Abstract:
The rapid changes in climate of a particular place can effect the lives of local peoples
and the area on which they are living. If we are able to detect those changes by
mapping the spatial and temporal features of the high resolution satellite image and
able to predict the changes before, then we can save ourselves from calamities. In
this paper we have used two version of ConvLSTM to capture the spatio-temporal
features of high resolution multi-spectral time series satellite images(Landsat-8 image
data) and predict the next frame. In the first model(basic ConvLSTM) we simply
use the ConvLSTM and predict the next image. The second model we have used is
ConvLSTM with additional layer of 3D convolution and 3D Trans-convolution with
extract more information about temporal and spatial features. The second model
is fast in compare to first basic ConvLSTM model. The predicted result are shown
in this paper after conducting experiments demonstrate that second model performs
better.
