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:: Simple classifiers of satellite data for hydrologic modelling. R. S.Drayton, T. R. E. Chidley & W. C. Collins

Document type:: Multivolume work

Structure type:: Chapter

Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 709 Simple classifiers of satellite data for hydrologic modelling R.S.Drayton University College, Cardiff, UK T.R.E.Chidley & W.C.Collins University of Aston, Birmingham, UK ABSTRACT: Hydrological models are normally based on parameters extracted from conventional maps such as drainage density and land cover. In this paper we examine the use of parameters derived from thematic classif ications of satellite imagery. The advantage of this technique is that the satellite image becomes an up-to- date, easily managed source of data for monitoring of water resources. The methods of classification range ■'from simple density slicing to supervised classification. A model was constructed in which run-off character istics were regressed on thematic classifications. The problem of achieving sufficient variance in the hydro- logical parameters within one satellite image are discussed, and recommendations for distributed modelling are made. 1 INTRODUCTION One of the principal aims of applied hydrology is to make estimates of streamflow. Frequently, the hydro logist is asked to mak- such estimates in the absence of observed, historic streamflows, and is required to use his skills to construct mathematical models which can predict future flows. These fall into two broad categories: statistical models which provide estimates of river flows having a specified probabi lity, or process models which provide estimates of streamflow resulting from certain specified rainfall sequences. In this paper we investigate the ways in which satellite data can be employed in such models. The advantage of this approach is that the rectified and classified image becomes an up-to-date, easily manageable source of data for monitoring water resources. The obvious but rather uninspired way to use satel lite data is to construct the conventional maps from which existing hydrological models draw their inform ation. The benefits of timelines and global coverage have been claimed many times, while the limitations of satellite sensors in evaluating hydrological variables have been explored by Rango et al, 1983 (thematic features) and by Drayton and Chidley, 1985 (geomorphic features). The conclusion appears to be that satellite sensors may be used to evaluate con ventional parameters to a precision suitable for regional models. A far more promising approach is to construct new models which are appropriate to the view of the world offered by the satellites. The fundamental difference in this view is that it is holistic; it brings to gether the various aspects of the earth's surface rather than separating them, as happens with maps. Thus, the reflectance of a patch of ground depends not only on its vegetal cover, its soil type and its moisture content, but also on the interactions which occur between them, and with climate. All of this information is also relevant to its hydrological response, and is conveniently integrated or compres sed into this single characteristic, namely its spectral signature. Thus the judicious use of para meters based on spectral characteristics is likely to yield hydrological parameters which are far more powerful than any parameters derived from maps. Thus, our aim was to produce interpretations of our study catchments, based on their spectral properties, to build hydrological models around them, and to compare their efficiency with existing models using conventional classifications. This is different from the approach by Gurnell et al (1985) in which it was heathland vegetation which was considered to be the mechanism which brought the hydrological information together, and the satellite systems were used only to monitor the heathland. The benefits of using satellite data are not con fined to thematic considerations alone. There is an enormous benefit to be gained from the structure and organisation of the data, which is distributed uniformly over the scene, and is organised in a regular grid cell structure. Distributed hydrologic models do exist but their usefulness has been diminished by the logistical problems of estimating values at many node points. Satellite data is clearly well provided with the means to overcome such problems. Our current work is concerned with ways in which the holistic nature of satellite data can be pres erved in hydrological models. As a first step we have examined its use in "lumped" models, so that the thematic benefits can be clearly distinguished from those of distribution. Work is in hand to examine the benefits of data structure, in relation to finite difference groundwater models, and will be reported later. 2 BACKGROUND TO MODEL The study reported here was based on a group of river basins in the South Wales area, for which hydrologic data were available. (For details see Chidley and Drayton, 1985). Although lying within the same region the basins show a good variety of vegetal, geologic and climatic characteristics. Our aim was to evaluate the usefulness of the thematic classifications which are unique to satel lite data. So, as a first step we considered a lumped model in which we could eliminate the benefits derived from distributed data. We considered a gen eralised lumped rainfall-runoff model, which would provide estimates of annual runoff (catchment yield), based on the inputs of annual rainfall and a set of characteristics evaluated from the satellite data. We assumed that any one year's runoff could be considered as being composed of the sum of runoff from n different runoff types, and that each type has a response which depends on the magnitude of rainfall. Then total runoff, RO = E f(RF) A n n n In this exploratory model we assume that the distribution of run off types is constant from year to year. Then the model reduces to the simple statement

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