| Titre | Classification of remotely sensed imagery for surficial geological mapping in Canada's North |
| Auteur | Harris, J; Grunsky, E; McMartin, I |
| Source | First Break vol. 25, 2007 p. 85-95 |
| Liens | Online - En ligne
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| Image |  |
| Année | 2007 |
| Séries alt. | Commission géologique du Canada, Contributions aux publications extérieures 20070170 |
| Document | publication en série |
| Lang. | anglais |
| Media | papier |
| Formats | pdf (Adobe® Reader®) |
| Province | Nunavut |
| SNRC | 66A |
| Région | Schultz Lake; Thelon River |
| Lat/Long OENS | -98.0000 -96.0000 65.0000 64.0000 |
| Sujets | télédétection; imagerie par satellite; techniques de cartographie; cartographie par ordinateur; imagerie radar; modélisation numérique de terrain; interprétation de photos aériennes; travaux de
prospection; analyses statistiques; géologie du substratum rocheux; Archéen; dépôts postglaciaires; dépôts glaciaires; sables; graviers; dépôts organiques; tills; blocs; classification; géologie des dépôts meubles/géomorphologie; Phanérozoïque;
Cénozoïque; Quaternaire; Précambrien; Protérozoïque |
| Illustrations | croquis cartographiques; modèles altimétriques numériques; images satellitaires; tableaux; graphiques |
| Programme | La mise en valeur des ressources du Nord |
| Résumé | (Sommaire disponible en anglais seulement)
Mapping in the North is an expensive proposition due to remoteness, lack of infrastructure, logistical problems and the generally short mapping season.
Remotely sensed data offers a useful source of information to the mapping geologist for not only updating existing geological maps but as a first order source of geological information in areas that have not been well-mapped. Needless to say areas
that have not been mapped in detail comprise many areas of Canada's North.
This paper focuses on the use of remotely sensed data (RADARSAT, LANDSAT) in conjunction with a digital elevation model (DEM) data for producing predictive
(classifications) maps of surficial units in the Shultz Lake area (NTS 66A), Nunavut and is based on work by Grunsky (2002) and Grunsky et al. (2006). A computer-assisted approach is employed which involves identifying representative areas on air
photos (supported by field work) of various surficial units, collecting signatures of these "training areas" from the remotely sensed imagery and then identifying similar areas on the imagery using a maximum likelihood classification algorithm. The
methodology for producing predictive maps of surficial units presented in this paper can be used in other Northern environments. |
| GEOSCAN ID | 224138 |
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