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WAS 1. $8 43 094 NASA Conference Publication 3099 Multisource Data Integration in Remote Sensing Procoef ae wodrksihopn hegld sat t he Univerofs Miartylyan d ColPlarke, Mgaryela nd June 14-15, 1990 NASA NASA Conference Publication 3099 Multisource Data Integration in Remote Sensing James C. Tilton, Editor Goddard Space Flight Center Greenbeit, Maryland Procofe a weorksdhop isponnsogred sby the Institute of Electarndi Elcecatrolni c Engineers (IEEE) and the NASA Goddard Space Flight Center and held at the Univerofs Miartylyan d ColPlarke, gMareyla nd June 14-15, 1990 NASA National Aeronautics and Space Administration Office of Management Scientific and Technical Information Division 1991 <= FOREWORD On June 14-15, 1990, Technical Committee 7 (TC7) of the International Association for Pattern Recognition (IAPR) held®% Workshop on “Multisource Data Integration in Remote Sensing” in ColPlarke, Mgaryelan d. The original plan for this workshop was to place it in between two major, related conferences: the International Geoscience and Remote Sensing Symposium (IGARat StheS en'd o9f€M0ay )199 0, in College Park, MD; and the International Conference on Pattern Recognition (ICPRi'n 9midQ-J)un e 199in 0Atl,ant ic City, NJ. Such a configuratioonf two major conferences in geographically and ly close range would have offered an parce h ens ny hh may EM I mall : to bring together scientists from remote lications and from the methodology of pattern recognition. Due to the postponement oft he1 ‘90, the time between the two conferences became too long to allow participants of both conferences to attend the workshop by a short prolongation of their stay in the area. We therefore moved the workshop close to the ICPR to at least partly reach our goal. The subject of the workshop, Multisource Data Integration in Remote Sensing, seems to have become a real challenge for the near future. New instruments and new sensors will provide us with a large variety of new views of the “real world." This huge amount of data has to be combined and integrated in a (computer-)model of this world. But also, the knowledge of how these data are gathered and what their characteristic properties are is among the useful sources of information that contribute to a meaningful interpretation. Multiple sources may give us complementary views of the world -- consistent observations from different (and independent) data sources support each other and increase their credibility, while contradictions that may be caused by noise, errors during processing, or misinterpretations, can be identified as such. As a consequence, data integration can produce results that are very reliable, and represents a valid source of information for any geographical information system (GIS). The workshop structure consisted of three sessions of three to five individual presentations. All papers were discussed both individually and in the general context of the session. Additionally, all papers were considered under four specific aspects: 1. What an the characteristic properties of the data sources that are explored in the individual approach? 2. In which category does the used integration method fall? 3. What is the result of the integration and what are the improvements realized? 4. What are the major advantages of the proposed methods? Four participants generously volunteered to consider the papers under one of the above aspects. Started as an experiment to encourage lively discussion, the four summaries (three of which are included herein) prove the success of this approach, and give also a useful index to the presented papers. It was an interesting experience for the authors to get a feedback on their own presentations. Last but not least, I would especially like to thank Dr. James C. Tilton of NASA Goddard Space Flight Center for the excellent organization of this workshop. I would like to further acknowledge the sors of the workshop, the IAPR, NASA Goddard Space Flight Center, and the Washington/Northern Virginia Chapter of the IEEE Geoscience and Remote Sensing Society. My thanks go also to the authors that have contributed papers and to all the active participants that made the workshop more than just a sequence of presentations. I hope that activities of IAPR-TC7 will continue in the future under the leadership of the new chairman of TC7, Dr. Tilton, and that we can reassemble for another interesting workshop -- probably in 2 years -- on the occasion of the next ICPR, which will be held in The Hague, The Netherlands. Dr. Walter G. Kropatsch ill CONTENTS PRESENTATIONS Refinement of Ground Reference Data with Segmented Image Data Jon W. Robinson, ST Systems Corporation, Lanham, MD, USA James C. Tilton, NASA Goddard Space Flight Center, Greenbelt, MD, USA Near Ground Level Sensing for Spatial Analysis of Vegetation 11 John Rasure, Tom Sauera,n d Charlie Gage, Department of Electrical and Computer Engineering, University of New Mexico, AlbuquerqNuM,e U,S A Integration of SAR and DEM Data - Geometrical Considerations Walter G. Kropatsch, Institute for Informatics, UnivInnsebrucrk, Isnnsibructk, yAust ria Towards Operational Multisensor Data Registration Eric Rignot, Ronald Kwok, and John Curlander, Jet Propulsion Laboratory, CaliInsftitoute rofn Tecihnoalog y, PasadenaC,A , USA Combined Fluorescence, Reflectance, and Ground Measurements of a Stressed Norway Spruce Forest for Forest Damage Assessment C. Banninger, Institute for Image Processing and Computer Graphics, Joanneum Research, Graz, Austria A ical Approach to Multisource Data Integration: Analysing Infrared 61 and Visible Data N. NandhElecatrikcal uEngmineearinrg D,epar,tme nt, Univof Veirgrinias, Ciharitouesyvill e, VA, USA A Method for Classification of Multisource Data using Interval- Valued Probabilities 75 and Its Applictao HtIRiISo Dnat a H. Kim and P.H . Swain, School of Electrical Engineerinagn d Laboratory for Applications of Remote Sensing. Purdue University, West Lafayetie, IN, USA Improved Disparity Map Analysis Through the Fusion of Monocular Segmentations 83 FredPe. Preriiantc a nd David M. McKeown, Digital Mapping Laboratory, Carnegie Mellon University, Pittsburgh, PA, USA Use of Information Fusion to Improve the Detection of Man-Made Structures in Aerial Imagery Jeffrey Shugelt and David M. McKeown, Digital Mapping Laboratory, Carnegie Mellon University, Pittsburgh, PA, USA A, Computer Vision System for the Recognition of Trees in Acrial Photographs 11 A. Pinz, Insanae of Surveying and Remote Sensing, Univof Aegricrultusre, iWietn, yAust ria ee a ee 125 David G. Tilley, The Johns Hopkins University Applied Physics Laboratory, LaureMDl, ,US A A Proposal to Extend Our Understanding of the Global Economy 135 Robbin R. Hough, Oakland University, Rochester, MI, USA, and Manfred Ehlers, University of Maine, Orono, ME, USA Summary of Data Sources Utilized in Workshop Papers 143 James C. Tilton, NASA Goddard Space F light Center, GreenbeltM,D , USA Summary of Types of Data Fusion Methods Utilized in Workshop Papers 145 Sylvia S. Shen, Lockheed Palo Alto Research Lab., Palo AltCoA,, US A Summary of Types of Data Output Produced by Studies Described In Workshop Papers 15! Axel J. Pinz, Instinate of Surveying and Remote Sensing, Univof Aegricrultusre, iWietn, yAust ria 155 vi PRESENTATIONS ) d n e a i d s P . a o# e 1 : A l i l l n i i A e| a o t f z i i e l lc n e e > ar t l i t r y a tti a l t el b a i i l e l j U u i a M e e B i tf a e i i | e i i ) l e e f u Ha i e i f A This :' I Ie iil A : He : ; 82 a) LH i! a; UE He A E a i aia bas ui iat a Ls TH 5 Fe LH: iE bai H i HL 1 a taHlie Hia i t i l iHa e i iL t r a bi a t e: ir v a e T2 uB 3 u e.i eg z ! ; y : te w2 9 il 8 z et H : s a 2 e 8 a l2 it l m t t e n 3 iu aa k ! HH ig E e and savtihen regsul t. An exasnple of the final result from CHGVAL#.PRfoOr a Tocic £28x 128s hction ofd atai sg iveni nF igure4 L | H B h ~ SHill i T £ 1a c t gaatice e h Hy a h a t Hes e H i :53 l i t t ih