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ISPRS International Journal of Geo-Information, Volume 11, Issue 6

June 2022 - 33 articles

Cover Story: Geospatial data analysis often requires computing a distance transform (DT) for a given vector feature. Computing a DT on traditional geographic information systems (GIS) is usually based on image processing methods, which are prone to distortion resulting from flat maps. Discrete global grid systems (DGGS) are relatively new low-distortion globe-based GIS that discretize the Earth into highly regular cells. In this paper, we introduce an efficient DT algorithm for DGGS that exploits the hierarchy of a DGGS and its mathematical properties. We demonstrate that our method is efficient and has minimal distortion by comparing its speed and distortion with the DT methods used in traditional GIS and general 3D meshes. View this paper
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Articles (33)

  • Article
  • Open Access
25 Citations
6,375 Views
16 Pages

Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms

  • Usman Ali,
  • Travis J. Esau,
  • Aitazaz A. Farooque,
  • Qamar U. Zaman,
  • Farhat Abbas and
  • Mathieu F. Bilodeau

Land use and land cover (LULC) classification maps help understand the state and trends of agricultural production and provide insights for applications in environmental monitoring. One of the major downfalls of the LULC technique is inherently linke...

  • Article
  • Open Access
14 Citations
3,700 Views
14 Pages

Recognizing building group patterns is fundamental to numerous fields, such as urban landscape evaluation, social analysis, and map generalization. Despite the increasing number of algorithms available for building group pattern recognition, there is...

  • Article
  • Open Access
5 Citations
2,657 Views
17 Pages

Residential areas is one of the basic geographical elements on the map and an important content of the map representation. Multi-scale residential areas matching refers to the process of identifying and associating entities with the same name in diff...

  • Article
  • Open Access
13 Citations
3,369 Views
18 Pages

In urban environmental management and public health evaluation efforts, there is an urgent need for fine-grained urban air quality monitoring. However, the high price and sparse distribution of air quality monitoring equipment make it difficult to de...

  • Article
  • Open Access
15 Citations
5,837 Views
17 Pages

Understanding organism movement is at the heart of many ecological disciplines. The study of landscape connectivity—the extent to which a landscape facilitates organism movement—has grown to become a central focus of spatial ecology and c...

  • Article
  • Open Access
24 Citations
4,200 Views
17 Pages

The evaluation of ecological risk and the construction of ecological security patterns are significant for the conservation of World Natural Heritage sites with high outstanding universal value. This paper constructed a landscape ecological risk eval...

  • Article
  • Open Access
8 Citations
3,313 Views
17 Pages

Improving LST Downscaling Quality on Regional and Field-Scale by Parameterizing the DisTrad Method

  • Taha I. M. Ibrahim,
  • Sadiq Al-Maliki,
  • Omar Salameh,
  • István Waltner and
  • Zoltán Vekerdy

Many scientists have been investigating Land Surface Temperature (LST) because of its relevance in water management science due to its direct influence on the hydrological water cycle. This effect stems from being one of the most significant variable...

  • Article
  • Open Access
8 Citations
4,262 Views
22 Pages

Accurate extraction of urban landscape features in the historic district of China is an essential task for the protection of the cultural and historical heritage. In recent years, deep learning (DL)-based methods have made substantial progress in lan...

  • Article
  • Open Access
21 Citations
4,107 Views
24 Pages

Streets are an important component of urban landscapes and reflect the image, quality of life, and vitality of public spaces. With the help of the Google Cityscapes urban dataset and the DeepLab-v3 deep learning model, we segmented panoramic images t...

  • Article
  • Open Access
27 Citations
7,936 Views
23 Pages

Landslide Susceptibility Mapping Using Machine Learning: A Danish Case Study

  • Angelina Ageenko,
  • Lærke Christina Hansen,
  • Kevin Lundholm Lyng,
  • Lars Bodum and
  • Jamal Jokar Arsanjani

Mapping of landslides, conducted in 2021 by the Geological Survey of Denmark and Greenland (GEUS), revealed 3202 landslides in Denmark, indicating that they might pose a bigger problem than previously acknowledged. Moreover, the changing climate is a...

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ISPRS Int. J. Geo-Inf. - ISSN 2220-9964