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Remote sensing for resources development and environmental management (Volume 1)

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Bibliographic data

fullscreen: Remote sensing for resources development and environmental management (Volume 1)

Multivolume work

Persistent identifier:
856342815
Title:
Remote sensing for resources development and environmental management
Sub title:
proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986
Year of publication:
1986
Place of publication:
Rotterdam
Boston
Publisher of the original:
A. A. Balkema
Identifier (digital):
856342815
Language:
English
Additional Notes:
Volume 1-3 erschienen von 1986-1988
Editor:
Damen, M. C. J.
Document type:
Multivolume work

Volume

Persistent identifier:
856343064
Title:
Remote sensing for resources development and environmental management
Sub title:
proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986
Scope:
XV, 547 Seiten
Year of publication:
1986
Place of publication:
Rotterdam
Boston
Publisher of the original:
A. A. Balkema
Identifier (digital):
856343064
Illustration:
Illustrationen, Diagramme
Signature of the source:
ZS 312(26,7,1)
Language:
English
Usage licence:
Attribution 4.0 International (CC BY 4.0)
Editor:
Damen, M. C. J.
Publisher of the digital copy:
Technische Informationsbibliothek Hannover
Place of publication of the digital copy:
Hannover
Year of publication of the original:
2016
Document type:
Volume
Collection:
Earth sciences

Chapter

Title:
4 Renewable resources in rural areas: Vegetation, forestry, agriculture, soil survey, land and water use. Chairman: J. Besenicar, Liaisons: M. Molenaar, Th. A. de Boer
Document type:
Multivolume work
Structure type:
Chapter

Chapter

Title:
Spruce budworm infestation detection using an airborne pushbroom scanner and Thematic Mapper data. H. Epp, R. Reed
Document type:
Multivolume work
Structure type:
Chapter

Contents

Table of contents

  • Remote sensing for resources development and environmental management
  • Remote sensing for resources development and environmental management (Volume 1)
  • Cover
  • Title page
  • Title page
  • Title page
  • Preface
  • Organization of the Symposium
  • Working Groups
  • Table of contents
  • 1 Visible and infrared data. Chairman: F. Quiel, Liaison: N J. Mulder
  • 2 Microwave data. Chairman: N. Lannelongue, Liaison: L. Krul
  • Spatial feature extraction from radar imagery. G. Bellavia, J. Elgy
  • Synthetic geological map obtained by remote sensing An application to Palawan Island. F. Bénard & C. Muller
  • The determination of optimum parameters for identification of agricultural crops with airborne SLAR data. P. Binnenkade
  • SLAR as a research tool. G. P. de Loor & P. Hoogeboom
  • Developing tools for digital radar image data evaluation. G. Domik & F. Leberl, J. Raggam
  • Measurements of the backscatter and attenuation properties of forest stands at X-, C- and L-band. D. H. Hoekman
  • Identifying agricultural crops in radar images. P. Hoogeboom
  • Shuttle imaging radar response from sand dunes and subsurface rocks of Alashan Plateau in north-central China. Guo Huadong, G. G. Schaber & C. S. Breed, A. J. Lewis
  • Oil drums as resolution targets for quality control of radar survey data. B. N. Koopmans
  • Detection by side-looking radar of geological structures under thin cover sands in arid areas. B. N. Koopmans
  • Geological analysis of Seasat SAR and SIR-B data in Haiti. Ph. Rebillard, B. Mercier de l'Epinay
  • Digital elevation modeling with stereo SIR-B image data. R. Simard, F. Plourde & T. Toutin
  • EARTHSCAN - A range of remote sensing systems. D. R. Sloggett & C. McGeachy
  • Evaluation of digitally processed Landsat imagery and SIR-A imagery for geological analysis of West Java region, Indonesia. Indroyono Soesilo & Richard A. Hoppin
  • Relating L-band scatterometer data with soil moisture content and roughness. P. J. F. Swart
  • Shuttle Imaging Radar (SIR-A) interpretation of the Kashgar region in western Xinjiang, China. Dirk Werle
  • 3 Spectral signatures of objects. Chairman: G. Guyot, Liaison: N. J. J. Bunnik
  • 4 Renewable resources in rural areas: Vegetation, forestry, agriculture, soil survey, land and water use. Chairman: J. Besenicar, Liaisons: M. Molenaar, Th. A. de Boer
  • Cover

Full text

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Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 
Spruce budworm infestation detection using an airborne 
pushbroom scanner and Thematic Mapper data 
H.Epp 
Canada Centre for Remote Sensing, Ottawa, Ontario 
R.Reed 
Saskatchewan Parks and Renewable Resources, Prince Albert, Canada 
ABSTRACT: Damage to white spruce stands in Saskatchewan by spruce budworm (Choristoneura fumiferana) has 
increased in the last three years. Due to dwindling wood supplies, loss of merchantable spruce and perhaps 
more importantly, regeneration, future spruce stands must be protected by limiting budworm spread. Forest 
managers, therefore require data of current year damage to softwood stands by spruce budworm larvae. Tradi 
tionally, federal and provincial forestry agencies conduct annual aerial sketch mapping suveys to record the 
extent and severity of damage to growth which gives the attacked trees a reddish-brown appearance. Useful 
information about the status of the spruce budworm is gathered but more reliable surveys related to individual 
stands could provide better timber forecasts. 
This paper reports on the results of a project undertaken to investigate the potential of high resolution 
MEIS-II pushbroom scanner and Thematic Mapper data for detecting current year spruce budworm infestation. 
In the summer of 1985 the Canada Centre for Remote Sensing and the Forest Inventory Section of Saskatchewan 
Parks and Renewable Resources assessed the capability of an airborne multispectral pushbroom scanner and 
Thematic Mapper data to detect current year spruce budworm damage. On July 4, 1985 data were acquired with an 
electro-optical pushbroom scanner of approximately 5 m resolution and 6 km swath width of a test site in east- 
central Saskatchewan. Thematic Mapper data of the same area were acquired on August 26, 1985 while independent 
infrared aerial photography was acquired on July 21, 1985 with a 240 mm mapping camera. 
From the aerial photography and natural colour images created from the pusbhroom scanner data it was possible 
to detect and identify areas of spruce budworm damage. One level of budworm infestation, with indications of a 
second level, was possible in some parts of the study area with the MEIS-II scanner. The lower resolution 
Thematic Mapper data was only able to identify the severely affected spruce budworm areas but there was confu 
sion with other vegetation types. The biowindow, where the foliage turns reddish-brown, is usually very short, 
lasting only four to eight weeks. It is, therefore, difficult to obtain cloudfree imagery of affected spruce 
budworm areas. 
Classifications performed on the MEIS-II and TM data indicate that only the real-time parallelipiped classi 
fier will give satisfactory results, but only in the drier areas. Other enhancements such as principal compo 
nent and Martin Taylor did not improve on the initial contrast stretched images. 
Spatial resolution was not a significant factor in determining which sensor could differentiate budworm 
infestation. The higher radiometric resolution with the higher signal-to-noise ratio in the MEIS-II sensor and 
the narrower band widths did make a significant improvement in budworm detection. 
The results of the study suggests the possibility of a spruce budworm infestation survey which could provide 
more accurate data of current year damage than those presently produced by aerial sketch mapping. Improved 
data could help program planning and assessment and ultimately improve wood supply. 
INTRODUCTION 
The current spruce budworm (Choristoneura fumiferana 
Clem.) epidemic although limited in extent, is the 
first significant occurrence in Saskatchewan, Canada, 
since 1968. The current epidemic began in 1982 when 
2000 ha of white spruce (Picea glauca, Moench) were 
severely defoliated. This increased to 4800 ha in 
1983. At the same time two new infestations resulted 
in moderate to severe defoliation of an estimated 
7900 ha. As a result timber harvesting and salvage 
operations were stepped up in an attempt to reduce 
the infestation (Stanley and Reed, 1986). Infesta 
tion areas had increased to 8300 ha by 1985 
(Table 1). Areas of infestation in Saskatchewan are 
small compared to eastern Canada where 
189.9 million ha were affected in 1983 (Kucera and 
Taylor, 1984). 
This paper reports the results of a remote sensing 
project jointly undertaken by Saskatchewan Parks and 
Renewable Resources (SPRR) and the Canada Centre for 
Remote Sensing (CCRS). The goal of the study was to 
investigate the potential of the high resolution 
MEIS-II pushbroom scanner (McColl et al., 1984) and 
LANDSAT Thematic Mapper (TM) data for detecting 
current year spruce budworm infestation. 
Spruce budworm outbreaks cause growth loss and 
increased mortality, thereby reducing harvestable 
yields (McLean and Erdle, 1984). Because decisions 
Table 1. 1985 spruce budworm infestations in 
Saskatchewan (in ha). 
Location 
Light 
Moderate 
Heavy 
Severe 
Total 
Red Earth 
1093.0 
1802.3 
1356.3 
134.8 
4386.4 
Tall Pines 
1114.8 
726.9 
753.6 
475.4 
3070.7 
Tenant Lake 
981.3 
807.4 
246.5 
575.0 
2610.2 
Woody Tower 
477.3 
119.9 
0.0 
2.3 
599.5 
Total 
3666.4 
3456.5 
2356.4 
1187.5 
10666.8 
(after Stanley and Reed, 1986) 
and management plans on forest utilization are based 
on forecasts of forest development, it is important 
that known outbreaks of spruce budworm are mapped 
accurately. 
The Canadian Forestry Service and the Forest 
Inventory Section of Saskatchewan Parks and Renewable 
Resources monitor the activities of the spruce bud 
worm in Saskatchewan. The Canadian Forestry Service 
records the extent and severity of current year 
infestation by aerial sketch mapping surveys on the 
basis of 1 km units. This is carried out in July by 
which time damage to current year growth is quite 
evident. 
In 1985, personnel from the Forest Inventory
	        

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