Various embodiments are disclosed for a machine learning system for automatic genotype selection and performance evaluation using multi-source and spatiotemporal remote sensing data collected from an unmanned aerial system (UAS). A computing device may be configured to access images of a field having a first genotype and a second genotype of at least one crop or plant planted therein. The computing device may apply an image processing routine to the images to analyze the images of the field and determine characteristics of the first genotype and the second genotype of the at least one crop or plant planted in the field. The computing device may then apply a machine learning routine to forecast a first estimated yield of the first genotype and a second estimated yield of the second genotype using the identified characteristics of the first genotype and the second genotype.

Crop is routed past a sample window on an agricultural combine harvester. Light it is impinged on the crop from an illumination source and reflected radiation is directed to a sensor. The output of the sensor is indicative of various constituents in the harvested crop. The illumination source is controlled based on the temperature proximate the crop sample.

The present disclosure relates to methods and systems for obtaining image information of an organism including a set of optical data; calculating a growth index based on the set of optical data; and calculating an anticipated harvest time based on the growth index, where the image information includes at least one of: (a) visible image data obtained from an image sensor and non-visible image data obtained from the image sensor, and (b) a set of image data from at least two image capture devices, where the at least two image capture devices capture the set of image data from at least two positions.

There is provided an information processing apparatus including a macro measurement analysis calculation section configured to calculate detection data from a macro measurement section adapted to perform sensing at a first spatial resolution for a first measurement range for a measurement target, a micro measurement analysis calculation section configured to calculate detection data from a micro measurement section adapted to perform sensing at a second spatial resolution for a second measurement range, the second spatial resolution being higher than the first spatial resolution, the second measurement range being included in the first measurement range for the measurement target, and an inverse model calculation section configured to acquire a model parameter used for an inverse model calculation using a calculation result from the macro measurement analysis calculation section, on a basis of the detection data from the micro measurement section determined by the micro measurement analysis calculation section.

A sensor element is used to collect environment information on a surface of the earth or a surface layer of the earth by being scattered in a target region where the environment information is collected. At least one of reflection properties, transmission properties, absorption properties, or luminescence properties with respective to an electromagnetic wave with a specific wavelength, or light emitting properties changes in accordance with an environment.

An apparatus for remote detection of plant growth dynamics is described. The apparatus includes an excitation LED (light emitting diode) module, a detection module and a controller module coupled to the excitation LED module and the detection module. The excitation LED module includes at least one LED. Each LED is configured to emit an excitation light in response to an excitation control signal. The excitation light has an emitted light spectrum. The detection module includes a photodetector configured to detect an initial chlorophyll a fluorescence (“ChlF”) light and an excited ChlF light from a plant species. The photodetector is further configured to convert the detected initial ChlF light into an initial detection electrical signal and the detected excited ChlF light into an excited detection electrical signal. The excited ChlF light is emitted from the plant species in response to receiving the excitation light. The controller module is configured to provide the excitation control signal to the excitation module, to capture the initial and excited detection electrical signals from the detection module and to determine chlorophyll fluorescence data based, at least in part, on the initial and excited detection electrical signals. The excitation LED module and the detection module are configured to be positioned remotely from the plant species. The chlorophyll fluorescence data represents a growth characteristic of the plant species.

Technology is provided for identifying concrete and/or asphalt (or other materials) in a multispectral satellite image that has multiple bands including a first set of bands from a first sensor and a second set of bands from a second sensor. The second sensor is at a different position on a focal plane as compared to the first sensor so that a single location depicted in the multispectral image will have been sensed at different times by the first sensor and the second sensor. The system identifies moving vehicles in the multispectral image and subsequently identifies sample pixels in the multispectral image that are near the moving vehicles. These pixels are high confidence samples of roads made of concrete and/or asphalt. Additional pixels are identified in the multispectral image having spectral characteristics that are within a threshold of spectral characteristics of the sample pixels. These additional pixels also depict concrete and/or asphalt.

An apparatus for detecting a plant health status is described. The apparatus includes a light source positioned relative to the plant and a detector positioned relative to the plant. The light source is configured to emit a white light or an ultraviolet light. The ultraviolet (UV) light corresponds to UV-A and has a wavelength in the range of 340 nanometers (run) to 400 nm. The detector is configured to receive evaluation light. The evaluation light is related to the emitted light and corresponds to a health status of the plant.

A scan using a pulsed distance measuring light with two wavelengths of which reflectances are different with respect to a content of a nitrogen by a laser scanner, the two wavelengths are separated, lights are received, a distance measurement value and a light amount are detected for each pulsed distance measuring light and for each of the two wavelengths, a height of a crop is detected based on the distance measurement value, a received light amount ratio of the two wavelengths is detected, and a growth condition of the crop is detected based on the detected height and the received light amount ratio.

Methods, systems and devices for use in aerial or satellite-based applications to detect elements or magnitudes of interest, or monitor their changes, in a target location are disclosed. A transducing system includes a detector device to sense, transduce or detect optical properties of at least one transducing agent linked to the elements or magnitudes of interest. Based on the optical property of the transducing agent, the system generates information of the element or magnitude of interest. The methods and systems provide tools for detecting magnitudes from remote locations which are usually difficult or costly to measure on-site, thereby providing an efficient detection system for aerial detection systems.