such big geospatial data can be used as a proxy measure of the‘digital footprints’left by us on the planet and ...Mobile internet and wireless communication technologies have produced unprecedented location-aware data.Such big geospatial data can be used as a proxy measure of the‘digital footprints’left by us on the planet and provide a valuable opportunity to understand the dynamic and short-term human disturbance on the nature at fine scales.This study investigated the spatiotemporal variations of human’s digital footprints on the Qinghai-Tibet Plateau using smartphone-users-generated Tencent’s location request data.The results showed that human’s digital footprints cover less than 5%of Qinghai and Tibet,exhibiting either a U-shaped or an N-shaped temporal change pattern during the major festivals.Spatial changes of the digital footprints manifested a transition process from dispersion to concentration in Xining and Lhasa.Human disturbance assessment of seven large nature reserves on the plateau showed that the Qinghai Lake is the most disturbed one as shown by 14.6%of its area is stained with human digital footprints and the areal average of footprint intensity is 1.59,and the disturbance was significantly escalated during the National Day holiday.By contrast,the Qangtang and Hoh Xil are the least affected nature reserves with the two indices less than 1%and 0.1,respectively.展开更多
文摘Despite its tiny territory,Macao boasts a large volume of tourist activities,which serves as the pillar of its economy.Environment and natural resources are the cornerstone of tourism,but are also subject to the negative impact of tourism.Based on the theory and methodology of ecological footprint analysis,this paper calculated the touristic ecological footprint and deficit of Macao in 2009,in an effort to bring to light the current status of excessive consumption of resources by tourism.As the findings show,the non-transferable touristic ecological footprint and touristic ecological deficit of Macao in 2009 are respectively 18 300.891 gha and 12 737.584 gha,and the former is 3.29 times as large as the touristic ecological carrying capacity.Touristic ecological footprint of Macao is highly efficient in economic sense but currently tourism is developing in an unsustainable manner,so appropriate initiatives are in need to strike a balance between tourism development and resource conservation and to promote the sustainability of tourism industry of Macao.
基金Chao Chen and Xia Chen contributed equally on this work. The work was partially supported by the National Natural Science Foundation of China （Grant Nos. 61602067, 61402369 and 61572048）, the Fundamental Research Funds for the Central Universities （106112015CD- JXY180001）, Open Research Fund Program of Shenzhen Key Laboratory of Spatial Smart Sensing and Services （Shenzhen University）, and Chongqing Basic and Frontier Research Program （cstc2015jcyjA00016）.
文摘To facilitate the travel preparation process to a city, a lot of work has been done to recommend a POI or a sequence of POIs automatically to satisfy users＇ needs. How- ever, most of the existing work ignores the issue of planning the detailed travel routes between POIs, leaving the task to online map services or commercial GPS navigators. Such a service or navigator in terms of suggesting the shortest travel distance or time, which cannot meet the diverse requirements of users. For instance, in the case of traveling by driving for leisure purpose, the scenic view along the travel routes would be of great importance to users, and a good planning ser- vice should put the sceneries of the route in higher priority rather than the distance or time taken. To this end, in this paper, we propose a novel framework called ScenicPlanner for route recommendation, leveraging a combination of get- tagged image and check-in digital footprints from location- based social networks （LBSNs）. First, we enrich the road net- work and assign a proper scenic view score to each road seg- ment to model the scenic road network, by extracting relevant information from get-tagged images and check-ins. Then, we apply heuristic algorithms to iteratively add road segment and determine the travelling order of added road segments with the objective of maximizing the total scenic view score while satisfying the user-specified constraints （i.e., origin, desti- nation and the total travel distance）. Finally, to validate the efficiency and effectiveness of the proposed framework, we conduct extensive experiments on three real-world data sets from the Bay Area in the city of San Francisco, which con- tain a road network crawled from OpenStreetMap, more than 31 000 geo-tagged images generated by 1 571 Flickr users in one year, and 110 214 check-ins left by 15 680 Foursquare users in six months.
基金Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20040401)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA19040501)+2 种基金National Key Research and Development Program of China(2017YFB0503605)National Key Research and Development Program of China(2017YFC1503003)National Natural Science Foundation of China(41901395)。
文摘Mobile internet and wireless communication technologies have produced unprecedented location-aware data.Such big geospatial data can be used as a proxy measure of the‘digital footprints’left by us on the planet and provide a valuable opportunity to understand the dynamic and short-term human disturbance on the nature at fine scales.This study investigated the spatiotemporal variations of human’s digital footprints on the Qinghai-Tibet Plateau using smartphone-users-generated Tencent’s location request data.The results showed that human’s digital footprints cover less than 5%of Qinghai and Tibet,exhibiting either a U-shaped or an N-shaped temporal change pattern during the major festivals.Spatial changes of the digital footprints manifested a transition process from dispersion to concentration in Xining and Lhasa.Human disturbance assessment of seven large nature reserves on the plateau showed that the Qinghai Lake is the most disturbed one as shown by 14.6%of its area is stained with human digital footprints and the areal average of footprint intensity is 1.59,and the disturbance was significantly escalated during the National Day holiday.By contrast,the Qangtang and Hoh Xil are the least affected nature reserves with the two indices less than 1%and 0.1,respectively.
