Access routes to high mountain huts facing climate-induced environmental changes and adaptive strategies in the Western Alps since the 1990s     

Jacques Mourey  Ludovic Ravanel  Christophe Lambiel  Joël Strecker  Mattia Piccardi 《Norsk geografisk tidsskrift. Norwegian journal of geography》2019,73(4):215-228

ABSTRACT

In the European Alps, high mountain environments are subject to major impacts resulting from climate change, which strongly affect human activities such as mountaineering. The purpose of the study was to examine changes in access routes to 30 high mountain huts in the Western Alps since the 1990s. Data were derived from the use of two different methods, geo-historical studies and a questionnaire, and were used to identify both the climate-related processes affecting the climbing routes and the strategies implemented by public entities, Alpine clubs, guide companies, and hut keepers to maintain acceptable safety and technical conditions. The case studies revealed issues affecting three access routes and the results from the questionnaire showed that the main processes affecting access routes were loss of ice thickness and retreat from the front of the glaciated areas. Commonly, in situ equipment was installed to facilitate access for mountaineers and/or a part of a route was relocated to a safer area. The authors conclude that in most cases, the measures were effective but they were limited by financial, ethical and legal issues, especially in protected or classified areas that could jeopardise their durability and effectiveness.  相似文献   

Alexander Dodge. 2020. Reassembling Liquefied Natural Gas Production Networks     

Gavin Bridge  Håvard Haarstad 《Norsk geografisk tidsskrift. Norwegian journal of geography》2020,74(2):126-127

  相似文献   

Identifying primary public transit corridors using multi-source big transit data     

Tong Zhang  Yicong Li  Hui Yang  Chenrong Cui  Jing Li  Qinghua Qiao 《International journal of geographical information science》2020,34(6):1137-1161

ABSTRACT

Effective public transit planning needs to address realistic travel demands, which can be illustrated by corridors across major residential areas and activity centers. It is vital to identify public transit corridors that contain the most significant transit travel demand patterns. We propose a two-stage approach to discover primary public transit corridors at high spatio-temporal resolutions using massive real-world smart card and bus trajectory data, which manifest rich transit demand patterns over space and time. The first stage was to reconstruct chained trips for individual passengers using multi-source massive public transit data. In the second stage, a shared-flow clustering algorithm was developed to identify public transit corridors based on reconstructed individual transit trips. The proposed approach was evaluated using transit data collected in Shenzhen, China. Experimental results demonstrated that the proposed approach is a practical tool for extracting time-varying corridors for many potential applications, such as transit planning and management.  相似文献   

A land-use mix allocation model considering adjacency,intensity, and proximity     

Sunyong Eom  Tsutomu Suzuki  Myeong-Hun Lee 《International journal of geographical information science》2020,34(5):899-923

ABSTRACT

Land-Use Mix (LUM) refers to the strategy of integrating complementary functions within a building or area. While LUM has become a dominant approach in urban planning, its actual benefits and vision for spatial planning remain unclear. To clarify this issue, this study discerns the spatial features of land-use patterns depending on the compatibilities among land-use categories. Accordingly, this study introduces three LUM measures – adjacency, intensity, and proximity – to identify differences in the spatial distribution of land-use categories. Based on these measures, a land-use allocation model is developed to specify spatial patterns satisfying the given compatibilities. This model is tested by applying the concept of the neighborhood unit on a case study of normative land-use patterns subject to specified compatibilities. The results describe spatial features of four compatibility sets, including a set exhibiting a compatibility conflict between the same land-use pair and LUM measures when, for example, a given land-use pair is compatible in terms of intensity but incompatible in terms of proximity. Understanding the spatial features of a normative land-use pattern that satisfies various possible compatibilities will facilitate the incorporation of the LUM approach into local planning guidance and zoning ordinances.  相似文献   

Pedestrian network generation based on crowdsourced tracking data     

Xue Yang  Chang Ren  Yang Chen  Zhong Xie  Qingquan Li 《International journal of geographical information science》2020,34(5):1051-1074

ABSTRACT

Pedestrian networks play an important role in various applications, such as pedestrian navigation services and mobility modeling. This paper presents a novel method to extract pedestrian networks from crowdsourced tracking data based on a two-layer framework. This framework includes a walking pattern classification layer and a pedestrian network generation layer. In the first layer, we propose a multi-scale fractal dimension (MFD) algorithm in order to recognize the two different types of walking patterns: walking with a clear destination (WCD) or walking without a clear destination (WOCD). In the second layer, we generate the pedestrian network by combining the pedestrian regions and pedestrian paths. The pedestrian regions are extracted based on a modified connected component analysis (CCA) algorithm from the WOCD traces. We generate the pedestrian paths using a kernel density estimation (KDE)-based point clustering algorithm from the WCD traces. The pedestrian network generation results using two actual crowdsourced datasets show that the proposed method has good performance in both geometrical correctness and topological correctness.  相似文献   

Australian ‘gayborhoods’ and ‘lesborhoods’: a new method for estimating the number and prevalence of adult gay men and lesbian women living in each Australian postcode     

Denton Callander  Julie Mooney-Somers  Phillip Keen  Rebecca Guy  Tim Duck  Benjamin R. Bavinton 《International journal of geographical information science》2020,34(11):2160-2176

ABSTRACT

Gay men and lesbian women often demonstrate unique settlement patterns, forming what have been referred to as ‘gayborhoods’. This study sought to provide the first postcode-level estimates of population size and prevalence of gay and lesbian people in Australia. Data on same-gender-partnered households from the Australian Census were combined with information from six different surveys conducted from 2011 to 2017. We estimated that in 2016 there were 132,203 gay men (1.5% of adult males; 95% CI: 1.4–1.6) and 79,931 lesbian women (0.9% of adult females; 95% CI: 0.8–1.0) in Australia. While many postcodes were sparsely populated by gay and lesbian people (40.1% had prevalences of <0.1%), 24.6% were moderately populated (prevalences in the 50-95th percentile) and 2.7% were highly populated (95th percentile). By jurisdiction, the Australian Capital Territory had the highest prevalences of gay men (2.1%; 95% CI: 2.0–2.2) and lesbian women (1.5%; 95% CI: 1.4–1.6). Although the majority of highly populated postcodes were found in major cities (83.7%), some were also found in regional and remote area (16.3%). This method can be applied in other countries to enhance populate estimates. The accompanying dataset can be used to guide service delivery, conduct geographically contextualised research and develop policies relevant to gay men and lesbian women in Australia.  相似文献   

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing     

Peng Yue  Fan Gao  Boyi Shangguan  Zheren Yan 《International journal of geographical information science》2020,34(11):2243-2274

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.  相似文献   

A comparison of neighbourhood relations based on ordinary Delaunay diagrams and area Delaunay diagrams: an application to define the neighbourhood relations of buildings     

Hiroyuki Usui  Akihiro Teraki  Kei-ichi Okunuki  Toshiaki Satoh 《International journal of geographical information science》2020,34(11):2177-2203

ABSTRACT

The aim of this article is to describe a convenient but robust method for defining neighbourhood relations among buildings based on ordinary Delaunay diagrams (ODDs) and area Delaunay diagrams (ADDs). ODDs and ADDs are defined as a set of edges connecting the generators of adjacent ordinary Voronoi cells (points representing centroids of building polygons) and a set of edges connecting two centroids of building polygons, which are the generators of adjacent area Voronoi cells, respectively. Although ADDs are more robust than ODDs, computation time of ODDs is shorter than that of ADDs (the order of their computation time complexity is O(nlogn)). If ODDs can approximate ADDs with a certain degree of accuracy, the former can be used as an alternative. Therefore, we computed the ratio of the number of ADD edges to that of ODD edges overlapping ADDs at building and regional scales. The results indicate that: (1) for approximately 60% of all buildings, ODDs can exactly overlap ADDs with extra ODD edges; (2) at a regional scale, ODDs can overlap approximately 90% of ADDs with 10% extra ODD edges; and (3) focusing on judging errors, although ADDs are more accurate than ODDs, the difference is only approximately 1%.  相似文献   

A hybrid integrated deep learning model for the prediction of citywide spatio-temporal flow volumes     

Yibin Ren  Huanfa Chen  Tao Cheng  Yang Zhang  Ge Chen 《International journal of geographical information science》2020,34(4):802-823

ABSTRACT

The spatio-temporal residual network (ST-ResNet) leverages the power of deep learning (DL) for predicting the volume of citywide spatio-temporal flows. However, this model, neglects the dynamic dependency of the input flows in the temporal dimension, which affects what spatio-temporal features may be captured in the result. This study introduces a long short-term memory (LSTM) neural network into the ST-ResNet to form a hybrid integrated-DL model to predict the volumes of citywide spatio-temporal flows (called HIDLST). The new model can dynamically learn the temporal dependency among flows via the feedback connection in the LSTM to improve accurate captures of spatio-temporal features in the flows. We test the HIDLST model by predicting the volumes of citywide taxi flows in Beijing, China. We tune the hyperparameters of the HIDLST model to optimize the prediction accuracy. A comparative study shows that the proposed model consistently outperforms ST-ResNet and several other typical DL-based models on prediction accuracy. Furthermore, we discuss the distribution of prediction errors and the contributions of the different spatio-temporal patterns.  相似文献   

Detecting regional dominant movement patterns in trajectory data with a convolutional neural network     

Can Yang  Győző Gidófalvi 《International journal of geographical information science》2020,34(5):996-1021

  相似文献