Remote Sensing of Residential Landscape Irrigation in Weber County, Utah: Implications for Water Conservation, Image Analysis, and Drone Applications

Annelise M. Turman (), Robert B. Sowby, Gustavious P. Williams and Neil C. Hansen
Additional contact information
Annelise M. Turman: Department of Civil and Environmental Engineering, University of Virginia, Thornton Hall, 351 McCormick Rd, Charlottesville, VA 22904, USA
Robert B. Sowby: Department of Civil and Construction Engineering, Brigham Young University, EB 430, Provo, UT 84602, USA
Gustavious P. Williams: Department of Civil and Construction Engineering, Brigham Young University, EB 430, Provo, UT 84602, USA
Neil C. Hansen: Department of Plant and Wildlife Sciences, Brigham Young University, LSB 4105, Provo, UT 84604, USA

Sustainability, 2024, vol. 16, issue 21, 1-21

Abstract: Analyzing irrigation patterns to promote efficient water use in urban areas is challenging. Analysis of irrigation by remote sensing (AIRS) combines multispectral aerial imagery, evapotranspiration data, and ground-truth measurements to overcome these challenges. We demonstrate AIRS on eight neighborhoods in Weber County, Utah, using 0.6 m National Agriculture Imagery Program (NAIP) and 0.07 m drone imagery, reference evapotranspiration (ET), and water use records. We calculate the difference between the actual and hypothetical water required for each parcel and compare water use over three time periods (2018, 2021, and 2023). We find that the quantity of overwatering, as well as the number of customers overwatering, is decreasing over time. AIRS provides repeatable estimates of irrigated area and irrigation demand that allow water utilities to track water user habits and landscape changes over time and, when controlling for other variables, see if water conservation efforts are effective. In terms of image analysis, we find that (1) both NAIP and drone imagery are sufficient to measure irrigated area in urban settings, (2) the selection of a threshold value for the normalized difference vegetation index (NDVI) becomes less critical for higher-resolution imagery, and (3) irrigated area measurement can be enhanced by combining NDVI with other tools such as building footprint extraction, object classification, and deep learning.

Keywords: irrigation; NDVI; urban water use; landscape; sustainability; conservation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/21/9356/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/21/9356/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:21:p:9356-:d:1508371

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().