Skip to Main Content
Modeling residential lawn fertilization practices: integrating high resolution remote sensing with socioeconomic dataAuthor(s): Weiqi Zhou; Austin Troy; Morgan. Grove
Source: Environmental Management. 41(5): 742-752.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
View PDF (496.7 KB)
DescriptionThis 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 and greenness data were used to estimate two measures of household lawn fertilization practices, household annual fertilizer nitrogen application amount (N_yr) and household annual fertilizer nitrogen application rate (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.
- Check the Northern Research Station web site to request a printed copy of this publication.
- Our on-line publications are scanned and captured using Adobe Acrobat.
- During the capture process some typographical errors may occur.
- Please contact Sharon Hobrla, email@example.com if you notice any errors which make this publication unusable.
CitationZhou, Weiqi; Troy, Austin; Grove, Morgan. 2008. Modeling residential lawn fertilization practices: integrating high resolution remote sensing with socioeconomic data. Environmental Management. 41(5): 742-752.
KeywordsLawn fertilization, Lawn greenness, Remote sensing, Socioeconomic characteristics, Modeling, Object-oriented classification, LTER
- Can money buy green? Demographic and socioeconomic predictors of lawn-care expenditures and lawn greenness in urban residential areas
- Nitrogen input from residential lawn care practices in suburban watersheds in Baltimore county, MD
- The effects of landscape cover on surface soils in a low density residential neighborhood in Baltimore, Maryland
XML: View XML