USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE
ABSTRACT: We modified the standard, stratified random block design used typically in aerial sur-veys of moose (Alces alces). We laid a grid of approximately 9 km2 cells over our study area, and GIS was then used to allocate polygons into one of 2 strata within each grid cell. The 2 strata were based...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.687.867 2023-05-15T13:12:54+02:00 USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE Douglas C. Heard Andrew B. D. Walker Jeremy B. Ayotte Glen S. Watts The Pennsylvania State University CiteSeerX Archives http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.687.867 http://alcesjournal.org/index.php/alces/article/viewFile/41/40/ en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.687.867 http://alcesjournal.org/index.php/alces/article/viewFile/41/40/ Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://alcesjournal.org/index.php/alces/article/viewFile/41/40/ Key words Alces alces British Columbia GIS moose stratified random block survey vegetation text ftciteseerx 2016-01-08T18:12:53Z ABSTRACT: We modified the standard, stratified random block design used typically in aerial sur-veys of moose (Alces alces). We laid a grid of approximately 9 km2 cells over our study area, and GIS was then used to allocate polygons into one of 2 strata within each grid cell. The 2 strata were based upon vegetation attributes that were predicted to have either high or low moose density from previous research. We assumed that polygons of early seral forest stands (<40 yr), shrubs, and meadows would have high moose density relative to other vegetation attributes. Vegetation polygons were often <1 km2, consequently, single grid cells usually included>1 high and low density polygons. Adjacent cells were amalgamated to produce sample units with>4 km2 of high density stratum area. Real-time navigation was used and the flight track was recorded over a map of sample units, strata boundaries, and topographic features to accurately identify polygon boundaries and assign each sighted moose to the appropriate strata. We concluded that our approach was efficient and effective in fine-grained en-vironments where the relative selection by moose for vegetation patches is well understood, and those patches are mapped in digital databases. Text Alces alces Unknown |
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English |
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Key words Alces alces British Columbia GIS moose stratified random block survey vegetation |
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Key words Alces alces British Columbia GIS moose stratified random block survey vegetation Douglas C. Heard Andrew B. D. Walker Jeremy B. Ayotte Glen S. Watts USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE |
topic_facet |
Key words Alces alces British Columbia GIS moose stratified random block survey vegetation |
description |
ABSTRACT: We modified the standard, stratified random block design used typically in aerial sur-veys of moose (Alces alces). We laid a grid of approximately 9 km2 cells over our study area, and GIS was then used to allocate polygons into one of 2 strata within each grid cell. The 2 strata were based upon vegetation attributes that were predicted to have either high or low moose density from previous research. We assumed that polygons of early seral forest stands (<40 yr), shrubs, and meadows would have high moose density relative to other vegetation attributes. Vegetation polygons were often <1 km2, consequently, single grid cells usually included>1 high and low density polygons. Adjacent cells were amalgamated to produce sample units with>4 km2 of high density stratum area. Real-time navigation was used and the flight track was recorded over a map of sample units, strata boundaries, and topographic features to accurately identify polygon boundaries and assign each sighted moose to the appropriate strata. We concluded that our approach was efficient and effective in fine-grained en-vironments where the relative selection by moose for vegetation patches is well understood, and those patches are mapped in digital databases. |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Douglas C. Heard Andrew B. D. Walker Jeremy B. Ayotte Glen S. Watts |
author_facet |
Douglas C. Heard Andrew B. D. Walker Jeremy B. Ayotte Glen S. Watts |
author_sort |
Douglas C. Heard |
title |
USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE |
title_short |
USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE |
title_full |
USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE |
title_fullStr |
USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE |
title_full_unstemmed |
USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE |
title_sort |
using gis to modify a stratified random block survey design for moose |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.687.867 http://alcesjournal.org/index.php/alces/article/viewFile/41/40/ |
genre |
Alces alces |
genre_facet |
Alces alces |
op_source |
http://alcesjournal.org/index.php/alces/article/viewFile/41/40/ |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.687.867 http://alcesjournal.org/index.php/alces/article/viewFile/41/40/ |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766254713044467712 |