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:: 1 Visible and infrared data. Chairman: F. Quiel, Liaison: N J. Mulder

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: Digital classification of forested areas using simulated TM- and SPOT- and Landsat 5/TM-data. H.- J. Stibig, M. Schardt

Document type:: Multivolume work

Structure type:: Chapter

79 Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 Digital classification of forested areas using simulated TM- and SPOT- and Landsat 5/TM-data H.-J.Stibig Dept. Luftbildmessung und Fernerkundung, Institute for Forest Economy and Inventory, University of Freiburg, FR Germany M.Schardt DFVLR (Deutsche Forschungs- und Versuchsanstalt für Luft- und Raumfahrt), FR Germany ABSTRACT: In the following piece of research both SPOT- and TM-images, as well as true Landsat 5/TM data have been digitally classified. The results show information about the possibilities of recognizing different types and age classes of trees, together with a high resolution of the classified forest units. Using both TM- and SPOT-data it is possible to differentiate between at least three age classes in forest stands. As well as distinguishing betv^en coniferous and deciduos trees, it is possible to recognize certain tree types in pure crop stands within these classes, depending on the time of year. The correctly classified forest unit is influenced by the form and size of the stands, but generally stands larger than an hectare can be recognized. Ihe classification of the Landsat 5/TM scenes was improved by taking into account topographical information and by using rnultitemporal data. ACKNOLEDGEMENT The results of the TM-simulation carried out by Kirch- hof, W. , Mauser, W. and Stibig, H.-J. , were pub lished in the research report FB-85-49 of the DFVLR (Deutsche Forschungs- und Versuchsanstalt fiir Luft- und Raumfahrt). 1 INTRODUCTION The digital classification of Landsat/MSS-images has already been carried out in countries with extensive forest areas, producing good results. Offering a high level of efficiency, their use has been shown for ge neral classifications, for example seperating deci duos from coniferous forest for the purpose of stra tification. for detailed inventory methods. However owing to the limitations of the geometrical resolu tion, Landsat/MSS data have proved of little use for forestry classification in Centra], Europe. The size of the planning units in the intensively managed forests is usually between 3 and 5 hectares and the treatment units are often smaller. Whereas an area of 2,56 hectares is necessary for one pure Landsat/MSS pixel. New sattelite images from SPOT- and Landsat 5/TM with a high geometrical resolution open up possibilities for the use of remote sensing for forestry purpose in Central Europe. 2 TEST SITES The strip overflown for the SPOT- and TM-simulation is situated west of Freiburg. Apart from agricultural and built up areas, the test area contains typical mixed deciduos forest of the Rhine valley. The main tree types are oak, ash and maple. There are also some single pure crop stands of spruce, douglas firs and red oak. A test area to the north-west of Freiburg in the Kaiserstuhl was chosen for the multitemporal evalua tion of the Landsat 5/TM data. This area consisted of two types of forest: 1. "Auwald": deciduos lowland forests near the Rhine. The main tree types are oak, white beech, poplar and maple as well as pure crop stands of douglas firs and pine. 2. Colline to submontane mixed deciduos forest consisting mainly of beech, white beech and oak, varying in height from 200 to 550 metres. 3 MATERIAL AND METHODS The simulation of the SPOT and TM data was carried out on behalf of the research centre of the European community (IRC) in ISPRA. The SPOT-simulation took place on the 26.5.1982 and was performed using a 10 band Daedelus scanner from a height of 7000 metres by the NGI (National Geographical Institute). The radiometrical simulation of the SPOT-simulation bands (S.S.) from the Daedelus bands was carried out by the CNES (Centre National d'Etude Spatial) (Tab. 1). The TM-simulation was flown on the 21.7.83 fron a height of 4000 metres by the DFVLR, using two Bendix- M2S-Scanners, one of which was modified to work in the middle infrared wavelengths. For the evaluation of the data, the scanner bands (T.M.S.) which most closely approach the TM bands were used (Tab. 1). The selected Landsat 5/TM-images are the scenes 195/27 taken on the 18.4.84 and the 7.7.84. In order to include the different tree types and age classes, the test areas were selected by using ground truth inventories, the interpretation of infrared false cölour composites and the .information from fo rest management plans. The geometrical rectification of the scenes took place with pass points on Gauß-Krüger coordinates using an exponential transformation polynom. The signature analysis of the test areas was per formed by comparing histogramms, the reflection curves of the mean values and the presentation of the object classes in two dimensional feature space. The quality of the training areas for the simulation data used for the maximum likehood method was esti mated using a confusing-matrix. The sub-scenes were finally classified according to the maximum likehood method. For the TM-scene of April a more simple classification by the defini tion of thresholds was sufficient for a forestry stratification, owing to the more distinct reflec tion differences. For that purpose the maxima and minima values for all the bands were cited. Additional information in the form of a digital terrain model was used for a further stratification according to height. To test the accuracy of the classification the results were compared with forestry planning maps of selected areas. The image processing systems FIPS (Freiburg's Image Processing System) of the dept. Luftbildmessung und Fernerkundung and DIBIAS of the DFZLR were used for the digital image analysis.

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