Monsanto Technology LLC

Landscan LLC

Jack F Paris

Dean Grundman

Gregory E Knoblauch

Stephen P Farrington

Daniel James Rooney

Michael J Unverferth

Mark Hull

Robert S Horton

Image acquisition and analysis systems for efficiently generating high resolution geo-referenced spectral imagery of a region of interest. In some examples, aerial spectral imaging systems for remote sensing of a geographic region, such as a vegetative landscape are disclosed for monitoring the development and health of the vegetative landscape. In some examples photogrammetry processes are applied to a first set of image frames captured with a first image sensor having a first field of view to generate external orientation data and surface elevation data and the generated external orientation data is translated into external orientation data for other image sensors co-located on the same apparatus for generating geo-referenced images of images captured by the one or more other image sensors.

Systems and methods for multispectral landscape mapping

A method for generating a raster file based on a plurality of primary index raster files that are associated with an area of interest (AOI) uses a computer coupled to a remote sensing device via a network. The method includes receiving a plurality of AOI raster files via the network, and generating the primary index raster files including a green biomass index (GBI) raster file and a pigmentation index (PGI) raster file. The method also includes generating a plurality of levels for each of the primary index raster files, generating a combination vegetation index (CVIPP) raster file based on a highest level of the GBI and PGI raster files, and generating a corn soybean map (CSM) raster file based on the CVIPP raster file. The method also includes storing the CSM raster file into the memory, and displaying a CSM report based on the CSM raster file.

Generating agricultural information products using remote sensing

A method for generating index raster files associated with an area of interest (AOI) uses a computer coupled to a remote sensing device via a network, wherein the computer includes an input device, a display, and a memory. The method includes receiving only three image raster files relating to the AOI from the remote sensing device, and receiving at least one set of three spectral control points (SCP) via the input device. The method also includes generating at least two independent vegetation index (VI) raster files and a soil brightness index (SBI) raster file based on the image raster files and the at least one set of three SCPs, storing each of the SBI raster file and the at least two VI raster files into the memory, and selectively displaying at least one of the SBI raster file and the at least two VI raster files.

A method for generating a supplementary index raster file based on a plurality of primary index raster files that are associated with an area of interest (AOI) uses a computer coupled to a remote sensing device via a network, wherein the computer includes an input device, a display, and a memory. The method includes generating the plurality of primary index raster files including at least two independent vegetation index (VI) raster files and a soil brightness index (SBI) raster file, wherein each primary index raster file includes a plurality of pixel values. The method also includes classifying each pixel value of the at least two VI raster files as one of a leafy material and a non-leafy material, generating a leaf pigmentation index (LPI) raster file based on the classified pixel values, storing the LPI raster file into the memory, and selectively displaying the LPI raster file.

A method for generating a supplementary index raster file based on a plurality of primary index raster files that are associated with an area of interest (AOI) uses a computer coupled to a remote sensing device via a network, wherein the computer includes an input device, a display, and a memory. The method includes generating the plurality of primary index raster files including at least two independent vegetation index (VI) raster files and a soil brightness index (SBI) raster file, wherein each primary index raster file includes a plurality of pixel values. The method also includes combining the at least two VI raster files to generate a classified soil brightness (CSB) raster file, classifying each pixel value of the CSB raster file into one of a plurality of classes, storing the CSB raster file into the memory, and displaying the CSB raster file.

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Clovis, CA, United States of America

Jack F Paris