Predicting Opportunities for Greening and Patterns of Vegetation on Private Urban Lands

This paper examines predictors of vegetative cover on private lands in Baltimore, Maryland. Using high-resolution spatial data, we generated two measures: “possible stewardship,” which is the proportion of private land that does not have built structures on it and hence has the possibility of supporting vegetation, and “realized stewardship,” which is the proportion of possible stewardship land upon which vegetation is growing. These measures were calculated at the parcel level and averaged by US Census block group. Realized stewardship was further defined by proportion of tree canopy and grass. Expenditures on yard supplies and services, available by block group, were used to help understand where vegetation condition appears to be the result of current activity, past legacies, or abandonment. PRIZM™ market segmentation data were tested as categorical predictors of possible and realized stewardship and yard expenditures. PRIZM™ segmentations are hierarchically clustered into 5, 15, and 62 categories, which correspond to population density, social stratification (income and education), and lifestyle clusters, respectively. We found that PRIZM 15 best predicted variation in possible stewardship and PRIZM 62 best predicted variation in realized stewardship. These results were further analyzed by regressing each dependent variable against a set of continuous variables reflective of each of the three PRIZM groupings. Housing age, vacancy, and population density were found to be critical determinants of both stewardship metrics. A number of lifestyle factors, such as average family size, marriage rates, and percentage of single-family detached homes, were strongly related to realized stewardship. The percentage of African Americans by block group was positively related to realized stewardship but negatively related to yard expenditures.     

Modeling Residential Lawn Fertilization Practices: Integrating High Resolution Remote Sensing with Socioeconomic Data

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 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.     

A long-term survey on anthropogenic impacts to the water quality of coral reefs, southern Taiwan

Before 2001, the ecological protection area in the Kenting National Park (KTNP), southern Taiwan, was poorly described. In this study, a set of four-year data (2001-2004) of seawater qualities at 19 sampling sites around the Nanwan Bay in the KTNP was used to explore anthropogenic impacts to ecological environment, especially coral reefs. The parameters of water quality were analyzed immediately after collection. The results showed that higher values of nutrients and suspended solids were attributed to the higher run-off around Nanwan Bay. The fluxes of nutrients and suspended solids were consistently correlated to rainfall. Hence, equations were developed to calculate nutrient fluxes and suspended solids by using only rainfall data. Our results show that suspended solids and ammonia were the dominant factors leading to the drop in coral coverage. In summary, the water quality in the intertidal zone of Nanwan Bay has been degraded and required greater attention.