Dasymetric Algorithms Using Land Cover to Estimate Human Population at Smaller Spatial Scales
Bibliographic Data
| ID | 22032812 |
|---|---|
| Authors | Ida Maria Bonnevie (0000-0003-1085-6331, Aalborg University, corresponding author), Henning Sten Hansen (0000-0001-7004-0698, Aalborg University), Lise Schrøder (0000-0001-5362-7593, Aalborg University) |
| Year | 2024 |
| Volume | 13 |
| Issue | 12 |
| Pages | 427 |
| Publication date | 2024-11-29 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi13120427 |
| OpenAlex | W4404859683 |
| Language | EN |
| Citations received | 2 |
| References cited | 26 |
Data repositories such as Eurostat and OECD provide important socioeconomic datasets useful to guide decision support towards reaching sustainable development goals. However, socioeconomic data are typically available at a limited spatiotemporal scale. In the Horizon Europe-funded AquaINFRA project, a specific scope is to make EU data more analysis ready. As part of this, transformations of data into common spatial entities are needed to facilitate cross-analysis in, for example, social-ecological modelling. This paper uses CORINE land cover as ancillary data and EUROSTAT population data to investigate binary and weighted dasymetric refinement strategies to arrive at areal interpolation algorithms to estimate population data at smaller spatial scales. Six different algorithms are presented, and their accuracies are tested with quality measures. Their limitations and further development potentials on how to make them more precise and expand their usefulness in the future to other types of socioeconomic data are discussed
Ancillary data · Cartography · Data mining · Data science · Geography · Land cover · Land use · Population · Remote sensing · Computer Science · Human Mobility and Location-Based Analysis · Impact of Light on Environment and Health · Land Use and Ecosystem Services · Artificial Intelligence · Ecology
The spatial allocation of population
The Fair Guiding Principles for scientific data management and stewardship
Improved Population Mapping for China Using the 3D Building, Nighttime Light, Points-of-Interest, and Land Use/Cover Data within a Multiscale Geographically Weighted Regression Model
Random Forest Variable Importance Measures for Spatial Dynamics
An ANN-based method for population Dasymetric mapping to avoid the scale heterogeneity
Mapping regional economic activity from night-time light satellite imagery
Dasymetric Mapping and Areal Interpolation
Analysing spatiotemporal patterns of tourism in Europe at high-resolution with conventional and big data sources
Spatial Regression Models for Demographic Analysis
A Method of Mapping Densities of Population
| Unique citing works | 2 |
|---|---|
| Citations per year | 2 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |