The strong urbanization impetus of developing countries leads to various urbanization phenomena such as building constructions, reconstructions and demolitions. It is desirable to monitor and recognize these changes by utilizing temporal and spatial information in an automatic way. In this paper, time-series segmentation and unsupervised classification are combined to mine and recognize segments of temporal change patterns. Our preliminary results show that the proposed approach is effective and reduces the negative consequences due to information inflation.
Temporal and Spatial Change Pattern Recognition by Means of Sentinel-1 SAR Time-Series
Che M.;Gamba P.
2020-01-01
Abstract
The strong urbanization impetus of developing countries leads to various urbanization phenomena such as building constructions, reconstructions and demolitions. It is desirable to monitor and recognize these changes by utilizing temporal and spatial information in an automatic way. In this paper, time-series segmentation and unsupervised classification are combined to mine and recognize segments of temporal change patterns. Our preliminary results show that the proposed approach is effective and reduces the negative consequences due to information inflation.File in questo prodotto:
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