Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

baltsavias, emmanuel p.

Bibliographic data

Monograph

Persistent identifier:: 856473650

Author:: Baltsavias, Emmanuel P.

Title:: Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

Sub title:: Joint ISPRS/EARSeL Workshop ; 3 - 4 June 1999, Valladolid, Spain

Scope:: III, 209 Seiten

Year of publication:: 1999

Place of publication:: Coventry

Publisher of the original:: RICS Books

Identifier (digital):: 856473650

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

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

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:: Monograph

Collection:: Earth sciences

Chapter

Title:: TECHNICAL SESSION 7 APPLICATIONS IN FORESTRY

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: SENSOR FUSED IMAGES FOR VISUAL INTERPRETATION OF FOREST STAND BORDERS. R. Fritz, I. Freeh, B. Koch, Chr. Ueffing

Document type:: Monograph

Structure type:: Chapter

International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 184 SENSOR FUSED IMAGES FOR VISUAL INTERPRETATION OF FOREST STAND BORDERS R. Fritz, I. Freeh, B. Koch, Chr. Ueffing Dept, of Remote Sensing and LIS, University of Freiburg, Tennenbacherstr. 4, 79106 Freiburg, Germany, feminfo@felis.uni-freiburg.de KEYWORDS: IHS-Transformation, Adaptive Image Fusion, Forest Stand Border Delineation, Quality Analysis. ABSTRACT In the last years forest cartography is changing from an analog to a digital generation and presentation. For this purpose, forest departments develop and implement Forest Geographic Information Systems. Till now, the actual stand borders are delineated based on B/W orthophotos. This procedure requires at least four processing steps to integrate stand delineations assessed during forest inventories into the final digital forest management map. Each step produces errors and makes the procedure of data integration labour- and cost-intensive. With the availability of high resolution satellite data, the use of such data for forest map production becomes feasible. Due to the information requirements, high spatial and spectral resolution is needed. The fusion of image data provides an opportunity to meet these requirements. Different fusion techniques have been tested, such as IHS-, PC- and Brovey- transformation to combine the spectral and spatial information of satellite data. All three sensor fusion methods show a visual improvement of the images by the synergy effect combining high spectral and spatial satellite data, whereby the IHS transformation showed best colour differentiation for visual interpretation. Due to the good performance of the IHS transformed images, the applicability of sensor fusion techniques for forest inventory mapping has been investigated with an IHS transformed product of Landsat TM and IRS-1C pan [IHS_TM]. This product was compared to an IHS transformed SPOT XS and PAN [IHS_SP], IRS-1C pan [Pan] alone, a B/W orthophoto [Ortho] and a simulated QuickBird image [Qsim] with lm resolution. The resulting image fusion products have been interpreted and digitized ‘on-screen’ by two persons in order to delineate stand borders. The comparative evaluation is performed in two steps: (1) measuring the visibility percentage of forest stand borders in reference to the official forest inventory maps and (2) calculation of quality measure criteria. The total length of stand borders in the test area is more than 40km. In every image product more than 70 % of stand borders have been detected, with IHS 72%, PAN 76% and simulated QUICK 85 % correspondence. Another tested approach was to combine Landsat TM and KVR-1000 (2m resolution) with different fusion techniques. In a first step, an adaptive image fusion (AIF) was calculated. In a second step, the resulting image was combined with the high resolution data, again with an IHS transformation. The output of this transformation shows very good results for visual interpretation and will be used as photorealistic background for tourist information systems. A precondition of this method is a very accurate rectification of the input data. Otherwise, it will provide poor results with a lot of artefacts. 1. INTRODUCTION With further development of information technology the requirements of forest departments for using geographic information systems increased at the end of the 80s (Teuffel and Krebs, 1996). The result of this development was the implementation of Forest Geographic Information Systems. The forest cartography is changing from an analog to a digital generation and presentation. Parallel to the digital development in forest cartography, the geometric resolution of new generation of satellites is also increasing. The existing optical satellite systems (TM and SPOT) did not prove suitable for forest mapping applications in intensive and small plot forest conditions, as in Middle Europe. With the relatively low geometric resolution of the existing satellite systems, the complex conditions of the forest areas can not be mapped. Consequently, satellite data have not been implemented in forest map generation. With the availability of high resolution satellite data with up to 6m in panchromatic band, the use of satellite data in the forest map preparation chain may be possible with the required map accuracy. The present research project on one hand verifies the potential of high resolution satellite data for digital forest map production and on the other demonstrates the application of sensor fusion techniques to combine the spectral and spatial information of satellite data.

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