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:: 856343064

Title:: Remote sensing for resources development and environmental management

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

Scope:: XV, 547 Seiten

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856343064

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(26,7,1)

Language:: English

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

Editor:: Damen, M. C. J.

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:: 4 Renewable resources in rural areas: Vegetation, forestry, agriculture, soil survey, land and water use. Chairman: J. Besenicar, Liaisons: M. Molenaar, Th. A. de Boer

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: An efficient classification scheme for verifying lack fidelity of existing county level findings to cultivated land cover areas. Yang Kai, Lin Kaiyu, Chen Jun & Lu Jian

Document type:: Multivolume work

Structure type:: Chapter

Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 541 An efficient classification scheme for verifying lack fidelity of existing county level findings to cultivated land cover areas Yang Kai, Lin Kaiyu, Chen Jun & Lu Jian Wuhan Technical University of Surveying and Mapping, China ABSTRACT: In order to verify the lack fidelity of existing findings to cultivated land cover areas in county level for the purpose of rural economical planning, a special com puter aidded classification scheme has been tested and is introduced in this paper. The schene consists of three main aspects, namely the preprocessing of IANDSAT MSS multitem poral image data, the selecting of optimum feature image set and the classification pro cessing with auxiliary ground height information. Based on this schene, the improvement of classification accuracy amongting to 8% was obtained, and the man-male mistakes in existing findings of testing county have been checked out. 1. Introduction In order to meet the needs of planning for develo ping- rural economies, it is neccesory for the author ities of different level's goverments to know the actual situation of land cover types. But unfortu nately, the existing county level findings in ques tion in China are mostly not reliable enough for planning purpose. This is because not only of the technical reasons, but mainly of the historical and man-made reasons, for instance, the definition of distal ce or area measure for cultivated land was not corresponding to the couversion between Chinese rule and metric one; and the peasents used to report the cultivated land areas less than actual one for paying less agricultural tax. However, the uncorrectness of existing findings to cultivated land was rather systenatical, especially within a local regin. So it becomes possible to estimate the actual cultiva ted lend areas all over the regin, by determining the correction factor from some sampling area, e.g. a typical county. This is the main purpose of our subject. Under above description, the next question could be hov can detormine the actual land cover situation in county level. There are options, the one is based on cor ventional photogrammetry procedure which is accurate but time consuming; the other is based on satellite remote sensing techniques which is less accurate than the former but rather time saving. We have chosen the latter one. Of course, the problem following our choice is to design a scheme to impro ve the classification accuracy based on satellite images, which is the key point that our research subject was going to solve. Our classification scheme can be cha.racterrized by following key words: LANDSAT images; multitem poral data, image transformation in multispectral domair, feature image selection, and computer-aided classification with auxiliary ground height informa tion. The principle of the scheme and corresponding experimental results will be introduced as follows. 2. Pieparation of basic image data The Xian-ning county of Hubei province in China was selected as sampling and testing area. Three types of basic image data, were neccesary for performing the classification scheme, namely: 1. origional LANDSAT MSS images within the county bound ery. In this experiment two-temporal LANDSAT MSS images with total 8 bands were used, which were seperately imaged on Oct. 16, 1978 (digital image CCT) and on June 16, 1979 (negtives with scale 1:3*36 million). Three steps was needed to form the required image windows as shown in figure 1 (taking one band as example). (a) read (or scan) a rectangular image window covering testing county area from the raw image carrievs; (b) digitally rectify the image window based on selected control points; (c) digitally mask the rectified image and form the image windows within the county boundary. 2. digital terrain model (DTM) image The DTM image in our exeriment was created by direct reading the height value of DTM grid with 200m intervals on existing topographic map. Then it is densified in computer by interpola.tion method for each DTM pixels which have the same geometric resolusion as origional image ha.s. 3* real ground feature encoding image in selected sampling areas vVithin the testing county area six sampling area.s selected, which were distributed at typical parts of the county, seperately with the height range; (1) 0 - 20m, (2) 21 - 50m, (3) 51 - 100m, (4) 101 - 200m and (5) 201 - 900m. Each of them has 60 x 60 pixels whose class attribute has been Figure 1. image window within county boundary.

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