Date of Submission

7-2025

Document Type

Thesis

Degree Name

Master of Science in Environmental Science

Department

Biology and Environmental Sciences

Advisor

Sharon Kahara, Ph.D.

Committee Member

Buddhika Madurapperuma, Ph.D.

Committee Member

Matthew Fulda

Keywords

California’s Rangelands, Light Rotational Grazing, Unmanned Aerial Systems, NDVI/GCC Values, Data-Driven Adaptive Management, Sustainable Grazing Practices

LCSH

Rangelands, Rotational grazing, Drone aircraft

Abstract

California's rangelands, vital for biodiversity and cattle production, face threats from land use changes and climate changes, necessitating robust management strategies. While overgrazing has been studied extensively, the effects of light rotational grazing on vegetation have seldom been assessed. This study used Unmanned Aerial Systems (UASs) and multispectral imagery to assess the seasonal impacts of light rotational grazing on vegetation health and coverage in wetland mitigation areas near Willits, California. Data were collected in May (spring) and November (fall) 2024 using a DJI M3M drone and MicaSense camera capturing RGB and Near-Infrared (NIR) bands. Green Chromatic Coordinate (GCC) and Normalized Difference Vegetation Index (NDVI) values were calculated for grazed and non-grazed experimental plots. Results indicate that grazed plots consistently exhibited significantly higher mean GCC values than non-grazed plots in both spring (0.45 vs. 0.42, p=0.008) and fall (0.38 vs. 0.34, p=0.001), suggesting enhanced vegetation greenness and photosynthetic activity. For NDVI, grazed plots showed significantly higher values in spring (0.41 vs. 0.35, p=0.043), implying greater initial productivity. While this difference diminished by fall (p=0.904), pixel distribution analysis revealed that grazed areas maintained higher proportions of vigorous vegetation and greater heterogeneity (58% vs. 47.9% high NDVI in fall). These findings suggest that light, managed grazing can positively influence rangeland vegetation, promoting sustained greenness, vigor, and structural diversity, particularly extending into the fall dormant period. This research also demonstrates the effectiveness of UAV-based remote sensing as a scalable tool for data-driven adaptive management, supporting sustainable grazing practices that balance ecological health with agricultural productivity in rangeland ecosystems.

Available for download on Friday, August 28, 2026

Share

COinS