2-Year Proposed Project Description for HERO
Dr. John Rogan, Principle Investigator
Application of Remote Sensing Data and Technology to Monitor Large-area Forest Cover Change in New England: The Massachusetts Forest Monitoring Project (MaFoMP)
Typically mandated to operate over large areas, operational monitoring programs face daunting logistical and methodological constraints, in addition to data acquisition and analysis costs that differ from standard case study approaches to land cover change. The leading constraints include: choice of appropriate classification scheme, issues concerning data consistency and map accuracy (i.e., calibration and validation), very large data volumes, and time consumption related to data processing and interpretation. Large area monitoring programs are not common, but are expected to increase in the near future. While a large body of work has accumulated regarding land cover change monitoring using remote sensing data, very little guidance exists for addressing large area change mapping, especially in an operational context.
Therefore, MAFoMP serves as a large area land cover monitoring program in Massachusetts. Although the majority of Massachusetts is covered in forest, little is known about the patterns and processes of timber harvest and forest growth at landscape to regional scales. MAFoMP monitors forest cover change in Massachusetts using remote sensing data and state-of-the-art image processing techniques. The project acquires, processes, and classifies Landsat imagery over three-year intervals from 1973 to 2003. Ancillary data such as slope and precipitation are input in the machine-learning classification process. Calibration and validation data sets are assembled using field data, state timber harvest records, and US Forest Service FIA plot data. Preliminary results indicate high and consistent change map accuracy (~82%) and efficient techniques that should prove useful to burgeoning monitoring initiatives.
Year 1: Summer – Fall 2005 and Spring 2006
Products from Year 1:
Year 2: Summer – Fall 2006 and Spring 2007
Products from Year 2: