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Cloud Effects Correction Of Drone-Collected Crop Imagery For Precision Agriculture

Award Information
Agency: Department of Agriculture
Branch: N/A
Contract: 2018-33610-28555
Agency Tracking Number: 2018-00266
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 8.13
Solicitation Number: N/A
Timeline
Solicitation Year: 2018
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-09-01
Award End Date (Contract End Date): 2019-04-30
Small Business Information
4 4TH AVE, Burlington, MA, 01803-3304
DUNS: 047627732
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Marsha Fox
 Vice President of Operations
 (781) 273-4770
 mfox@spectral.com
Business Contact
 Leslie McCarthy
Title: Technical Publications
Phone: (781) 273-4770
Email: lmccarthy@spectral.com
Research Institution
N/A
Abstract
The effect of cloud shadows on aerial imagery is an unsolved problem that has been identified by many operators of unmanned aerial vehicle (drone)-based remote sensing systems for agriculture. Shadows affect the ability to compare imagery, including multispectral and hyperspectral imagery (MSI and HSI), taken over periods of time, and the ability to quantify image data analytics, including NDVI and more sophisticated metrics for crop health, water stress, pigments, diseases, and soil nutrients. The overall objective of Phase I of this effort is to demonstrate component technologies needed to provide cloud effects correction in drone imagery, including development of a preliminary design for hardware and data post-processing software. Critical components include the collection and storage of skydata, algorithms to transform the data into quantifiable shadow and other cloud effects, and finally application of irradiance to cloud shadow correction in the down-looking imagery.

* Information listed above is at the time of submission. *

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