Abstract
Abstract. Monitoring observable processes in Satellite Image Time Series (SITS) is one of the crucial way to understand dynamics of our planet that is facing unexpected behaviors due to climate change. In this paper, we propose a novel method to assess the evolution of objects (and especially their surface) through time. To do so, we first build a space-time tree representation of image time series. The so-called space-time tree is a hierarchical representation of an image sequences into a nested set of nodes characterizing the observed regions at multiple spatial and temporal scales. Then, we measure for each node the spatial area occupied at each time sample, and we focus on its evolution through time. We thus define the spatio-temporal stability of each node. We use this attribute to identify and measure changing areas in a remotely-sensed scene. We illustrate the purpose of our method with some experiments in a coastal environment using Sentinel-2 images, and in a flood occurred area with Sentinel-1 images.
Highlights
1.1 MotivationDue to the climate change, it is crucial to have information about earth dynamics regularly
The authors built a graph from predefined objects and analyzed the evolution of an object through time. They aim to find objects which share a similar evolution. We focus on such evolution but propose to do so through the definition of a novel spatio-temporal stability measure computed from a morphological hierarchy
Our contributions are twofold: i) we propose a new attribute called spatio-temporal stability to describe the evolution of regions through time; ii) we demonstrate the practical interest of this attribute for Earth Observation with two applications related to monitoring of water areas: flood mapping from Sentinel-1 and intertidal monitoring with Sentinel-2
Summary
1.1 MotivationDue to the climate change, it is crucial to have information about earth dynamics regularly. Sea level rise is changing rapidly and up to date information about our earth is required. Remote sensing images enable us to observe our earth with improved technology. New satellite missions such as Sentinel provide effective temporal resolution with approximately 5 days revisit time. Satellite image time series (SITS) analysis continues to gain popularity in the literature. Such data combine spatial and temporal dimensions and they can be used for many problems such as assessing the temporal evolution of phenomena or objects (Meger et al, 2019). Accurate unsupervised methods are needed to understand our entire Earth without requirement of reference data
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
