MULTI-TEMPORAL SPATIAL DATA AFRICA
To plan for the future, it is essential to understand the present as well as the past. Hindsight is the most valuable asset when examining how to proceed. Apart from natural catastrophes, conditions do not happen, they develop! This paper proposes that in order to change or influence conditions, not...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2017-11-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W2/27/2017/isprs-archives-XLII-3-W2-27-2017.pdf |
| Summary: | To plan for the future, it is essential to understand the present as well as the past. Hindsight is the most valuable asset when examining how to proceed. Apart from natural catastrophes, conditions do not happen, they develop! This paper proposes that in order to change or influence conditions, not only must their present state be considered, but it is essential to investigate what triggered them in the first place. This requires access to records that might have to reach back for as much as many years. In Africa, such records are hard, if not impossible, to retrieve. Moreover, whatever records can be located are likely to have been compiled by a variety of different agencies, each presenting their own versions of events and consequently, often contradictory. To overcome such problems, it is proposed to use aerial photography that has been taken and hopefully archived over the past decades. Such aerial imagery can provide temporal geospatial data to trace the course, interaction and consequences of events. Combined with more recent satellite imagery, they provide unbiased evidence of past developments that can now be analyzed and assessed based on our awareness of today. This presentation deals with advanced data conversion and automated processing procedures conceived for convenient and user-friendly information access, as well as data mining and bigdata processing. |
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| ISSN: | 1682-1750 2194-9034 |