In-situ and UAV dataset with crop and soil parameters obtained from winter wheat fields

This dataset was created as a result of two seasons of ground observation and measurements conducted on commercial winter wheat fields in Zlatia test site, Bulgaria. The study was part of the TS2AgroBg project (“Testing Sentinel-2 vegetation indices for the assessment of the state of winter crops in Bulgaria”) funded by the European Space Agency (Contract № 4000117474/16/NL/NDe) under the Plan for European Cooperating States. The aim of the field campaigns was to collect in-situ data for different biophysical, biochemical, phenological, and other crop and soil parameters that characterize and affect the crop status and the spectral reflectance of the crop-soil system. The data were used to calibrate and validate empirical models for prediction and mapping of important crop parameters, such as leaf area index, biomass, chlorophyll content, etc., based on spectral data from the Sentinel-2 satellites. In addition, a methodology for integral assessment of crop status based on a combination of such parameters was developed. The dataset consists of two main parts. The first part contains data collected from 20 m by 20 m plots (Elementary Sampling Units, ESUs), includes the following parameters:

Leaf Area Index (LAI);

Fraction of Absorbed Photosynthetically Active Radiation (fAPAR);

Fraction of Intercepted Photosynthetically Active Radiation (fIPAR);

Vegetation cover fraction (fCover);

Chlorophyll Content (CC);

Above ground biomass (AGB): fresh and dry;

Plant nitrogen content;

Biological yield;

Soil moisture content at the surface layer;

Reflectance in the 350 nm to 2500 nm spectral range;

Crop development stage;

Crop density;

Crop height;

Total area coverage;

Assessment score of damages caused by diseases or pests;

Weeds: type, biomass, development stage, height, and overall weed score.

The second part contains auxiliary data, including:

Soil profile data from four locations within the study fields;

Crop calendar and management information;

Unmanned Aerial Vehicle (UAV) multispectral imagery;

Meteorological data from an automated weather station installed in the study area.