From Yardstick to Gyroscope -
Interdisciplinary Methods for the Long-Term Study of Social-Ecological Systems
Sense of Place: Domesticated nature, telephone surveys, and ethnography
Instructors - J. Morgan Grove, Laura Ogden
Date - January 28, 2007

Zhou, W., A. R. Troy, and J. M. Grove. (in press). Modeling residential lawn fertilization practices: Integrating high resolution remote sensing with socioeconomic data. Environmental Management xx:xx-xx.
Publication

This article investigates how remotely sensed lawn characteristics, such as parcel lawn area and parcel lawn greenness, combined with household characteristics, can be used to predict household lawn fertilization practices on private residential lands. This study involves two watersheds, Glyndon and Baisman’s Run, in Baltimore County, Maryland, USA. Parcel lawn area and lawn greenness were derived from high-resolution aerial imagery using an object-oriented classification approach. Four indicators of household characteristics, including lot size, square footage of the house, housing value, and housing age were obtained from a property database. Residential lawn care survey data combined with remotely sensed parcel lawn area data were used to estimate two measures of household lawn fertilization practices, household annual fertilizer nitrogen application rate (N_yr) and household annual fertilizer nitrogen application rate per unit lawn area (N_ha_yr). Using multiple regression with multi-model inferential procedures, we found that a combination of parcel lawn area and parcel lawn greenness best predicts N_yr, whereas a combination of parcel lawn greenness and lot size best predicts variation in N_ha_yr. Our analyses show that household fertilization practices can be effectively predicted by remotely sensed lawn indices and household characteristics. This has significant implications for urban watershed managers and modelers.