University of Illinois

Kaiyu Guan

Chongya Jiang

Jian Peng

Sibo Wang

Yunan Luo

Bin Peng

Sheng Wang

One or more cameras or other image collecting devices are used at or near the surface of a field including crops to acquire images of the crop canopy. This can be done by tilting the cameras relative to the zenith. Additional imagery, such as airborne or satellite of the same crop canopies is also acquired, with at least some of the imagery having similar geographical and time-stamped information. A machined-learning model will take the near surface imagery and be trained to apply the information to the remote imagery of the air or satellite to be applied to a greater area, which provides plant growth information to the wide area of the remote imagery.

Monitoring plant growth conditions by coupling near surface and remote sensing imageries

The ability to scale data can provide numerous advantages, especially with regard to agricultural information. For example, agroecosystems include land and data associated with the land, such as physical traits and information. This can include, for example, information related to the soil, crops, other vegetation, and other information related to the land. In order to be able to quickly and accurately know such information and traits, ground truth data can be scaled using aerial and/or satellite imagery. Models and other machine learning can utilize ground truth data to scale limited field area data (e.g., 0.1-1 km) and accurately apply the same to large swaths of land (e.g., >100 km) with accuracy for the field traits and/or characteristics.

Systems and methods for quantifying agroecosystem variables through multi-tier scaling from ground data, to mobile platforms, and to satellite observations

Aspects of the subject disclosure may include, for example, performing, by a processing system, image fusion using two or more groups of images to generate predicted images, wherein each group of the two or more groups has one of a different resolution, a different frequency temporal pattern or a combination thereof than another of the two or more groups. Gap filling can be performed by the processing system to correct images of the two or more groups. Additional embodiments are disclosed.

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Urbana, IL, United States of America

Kaiyu Guan