HERO: Human-Environment Regional Observatory

Forest-Change Monitoring


In the Massachusetts Forest Monitoring Program (MAFoMP), Clark students work with faculty to apply remote sensing data and technology to monitor large-area forest cover change in Massachusetts. With the addition of an NSF REU Site grant, a summer program for Clark and Non-Clark students has now been added and has just completed its second  successful 8-week summer program on Massachusetts Forest mapping.

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.

This research aims to establish 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 is a program to monitor forest cover changes in Massachusetts using remote sensing data and state-of-the-art image processing techniques. We acquire, process, and classify Landsat imagery over three-year intervals from 1973 to present. Ancillary data such as slope and precipitation are used as inputs 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. This project will therefore contribute to improving the accuracy and efficiency of large-scale land-use change monitoring initiatives in Massachusetts and elsewhere.

View MaFoMP's current research proposal.

Research Products

Research Posters

Using classification trees with Landsat imagery, ancilliary variables, and FIA data to map tree species in Massachusetts, USA (Schwert 2010) [PDF]

Combining FIA species data with fragmentation maps to assess the effect of fragmentation on Pitch pine distribution in Massachusetts, USA (Wright 2010) [PDF]

A new method for pre-dating and post-dating land-cover maps with Landsat and ASTER imagery using a Kauth Thomas Change Index (Caiazzo 2010) [PDF]

The use of statistical models with Landsat imagery, ancillary variables, and FIA data to map tree species in Massachusetts, USA (Schwert 2010) [PDF]

A multitemporal assessment of forest fragmentation in Massachusetts (USA) using remotely sensed data (Wright 2010) [PDF]

Integrating fuzzy classification with observation-driven thresholding rules to improve forest type discrimination in mixed forest land cover (Bumbarger 2009) [PDF]

Determining habitat suitability of Asian longhorn beetle Anoplophora glabripennis in Massachusetts, U.S. using the Mahalanobis typicality approach (Shmookler 2009) [PDF]

Creating a Historical Database for Land-Cover Change Detection (Frazier 2006) [PDF]

A comparison of machine learning algorithms: the effects of classification scheme detail on map accuracy     (Fortier 2007)

Research Presentations

Mapping Wildfire Disturbances in Southern California Using Machine Learning Algorithms (Rogan 2005)

Application of remotely sensed data and technology to map land change in Massachusetts (MaFoMP 2007)

Integrating remotely sensed data and environmental variables to map forest cover in Massachusetts (MaFoMP 2007)

Integrating fuzzy classifications and in situ canopy measurement to improve forest class discrimination (Bumbarger 2009) [PPT]

A new method for updating and backdating land-cover maps using Landsat and ASTER imagery: Massachusetts, USA (Caiazzo 2009) [PDF]

Download Land Cover Data [ZIP]
Download Massachusetts Forest Data [ZIP]

Click the map below to see our circa 2000 Land-cover product.

Please contact Professor John Rogan at jrogan@clarku.edu for more information.

Visit Professor Rogan's School of Geography Web site.