Trends and concerns in digital cartography

CISRG discussion paper ;

Deep learning methods applied to digital elevation models: state of the art

Deep Learning (DL) has a wide variety of applications in various thematic domains, including spatial information. Although with limitations, it is also starting to be considered in operations related to Digital Elevation Models (DEMs). This study aims to review the methods of DL applied in the field of altimetric spatial information in general, and DEMs in particular. Void Filling (VF), Super-Resolution (SR), landform classification and hydrography extraction are just some of the operations where traditional methods are being replaced by DL methods. Our review concludes that although these methods have great potential, there are aspects that need to be improved. More appropriate terrain information or algorithm parameterisation are some of the challenges that this methodology still needs to face.Functional Quality of Digital Elevation Models in Engineering’ of the State Agency Research of SpainPID2019-106195RB- I00/AEI/10.13039/50110001103

Exploring object-oriented GIS for watershed resource management

The adoption of object-oriented programming for spatial technological advancement is an emerging trend in GIS. This research seeks to explore Object-Oriented GIS (OOGIS) and its potential application in watershed resource management. OOGIS provides a more intuitive and realistic abstraction of real world features as intelligent objects. The ability to embed behavior, geometry, and attribution with the objects provides considerable advantages in the processing and analysis of geospatial data. The main objective of this research was to design a prototype OOGIS for watershed resource management using the object relational Arclnfo 8.1 Geodatabase. The study builds on the OOGIS concepts of inheritance, polymorphism, and encapsulation and defines a schema for the project. Behavior is embedded in the watershed features through the use of methods and reflex methods that automatically perform functions such as data validation and text placement. Message propagation is tested using related objects, and a smart object-based topologically integrated geometric network is established for streams and roads. Because of the embedded topological relationships and methods this network is self-adapting. The resulting system indicates that OOGIS has many advantages over the more traditional entity-relationship model. The system provides a more intuitive representation of a watershed through the integration of intelligent behaviors and is particularly effective in addressing GIS maintenance issues at a database level through the use of reflex validation methods

Quality Assessment of Hydrogeomorphological Features Derived from Digital Terrain Models

Digital terrain models (DTM) provide a model for representing the continuous earth elevation surface that can contain errors introduced by the main phases of generation and modelling. Uncertainty of the model is rarely considered by users. Assessment of uncertainty require information on the nature, amount and spatial structure of the errors. DTMs of di®erent original resolution were compared in order to assess the quality of derived hydrological and morphological features. SRTM dataset with resolution of 100m, DEM dataset mosaic from various sources with a resolution of 60m and ASTER derived dataset with a resolution of 30m were used. The error propagation was modelled with a stochastic approach. The probabilistic distribution of extracted hydrological features was drawn considering the spatial structure of errors in the datasets. The features considered were stream network and watershed divides net. The distribution of the Strahler order of the features was studied. An analysis of the overall probability of features extracted from variously prepared datasets was carried in order to get information on where is the most probable stream network or watershed divides net.JRC.H.6-Spatial data infrastructure

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Enhanced Place Name Search Using Semantic Gazetteers

With the increased availability of geospatial data and efficient geo-referencing services, people are now more likely to engage in geospatial searches for information on the Web. Searching by address is supported by geocoding which converts an address to a geographic coordinate. Addresses are one form of geospatial referencing that are relatively well understood and easy for people to use, but place names are generally the most intuitive natural language expressions that people use for locations. This thesis presents an approach, for enhancing place name searches with a geo-ontology and a semantically enabled gazetteer. This approach investigates the extension of general spatial relationships to domain specific semantically rich concepts and spatial relationships. Hydrography is selected as the domain, and the thesis investigates the specification of semantic relationships between hydrographic features as functions of spatial relationships between their footprints. A Gazetteer Ontology (GazOntology) based on ISO Standards is developed to associate a feature with a Spatial Reference. The Spatial Reference can be a GeoIdentifier which is a text based representation of a feature usually a place name or zip code or the spatial reference can be a Geometry representation which is a spatial footprint of the feature. A Hydrological Features Ontology (HydroOntology) is developed to model canonical forms of hydrological features and their hydrological relationships. The classes modelled are endurant classes modelled in foundational ontologies such as DOLCE. Semantics of these relationships in a hydrological context are specified in a HydroOntology. The HydroOntology and GazOntology can be viewed as the semantic schema for the HydroGazetteer. The HydroGazetteer was developed as an RDF triplestore and populated with instances of named hydrographic features from the National Hydrography Dataset (NHD) for several watersheds in the state of Maine. In order to determine what instances of surface hydrology features participate in the specified semantic relationships, information was obtained through spatial analysis of the National Hydrography Dataset (NHD), the NHDPlus data set and the Geographic Names Information System (GNIS). The 9 intersection model between point, line, directed line, and region geometries which identifies sets of relationship between geometries independent of what these geometries represent in the world provided the basis for identifying semantic relationships between the canonical hydrographic feature types. The developed ontologies enable the HydroGazetteer to answer different categories of queries, namely place name queries involving the taxonomy of feature types, queries on relations between named places, and place name queries with reasoning. A simple user interface to select a hydrological relationship and a hydrological feature name was developed and the results are displayed on a USGS topographic base map. The approach demonstrates that spatial semantics can provide effective query disambiguation and more targeted spatial queries between named places based on relationships such as upstream, downstream, or flows through

Automatic Geospatial Data Conflation Using Semantic Web Technologies

Duplicate geospatial data collections and maintenance are an extensive problem across Australia government organisations. This research examines how Semantic Web technologies can be used to automate the geospatial data conflation process. The research presents a new approach where generation of OWL ontologies based on output data models and presenting geospatial data as RDF triples serve as the basis for the solution and SWRL rules serve as the core to automate the geospatial data conflation processes

Evaluating the suitability of multi-scale terrain attribute calculation approaches for seabed mapping applications

The scale dependence of benthic terrain attributes is well-accepted, and multi-scale methods are increasingly applied for benthic habitat mapping. There are, however, multiple ways to calculate terrain attributes at multiple scales, and the suitability of these approaches depends on the purpose of the analysis and data characteristics. There are currently few guidelines establishing the appropriateness of multi-scale raster calculation approaches for specific benthic habitat mapping applications. First, we identify three common purposes for calculating terrain attributes at multiple scales for benthic habitat mapping: (i) characterizing scale-specific terrain features, (ii) reducing data artefacts and errors, and (iii) reducing the mischaracterization of ground-truth data due to inaccurate sample positioning. We then define criteria that calculation approaches should fulfill to address these purposes. At two study sites, five raster terrain attributes, including measures of orientation, relative position, terrain variability, slope, and rugosity were calculated at multiple scales using four approaches to compare the suitability of the approaches for these three purposes. Results suggested that specific calculation approaches were better suited to certain tasks. A transferable parameter, termed the ‘analysis distance’, was necessary to compare attributes calculated using different approaches, and we emphasize the utility of such a parameter for facilitating the generalized comparison of terrain attributes across methods, sites, and scales