Time Series Indicators

Four experimental prototypes have been developed related to Indicators and Variables as part of WP41: Crop growth condition (CGC), Crop Emergence Date (CED) Map, Generic Land Cover Metrics and Multi-annual trends & potential change

Example: Crop Growth Conditon:

This prototype relies on Sentinel-2 time series, focussing on the most important time slots within the growing cycle of the crop types.
Production: In this specific case, the LAI is actually a GAI being not limited to the one-sided green leaf area per unit ground surface – as it is usually the case – but taking into account that in the case of cereals, the whole plant shows photosynthetic activity. The LAI/GAI is calculated with the BVnet algorithm with reflectance values deriving from the ProSail radiative transfer model. This model uses the Sentinel-2 bands at 10 m and 20 m-resolution except the blue band (B2) and the B8 due to its
overlap with B7 and B8a.


Method: The method aims at retrieving important growing parameters per crop, per period and per
parcel to get a detailed profile of the crop development by applying the following steps:

  • Identification of crop types at parcel level with the help of LPIS data

  • Verification of the LAI profiles for winter barley, winter wheat and maize at parcel level with the local average profile

  • Retrieving growing conditions per crop type, i.e. crop development in terms of earliness, maximum, maturity and management aspects such as time for sowing and harvesting.

Improvement: This product allows to identify local marginal behaviour along the season in terms of crop growth cycle, crop development or management practices by depicting quantitative anomaly derived from the comparison between the LAI profiles of each field with its surrounding ones.


The analysis of the individual development of crops within one growing season supports an accurate classification respectively the differentiation between crop types as well as between agricultural areas and other vegetation cover. Additionally, the accurate monitoring of the growing phase, starting with time of sowing, the sprouting of the plants, growing, growing peak, maturing, ending up with harvesting could support the selection of suitable time slots for EO data and thus reducing the amount of data.  The results of the crop growth condition prototype at the Belgium test site revealed a shift of 2-3 weeks for the beginning of the growing cycle within the year (compared to the local average) and proves thus quite promising

A detailed description of Time Series Indicators prototypes is available here. The prototypes are available in a WMS viewing service hosted at geoservice.dlr.de. Furthermore the complete prototype data sets are available for download in GeoTiff format below. The prototypes are available in a WMS viewing service hosted at geoservice.dlr.de. Furthermore the complete prototype data sets are available for download in GeoTiff format below.

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme, under grant agreement no 730008.