A Web Service for Phenology Metrics Extraction from Big Earth Observation Data

Phenology is the study of timing recurrent biological events, being an important indicator of annual plant growth. From remote sensing images, it is possible to obtain metrics used for phenological monitoring, which are useful in understanding vegetation dynamics. Although there are many implementations for estimating crop phenology from remote sensing data, these implementations require software package installation and programming skills to use them. Besides that, analysts face with hardware limitations to process the big Earth observation (EO) data currently available from different providers. To minimize these efforts and limitations, this paper presents a web service called Web Crop Phenology Metrics Service (WCPMS) to extract phenological metrics from large volumes of remote sensing images modeled as multidimensional data cubes, produced by the Brazil Data Cube (BDC) project of the National Institute for Space Research (INPE). WCPMS allows analysts to calculate phenology metrics from big image data sets without needing to download them or to install software tools on personal computers. This paper describes the WCPMS architecture and Jupyter notebooks with examples about how to use it.