Satellite “Image-Banks” in Forest Information Systems? Prospects for Accurate Estimation of Forest Change and Growth from Data-Fusion Models.

Keith Rennolls
School of Computing and Mathematical Sciences,
University of Greenwich, London SE10 9LS, UK.

Forest Information Services and Systems (FISs)  are becoming increasingly numerous largely because of the relatively recent increased ease of development of distributed  systems  within the context of the Internet and WWW.  Such systems vary both in design and implementation.  Some systems use remote sensed imagery, and in particular satellite imagery, as their primary data source for land-use map construction.  It seems, in general, on a rather longer time scale, such systems discard their base  imagery, and offer maps and  summary  tables  as  their information products. Others FISs make no use of remotely sensed imagery. We ask the question: what FISs use sequences of satellite imagery as a continuing explicit feature of their information offerings, either as a means or  adjuct to information display, or a means of re-analysis? A partial review is conducted in relation to this question with  the  answer “very few”.  It is argued and  conjectured that any FIS concerned with spatially explicit information, on Forests, the Environment, or land-use in general, which aims to be flexible in terms of what is mapped, which aims to be accurate in estimating and mapping change, and to make forecasts, MUST, in the long term, retain and make adaptive use of historical series of satellite imagery. This conjecture is based on  the  fact that any map, no matter how good, is just a particular model, calibrated at one time, from the currently available data. Re-analysis and improved modelling with new data demands access to the old raw data!  The reviewed FISs are examined in relation to this conjecture.  The paper considers some of the problems involved in making use of historical  series  of  satellite  imagery, and makes some suggestions on how FISs of the future might make use image-fusion modelling techniques to make the conjecture become a fact.

Keywords: Forest Information System, remotely sensed images, historical series, accuracy, spatio-temporal models, image-fusion, change-detection.

In: McRoberts, R. et al. (eds).  Proceedings of the joint meeting of The 6th International Symposium On Spatial Accuracy Assessment In Natural Resources and Environmental Sciences and The 15th Annual Conference of The International Environmetrics Society, June 28 – July 1 2004, Portland, Maine, USA.

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