Remote sensing for resources development and environmental management: Remote sensing for resources development and environmental management

Damen, M. C. J.

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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:: Classification of the Riverina Forests of south east Australia using co-registered Landsat MSS and SIR-B radar data. A. K. Skidmore, P. W. Woodgate & J. A. Richards

Document type:: Multivolume work

Structure type:: Chapter

:ati*ns. H*w- ! information 'est*. It is ¡ateilite data lappe r and : information. Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 Classification of the Riverina Forests of south east Australia using co-registered Landsat MSS and SIR-B radar data i postgraduate »graphy uni- ! author is Director, on Systems ; valuable thankful to mission in it, Government for their •P. Revised .a, New Delhi, >82. A compa- .cation pro- ir an area of Basilicata, f of Environ, >• Automatic sensed data. >s, Division ‘each to world ■ s. Rep. No. Stockholm. il rain forest. I. [ues for image in remote •ess. A.K.Skidmore, P.W.Woodgate & J.A.Richards Centre for Remote Sensing, University of New South Wales, Kensington, Australia Abstract: The Riverina forests of south east Australia have been extensively managed for 150 years as a productive source of railway sleepers and sawn timber. This study was the first Australian forestry application to evaluate the use of SIR-B radar (co-registered with Landsat MSS data) for mapping forest types and site quality classes. The techniques used for radar speckle reduction, registration of images and classification or cover classes are discussed. Results show that the classification accuracy was superior when the two data sources were used in combination rather than individually. 1. Introduction The objective of the study was to map forest types and site qualities of the Riverina forests using SIR-B imagery as a data source by itself and in combination with Landsat MSS data. The study area straddles the Murray River, which is the bordei between the States of New South Wales and Victoria in Australia (see Figure 1). Figure 1 - Location of the study area About 15,000 years ago, a 10m high fault line developed in a north-south direction across the course of the Murray River, effectively damming the river and causing the river to diverge into two arms, to the north and south. The huge triangular sedimentary delta that formed was subject to periodic flood inundation caused by the high winter/spring precipitation in the headwaters of the Murray River. This flood plain is now dominated by virtually pure monospecific stands of River Red Gum (Eucalyptus camaldulensis), due to this species' unique ability to withstand periodic flooding, in lower lying areas of the delta, shallow lakes and swamps are in various stages of silting up. Aeolian sand hills rise up to 12m above the flood plain and support tree species including Yellow Box (Eucalyptus melliodora) and Grey Box (Eucalyptus microcarpa). However, local variation in topography is generally less than 2m, anc shadowing effects can be considered minimal or non-existant. Interestingly, at the time of the SIR-B overpass, the forest complex was experiencing an 80% flood of the total forest area. The Landsat image was recorded about a month later when the flood had just receded. Three site quality classes have been defined for River Red Gum stands (Table 1). Site quality is the actual (or potential maximum average) height of trees in a forest stand, and is also an indication o the stand density. Stand density is a measure of stand basal area (i.e cross sectional area of tree stems at 1.3m per unit area) or stocking Table 1 also details the other major cover types in the study area. This present forest structure has been modified by man's activities. The Aboriginal population regularly burnt the forest to maintain an open woodland condition of veteran trees, which enhanced the value of the forest for hunting. From the 1840's, European man used the forest for grazing runs and for timber. Curren logging is on a selection basis, with some overmature trees being removed during logging to improve regeneration. Stands are uneven-aged and very variable in tree size and distribution as a result of this history. However, stand density (basal area or stocking) is correlated to site quality (see Table 1), with red gum (site quality 1) being the densest forest. The study area was selected because the Centre for Remote Sensing at the University of New South Wales had acquired a clear Table 1 - Major cover types in thè Riverina Forests Land cover Typical location of type occurence Definition and description of land cover type River Red Gum Site Quality 1 Frequently flooded e.g. river bends. Areas with good access to subterranean water. Dominant tree height (or pot- ential tree height) of 31-45 m. Higher stand density (70 m^/ha).Heavily stocked regen eration. Ground cover of leaf litter or grass. River Red Gum Site Quality 2 Intermediate levels of the floodplain. Depth to watertable 6-9 m. Dominant heights of 21-31 m. Increasing number of woody understorey plants. Moderate stand density. River Red Gum Site Quality 3 Higher levels of flood- plain. Depth to water- table > 9 m. Infrequent floods of short duration Poor stand development. Open savannah woodland of <21 m in height. Woody understorey species more pronounced. Yellow and Grey Box Irregularly flooded and flood-free areas Stands vary in dominant height from 6-30 m. Grass component in understorey. Swamps and Giant Tussock Rushland Watercourse and semipermanent swamps Tussock grass formation of 2-3 m. SIR-B radar image of the Riverina forests from the flight of Space Shuttle Challenger in October 1984. Comprehensive forest type and site quality maps already existed for the area, and were made available by the Forestry Commission of N.S.W. and the Department o Conservation, Forests and Lands of Victoria. A unique opportunity thus occured to generate forest type maps using SIR-B imaging rada combined with Landsat MSS data of approximately the same dates. Details of the Landsat MSS and SIR-B radar are described in Table 2. Table 2 - Description of the Landsat MSS and Sir-B radar Landsat MSS SlR-B Radar Source Landsat-4 Space Shuttle Acquisition date 17 November 1984 13 October 1984 Acquisition time 0930 0100 Pixel resolution 79 x 56 m 12.5 m Wavelength 5 x 10-5 cm - 1.1 x 10-5 cm 23.5 cm Incidence angle orthogonal 32.7 - 39.3 degrees Two obstacles had to be overcome to meet the objectives of the study. The first was radar speckle, which is an unavoidable product of the illumination of a surface by coherent monochromatic radiation. Despite the fact that SIR-B imagery was produced by averaging four independent looks, further speckle reduction was necessary prior to classification to prevent aberrant speckled pixels from causing misclassification. Secondly, spatial resolution

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