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

damen, m. c. j.

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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

932 REFERENCES ID # ENTITY ENTITY DATA TYPE ATTRIBUTES SOURCE (unique random) (point line polygon) (bedrock surficial) (Can. Geol. Survey ) Figure 5. Standardized entity file 5.3 Datalogical Model As explained earlier, the point file (or points record type) is of great importance. Polygonal and line data refer to points, which are stored uniquely. But since several occurrences of polygons (adjacent polygons, for example) will refer to the same points, an auxiliary record type must be used. Lines and polygons can be represented by the same record type, which would carry an indicator as to whether a line or polygon is represented, with the assumption in the latter case that there is a line segment from the last point back to the first. Taking geological data as an example, the data record for a particular occurrence will contain information for a particular area, including a unique identifier, the source of the data, a pointer to the correct polygon in the line/polygon records and a pointer to the appropriate paradigm file. The structure of this data will be as shown in Figure 5. With some variations, survey control, hydrography, surface cover and DEM data can be handled in much the same way. For example, hydrography involves both line data (for rivers) and polygon data (for lakes), but can otherwise be handled as described above. Processing of DEM data, due to its complexity, will have to be handled by a special applications program outside of the DBMS. Within the data base it will suffice, therefore, to have some basic information, the DEM type, the source of the data etc., as well as a pointer to the correct data record in a separate file of DEM information. Transportation data, including such things as roads and power lines, can also be handled as described above, except that an extra "level" of information may be required. Different sections of a highway may have been built by different contrac tors, for example, and therefore there may have to be a record type which is subordinate to, or "owned by", the record type for roads, which describes a segment of a road that has constant attributes. 6. CONCLUSIONS Land related information systems are becoming more important as tools to assist in spatial data management. By interfacing such systems with modern data acquisition and storage technology, such as satellite remote sensing and data base management systems, further significant payoffs are possible. This paper has reported on research that is integrating a range of spatial data types into an LRIS. Apart from the normal range of conventionally derived thematic data, also included are remotely sensed data as well as DEM and survey data. This has resulted in design criteria involving a more complex conceptual model than would be typical of less comprehensive geographic information systems. As well, the research has resolved certain practical aspects of data acquisition and storage. What remains to be done is to complete the development of the prototype LRIS in order to undertake an evaluation of the system to assess its potential for more extensive application. Anderson, J.R. et al 1976. A land use and land cover classification system for use with remote sensor data. U.S.G.S. Prof. Paper 964. Barber, D.G. 1982. Geographic analysis for small computers. Computer Graphics Week, Harvard University, Cambridge, Mass., July 1982. Baxter, R.S. 1976. Computer and statistical techniques for planners. London, Methuen, 336 p. Bradley, J. 1982. File and data base techniques. New York, Holt, Rinehart and Winston. Burton, W. 1979. Implementation of the binary searchable grid chain representation for curves and regional boundaries. Geo-Proc., 1:1, p. 37-52. Colvocoresses, A.P. 1982. An automated mapping satel lite system (Mapsat). P.E.R.S., 48:10, p.1585-1591. Dangermond, J. and T. Burns 1986. A successful case study in geographic information implementation: Anchorage, Alaska. ACSM-ASPRS Annual Convention, Washington, March 1986, 3, p. 258-265. Dangermond, J. and C. Freedman 1984. Findings regarding a conceptual model of a municipal data base and implications for software design. Intern. Symp. on Spatial Data Handling, Zurich, Aug. 1984, II, p. 479-496. Date, C.J. 1986. An introduction to database sys tems. Fourth Ed. Reading, Mass., Addison-Wesley. Edson, D. 1975. Digitial cartographic data base: preliminary description. In John Kavalinas and Frederick Broome (eds.), Auto-Carto II, Intern. Symp. on Comp.-Assist. Cart., Sept.1985, p.523-538. Haralick, R.M. 1980. A spatial data structure for geographic information systems. In H. Freeman and G.G. Pieroni (eds.), Map Data Processing. New York, Academic Press, 374 p. Holmes, R.A. 1984. Advanced sensor systems: Thematic Mapper and beyond. R.S.E., 15, p. 213-221. Kozak, E.L. 1980. Land related information systems current situation analysis (User Survey). Working Paper, LRIS Coord. Proj. Edmonton, Bureau of Statistics Treasury, 40 p. Lodwick, G.D. 1981. A computer system for monitor ing environmental changes in multitemporal Landsat data. C.J.R.S, 7:1, p. 24-33. Lodwick, G.D. and S.H. Paine 1985. A digital eleva tion model of the Barnes Ice Cap derived from Landsat MSS data. P.E.R.S., 51:12, p. 1937-1944. LRIS 1981. Land-related information systems a net work concept. Report No. 2, LRIS Coord. Proj. Edmonton, Bureau of Statistics Treasury, 31 p. Mepham, M.P. and S.H. Paine 1986. An evaluation of storage methods for Landsat-derived raster data. ASPRS-ACSM Fall Convention, Anchorage, Sept. 1986. Miller, S.W. 1980. A compact raster format for handling spatial data. ACSM Fall Technical Meeting, Niagara, Oct. 1980, 18 p. Moore, R. et al 1984. Towards a CODASYL database for the U.K. river network. Intern. Symp. on Spatial Data Handling, Zurich, Aug. 1984, II, p. 574-575. Myhre, R.J. 1982. Satellite photos can aid naviga tion on aerial photo missions. P.E.R.S., 48:2, p. 275-279. Paine, S.H. 1984. Using Landsat imagery for position-based surface-cover mapping in the Rocky Mountains. C.J.R.S., 10:2, p. 190-200. Paine, S.H. and M.P. Mepham 1986. Spatial filtering of digital Landsat data for extraction of mapping information. Tenth Canadian Symposium on Remote Sensing, Edmonton, May 1986. Peucker, T.K. and N.R. Chrisman 1975. Cartographic data structures. The Amer. Cartog. 2:1, p. 55-69. Schreier, H. et al 1982. The use of digital multi date Landsat imagery in terrain classification. P.E.R.S., 148:1, p. 111-119. Welch, R. 1985. Cartographic potential of SPOT image data, P.E.R.S., 51:8, p. 1085-1091. Welch, R. et al 1985. Comparative evaluations of the geodetic accuracy and cartographic potential of Landsat-4 and Landsat-5 Thematic Mapper image data. P.E.R.S., 51:9, p. 1249-1262. Sym The anal alter Gerha Compre ABSTR major Resoui Sy s t e se 1ecl and t discur Speci base, mode 1 thè ci c r op s prò v ii deter repre: In coi base, to e v deteri Farmi evalu resu 1 and di 1. IN' The C Evalu a sys evalu from scena inc lu while or me the e produ in i commo The r by Cl adapt inven use, d e v e natur CRIES a) to resou many of b) tc su r v compa aided

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