Lychee tree health monitoring and anomaly detection using multispectral satellite imagery in Tezpur, Assam

Sanjit Maitra; Rituraj Gogoi

doi:10.1117/12.2682776

20 October 2023 Lychee tree health monitoring and anomaly detection using multispectral satellite imagery in Tezpur, Assam

Sanjit Maitra, Rituraj Gogoi

Author Affiliations +

Proceedings Volume 12727, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV; 127271B (2023) https://doi.org/10.1117/12.2682776
Event: SPIE Remote Sensing, 2023, Amsterdam, Netherlands

Abstract

Lychee is a tropical evergreen fruit which is mainly produced in South-East Asian countries. The north-eastern state of Assam in India is one of the largest exporters of lychee which mainly comes from areas around Tezpur town in the district. Health monitoring is critical in the region which is capable to trigger alarm in case of abnormalities during the growing season itself such that necessary steps can be taken to limit the damage. The proposed method tracks the photosynthetic activity through indices as an indicator of the health. This supervised approach considers the usual growth pattern as training set to define the normal growth using satellite image derived indices. The behavior pattern on the test time series sequence which is not conforming to the usual growth pattern is tagged as anomalous incorporating the temporal variation of the indicators across seasons and within class variability of the different types of the lychee trees present in the area of study.

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(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Sanjit Maitra and Rituraj Gogoi "Lychee tree health monitoring and anomaly detection using multispectral satellite imagery in Tezpur, Assam", Proc. SPIE 12727, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV, 127271B (20 October 2023); https://doi.org/10.1117/12.2682776

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KEYWORDS

Earth observing sensors

Satellite imaging

Satellites

Multispectral imaging

Image fusion

Crop monitoring

Data modeling

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