Abstract
Besides OpenStreetMap (OSM), there are other local sources, such as open government data (OGD), that have the potential to enrich the modeling process with decision criteria that uniquely reflect some local patterns. However, both data are affected by uncertainty issues, which limits their usability. This work addresses the imprecisions on suitability layers generated from such data. The proposed method is founded on fuzzy logic theories. The model integrates OGD, OSM data and remote sensing products and generate reliable landfill suitability results. A comparison analysis demonstrates that the proposed method generates more accurate, representative and reliable suitability results than traditional methods. Furthermore, the method has facilitated the introduction of open government data for suitability studies, whose fusion improved estimations of population distribution and land-use mapping than solely relying on free remotely sensed images. The proposed method is applicable for preparing decision maps from open datasets that have undergone similar generalization procedures as the source of their uncertainty. The study provides evidence for the applicability of OGD and other related open data initiatives (ODIs) for land-use suitability studies, especially in developing countries.
Highlights
A major bottleneck of suitability studies is the availability of data suitable to generate representative and sufficient criteria that satisfy the area’s local characteristics under investigation
Various open government data contain points of interest (POI), which offer a useful reflection of the spatial distribution, spatial pattern, and categories of infrastructures, which are an important source of suitability indicators
To account for the uncertainty in feature boundaries, we propose the addition of modifiers such as “very” and “somewhat” to arrive at a more accurate representation of the scenarios
Summary
A major bottleneck of suitability studies is the availability of data suitable to generate representative and sufficient criteria that satisfy the area’s local characteristics under investigation. The urge to explore various open data sources to capture local characteristics has prompted a more in-depth exploration of two available data sources—Open Street Map (OSM) and open government data (OGD). OSM is one of the prominent free Volunteered geographic information (VGI) data sources common in developing countries. Government Data (GD) is another precious resource whose potential is yet to be explored for suitability studies, especially in developing countries. Various open government data contain points of interest (POI), which offer a useful reflection of the spatial distribution, spatial pattern, and categories of infrastructures, which are an important source of suitability indicators. The uniqueness of POIs is that a single POI may contain much information compared to common points’ features of an ordinary map or point data. Each of the data sources has its related challenges
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