Code from: Using cameras for precise measurement of two-dimensional plant features

Images are used frequently in plant phenotyping to capture measurements. This chapter offers a repeatable method for capturing two-dimensional measurements of plant parts in field or laboratory settings using a variety of camera styles (cellular phone, DSLR), with the addition of a printed calibration pattern. The method is based on calibrating the camera using information available from the EXIF tags from the image, as well as visual information from the pattern. Code is provided to implement the method, as well as a dataset for testing. We include steps to verify protocol correctness by imaging an artifact. The use of this protocol for two-dimensional plant phenotypoing will allow data capture from different cameras and environments, with comparison on the same physical scale.

USDA Forest Service Remote Sensing Applications Center and Geospatial Technology and Applications Center

The Forest Service's Remote Sensing Applications Center (RSAC) is in Salt Lake City, Utah, co-located with the agency's Geospatial Service and Technology Center. Guided by national steering committees and field sponsors, RSAC provides national assistance to agency field units in applying the most advanced geospatial technology toward improved monitoring and mapping of natural resources. RSAC's principal goal is to develop and implement less costly ways for the Forest Service to obtain needed forest resource information.

Maps and Multimedia

VegScape - Vegetation Condition Explorer

VegScape https://nassgeodata.gmu.edu/VegScape/ delivers interactive vegetation indices so that web users can explore, visualize, query, and disseminate current vegetative cover maps and data without the need for specialized expertise, software, or high end computers. New satellite-based data are loaded on a weekly basis during the growing season. One can compare year-to-year change since the year 2000, compare conditions at a given times to mean, median and ratio vegetative cover, and can overlay a crop mask to help identify crop land versus non-crop land, among many functions. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), and mean, median, and ratio comparisons to prior years have proven useful for assessing crop condition and identifying the land area impacted by floods, drought, major weather anomalies, and vulnerabilities of early/late season crops. The National Aeronautics Space Administration's MODIS satellite is used for this project and provides imaging at 250 meter (15 acres) per pixel resolution. Additionally, the data can be directly exported to Google Earth for mashups or delivered to other applications via web services.

Agroecosystems & Environment