Advancing Vegetation Monitoring Strategies in Arid Ecosystems Using Unmanned Aircraft Systems

Arid ecosystems present unique challenges for environmental monitoring using remotely sensed data because vegetation communities in drylands are often sparsely distributed and have heterogeneous species and soil composition. Unmanned Aircraft Systems (UAS) offer centimeter-scale spatial resolution and flexible deployment that can better address the scale of these communities. This work explores two complementary approaches for integrating UAS into scalable and adaptable vegetation monitoring strategies in arid ecosystems. Chapter 1 evaluated the potential of high-resolution, multispectral UAS imagery to classify perennial vegetation cover in the Mojave Desert and upscaled those estimates to coarser resolution, freely accessible satellite data using Random Forest modeling. Chapter 2 investigated an alternative to traditional photogrammetric workflows by treating individual aerial images as independent sampling units. These approaches together illustrate how UAS can bridge the gap between fine-scale and landscape-scale vegetation monitoring, enabling flexible, scalable workflows that adapt to management priorities and the ecological context within arid ecosystems.

Level thesis:degree_level

Master's Degree

Year dc:date.issued

2025

Author dc:creator

• Machuca, Faith Jordan

Advisor dc:contributor.advisor

• Nussear, Ken

Committee members dc:contributor.committeemember

• Trugman, Daniel
• Albright, Tom

• Arid Ecosystems
• Environmental Monitoring
• Remote Sensing
• Unmanned Aircraft Systems
• Vegetation Monitoring

Language dc:language.iso

en_US, English

Repository record dc:identifier.uri

https://scholarwolf.unr.edu/handle/11714/11576

OAI identifier oai:identifier

oai:scholarwolf.unr.edu:11714/11576