Land inventory, creation of electronic field maps, detection of intrusions into land use boundaries, creation of orthophotographic maps and highly accurate 3d terrain models. NDVI determination and development of precision farming instructions. Assessment of soil quality and yield forecasting. Monitoring of agricultural lands, support and supervision of agricultural operations. Harvest planning.
The way vegetation reflects in the red and near-white IR parts of the electromagnetic spectrum is directly related to the proportion of green biomass. The state of vegetation is quantitatively assessed using the so-called Normalised Difference Vegetation Index (NDVI), which also characterises the density of vegetation. The NDVI enables crop producers to appraise the germinating capacity and growth rate of plants and the productivity of farmlands. The index is calculated as the difference between the spectral reflectance measurements in the near-infrared and red parts of the spectrum divided by their sum.
The NDVI varies between -1 and 1.
Green vegetation's reflectance in the red part of the spectrum is always lower than that in the near-IR part, because chlorophyll absorbs visible light; therefore the NDVI cannot be negative for green vegetation.
Soil quality assessment, yield forecasting
Agrochemical soil analysis in combination with NDVI maps helps develop instructions for the differentiated introduction of mineral fertilisers. If no agrochemical survey data is available, the NDTV maps may be used for optimising the sampling process: instead of taking soil samples based on a regular grid, samples may be taken in certain areas, which reduces the number of samples to be taken and helps mitigate the influence of random factors on the analysis results.
Land auditing with the use of UAVs helps identify inarable lands; compare the actual field boundaries with those specified in the cadastre; analyse the condition of crops (death or oversowing); detect procedural irregularities; create a 3D model of the target field; and assist security services in their work.
Specification of farmland boundaries as compared to cadastre plan
The accuracy of information about a field's area and boundaries directly affects the cost estimates for its treatment and the evaluation of its productivity. Discrepancies between maps dating back to the 1970s and the 1980s and the actual state of affairs may reach 20%. This leads to miscalculated procurement costs for seeding materials and pesticides, and also to incorrect assessments of land productivity. Inventorying lands with the use of UAVs is significantly more accurate and effective than the conventional methods of ground-based surveying or satellite imagery analysis.
UAV-assisted remote sensing allows for building a highly accurate orthophotographic mapand a a 3D model of the area, for specifying field boundaries and areas, for updating information about the actual land use, and for determining the type of vegetation.
Storage clamp measurements and clearing prioritisation
UAV-assisted aerial photography and thermal imaging of storage clamps for root vegetables allows for combining a highly accurate orthophotographic field map with the results of a thermal imaging survey to build 3D storage clamp models, calculate the volume of stored crops with a high degree of automation, and prioritise their clearing order (the heat emission captured by the thermal imager allows for quantitative assessment of the speed of decomposition processes). In November 2016, Aviarobots tested this method on sugarbeet storage clamps in Voronezh Region.
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