Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 1023-1029, 2016
https://doi.org/10.5194/isprs-archives-XLI-B1-1023-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
06 Jun 2016
UAV MULTISPECTRAL SURVEY TO MAP SOIL AND CROP FOR PRECISION FARMING APPLICATIONS
Giovanna Sona1, Daniele Passoni1, Livio Pinto1, Diana Pagliari1, Daniele Masseroni2, Bianca Ortuani2, and Arianna Facchi2 1Dept.Eng.Civil and Environ., Politecnico di Milano, Piazza L.Da Vinci 32, 20123 Milano, Italy
2Dept. of Agricultural and Environmental Sciences, University of Milan, Via Celoria 2, 20123 Milano, Italy
Keywords: UAV, multispectral images, DEM, orthophoto, NDVI, precision farming, soil and crop characterization Abstract. New sensors mounted on UAV and optimal procedures for survey, data acquisition and analysis are continuously developed and tested for applications in precision farming. Procedures to integrate multispectral aerial data about soil and crop and ground-based proximal geophysical data are a recent research topic aimed to delineate homogeneous zones for the management of agricultural inputs (i.e., water, nutrients). Multispectral and multitemporal orthomosaics were produced over a test field (a 100 m x 200 m plot within a maize field), to map vegetation and soil indices, as well as crop heights, with suitable ground resolution. UAV flights were performed in two moments during the crop season, before sowing on bare soil, and just before flowering when maize was nearly at the maximum height. Two cameras, for color (RGB) and false color (NIR-RG) images, were used.

The images were processed in Agisoft Photoscan to produce Digital Surface Model (DSM) of bare soil and crop, and multispectral orthophotos. To overcome some difficulties in the automatic searching of matching points for the block adjustment of the crop image, also the scientific software developed by Politecnico of Milan was used to enhance images orientation.

Surveys and image processing are described, as well as results about classification of multispectral-multitemporal orthophotos and soil indices.

Conference paper (PDF, 1070 KB)


Citation: Sona, G., Passoni, D., Pinto, L., Pagliari, D., Masseroni, D., Ortuani, B., and Facchi, A.: UAV MULTISPECTRAL SURVEY TO MAP SOIL AND CROP FOR PRECISION FARMING APPLICATIONS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 1023-1029, https://doi.org/10.5194/isprs-archives-XLI-B1-1023-2016, 2016.

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