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

2.2. Digitized map data Digital map data will be used for improving the accuracy of estimates and to separate forest and non-forest, land from each other. The spectral response of peatlands differs from that of the mineral soils with the same growing stock according to our earlier studies. Further, some peatlands can not be separated from mineral soils. Therefore, digital peatland information will be used in order to improve the accuracy of estimates. These digital data are provided by the National Board of Survey. The peatland data, digitized from a generalization of a base map with the scale of 1 : 100 000, are now available for the whole country. Agricultural areas and roads will be digitized from base maps having a scale of 1 : 50 000 (if the preliminary tests show these data to be useful). A combination of a numerical interpretation and digital map information will be used in classifying agricultural areas, because the map data are not necessarily up to date. Urban areas can be obtained from the house register provided by the statistical centre of Finland. The coordinates of each house in Finland are known. A digital urban area mask can be produced from this information. Water areas could be obtained from base maps but they can be obtained relatively reliably also from satellite images. Some administrative information such as community boundaries and, in the future, boundaries of forest holdings will also be used in t he digital form in order to differenta- tiate computation units. 2.3. Ground truth data The recent NFI data can serve as ground truth data. In the future sampling design, the needs of satellite image interpretation must be taken into account more thoroughly. Such problems as 1) the sampling intensity of permanent and temporary plots, 2) the rotation period of inventory, and 3) the size and the form of the sample plot and of the cluster will have to be addressed. Choices must be made, for example, between one relatively small or several even smaller plots in the same stand. (The satellite image information is essentially standwise information rather than sample plot information.) 3. IMAGE INTERPRETATION The image analysis consists of preprocessing of t he image (removal of noise, striping, etc.), choice of features, classification, and postprocessing (generalization). All inventory variables should be estimated. One possibility is to use some lion-parametric method such as nearest neighbor classification (see Appendix I ). This method can also lie referred to as a 'nearest neighbor fuzzy classification'. Each interpretation class consists of one sample plot (one or several pixels depending on what kind of features will be used). Each pixel to be classified will be shared between several classes according to Appendix 1. The shares are inversely proportional to the squared feature space 420

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