Change analysis of Northborough, Massachusetts, 1987-2001

Kristopher Kuzera and Silvia Petrova

1987 LANDSAT TM – 30m resolutionFalse Color Composite Bands 2,3,4

Study areaNorthborough, located in central Massachusetts, has a population of14,013 from the year 2000. The town has experienced enormous amounts of land cover change in recent decades due to the continuing expansion of the Greater Boston metropolitan area, as well as the introduction of the electronics industry into the region, making it a good candidate for landcover change analysis.

ObjectiveThe objective is to compare land cover change in Northborough, Massachusetts using the images from the Landsat Thematic Mapper (TM) satellite from September 10, 1987 and ASTER satellite from August 29, 2001. Land cover classification based on spectral classes has been performed and reclassified into information classes. Change analysis has been done at 30 meter resolution for both the TM and ASTER images. Normalized Differences Vegetation Indexes (NDVI) have been created to compare biomass levels and changein vegetation over the 14 year period.

Band 2 GREEN

Band 3 RED

Band 4 NEAR INFRARED

Band 5 MIDDLE INFRARED

False Color Composite Bands 3,4,5

Band 1 GREEN

Band 2 RED

Band 3 NEAR INFRARED

Band 4 MIDDLE INFRARED

False Color Composite Bands 1,2,3

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2 0

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2001 ASTER – 30m resolutionFalse Color Composite Bands 1,2,3

Land Cover Classification 1987

Land Cover Classification 2001

NDVI ASTER 2001

NDVI Landsat TM 1987

Training Sites

1999

1985

Prior Knowledge Land Cover Maps

1985

1971

Prior Knowledge Land Cover Maps

ToolsAll analysis was performedusing IDRISI Kilimanjaro.

MethodologyTo prepare for change analysis, the following procedures were used

to synchronize and classify the imagery from both time periods.• Noise was removed from TM bands 2 and 3 using Principal

Components Analysis.• Both TM and ASTER imagery were geo-referenced to a

matching coordinate system, SPC83MA1. • Training sites were developed to classify both of the imagery.• Signatures were created for the 11 different land use categories.• Maximum Likelihood classifier was used, incorporating prior

knowledge land use maps from MassGIS, to categorize each

pixel into the appropriate land cover classes.

CROSSTAB module was used to compare both change and persistence for each of the land cover classes. The graph above demonstrates amount of change (in square kilometers) for each from 1987 to 2001. The map below shows both change and persistence of areas between built and nonbuilt categories.

Comparison of Built and

Nonbuilt areas, 1987-2001

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Land Cover Change Comparison(Landsat TM '87 30m resolution vs. ASTER '01 30m resolution)

Landsat TM '87ASTER '01

sq. k

ilom

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Change Analysis of Land CoverAfter classifying the imagery into appropriate categories, it became evident that change occurred in different directions for most of the land cover classes. Certain categories, such as residential and grass, gained while others, like forest and cropland, lost over the period. Increases in residential and industrial/commercial areas are likely the result of the general growing trend westward of the Greater Boston area. Expanding golf and other recreational areas increased grass classifications. Forested and agricultural lands suffered large losses due to these expansions, primarily because the town is quickly converting from a rural to a suburban setting. Other small changes are likely due to differences in satellite platforms or slight climate variations, resulting in misclassifications.

1987 2001 Residential replaces forest.

Cleared land for new development resembles industrial/commercial. Orthophoto

1m resolution

Birchwood community, first built in late 1980s, shows change from forest to residential .

Change Analysis using NDVIChange analysis was also done using the NDVI images from both years. These images were compiled using the red and near infrared bands from each satellite imagery. IMAGEDIFF module was used to analyze the direction of change by creating a standardized anomaly image classified into six categories.

Change greater than one positive standard deviation from the mean shows large growth in vegetation, while change exceeding one negative standard deviation show large loss in vegetation. The pixels within one standard deviation from the mean show small change in vegetation. This is likely due to either differences in moisture and saturation levels between the 14-year period or in satellite platforms.

Standardized AnomalyImage

Within the Birchwood community, positive standard deviation values are the result of residential grass replacing cleared land from 1987. Negative values indicate the conversion from forest to residential.

Expanding residential lands frequently target forested areas.

Total change 14.5 sq. kilometers

Conversion from forest to residential, the dominant land cover swap, accounted for 35.3 % of the total change.

6.5%

35.2% 26.8%

5.8%5.0% 4.6%

4.4%

4.4%4.1%

3.1%

Deciduous to Low Dens. Res.

Deciduous to High Dens. Res.

Conifer to Low Dens. Res.

Cropland to Low Dens. Res.

Low to High Dens. Res.

Ind./Comm. to High Dens. Res.

High to Low Dens. Res.

Low Dens. Res. to Deciduous

Deciduous to Conifer

All other change

Swapping of Major Land Use Categories

Change from Forest to Residential