Remote sensing for resources development and environmental management: Remote sensing for resources development and environmental management

Damen, M. C. J.

Bibliographic data

Multivolume work

Persistent identifier:: 856342815

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856342815

Language:: English

Additional Notes:: Volume 1-3 erschienen von 1986-1988

Editor:: Damen, M. C. J.

Document type:: Multivolume work

Volume

Persistent identifier:: 856641294

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Scope:: IX Seiten, Seiten 551-956

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A,. A. Balkema

Identifier (digital):: 856641294

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(26,7,2)

Language:: English

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

Editor:: Damen, M. C. J.

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:: 8 Geo-information systems. Chairman: J. J. Nossin

Write comment:: Wegen zu enger Bindung kommt es teilweise im Original zu Textverlust.

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: A comprehensive LRIS of the Kananaskis Valley using Landsat data. G. D. Lodwick, S. H. Paine, M. P. Mepham & A. W. Colijn

Document type:: Multivolume work

Structure type:: Chapter

in the database ilationship is lat properties, icular property what properties th the property on of adjacency plicitly encode SURVEY CONTROL V files s that will be i to a specific y to cover only i quick response desirable that ist in the area ng the inquiry, dex is being will be divided l tiles. These in terms of the s is no plan to h map sheets or f the earth’s timize the size >t is more than retrieval time, iber of entities i tile, and the sgion covered by n been proposed ept listing the red by the tile, to restrict the e entities that of interest. 1 be defined by Dverlapping the fy the entities istrates how the . Usually, the m required, but >ical approaches e discussed in The relational arity, as shown M's DB2 (Date, it is necessary se analogue of processing, and mnections among :k approach, on >rd types, the so necessary to INDEX_1 R0AD_17 PT 921 .. . PT 1004 INDEX_2 WELL_2 3 PLAN 24 PT 5197 . . . PT 5203 INDEX_3 R0AD_17 PT_1004 . . . PT_1029 PLAN_92 INDEX_4 R0AD_17 PT_1029 . . . PT_1102 PLAN 24 PT 5203 . . . PT 5197 sets. Restricted access (such as read-only access) for certain classes of users, oi different "user views", can be provided by means of different subschemas. And, on the VAX-11 DBMS in particular, retrieval efficiency can be optimized by means of a storage schema, which provides details on such things as indices, and attempts to store related items on the same page of disk storage. 5.2 Infological Model The infological model is related to human concepts and real world representation. In other words the data are organized in terms of representing reality the way humans perceive it. The most common infological model is a hierarchical tree structure which would break the data into levels as shown in Figure 4. This type of model is feasible to implement in a database but it does have some limitations. If there are a large number of classes near the root of the tree it is difficult to navigate around the data to establish and utilize the various relationships. This type of model also has a problem with data redundancy, which arises from the need for each entity to have its own non-unique attributes. This results in nonstandardized entity/attribute records, where a geology polygon would require fewer record fields than the same polygon representing surface cover. Figure 3. Spatial indexing define connections between different record types. These connections are defined by means of DBTG (Database Task Group) sets. The relational approach offers the advantage of flexibility, since there are no pre-defined link ages. Any query that can be formulated in the query language can be accomplished. For this reason, relational DBMSs, such as ARC/INFO (Dangermond and Freedman, 1984), are popular for LRIS design. The network approach, on the other hand, offers the potential advantage of greater efficiency of those queries for which suitable linkages have been pre-defined. Of course, when suitable DBTG sets have not been pre-defined, a query may either be impossible or very inefficient to answer. In a network database one is said to "navigate" through the database, and in such a database system it is necessary to structure the record types and DBTG sets in such a way tnat frequently occurring queries can be satisfied by relatively simple navigation through the database. As a general rule, the inclusion of more DBTG sets improves retrieval speed, but may make the speed of updating, both insertion of new records and changing values in existing records, slower, because more pointers and indexes must be changed. In the current project much of the data is not volatile; much of it will change rarely, if ever. Even those data that do change will not need to be updated in "real-time". Consequently, the design of the database is oriented toward efficient retrieval at the cost of slower updates. GEOLOGY SURFICIAL BEDROCK ALLUVIUM COLLUVIUM AEOLIAN SEDIMENTARY METAMORPHIC IGNEOUS Figure 4. Hierarchical infological model With these limitations in mind, a different infological model has been designed. This model also takes into account the nature of the network database model, which allows definition of backwards and forwards file pointers. This infological model utilizes paradigm files to reduce redundancy and to allow easier navigation and establishment of rela tionships. A paradigm file contains a set of standardized entity attribute records as shown in Table 2. Table 2. Geologic bedrock paradigm file. Geologic Geologic Formation Rock Structure code age name type D Devonian undiff Dbf Devonian Banff Dbw Devonian Bow J Jurassic undiff Jcl Jurassic Coleman This prototype LRIS will use the VAX-11 DBMS, which is a "CODASYL compliant" network data base management system, and which runs under the VMS operating system on a DEC VAX-11/750. A good Fortran interface, and the retrieval efficiencies that are possible with a network database system are among the reasons for choosing it. As with all CODASYL network DBMS's, a database is defined by defining a schema, which contains, among other things, definitions of the record types and the DBTG These paradigm files are very stable, allowing easy updating and multiple entry to and from various different entities. Thus, it is possible to standardize the basic entity attribute record structure by utilizing the pointers to these files as shown in Figure 5. This reduces data redundancy in many cases and provides a framework for the definition of the relationships between the various data.

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