GeoUAV Keynote 2
UAV observations for agricultural and environmental applications
Abstract: Two main applications could benefit from the use of UAV: (I) phenotyping, i.e. characterizing the structural and functional traits of cultivars for accelerating the genetic progress,
and (ii) Precision agriculture for optimizing the use of inputs for productivity and quality while preserving the environment.
A review of current accessible traits for phenotyping is presented with a discussion on the best adapted sensors and vectors. This is the domain of multicopters that may carry for 10-20 minutes a payload of few hundred grams up to few kilograms at variable altitude and speed. A range of sensors may be used including high resolution RGB cameras, multispectral and hyperspectral cameras, thermal infrared cameras and LIDARs. Low altitude flights allow getting spatial resolution better than a fraction of mm. Several examples are given to illustrate the versatility of UAVs for high throughput phenotyping. The interpretation methods need to be well suited in order to provide estimates of canopy traits decontaminated from possible artifacts due to the variability that should probably become the standard method for field conditions.
For precision agriculture, due to the spatial coverage requirements, fixed wings vectors will be preferred with autonomy from half an hour up to few hours, higher speed and altitudes. In these conditions, the payload is obviously more limited with consequences on the number of variables accessible. The variability of incident radiation as well as the desired larger swath poses specific problems that are here illustrated. Examples of applications of UAVs for precision agriculture are given. The complementarity with satellite observations for field crops such as cereals, sunflower rapeseed or soybean is discussed.
Finally, conclusions are drawn on the current achievements, the possible complementarity between phenotyping and precision agriculture applications, and the main avenues for improving the use of UAVs for agriculture applications.
Bio: F. Baret received a PhD in the use of Remote sensing for crop monitoring in 1986. He is currently research Director at INRA, leading the remote sensing team. He coordinated several National and European projects. He is involved in the development of radiative transfer models at several scales (soil, leaf, canopy) and their use for the retrieval of biophysical variables. He developed retrieval algorithms (CYCLOPES, GEOV1, GEOV2, GEOV3) from satellite and airborne sensors as well as close range remote sensing. He is deeply involved in the validation of remote sensing products and chaired the CEOS/LPV working group. He recently expanded his activity on high throughput phenotyping with the development of measurement systems as well as interpretation methods. He is in charge of the development of phenotyping methods in field conditions within the PHENOME project. He authored more than 190 research papers (h=46 from WoK).