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:: 6 Hydrology: Surface water, oceanography, coastal zone, ice and snow. Chairman: K. A. Ulbricht, Co-chairman: Mikio Takagi, Liaison: R. Spanhoff

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

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: Environmental assessment for large scale civil engineering projects with data of DTM and remote sensing. Taichi Oshima & Atsushi Rikimaru, Youichi Kato & Masaharu Nakamura

Document type:: Multivolume work

Structure type:: Chapter

745 sensing for Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 itat use by xedwood 849-857. chubert 1980. evels in 118. In .). The water , New York. LANDSAT nal of Environmental assessment for large scale civil engineering projects with data of DTM and remote sensing Taichi Oshima & Atsushi Rikimaru Hosei University, Faculty of Engineering, Tokyo, Japan Youichi Kato & Masaharu Nakamura Pasco Corporation, Tokyo, Japan The LANDSAT emote ion, Canadian atic Sciences :y 1978. A iff report. .1, D.A. Wilson resource data r Service, ABSTRACT This study describes in Pre-surveying in what way the authors manege and analyze the numerical data of topography or DTM data and remote sensing data for project management of water resource development in the mountain district. At first,the conditions such as topography,geology,vegetation and water resources of the projected area are analyzed together with DTM data and remote sensing data. Secondly,using the first step data,the estimation mapping for grade of weatherd granite and degree of landslide danger are analyzed by 'Maximum-likelihood method' and 'Similarity analysis'. Furthermore,the site proposed for re-development around the dam reservoir are selected and listed with the classified grade. lekas, and 1.SPECIFICATION OF RESEARCH >ed data to map .on in the (l)Using data Airborn MSS(M 2 S)data American Observed date 1983.3.19 iporation Flight altitude 2,000m LANDSAT MSS data ired data. Observed date 1980.10.30 )36. Path-121 Row-37 ;) 1977. The Digital terrain data erosion of the Data intervals 25m X 25m >idity of Data origin 1:10,000 scale map of Treasury, Data input Digital dramscanner 3. Aero photo Black & White il. Scale 1:12,500 Taken in 1974 Ln Ontario by Aero photo Color jp production. Scale 1:10,000 Taken in 1981 Dn Remote (2)Methodology Heat condition index :s (Ontario Cluster analysis Maximum likelihood method application of Similarity analysis Vegitation index Lronmental DTM analysis <shop on New Principal component analysis it: The (3)Test site The basins of the Kaze and Jobaru io. rivers.Those areas are located in 1985. Airborne Kyushu Island in Japan. lake in the (4)Structure of Research Bulletin. This reserch consists of 4 units. t project a. Basic data obtained b. Basic analysis Environmental c. Application analysis Report No. 8526! d. Assessment LANDSAT data The block diagram of general flow he basin - wide is shown in fig.l . tin. 21:931-940 Standards for ty in index 2.BASIC DATA OBTENTION AND ANALYSIS 03-ESM. 2.1 Airborne MSS data ( 1) Data acquisition Airborne MSS'data was acquired on March 19,1983 and flight altitude was 2,000m , therefore ground resolution is about 5m at nadir point. This MSS is BENu.CX Co. production , and it has ri bands, which are from blue-band to near infrared-band and also thermal infrared-band. MSS data was recorded by HDDT onboart with digital data. (2) Radiometric correction Radiometric data correction is necessary to eliminate image distortion caused by the temporal variation of solar radiadion and the spatial variation of path radiance effect and the viewing angle effect of the scanner. This correction system refers to black body data,skylight data,standerd reference lamp data of the inside of the scanner and also ground-truth gray target spectral data.On the other hand, the thermal infra red ban, and temperature calibration is also necessary, because of atmospheric absorption of thermal radia tion energy. This correction system refers to both high and low temperature black bodies,and also ground truth measurement data,which was mesured by a thermal infrared radiation thermometer at the same time of MSS operation. (3) Gecmetric Correction and Digital Mosaic Geometric data correction is the basic process for spatial superposition of multi-stage image (Airborne MSS and LANDSAT MSS) and mapping of image onto the DTM data. The schematic description of the correction process, three courses of airborne MSS data were connected to one image with digital mosaic analysis. (4) Thermal majority analysis image Using the majority process of the 3 X 3pixel filter, and normalization the small fluctuation. (5) Heat Condition Index Specific heat, heat capacity,and heat conduction, these parameters show the heat condition of the meterials. And these factors are deeply related to thermal image distri bution, especially characteristics of thermal continuity of plane space.Then heat condition process was done with the thermal stability model,which uses the standard deviation value of the 3X3 space filter. (6) Vegetation Index Analysis Using the spectral characteristics of chlorophyl-a, the image was processed as near-infrared band/red band. 2.2 LANDSAT DATA (1) Pre-processing Geometric correction was operated using several pairs of ground control data and resampling software system. The pixel size of result image is 25m X 25m . This size is just compatible to overlay on DTM data. (2) Vegetation Index Analysis The process and idea are the same as airborne MSS data. The effective bands of LANDSAT are near-IR band 7 / red band 5. (3) Lineament Analysis The processing method is 3X3 digital filter operation. And extracted lineament information is useful for application in topography,geomorphology and geology.

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