Multitemporal Earth Observation Image Analysis

Remote Sensing Image Sequences

SCIENCES - Information Seeking in Images and Videos

Multitemporal Earth Observation Image Analysis

Edited by

Clément Mallet, LaSTIG Laboratory (Gustave Eiffel University, IGN, French Mapping Agency), France.
Nesrine Chehata, ENSEGID-Bordeaux INP, France.

ISBN : 9781789451764

Publication Date : August 2024

Hardcover 272 pp

165.00 USD



Earth observation has witnessed a unique paradigm change in the last decade with a diverse and ever-growing number of data sources. Among them, time series of remote sensing images has proven to be invaluable for numerous environmental and climate studies.

Multitemporal Earth Observation Image Analysis provides illustrations of recent methodological advances in data processing and information extraction from imagery, with an emphasis on the temporal dimension uncovered either by recent satellite constellations (in particular the Sentinels from the European Copernicus programme) or archival aerial images available in national archives.

The book shows how complementary data sources can be efficiently used, how spatial and temporal information can be leveraged for biophysical parameter estimation, classification of land surfaces and object tracking, as well as how standard machine learning and state-of-the-art deep learning solutions can solve complex problems with real-world applications.


1. Broader Application of the Time-SIFT Method: Proof-of-Concept of 3-D-Monitoring Study Cases with Various Spatiotemporal Scales, Denis Feurer, Sean Bemis, Guillaume Coulouma, Hatem Mabrouk, Sylvain Massuel, Romina Vanessa Barbosa, Yoann Thomas, Jérôme Ammann and Fabrice Vinatier.
2. Hierarchical Crop Mapping from Satellite Image Sequences with Recurrent Neural Networks, Mehmet Ozgur Turkoglu, Stefano D'Aronco, Konrad Schindler and Jan Dirk Wegner.
3. Exploiting Multitemporal Multispectral High-resolution Satellite Data toward Annual Land Cover and Crop Type Mapping: A Case Study in Greece, Christina Karakizi, Konstantinos Karantzalos and Zacharias Kandylakis.
4. Irrigation Monitoring Using High Spatial and Temporal Resolutions Remote Sensing Time Series, Hassan Bazzi and Nicolas Baghdadi.
5. Trends in Satellite Time Series Processing for Vegetation Phenology Monitoring, Santiago Belda, Luca Pipia and Jochem Verrelst.
6. Data-Driven Spatio-Temporal Interpolation for Satellite-Derived Geophysical Tracers, Maxime Beauchamp and Ronan Fablet.
7. Recent Advances in Tropical Cyclone Forecasting Using Machine Learning on Reanalysis and Remote Sensing, Sophie Giffard-Roisin.

About the authors/editors

Clément Mallet is a senior scientist in remote sensing for land-cover mapping issues at the LaSTIG Laboratory (Gustave Eiffel University, IGN, French Mapping Agency), France. He is also Editor-in-Chief of the ISPRS Journal of Photogrammetry and Remote Sensing.

Nesrine Chehata is a senior lecturer in geomatics and AI for Earth observation at ENSEGID-Bordeaux INP, France. She is also President and Co-founder of AGEOS (African Association for Geospatial Development), President of FNAACC (National Forum of Climate Change Adaptation Actors in Tunisia) and an IEEE GRSS senior member.

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