Comparability and subjectivity of land cover maps produced with digital image classification techniques
Some recent experiences from Denmark and northern Germany
Bibliographic Data
| ID | 9849820 |
|---|---|
| Authors | Stefan Weiers (a German Aerospace Centre (DLR) , Linder Höhe, D-51147 , Köln , Germany, corresponding author), Geoff Groom (b National Environmental Research Institute, Department of Landscape Ecology , Kalø, Grenåvej 12, DK-8410 , Rønde , Denmark E-mail), Geoffrey Brian Groom (0000-0003-3820-6621), Michael Wissen (c German Aerospace Centre (DLR) , Linder Höhe, D-51147 , Köln , Germany) |
| Year | 2002 |
| Volume | 102 |
| Issue | 1 |
| Pages | 59-77 |
| Publication date | 2002-01-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Geografisk Tidsskrift-Danish Journal of Geography (JOURNAL) |
| Journal identifiers | ISSN: 0016-7223 • E-ISSN: 1903-2471 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00167223.2002.10649466 |
| OpenAlex | W2229800139 |
| Language | EN |
| References cited | 15 |
In many countries, including those of northwest Europe, there have been several decades of development work and application of satellite digital image data for the mapping of land cover. Considerable numbers of environmental and ecological projects and programmes now either use such land cover data or undertake such mapping for themselves, and the possibility to do land cover mapping from image data is increasingly appearing as a standard 'turn-key' component of GIS software. Into this context, this paper discusses issues related to this operationalisation of land cover mapping from image data. Specifically, it presents the methods and experiences of two recent land cover mapping projects, covering Denmark and parts of the German state of Schleswig-Holstein in terms of their comparability and their handling of subjecitive aspects of the mapping. These two independent but linked mapping exercises each developed and adopted specific operational procedures customised to their mapping objectives and their geographical contexts. Their methods and results reflect upon the needs to handle within statistical image analysis techniques such as supervised maximum likelihood classification subjective 'real-world' elements in as objective a way as possible
Biology · Cartography · Comparability · Cover (algebra · Epistemology · Geography · Land cover · Land use · Physical geography · Remote sensing · Subjectivity · Ecology · Engineering · Geographic Information Systems Studies · Land Use and Ecosystem Services · Mathematics · Philosophy · Remote Sensing in Agriculture
| Highly cited | No |
|---|