US 12,333,800 B2
System and method for mapping land cover types with landsat, sentinel-1, and sentinel-2 images
Xiangming Xiao, Norman, OK (US); and Jie Wang, Norman, OK (US)
Assigned to The Board of Regents of the University of Oklahoma, Norman, OK (US)
Filed by The Board of Regents of the University of Oklahoma, Norman, OK (US)
Filed on May 31, 2022, as Appl. No. 17/828,539.
Claims priority of provisional application 63/194,332, filed on May 28, 2021.
Prior Publication US 2022/0392215 A1, Dec. 8, 2022
Int. Cl. G06V 10/56 (2022.01); G06T 7/70 (2017.01); G06V 10/26 (2022.01); G06V 10/764 (2022.01); G06V 20/10 (2022.01)
CPC G06V 20/188 (2022.01) [G06T 7/70 (2017.01); G06V 10/26 (2022.01); G06V 10/56 (2022.01); G06V 10/764 (2022.01); G06T 2207/10024 (2013.01); G06T 2207/10048 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30188 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer system comprising:
at least one processor; and
at least one non-transitory computer-readable medium storing a set of instructions for running on the at least one processor, that when executed cause the at least one processor to:
receive first image data of a geographic region, the first image data having pixels and being geo-referenced such that each pixel has a known real-world location within the geographic region associated with the pixel, the image data including multiple pixels for real-world locations within the geographic region, the multiple pixels for the real-world locations collectively having pixel information selected from a group consisting of colors within a visible spectrum, infra-red, and shortwave infrared;
calculate for particular real-world locations within the geographic region, a plurality of vegetation indices with combinations of the pixel information;
generate at least one land cover mask with the vegetation indices, the at least one land cover mask identifying first real-world locations within the geographic region having a water-related land cover type, a non-vegetated land cover type and an evergreen land cover type;
classify second real-world locations within the geographic region that are not classified as the water-related land cover type, the non-vegetated land cover type and the evergreen land cover type as cropland; and
analyze a time-series of image data depicting the second real-world locations within the geographic region with phenology metrics to identify at least one particular type of cropland within the second real-world locations.