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:: 5 Non-renewable resources: Geology, geomorphology and engineering projects. Chairman: J. V. Taranik, Liaison: B. N. Koopmans

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

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: An evaluation of potential uranium deposit area by Landsat data analysis in Officer basin, South-Western part of Australia. H. Wada & K. Koide, Y. Maruyama & M. Nasu

Document type:: Multivolume work

Structure type:: Chapter

680 Figure 2. An outline of geology 4 DEPTH ESTIMATION OF THE SEDIMENTARY ROCKS 4.1 Hypothesis for estimation Basement rocks mainly are affected by mechanical ero sion agency under arid and semi arid climate. This hypothesis was presended by Bildel (1957) as the con ception of "double surface of leveling" (see figure 4), According to his conception the level of the sediment surface is changed by flood and climatic condition, (a) Wash plain of seasonal flooding is as much as 100 m above the weathering front. Pediments fringe the wash plain, (b) Wash plain is lowered by rejuvenation or climatic change. Inselberg and marginal pediments are exhumed or regraded to the lowered wash plain. This geomorphological process indicate that the wash plain being more extensive area or longer distance among inselbergs, have relatively deeper sedimentary deposits. Using this hypothesis, depth estimation was done with Landsat imagery data. rocks. sity depth 30° S Lower surface: basal surface of deep weathering (a) Recessional or rim inselberg Figure 3* Process of evaluation 3 METHOD 3.1 Data Landsat MSS (CCT) path 115 row 8l DATE 6th February 1973 3.2 Process of evaluation After several trial, depth estimation of sedimentary rocks, land coverage, ratio images are employed for the evaluation. Process of study is shown on the figure 3- Figure 4. Schematic explanation of hypothesis of "double surface leveling" 4.2 Depth estimation map The map is prepared with the following processes. (1) Basement rocks distribution Because of the heterogeneous nature of the study area, the unsupervised classification method is used. The analytical process involved the clustering method using an algorithum to divide the four-channel Land sat data into groups of points having homogeneous spectral characteristics. Coverage type was classified into sixteen items by the clustering. Then, three of them are interpreted that basement rocks are comming on or near the ground surface, by means of the ground survey and aerial photo-analysis. This pixel map is called "Basement rock distribution map". (2) Density of basement rocks Number of pixel classified to basement rock were counted in each mesh unit, 1 Km x lKm. The maximum number of it is 100, and minimum is 0. The original distribution map is shown on Fig. 5.a. The result was, however, too noisy to understand the trend of its distribution. Then, smoothing technique was em ployed to solve this problem. The original data was replaced by the average number of basement rock pixels of the surrounding mesh units. The smoothing window size was examined by 5 Km x 5Km, 7 Km x 7Km, and 9 Km x 9 Km. In this case window size, 9 Km x 9 Km was the most reliable for the purpouse (Fig. 5.b). (b) B B 0 (3) Depth estimation Basically trend of basement rock density must be Figure

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