Recent Advances in Land Surface Phenology Estimation with Multispectral Sensing

Irini Soubry, Ioannis Manakos, Chariton Kalaitzidis

Abstract

Vegetation phenology refers to changes in seasonal patterns of vegetation cycles, such as flowering and leaf fall, influenced by annual and seasonal fluctuations of biotic and abiotic drivers. Information about phenology is crucial for unravelling the underlying biological processes across vegetation communities in space and time. It is also important for ecosystem and resources management, conservation, restoration, policy and decision-making on local, national, and global scales. Numerous approaches to register Land Surface Phenology (LSP) appeared since Earth Observation from space became possible a few decades ago. This paper attempts to capture current progress and new capacities that arose with the advent of the free data policy, the Sentinel-era, new multispectral satellite sensors, cloud computing, and machine learning in LSP for natural and semi-natural environments. Spaceborne sensors’ capacity to capture LSP, data fusion, and synergies are discussed. Information about retrieval methods through open-source tools and global LSP products and phenology networks are presented.

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Paper Citation


in Harvard Style

Soubry I., Manakos I. and Kalaitzidis C. (2021). Recent Advances in Land Surface Phenology Estimation with Multispectral Sensing. In Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM, ISBN 978-989-758-503-6, pages 134-145. DOI: 10.5220/0010555801340145


in Bibtex Style

@conference{gistam21,
author={Irini Soubry and Ioannis Manakos and Chariton Kalaitzidis},
title={Recent Advances in Land Surface Phenology Estimation with Multispectral Sensing},
booktitle={Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,},
year={2021},
pages={134-145},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010555801340145},
isbn={978-989-758-503-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - Recent Advances in Land Surface Phenology Estimation with Multispectral Sensing
SN - 978-989-758-503-6
AU - Soubry I.
AU - Manakos I.
AU - Kalaitzidis C.
PY - 2021
SP - 134
EP - 145
DO - 10.5220/0010555801340145