Basic information
Original title:
Methodology of Multitemporal Multisensor Satellite Image Analysis
Acronym:
M3Sat
Researchers involved:
, ,
 
Duration:
1 July 2018–30 June 2022
Code:
J2-9251
Description

This project objective is to systematically evaluate existing satellite image time series (pre)processing approaches and develop a general processing time series analysis workflow for various applications, combined with the in-depth study of the impact of time series data properties (like radiometric features and density) on time series analysis and applications.

The final reliability and usefulness of time series results for a selected application depend on the data quality, the length and density of time series and the selected processing methods. In the project, we will presume radiometric and geometric adequacy of satellite data, and focus more on the multi-sensor harmonization, the generation of time series and validation of the most critical processing steps and their effect on final quality of results.

The consistency of the data is one of the main prerequisites in time series analysis, therefore calibration of sensor and image differences and harmonization of time series are very important tasks.

In terms of this perspective, the project focuses on the following objectives:

•          Development of a generic method for multi-sensor data calibration,

•          Harmonization of different sensor data into a single, long and dense time series,

•          Application of (massive) cloud data processing,

•          Systematic evaluation of the latest time series analysis algorithms (software tools), and

•          Observation of selected events and phenomena in Slovenia.

The goal is to facilitate multi-sensor data time series and achieve a multi-sensor harmonisation. The main objective of the project is to assess and improve the consistency of medium and high-resolution multi-sensor time series.

Project steps

The work is divided into five work packages:

•          WP 1: Data collection and analysis of multi-sensor fusion and calibration approaches

•          WP 2: Generation of long and dense time series

•          WP 3: Time series analysis

•          WP 4: Evaluation of the time series processing methodology for selected applications

•          WP 5: Project management

Lead partner

Project manager

Project manager at ZRC

Funded by

Slovenian Research Agency

Fields of research

Remote sensing T181 

Keywords

remote sensing • satellite data • high resolution • data harmonization • time series • time series analysis