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ISPRS International Journal of Geo-Information, Volume 11, Issue 7

July 2022 - 61 articles

Cover Story: Gridded population datasets (e.g., GHS-POP) show substantial variations in error rates depending on the geographic context. In general, cities in High-Income (HIC) and Upper-Middle-Income Countries (UMIC) have fewer model errors as compared to cities in Low- and Middle-Income Countries (LMIC). According to the global average, 75% of all urban spaces are wrongly estimated. The spatial patterns of errors (i.e., REE) show that in central mixed or non-residential areas, the population is overestimated, while in high-density residential areas (e.g., informal areas or high-rise built-up areas), the population is underestimated. Moreover, high model uncertainties exist in low-density or sparsely populated outskirts of cities. View this paper
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Articles (61)

  • Article
  • Open Access
13 Citations
3,075 Views
21 Pages

Achieving Differential Privacy Publishing of Location-Based Statistical Data Using Grid Clustering

  • Yan Yan,
  • Zichao Sun,
  • Adnan Mahmood,
  • Fei Xu,
  • Zhuoyue Dong and
  • Quan Z. Sheng

Statistical partitioning and publishing is commonly used in location-based big data services to address queries such as the number of points of interest, available vehicles, traffic flows, infected patients, etc., within a certain range. Adding noise...

  • Article
  • Open Access
29 Citations
5,268 Views
18 Pages

The Missing Millions in Maps: Exploring Causes of Uncertainties in Global Gridded Population Datasets

  • Monika Kuffer,
  • Maxwell Owusu,
  • Lorraine Oliveira,
  • Richard Sliuzas and
  • Frank van Rijn

Gridded population datasets model the population at a relatively high spatial and temporal granularity by reallocating official population data from irregular administrative units to regular grids (e.g., 1 km grid cells). Such population data are vit...

  • Article
  • Open Access
1 Citations
2,199 Views
25 Pages

The geometric features of ground objects can reflect the shape, contour, length, width, and pixel distribution of ground objects and have important applications in the process of object detection and recognition. However, the geometric features of ob...

  • Article
  • Open Access
39 Citations
5,593 Views
23 Pages

Hybrid Machine Learning Approach for Gully Erosion Mapping Susceptibility at a Watershed Scale

  • Sliman Hitouri,
  • Antonietta Varasano,
  • Meriame Mohajane,
  • Safae Ijlil,
  • Narjisse Essahlaoui,
  • Sk Ajim Ali,
  • Ali Essahlaoui,
  • Quoc Bao Pham,
  • Mirza Waleed and
  • Sasi Kiran Palateerdham
  • + 1 author

Gully erosion is a serious threat to the state of ecosystems all around the world. As a result, safeguarding the soil for our own benefit and from our own actions is a must for guaranteeing the long-term viability of a variety of ecosystem services....

  • Article
  • Open Access
35 Citations
9,166 Views
18 Pages

Crime Prediction and Monitoring in Porto, Portugal, Using Machine Learning, Spatial and Text Analytics

  • Miguel Saraiva,
  • Irina Matijošaitienė,
  • Saloni Mishra and
  • Ana Amante

Crimes are a common societal concern impacting quality of life and economic growth. Despite the global decrease in crime statistics, specific types of crime and feelings of insecurity, have often increased, leading safety and security agencies with t...

  • Article
  • Open Access
10 Citations
7,497 Views
14 Pages

Posyandu Application for Monitoring Children Under-Five: A 3-Year Data Quality Map in Indonesia

  • Fedri Ruluwedrata Rinawan,
  • Afina Faza,
  • Ari Indra Susanti,
  • Wanda Gusdya Purnama,
  • Noormarina Indraswari,
  • Didah,
  • Dani Ferdian,
  • Siti Nur Fatimah,
  • Ayi Purbasari and
  • Arief Zulianto
  • + 4 authors

Posyandu is an Indonesian mother-child health, community-based healthcare. The provision of the Posyandu data quality map is crucial for analyzing results but is limited. This research aimed to (a) demonstrate data quality analysis on its completenes...

  • Article
  • Open Access
18 Citations
3,231 Views
20 Pages

Landslide susceptibility prediction has the disadvantages of being challenging to apply to expanding landslide samples and the low accuracy of a subjective random selection of non-landslide samples. Taking Fu’an City, Fujian Province, as an exa...

  • Article
  • Open Access
1 Citations
2,998 Views
35 Pages

Extracting Human Activity Areas from Large-Scale Spatial Data with Varying Densities

  • Xiaoqi Shen,
  • Wenzhong Shi,
  • Zhewei Liu,
  • Anshu Zhang,
  • Lukang Wang and
  • Fanxin Zeng

Human activity area extraction, a popular research topic, refers to mining meaningful location clusters from raw activity data. However, varying densities of large-scale spatial data create a challenge for existing extraction methods. This research p...

  • Article
  • Open Access
10 Citations
5,010 Views
27 Pages

As a regional management unit to solve "urban diseases,” metropolitan areas are gradually attracting widespread attention. How to objectively and accurately delineate the boundaries of a metropolitan area is the primary prerequisite for carryin...

  • Article
  • Open Access
4 Citations
3,934 Views
19 Pages

Terrain Segmentation Using a U-Net for Improved Relief Shading

  • Marianna Farmakis-Serebryakova,
  • Magnus Heitzler and
  • Lorenz Hurni

Since landforms composing land surface vary in their properties and appearance, their shaded reliefs also present different visual impression of the terrain. In this work, we adapt a U-Net so that it can recognize a selection of landforms and can seg...

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