Pathways to Enhancing Analysis of Irrigation by Remote Sensing (AIRS) in Urban Settings

Abstract

In contrast to agricultural settings, irrigation of residential properties in urban settings is typified by small and irregular areas, many untrained water users, limited end-use metering, and differing groundcover. This makes analyzing irrigation patterns to promote efficient water use challenging. We explore the use of remote sensing tools and data sets to help characterize urban irrigation use in the United States. Herein, we review available multispectral imagery datasets and discuss tradeoffs among spatial resolution, collection frequency, and historical availability. We survey options for evapotranspiration data at various spatial and temporal scales that could be paired with the multispectral imagery to estimate irrigation demand. We call the general approach Analysis of Irrigation by Remote Sensing (AIRS). We discuss the potential of drones to capture higher-resolution temporal or spatial data in study areas and/or multiple flights in a single season to provide ground truth or establish patterns. We present data and analysis options that may be suitable depending on specific project objectives. Through a case study scenario, we illustrate some tradeoffs. As a starting point, we recommend public 1 m National Agriculture Imagery Program (NAIP) images for irrigated area estimates and normalized difference vegetation index (NDVI) calculations, combined with open-source OpenET for evapotranspiration, to provide historical snapshots of water use, vegetation quality, and general irrigation efficiency in urban areas. The method is most effective when paired with optional water use data and can provide information with which to design more optimal studies.