Abstract
Forest fragmentation and degradation are a problem in many areas of the world and are a cause for concern to land managers. Similarly, countries interested in curtailing climate change have a keen interest in monitoring forest degradation. Traditional methods for measuring forested landscape pattern dynamics with maps made from classified satellite imagery fall short with respect to the compatibility of their forest definitions with information needs. In addition, they are not easily amenable to interpretation using tools like confidence intervals derived from survey sampling theory. In this paper, we described a novel landscape monitoring approach that helps fill these gaps. In it, a grid of photo plots is efficiently created and overlaid on high-resolution imagery, points are labeled with respect to their land-use by a human interpreter, and mean values and their variance are calculated for a suite of point-based fragmentation metrics related to forest degradation. We presented three case studies employing this approach from the US states of Maryland and Pennsylvania, highlighted different survey sampling paradigms, and discussed the strengths and weaknesses of the method relative to traditional, satellite imagery-based approaches. Results indicate that the scale of forest fragmentation in Maryland is between 250 and 1000 m, and this agrees with compatible estimates derived from raster analytical methods. There is a positive relationship between an index of housing construction and change in forest aggregation as measured by our metrics, and strong agreement between metric values collected by human interpretation of imagery and those obtained from a land cover map from the same period. We showed how the metrics respond to simulated degradation, and offered suggestions for practitioners interested in leveraging rapid photointerpretation for forest degradation monitoring.
Highlights
Links between forest fragmentation, forest loss, and forest degradation have drawn interest in recent years due to increased focus on carbon monitoring and climate change mitigation strategies.For example, the United Nations’ Reducing Emissions from Deforestation and Degradation (REDD)program [1] requires the measurement and monitoring of forest cover in exchange for donor support for various forest conservation activities
There is a positive relationship between an index of housing construction and change in forest aggregation as measured by our metrics, and strong agreement between metric values collected by human interpretation of imagery and those obtained from a land cover map from the same period
Forest fragmentation has been proposed as one indicator of forest degradation [2], and its measurement and monitoring show promise for providing the information needed for REDD reporting [3,4]
Summary
Links between forest fragmentation, forest loss, and forest degradation have drawn interest in recent years due to increased focus on carbon monitoring and climate change mitigation strategies.For example, the United Nations’ Reducing Emissions from Deforestation and Degradation (REDD)program [1] requires the measurement and monitoring of forest cover in exchange for donor support for various forest conservation activities. Nationalor continent-scale satellite imagery products often provide accurate information for coarse-scale analysis and monitoring of forests and other valuable ecosystems, as well as serve as a base layer for many activities, like stratification of forest inventory plots for improved estimation of forest status and trends [8]. They are not suitable for all applications, such as when forest definitions from maps don’t align with information needs. Most candidate land cover maps, like the National Land Cover Database (NLCD) [9]
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