Land use change monitoring in Maryland using a probabilistic sample and rapid photointerpretation

Abstract

The U.S. state of Maryland needs to monitor land use change in order to address land management objectives. This paper presents a change detection method that, through automation and standard geographic information system (GIS) techniques, facilitates the estimation of landscape change via photointerpretation. Using the protocols developed, we show a net loss of forest land, with losses due primarily to urban development and most gains in forest land coming from agricultural land conversions. This study indicates that about 75,000 photo plots would be needed to estimate land use change in Maryland at the county-level, assuming a uniform sampling intensity and a maximum desired county-level sampling error of 20 percent, with an estimated time requirement of 125 h. The protocol we present for designing, planning and conducting a photointerpretation-based land use change procedure can be used by other regions and is well suited for land use change monitoring, assuming that analysis of opportunity costs suggests that existing or new remotely sensed imagery classifications do not meet user needs.