MOOSE HABITAT MAPPING IN CENTRAL NEWFOUNDLAND USING DIGITAL LANDSAT THEMATIC MAPPER DATA
Earth Resources Satellite sensors are increasingly used to provide rapid and current mapping of large areas for wildlife habitat analysis. In 1986 the Newfoundland and Labrador Wildlife Division undertook an experimental project to assess the feasibility of Landsat Thematic Mapper data to classify a...
Main Authors: | , , |
---|---|
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Lakehead University
1988
|
Subjects: | |
Online Access: | http://alcesjournal.org/index.php/alces/article/view/1271 |
id |
ftjalces:oai:ojs.pkp.sfu.ca:article/1271 |
---|---|
record_format |
openpolar |
spelling |
ftjalces:oai:ojs.pkp.sfu.ca:article/1271 2024-06-16T07:41:32+00:00 MOOSE HABITAT MAPPING IN CENTRAL NEWFOUNDLAND USING DIGITAL LANDSAT THEMATIC MAPPER DATA Oosenbrug, Sebastian M. Perrott, Timothy H. Butler, Charles E. 1988-01-01 application/pdf http://alcesjournal.org/index.php/alces/article/view/1271 eng eng Lakehead University http://alcesjournal.org/index.php/alces/article/view/1271/1343 http://alcesjournal.org/index.php/alces/article/view/1271 Alces: A Journal Devoted to the Biology and Management of Moose; Vol. 24 (1988): Alces Vol. 24 (1988); 167-177 2293-6629 0835-5851 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article 1988 ftjalces 2024-05-22T03:01:08Z Earth Resources Satellite sensors are increasingly used to provide rapid and current mapping of large areas for wildlife habitat analysis. In 1986 the Newfoundland and Labrador Wildlife Division undertook an experimental project to assess the feasibility of Landsat Thematic Mapper data to classify and inventory moose habitat. A TM digitized format was selected because of its superior 30 m resolution, seven spectral bands, and convenient summary statistics. An area for which considerable moose population data were available, Moose Management Unit 24, was chosen as the project area. Cloud-free imagery was available for 26 August 1985. Analysis of the digital data was performed on a DIPIX ARIES-III image analysis system. Surface verification and accuracy assessment was provided by 1:40,000 colour infrared aerial photography acquired in 1983, 1:12,500 provincial forest inventory maps compiled in 1978, as well as ground and aerial surveys in 1986 and 1987. Nine vegetation cover types were identified using a supervised classification. Classes notable for moose included mature deciduous forest, immature coniferous forest, recent cutovers/slash, immature deciduous forest, immature mixed forest, and mature coniferous forest. Long term objectives are to use satellite imagery and radio-telemetry information to evaluate changes in moose habitat potential for the various moose management units across the province. Article in Journal/Newspaper Newfoundland Alces (A Journal Devoted to the Biology and Management of Moose) Newfoundland |
institution |
Open Polar |
collection |
Alces (A Journal Devoted to the Biology and Management of Moose) |
op_collection_id |
ftjalces |
language |
English |
description |
Earth Resources Satellite sensors are increasingly used to provide rapid and current mapping of large areas for wildlife habitat analysis. In 1986 the Newfoundland and Labrador Wildlife Division undertook an experimental project to assess the feasibility of Landsat Thematic Mapper data to classify and inventory moose habitat. A TM digitized format was selected because of its superior 30 m resolution, seven spectral bands, and convenient summary statistics. An area for which considerable moose population data were available, Moose Management Unit 24, was chosen as the project area. Cloud-free imagery was available for 26 August 1985. Analysis of the digital data was performed on a DIPIX ARIES-III image analysis system. Surface verification and accuracy assessment was provided by 1:40,000 colour infrared aerial photography acquired in 1983, 1:12,500 provincial forest inventory maps compiled in 1978, as well as ground and aerial surveys in 1986 and 1987. Nine vegetation cover types were identified using a supervised classification. Classes notable for moose included mature deciduous forest, immature coniferous forest, recent cutovers/slash, immature deciduous forest, immature mixed forest, and mature coniferous forest. Long term objectives are to use satellite imagery and radio-telemetry information to evaluate changes in moose habitat potential for the various moose management units across the province. |
format |
Article in Journal/Newspaper |
author |
Oosenbrug, Sebastian M. Perrott, Timothy H. Butler, Charles E. |
spellingShingle |
Oosenbrug, Sebastian M. Perrott, Timothy H. Butler, Charles E. MOOSE HABITAT MAPPING IN CENTRAL NEWFOUNDLAND USING DIGITAL LANDSAT THEMATIC MAPPER DATA |
author_facet |
Oosenbrug, Sebastian M. Perrott, Timothy H. Butler, Charles E. |
author_sort |
Oosenbrug, Sebastian M. |
title |
MOOSE HABITAT MAPPING IN CENTRAL NEWFOUNDLAND USING DIGITAL LANDSAT THEMATIC MAPPER DATA |
title_short |
MOOSE HABITAT MAPPING IN CENTRAL NEWFOUNDLAND USING DIGITAL LANDSAT THEMATIC MAPPER DATA |
title_full |
MOOSE HABITAT MAPPING IN CENTRAL NEWFOUNDLAND USING DIGITAL LANDSAT THEMATIC MAPPER DATA |
title_fullStr |
MOOSE HABITAT MAPPING IN CENTRAL NEWFOUNDLAND USING DIGITAL LANDSAT THEMATIC MAPPER DATA |
title_full_unstemmed |
MOOSE HABITAT MAPPING IN CENTRAL NEWFOUNDLAND USING DIGITAL LANDSAT THEMATIC MAPPER DATA |
title_sort |
moose habitat mapping in central newfoundland using digital landsat thematic mapper data |
publisher |
Lakehead University |
publishDate |
1988 |
url |
http://alcesjournal.org/index.php/alces/article/view/1271 |
geographic |
Newfoundland |
geographic_facet |
Newfoundland |
genre |
Newfoundland |
genre_facet |
Newfoundland |
op_source |
Alces: A Journal Devoted to the Biology and Management of Moose; Vol. 24 (1988): Alces Vol. 24 (1988); 167-177 2293-6629 0835-5851 |
op_relation |
http://alcesjournal.org/index.php/alces/article/view/1271/1343 http://alcesjournal.org/index.php/alces/article/view/1271 |
_version_ |
1802008755729072128 |