Algae are an essential component of aquatic ecosystems. They provide food, habitat,structural support, and oxygen to marine, freshwater, and brackishwater environments alike. However, algae in excess can be problematic. Harmful algal blooms (HABs) are proliferations of both toxic and non-toxic algal species that can cause ecological and environmental damage in lakes, reservoirs, and rivers. As global temperatures rise, coupled with increasing nutrient inputs from eutrophication and atmospheric deposition, many predict HABs will also increase in frequency and intensity. There is a need to advance methods in algal bloom monitoring to keep pace with these global trends. As in situ techniques such as water quality samples, swimming, and laboratory assessments can be time-consuming and expensive, remote sensing may offer a faster, more cost-effective method to investigate blooms at greater spatial and temporal extents in freshwater ecosystems. Rivers, reservoirs, and lakes are particularly important because of their environmental, economic, cultural, and recreational roles in nature and society, and advancing remote sensing methods could improve our ability to monitor and mitigate blooms in these settings across the world. This dissertation explores the spatial and temporal dynamics of algal blooms, both “good” (non-toxic filamentous algae) and “bad” (toxic cyanobacteria), throughout freshwater environments of California. In Chapter 1, I introduce the importance and risks of algae, as well as a background of in situ and remote sensing methods to monitor algae. Chapter 2 examines the use of unoccupied aerial vehicle (UAV) imagery over the Klamath River to understand the distribution of aquatic plants and filamentous algae prior to the largest dam removal in history. Chapter 3 moves upstream in the Klamath River to two reservoirs, Iron Gate and Copco, and uses high-resolution Sentinel-2 satellite imagery to detect the spatial distribution and timing of potentially toxic blooms in a five-year time series. Chapter 4 integrates two statewide harmful algal bloom datasets (one of crowdsourced reports and another of 300-meter Sentinel-3 satellite imagery) with higher-resolution Sentinel-2 imagery in order to monitor a greater number of lakes and reservoirs in California with higher resolution data. Finally, in Chapter 5, I review the major findings, lessons learned, and challenges of this research and posit new directions of future research to improve remote sensing techniques of algal bloom detection in freshwater environments.