Location: Aerial Application Technology Research
Project Number: 3091-22000-037-009-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Jul 1, 2019
End Date: Jun 30, 2024
The overall goal of the project is to enhance the resilience of livestock production systems in the Great Plains, helping them meet the multiple environmental challenges of woody plant encroachment, more extreme climatic events (drought, heat/cold, precipitation, storms), and unpredictable wildfires. The remote sensing part of the project includes the following specific objectives: 1. Set up the GIS database with existing GIS and remote sensing data 2. Incorporate spatial data of management history into the GIS database 3. Acquire and process aerial images for Sonora Station and Martin and Reed ranches 4. Develop vegetation classifications based on the aerial images.
1. Setting up the GIS database with existing GIS and remote sensing data All available GIS data and historical remote sensing imageries and photos will be collected and processed to incorporate into the GIS database for Sonora Station and Martin and Reed ranches. Some historical aerial photos (negatives/prints) will need to be scanned and geo-preferenced. 2. Incorporating spatial data of management history into the GIS database Spatial data for boundaries of historical pastures will be developed with associate attribute data on management records (grazing, mechanical/chemical treatment, fire, etc.). Most of these data are currently in paper form and will take significant efforts, and collaboration with current and past superintendents, to organize and convert them into digital form with spatial data. 3. Acquisition and processing of aerial imagery for Sonora Station and Martin and Reed ranches Complete coverage of aerial imagery for Sonora Station and Martin and Reed ranches will be acquired twice a year, possibly one at the times of peak biomass and another for best separation and targeted vegetation groups. RGB/Near-infrared, hyperspectral, and thermal imagery of sufficient spatial resolutions will be acquired for the entire Station/ranches. These aerial images will be geo-referenced and mosaicked, which involve a very large amount of work. 4. Developing vegetation classifications based on the aerial imagery Methods will be developed for classifying key plant groups based on the aerial imagery, especially hyperspectral imagery, and ground based vegetation sampling. Along with other products such as vegetation indices, these classifications will be developed for all aerial imagery acquired. Continuing acquisition and classification of aerial imagery will develop a unique and powerful platform (with complete history of disturbance and vegetation responses) that can enable explorations of complex spatial-temporal interactions among vegetation, fire, herbivory and climate in the topo-edaphic contexts of the landscape.