Sharing and cooperation in geo-information technology

Aziz, T. Lukman

Bibliographic data

Monograph

Persistent identifier:: 856479470

Author:: Aziz, T. Lukman

Title:: Sharing and cooperation in geo-information technology

Sub title:: ISPRS Commission VI Symposium, April 15 - 17, 1999, Bandung, Indonesia

Scope:: 1 Online-Ressource (130 Seiten)

Year of publication:: 1999

Place of publication:: London

Publisher of the original:: RICS Books

Identifier (digital):: 856479470

Illustration:: Illustrationen, Diagramme

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:: WG VI/3: INTERNATIONAL COOPERATION AND TECHNOLOGY TRANSFER

Write comment:: Der Aufsatz "Promotion Of The General Understanding And Improvement Of Public Relations, [...] ist im Original nicht enthalten.

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: DISCRETE MATHEMATIC FOR SPATIAL DATA CLASSIFICATION AND UNDERSTANDING. Luigi Mussio, Rossella Nocera, Daniela poli

Document type:: Monograph

Structure type:: Chapter

74 International Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 6. Bandung-lndonesia 1999 DISCRETE MATHEMATIC FOR SPATIAL DATA CLASSIFICATION AND UNDERSTANDING Luigi Mussio* Rossella Nocera** Danielapoli * *DIIAR - Politecnico di Milano Piazza Leonardo da Vinci, 32-20133 Milano, Italy ** DIEMA - Universita degli Studi di Reggio Calabria Via Emilio Cuzzocrea, 48 - 89100 Regiio Calabria, Italy luigi@ipmtf2.topo.polimi.it ISPRS Commission VI - Working Group 1 Key words : Education, Data processing, Segmentation techniques and relational strategies ABSTRACT Data processing, in the field of information technology, requires new tools, involving discrete mathematics, like data compression, signal enhancement, data classification and understanding, hypertexts and multimedia (considering educational aspects too), because the mass of data implies automatic data management and doesn’t permit any a priori knowledge. The methodologies and procedures used in the class of problems concern different kinds of segmentation techniques and relational strategies, like clustering, parsing, vectorization, formalization, fitting and matching, on the other hand, the complexity of this approach imposes to perform optimal sampling and outlier detection just at the beginning, in order to define the set of data to be processed: rough data supply very poor information. For these reasons, no hypotheses about the distribution behavior of the data can be generally done and judgement should be acquired by distribution-free inference only. 1. THE CHANCE AND THE CHALLENGE (BELLONE, ET AL., 1997) As a matter of fact, history tells that nothing is definitely over in technique and nothing is forever acquired. The critical attitude drives not only to be severe in the judgement of the past, but also to be rightly and objectively fair in the judgement of present tendencies. These tendencies can be affected by trends and pressures that don’t come from the intimate structure of the technique and aren’t the logical and unavoidable development of it. When the technique loses this objectivity of judgement, it also loses the capability to be close to the reality of the world of today. It loses the fact that it should mainly take into account the social utility of their products; i.e. they should help humanity to live better in this world. The life of human on the earth is undermined by a technique that doesn’t put the human life itself at the centre of its attention. Data processing could become one of the totems of the present day. People give data processing and its enormous scope the task of solving many operational problems, of making really objective choices, of obliging the local authorities to perform rational and optimal intervention. Data processing, with its powerful equipment that would seem able to find the solution for every problem, has to be afraid mainly of its exasperating omnipresence, its ambitious independence and its underhand quantitative axiomatization. Data processing should be careful not to suffocate the reality of the product with its formal strictness that is often the result of many theoretical and practical compromises. Hoping to be not misunderstood, data processing is need, it must be enlarged and deepened as much as possible, but the final judgement of the practical results must be critically referred to reality. The evaluation must be critical, on the basis of experimental data realistically obtained by experimentation, of what this data processing can give. Data processing is necessary, but has to be critically evaluated. The simulation of many experimental data is one of the best possibilities offered to the technical operator by the power of data processing. However simulating something means to know already what is committed to the simulation; to this knowledge already acquired, the simulation doesn’t add too much: it just allows a little less subjective choice. Today data processing, in the field of information technology, requires new tools, involving discrete mathematics, like data compression, signal enhancement, data classification and understanding, hypertexts and multimedia (considering educational aspects too), because the mass of data implies automatic data management and doesn’t permit any a priori knowledge. The methodologies and procedures used in this class of problems concern different kinds of segmentation techniques and relational strategies, like clustering, parsing, vectorization, formalization, fitting and matching. On the other hand, the complexity of this approach imposes to perform optimal sampling and outlier detection just at the beginning, in order to define the set of data to be processed: rough data supply very poor information. For these reasons, no hypotheses about the distribution behavior of the data can be generally done and a judgement should be acquired by distribution-free inference only. The figure, enclose at the end of the paper, illustrates, step by step, the nearest neighbor procedure which is central in many methodologies and technicalities, presented in the follows. Notice that the actions of looking, seeing and recognizing, together with the aggregate of elements, like observer, point of view, scene objects, figures, etc., belong to the concept of vision, both concerning the problematic of Psychology and involving the field of Machine Vision. Anyway the authors should state that more information about very general methodologies and procedures, concerning the field of information technology, is still an open problem.

Access restriction

Copyright

fullscreen: Sharing and cooperation in geo-information technology

Monograph

Chapter

Chapter

Table of contents

Cite and reuse

Monograph

Chapter

Image

Image fragment

Citation links

Citation recommendation