Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A system and method processes original digital numbers (DNs) provided by a satellite imaging system to produce a set of spectral balanced and contrast enhanced multispectral images. Spectral balancing is achieved based on physical characteristics of sensors of the imaging system as well as compensation for atmospheric effects. The DNs in the multispectral bands may be processed using a relatively small amount of processing resources otherwise required to produce such images. Such images may be processed completely automatically and provide relatively easy visual interpretation. Each image pixel may be, for example, in an 8-bit or 16-bit format, and the image may be displayed and/or printed without applying any additional color correction and/or contrast stretches.

Abstract: A system and method processes original digital numbers (DNs) provided by a satellite imaging system to produce a set of spectral balanced and contrast enhanced multispectral images. Spectral balancing is achieved based on physical characteristics of sensors of the imaging system as well as compensation for atmospheric effects. The DNs in the multispectral bands may be processed using a relatively small amount of processing resources otherwise required to produce such images. Such images may be processed completely automatically and provide relatively easy visual interpretation. Each image pixel may be, for example, in an 8-bit or 16-bit format, and the image may be displayed and/or printed without applying any additional color correction and/or contrast stretches.

Abstract: The present invention is directed to a method for producing agricultural information on an area of interest, with the information based on raw, remote imaging data that is typically produced by a sensor associated with a satellite or aircraft. In one embodiment, the method includes processing raw, remote imaging data to produce reflectance factor data on the land of interest. The reflectance factor data is then used to produce agriculturally significant information. In one embodiment, a soil zone index map is produced for the land of interest. In another embodiment, the reflectance factor data is used to produce a green vegetation index map. In yet a further embodiment, the reflectance factor data at two points in time is used to produce a map for the land of interest that indicates the change in the green vegetation index over time.

Abstract: A system, method, and apparatus for remote sensing is disclosed. The system method, and apparatus can capture raw image data from outer space at a first resolution and provide multiple resolution images from this raw image data without requiring multiple-resolution image data to be captured. The raw image data is utilized to provide both a high resolution image directly from the data and also aggregates the raw image data to provide a lower resolution image. The system, method, and apparatus can further utilize a red edge band of the near infrared band for remote sensing.