Proceedings of the Symposium on Global and Environmental Monitoring: Proceedings of the Symposium on Global and Environmental Monitoring

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Persistent identifier:: 856665355

Title:: Proceedings of the Symposium on Global and Environmental Monitoring

Sub title:: techniques and impacts ; September 17 - 21, 1990, Victoria Conference Centre, Victoria, British Columbia, Canada

Year of publication:: 1990

Place of publication:: Victoria, BC

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 856665355

Language:: English

Document type:: Multivolume work

Volume

Persistent identifier:: 856669164

Title:: Proceedings of the Symposium on Global and Environmental Monitoring

Sub title:: techniques and impacts; September 17 - 21, 1990, Victoria Conference Centre, Victoria, British Columbia, Canada

Scope:: XIV, 912 Seiten

Year of publication:: 1990

Place of publication:: Victoria, BC

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 856669164

Illustration:: Illustrationen, Diagramme, Karten

Signature of the source:: ZS 312(28,7,1)

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: International Society for Photogrammetry and Remote Sensing, Commission of Photographic and Remote Sensing Data

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:: [WP-3 FOREST INVENTORY APPLICATIONS]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: SATELLITE IMAGE-BASED NATIONAL FOREST INVENTORY OF FINLAND. Erkki Tomppo

Document type:: Multivolume work

Structure type:: Chapter

421 distances . Our preliminary tests have shown that this method works quite well. The estimation of some changes such as thinning may require other methods, cf. Thomas (1990). The spatial information of the image can be taken into account in the feature choice and/or in the postprocessing. Segmentation techniques or Gibbsian random field modelling, for example, are possible postprocessing methods (see Besag (1986) and Tomppo (1987,1989)). Bias and the accuracy of the estimates must of course be kept under control. 4. DATA MANAGEMENT Special attention must be paid to data management; total single date coverage of the country with TM imagery involves about five Gbytes of data. The output of the image analysis will be compatible with the the forest management planning system (MELA) used by the Finnish Forest Research Institute. This system allows simulation of the development of the forest between two ground measurement (and image analysis) timepoints. In addition, themes can be presented in a raster form and the maps can be produced at different scales. The system allows the use of digital map data of other organizations, for example the National Board of Survey and the National Board of Forestry. In the future, the output will be formatted to be suitable for the databases of those organizations. 5. PRELIMINARY RESULTS The above methodology and input data have been applied in estimating NFI - variables in a few areas in eastern Finland. Sum characteristics of ordinary stand wise data, measured for forest management planning purposes, are available as comparison material. These data (referred here as FBI) -data) are based on visual ground estima tion and information from false colour aerial photographs. The data are measured by the local Forestry Board District and only non-company private forests are included. All the above mentioned digital map data are so far available only from the area of two communes, Tohmajarvi and Vartsila, the total area of non-company private land being 52 000 hectares. The digital communal boundaries were applied in order to restrict the test area. 1 he boundaries of lands of two forest companies were digitized in order to remove non-private forest areas from the test site, because the forest characteristics of company-ovned land were not known. Table 1 shows the satellite image-based estimates ( NFI) and the estimates of Forestry Board District (FBD) for some mean characteristics. (Note that the total number of NFI -variables is about 200.)

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