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

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.

A new indicator for enhancing fire fuel mapping in Marivan forests, west of Iran

“…The use of these globally standardized MODIS vegetation indices is particularly advantageous as they are specifically designed to facilitate consistent spatial and temporal comparisons of vegetation conditions [28]. The MODIS NDVI products have been widely employed in several time series analyses of vegetation phenology [29,30]. The second dataset is the statistical data provided by Kurdistan Province's Department of Natural Resources and Watershed, which encompasses a very rough estimate of the fire incidences but misses precise locations (coordinates), area, type, and causes of reported fires.…”

Estimating Crop Sowing and Harvesting Dates Using Satellite Vegetation Index: A Comparative Analysis

“…To extract sowing and harvest dates from earth observation, several time-series methods have been developed [11,16,[18][19][20][21]. The first phenology extraction software is the TIMESAT, released in the early 2000s [2,22,23].…”