1. Change analysis of Northborough, Massachusetts, 1987-2001 Kristopher Kuzera and Silvia Petrova 1987 LANDSAT TM – 30m resolution False Color Composite Bands 2,3,4 Study area Northborough, located in central Massachusetts, has a population of 14,013 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 land cover change analysis. Objective The 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 change in 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 1 9 8 7 2 0 0 1 2001 ASTER – 30m resolution False 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 Tools All analysis was performed using IDRISI Kilimanjaro. Methodology To 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 sq. kilometers Change Analysis of Land Cover After 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 NDVI Change 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 Anomaly Image 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. Swapping of Major Land Use Categories Change from Forest to Residential