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:: 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:: Regional geologic mapping of digitally enhanced Landsat imagery in the southcentral Alborz mountains of northern Iran. Sima Bagheri, Ralph W. Kiefer

Document type:: Multivolume work

Structure type:: Chapter

556 1 NlN hn» . r * «SIS Figure 2 ' ■ % ••Wfl» { «* 1ME» *i v , .«teff h3 ■ - f ' - Figure 1. The Study Site (southcentral Alborz Mountains of northern Iran) Landsat MSS Band 5 image - scale about 1:1,600,000. The visual image interpretation was accomplished by means of a color additive viewer using 70mm black and white film positives of the four Landsat MSS bands. The interpretation depended upon the evaluation of image tone, texture, fabric and relief. Another visual image interpretation method was the use of Ronchi rulings for analyzing images to identify linear features. The Ronchi ruling used in this study is a diffraction grating having a spacing of 79 line pairs per centimeter. When the ruling is rotated between the eyes and the Landsat image, lines on the image that are perpendicular to the direction of ruling are enhanced (by diffraction), and lines in other directions become diffuse (Pohn, 1978). The computer-assisted image interpretation techniques provided superior results to the visual image inter pretation techniques. Spectral band ratioing was attempted, using blue for the MSS band ratio 5/4, green for MSS 7/6, and red for MSS 6/5. This technique did not enhance faults and other lineaments. It did, however, provide a clearer picture of alluvial deposits of different ages. The second method of analysis was computer-assisted image processing of Landsat digital data in which the lineaments were enhanced for the purpose of inter pretation. In geological analysis, enhancement techniques are often performed on band 7 which is the preferred near-infrared band. The enhancement routines used here are suitable for diverse topo graphy and complex structural geology. The enhance ment is a form of digital image processing and involves the adjustment of brightness value for each individual pixel. Potentially useful enhancements include contrast stretching (linear, non-linear), band ratioing, high pass filtering and diagonal derivative processing. The most effective enhanced product for this study was computer-enhanced high- pass-filtered, contrast-stretched image of MSS band 7, as shown in Figure 2. This enhancement facil itated the interpretation and was especially useful in distinguishing between structural features and artifacts. The lineament map (Figure 3) was produced from the computer-enhanced Landsat data and is based on the application of the following criteria for lineament identification (Short & Lowman, 1973): (1) lines of variable length, straightness and continuity which are differentiated by tonal contrast in images; (2) tonal discontinuities; (3) bands of variable width which contrast in tone to the area immediately adjacent; (4) alignment of topographic forms; (5) alignment of drainage patterns; (6) association of vegetation along linear trends; and (7) co alignment of cultural features (e.g., farms, roads pattern, etc.) with underlying structural and/or surrounding topographical control. In addition to enhancement algorithms, an attempt was made to obtain a lithological classification using computer-based spectral pattern recognition. The classification routine was applied to the Landsat MSS data set in order to discriminate rock types by focusing on both sides of major lineaments and by attempting to identify whether the structural break occurs at near, or at some depth beneath, the surface. This discrimination provides an alternative Figure 3 concept tc can be geophysics ation. Ac ination cc cal mappi within the It should niques ha applicatic to the fa on cover c homogenity spectral s A superv classifier pixels in on the c programs. by field

Access restriction

Copyright

fullscreen: Remote sensing for resources development and environmental management (Volume 2)

Multivolume work

Volume

Chapter

Chapter

Table of contents

Cite and reuse

Volume

Chapter

Image

Image fragment

Citation links

Citation recommendation