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US Patent 10467475 Forest inventory assessment using remote sensing data

Patent 10467475 was granted and assigned to Yale University on November, 2019 by the United States Patent and Trademark Office.

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Patent
Patent

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Current Assignee
Yale University
Yale University
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10467475
Patent Inventor Names
Zachary Parisa0
Date of Patent
November 5, 2019
Patent Application Number
13704386
Date Filed
June 16, 2011
Patent Citations Received
‌
US Patent 11978227 Systems and methods for forest surveying
0
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US Patent 11587249 Artificial intelligence (AI) system and methods for generating estimated height maps from electro-optic imagery
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US Patent 11747468 System using a priori terrain height data for interferometric synthetic aperture radar (IFSAR) phase disambiguation and related methods
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US Patent 11302071 Artificial intelligence (AI) system using height seed initialization for extraction of digital elevation models (DEMs) and related methods
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US Patent 11481904 Automated determination of tree inventories in ecological regions using probabilistic analysis of overhead images
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US Patent 11238307 System for performing change detection within a 3D geospatial model based upon semantic change detection using deep learning and related methods
Patent Primary Examiner
‌
John E Breene
Patent abstract

Methods and systems are provided that inventory a plot of trees based on data including one or more (e.g., all) of radar images of the plot, spectral images of the plot (e.g., high resolution images taken by satellite), other data (e.g., elevation, slope, aspect), and actual tree survey data physically collected about the plot and/or another plot having similar characteristics. Although the actual tree survey data collected is typically less than the amount of actual survey data used by prior approaches, the present systems and methods are still capable of inventorying the entire plot with a high degree of confidence (e.g., at least 95% confidence).

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