| CPC G06Q 50/02 (2013.01) [G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06T 17/05 (2013.01); G06V 20/188 (2022.01)] | 20 Claims |
|
1. A computer-implemented method for automated forest inventory mapping, comprising:
receiving, by one or more processors, an image depicting an overhead view of a wooded area, the image comprising a plurality of pixels;
receiving, by the one or more processors, a set of climate data for a geographic region in which the wooded area is located;
receiving, by the one or more processors, point cloud data of a digital surface model of the wooded area;
processing the point cloud data by normalizing a resolution of the point cloud data to match a resolution of the image by computing average height values for points corresponding to each pixel and generating a height vector matching dimensions of the image;
concatenating, by the one or more processors, data corresponding to the plurality of pixels of the image, the set of climate data, and the point cloud data into a feature vector;
executing, by the one or more processors, a machine learning model using the feature vector to generate timber data for each of the plurality of pixels of the image by:
processing the feature vector through the machine learning model, wherein the machine learning model has been trained using ground truth data comprising tree measurements and correlated training feature vectors generated from satellite imagery, climate data, and point cloud data of the wooded area;
generating, for each pixel, timber data; and
applying a geographic normalization factor retrieved from a database based on the geographic region to adjust the generated timber data;
generating, by the one or more processors, a visualization overlay from the timber data; and
displaying the visualization overlay on a graphical user interface, wherein the visualization overlay enables real-time interaction with the timber data through user selection of individual pixels to view detailed timber metrics for corresponding geographic locations.
|