IMAP: Image Mapping & Analytics for Phenotyping

A set of PYTHON programs to implement image processing of ground and aerial images by offering via graphical user interface (GUI) 1) plot-level metrics extraction through a series of algorithms for image conversion, band math, radiometric/geometric calibrations, segmentation, masking, adaptive region of interest (ROI), gridding, heatmap, and batch process, 2) GIS interface for GeoTIFF pixels to Lat/Lon, UTM conversion, read/write shapefile, Lat/Lon to ROI, grid to polygon, and 3) utility GUI functions for zooming, panning, rotation, images to video, file I/O, and histogram.

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Field	Value
Tags	plant phenotyping image analysis Drone_Images satellite image calibration gis crop management water management software np301
Modified	2022-09-16
Release Date	2021-09-21
Identifier	d551116d-98a5-44bb-9a4d-15096fd6277c
Spatial / Geographical Coverage Area	POLYGON ((-373.59375715256 -65.778772326728, -373.59375715256 84.220160826965, -12.187442779541 84.220160826965, -12.187442779541 -65.778772326728))
Publisher	Ag Data Commons
Spatial / Geographical Coverage Location	Earth
Temporal Coverage	December 18, 2018 to August 30, 2021
License	U.S. Public Domain
Contact Name	Kim, James
Contact Email	james.kim2@usda.gov
Public Access Level	Public
Program Code	005:040 - Department of Agriculture - National Research
Bureau Code	005:18 - Agricultural Research Service

Extended Metadata:

Field	Value
Authors	Kim, James Y. (ORCID)
Peer Reviewed	No
Intended Use	IMAP serves as a GUI-based image analytic software for high throughput phenotyping (HTP) in plant breeding and sustainable crop management on field crops as well as plants in growth chambers or greenhouses. Ground or aerial (UAV or Satellite) images may be collected to study plant health conditions of field crops to extract the plot-level metrics such as normalized difference vegetation index (NDVI), leaf area index (LAI), LAI covariance, heatmap, etc. An RGB or multispectral image is read for ROI or grid analysis on segmented vegetation pixels. A metafile can be saved for all configuration parameters and loaded for quick retrieval. A set of seasonal images may be read and batch processed to generate metrics outputs and visualize a field map calendar.
Use Limitations	IMAP supports rectangular or oval ROI, processing images of rectangular fields (software update planned for images of circular fields). File/folder structure in batch process may need to be adjusted to read the end-user's data.
Equipment or Software Used	Anaconda Python 3.8 Wing Python IDE
Funding Sources	Agricultural Research Service 2020-21410-007-00D Agricultural Research Service 2020-21000-013-00D Agricultural Research Service 2020-11000-013-00D
Primary Article	Kim, J. Y. (2021). Software design for image mapping and analytics for high throughput phenotyping. Computers and Electronics in Agriculture, 191, 106550. https://doi.org/10.1016/j.compag.2021.106550 AgID: 10113/7564587
Dataset DOI (digital object identifier)	10.15482/USDA.ADC/1523140
Product Type	Software

Field	Value
OSTI Identifier
ISO Topic(s)	farming geoscientificInformation imageryBaseMapsEarthCover
National Agricultural Library Thesaurus Term	phenotype computer software image analysis aerial photography algorithms radiometry geometry geographic information systems remote sensing crop management water management plant breeding field crops greenhouses unmanned aerial vehicles satellites normalized difference vegetation index leaf area index multispectral imagery vegetation Research Technology and Engineering Natural Resources Earth and Environmental Sciences
Ag Data Commons Keywords	Maps & Multimedia Agroecosystems & Environment Geography Remote sensing Agroecosystems & Environment Geography Agroecosystems & Environment Agroecosystems & Environment Plant and animal Agroecosystems & Environment Management

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