Vegetation phenology from Sentinel 2 data: a GIS open source application

Lia Duarte; Sofia Scomparim; Ana Cláudia Teodoro

doi:10.1117/12.2636012

26 October 2022 Vegetation phenology from Sentinel 2 data: a GIS open source application

Lia Duarte, Sofia Scomparim, Ana Cláudia Teodoro

Proceedings Volume 12268, Earth Resources and Environmental Remote Sensing/GIS Applications XIII; 122680S (2022) https://doi.org/10.1117/12.2636012
Event: SPIE Remote Sensing, 2022, Berlin, Germany

Abstract

The vegetation phenology is defined as the seasonal timing of recurring biological events, the causes of their timing, their relationship to biotic and abiotic forces, and the interrelations among phases of the same or different species. Phenology is one of the most reliable indicators of vegetation dynamics. Geographical Information Systems (GIS) combined with freely available satellite imagery significantly contributes to the study of vegetation phenology. A GIS open-source application that estimates vegetation phenology metrics from time-series of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) as proxies for phenology was already been developed. The application was based on products from MODIS sensor (MOD13 data) and considered two crops, vineyards and maize. However, this application is now obsolete in the recent version of QGIS software. This work aims to develop an improved version of the open-source application to automatically extract the phenological metrics from a set of Sentinel 2 input data. Sentinel 2 has the advantage of also being free, with higher spatial, spectral, and temporal resolution, being particularly suitable for “in-season crop forecasting”. Several limitations found in the previous version can be surpassed with the use of Sentinel 2 data. For instance, the small farms, due to the presence of multiple land cover types within a pixel, can now be monitored with much greater confidence. The application is free and open source, so it can be modified according to the user requirements and adopted to different crops and regions.

Conference Presentation

Citation Download Citation

Lia Duarte, Sofia Scomparim, and Ana Cláudia Teodoro "Vegetation phenology from Sentinel 2 data: a GIS open source application", Proc. SPIE 12268, Earth Resources and Environmental Remote Sensing/GIS Applications XIII, 122680S (26 October 2022); https://doi.org/10.1117/12.2636012

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