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:: 1 Visible and infrared data. Chairman: F. Quiel, Liaison: N J. Mulder

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: A GIS-based image processing system for agricultural purposes (GIPS/ALP) - A discussion on its concept. J. Jin King Liu

Document type:: Multivolume work

Structure type:: Chapter

27 sments by birds and adjoining farmland Logy. 16:349-358. Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 A GIS-based image processing system for agricultural purposes (GIPS/ALP) - A discussion on its concept J.Jin King Liu Remote Sensing Group, Energy and Mining Research/Service Organization, Industrial Technology Research Institute, Shin Chu, Taiwan AB^TRAC.. Taree major bottlenecks wnich hinder the development of a complete operational application of remote sensing tecnniques to the monitoring and survey in low to medium economic return agricultural areas are the data volume, classification accuracy and the geometric accuracy. A GIS-based image processing system for agricultural land use and land cover purposes (GIPS/ALP) is thus devised to resolve these difficulties. Instead of handling the whole lot of image data, this algorithm samples only a small fraction of them for processing and classification based on the polygon files of tne agricultural fields in the GIS. And, consequently, this approach dramatically reduces ti.e data volume ;hich has to be processed even when spatial resolution is greatly improved. In addition, tne classification accuracy is considerably improved due to the purity of the pixels chosen and high accessibility of ancillary data available in GIS. -he field check strategy modified by this system can contribute the general accuracy, too. The geometric accuracy can be as good as that .in the GIS which has been claimed to be considerably higher than that can be derived from the most sophisticated corrected images. / 1. INTRODUCTION This paper is intended to discuss the basic concept for implementing a GIS-based image processing system for agricultural land cover and land use purposes (GIPS/ALP). Firstly, the bottlenecks in image classification which have to be resolved for economical application of remotely sensed data are briefly sketched. Secondly, the basic concepts of GIPS/ALP are parsed by detailing the implementing approaches. Finally, the unique advantages of this new approach are concluded. 2 2. THE BOTTLENECKS IN IMAGE CLASSIFICATION Three major bottlenecks which hinder the development of a complete operational application of remote sensing techniques to the monitoring and survey in low to medium economic return agricultural areas are the data volume, classification accuracy and geometric accuracy. It is argued by Allan (1984) that the smaller the phenomena of concern and the more frequently they need to be monitored the less likely it is that the current remote sensing systems will provide useful data. This is especially true for the situation in Taiwan where the land use patterns are complex and the crop fields are rather small (usually less than 100 by 100 meters). The average accuracy obtained for the first level of land use/land cover classification (Anderson et al 1976) is 83%>, and it decreases to 58% for the second level (Tseng & Sung 1978).It is generally recognized that in most geographic information systems, remote sensing inputs do not represent the primary source of data (Marble & Puequet 1983) because that remote sensing data themselves are not thematic and their derived or classified resulcs are generally less accurate in both position and class level. It would be delightful if the geometric accuracy of remote sensing outputs is comparable or equivalent to that in the data base of geographic information system. The previous discussion means that if both the classification and geometric results are to be more accurate to meet the needs for the management of agricultural lands in the environments such as Taiwan, spatial, and spectral resolution of the remote sensing systems should be greatly improved. Suppose these two conditions are realized, another issue will be accordingly raised. It is that the volume of data which has to be processed in a single project would be too large, in reality, the limitation of spatial, spectral and temperal resolution of remote sensing data for effective operational applications to agricultural purposes are basically lied in the data volume. This is manifested in the diagram by Allan (1984) which shows that at present stage the vr.iurae of remotely sensed data is too large to be economically handled for the purpose of crop discrimination. A GIS—based processing approach is thus devised to resolve these difficulties. Instead of handling the whole lot of image data, this algorithm samples only a small fraction of them on bas^s of the polygon file of the agricultural fields in '-he GIS. Further discussion is given in the following. 3. THE BASIC CONCEPT OF GIS BASED IMAGE PROCESSING 3.1 GIS and TSS data files One of the data files in geographic information system is the polygon file of which a polygon is an ordered set of coordinate points enclosing a crop filed. Each polygon can be referred by a point called a POLYCENTRE or FIELDCENTRE locatec at the geometric centre of the polygon as shown in figure la. In the other hand, the data files in remote sensing system are digital images. An image consists of discrete picture elements called PIXELS of which the location in space is indicated implicitly by the relative position of each pixel in the image as shown in figure lb. The GIS polygon file records a relatively permanent ground feature, i.e. the crop boundaries or cadastral boundaries. However, the content or the land use type of each polygon is changeable. The land cover types in GIS stand only for the condition of a particular time of a particular season in the past. Neverthless, what a land use planer or manager is interested in is the extent of each cover type of present time or in the near future as well as the extent of changes between between two certain times. This information can be obtained, if a sample of eacn crop field

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