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Digital elevation model: Applications & Products
A digital elevation model (DEM) or digital surface model (DSM) is a 3D computer graphics representation of elevation data to represent terrain or overlaying objects, commonly of a planet, moon, or asteroid. A "global DEM" refers to a discrete global grid. DEMs are used often in geographic information systems (GIS), and are the most common basis for…
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Digital elevation model topic overview
The analysis highlights Applications and Products as prominent areas in the source structure around Digital elevation model.
Related topics
102
Source areas
6
Connected nodes
125
Extracted relationships
90
Concept neighborhoods
34
Bridge connections
125
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Production · 37 topics
Uses · 28 topics
Overview · 15 topics
Types · 11 topics
Terminology · 7 topics
DEM file formats · 4 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How Digital elevation model connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around Digital elevation model shows recurring relationship patterns in the source. For example, Digital elevation model → Applications, Archived, ASTER GDEM2, ASTER-GDEM, Australia, Australian Journal, Australian National Gravity Database, Bibcode, Chapter, Comparison, Earth Sciences, Featherstone, Filmer, Gallant, GEODATA DEM-9S, Hirt, In Wilson, ISBN, June, New York Another extracted example is Digital elevation model → Advanced Spaceborne Thermal Emission, ASTER, Cosmo SkyMed, Earth Observation Satellite, ERS, European Remote-Sensing Satellite, HRS, Later, One, Other, RADARSAT-1, Reflection Radiometer, SAR, Shuttle Radar Topography Mission, SPOT5, SRTM, Terra, TerraSAR-X, The SPOT, VNIR. Use these groups to spot repeated connection types before inspecting the individual relationships.
Digital elevation model
Top relations
related to Further reading· 31
Digital elevation model → Applications, Archived, ASTER GDEM2, ASTER-GDEM, Australia, Australian Journal, Australian National Gravity Database, Bibcode, Chapter, Comparison, Earth Sciences, Featherstone, Filmer, Gallant, GEODATA DEM-9S, Hirt, In Wilson, ISBN, June, New York
related to Satellite mapping· 20
Digital elevation model → Advanced Spaceborne Thermal Emission, ASTER, Cosmo SkyMed, Earth Observation Satellite, ERS, European Remote-Sensing Satellite, HRS, Later, One, Other, RADARSAT-1, Reflection Radiometer, SAR, Shuttle Radar Topography Mission, SPOT5, SRTM, Terra, TerraSAR-X, The SPOT, VNIR
related to Terminology· 17
Digital elevation model → ASTER GDEM, CGIAR, DEM, DSM, DSMs, DTM, DTMs, ERSDAC, In, Most, Other, Some, Spot Image, SRTM, There, TIN, USGS
related to Production· 7
Digital elevation model → DEM, DEMs, GPS, Mappers, Note, Older, This
related to Rendering· 6
Digital elevation model → DEM, In, Some, The, This, Visualizations
Important terminology
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
Digital elevation model relationships Subject–Predicate–Object triples
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 90 structured relationships around Digital elevation model. Examples in this analysis include SRTM or the ASTER GDEM are originally DSMs → instance of → Some datasets and photogrammetry → instance of → The DEM could be acquired through techniques. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
SRTM or the ASTER GDEM are originally DSMs
instance of
Some datasets
0.80
text
although in forested areas
instance of
Some datasets
0.80
text
SRTM reaches into the tree canopy giving readings somewhere between a DSM
instance of
Some datasets
0.80
text
a DTM
instance of
Some datasets
0.80
text
photogrammetry
instance of
The DEM could be acquired through techniques
0.80
text
lidar
instance of
The DEM could be acquired through techniques
0.80
text
IfSAR or InSAR
instance of
The DEM could be acquired through techniques
0.80
text
land surveying
instance of
The DEM could be acquired through techniques
0.80
text
etc
instance of
The DEM could be acquired through techniques
0.80
text
Digital elevation model
related to Further reading
Wilson
0.60
section
Digital elevation model
related to Further reading
Gallant
0.60
section
Digital elevation model
related to Further reading
Chapter
0.60
section
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around Digital elevation model bring nearby vocabulary together. In this analysis, examples include Model, Terrain and Elevation. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Digital elevation model
Model
Terrain
Elevation
Models
Surface
Data
Ground
Survey
Relief
Dtm
Dsm
May
digital elevation model
Global
Model
Terrain
Dtm
Elevation
Represents
Models
Surface
Data
Ground
Survey
Satellite
elevation
Satellite
Terrain
Using
Srtm
Model
Models
Global
Quality
Maps
Radar
Used
Resolution
discrete global grid
Model
Terrain
Mission
Meters
Resolution
Free
Relief
Topography
Dtm
Satellite
Available
Grid
digital image correlation
Model
Terrain
Elevation
Models
Surface
Data
Ground
Survey
Dtm
Dsm
May
Dems
global relief model
Global
Model
Terrain
Dtm
Maps
Represents
Surface
Ground
Mission
Relief
Resolution
Topography
mars global surveyor
Model
Terrain
Mission
Resolution
Free
Relief
Topography
Dtm
Satellite
Available
Grid
Also
usgs dem
Model
Elevation
Global
Also
Data
Satellite
Grid
Quality
Dsm
Digital
Used
Surface
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For Digital elevation model, one of the stronger structural bridges in this analysis connects Digital elevation model with Production. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Min side: 3
Digital elevation model — Production· splits 88 ⟂ 38Digital elevation model — Uses· splits 97 ⟂ 29Digital elevation model — Sources· splits 109 ⟂ 17Digital elevation model — Overview· splits 110 ⟂ 16Digital elevation model — Types· splits 114 ⟂ 12Digital elevation model — Terminology· splits 118 ⟂ 8Digital elevation model — DEM file formats· splits 121 ⟂ 5
Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Digital elevation model
Nodes126
Edges125
Triples90
Avg. degree1.98
Density0.015873
Components1
Source & methodology
TTTA analyzes the structure around Digital elevation model to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Applications & Products, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
