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Development of Population Density and Land Use Based Regression Model

This study aims to develop and refine a regression-based model using National Land Cover Data (NLCD) and population density to predict percent imperviousness. The model will estimate imperviousness in Connecticut Census tracts and watersheds, which will help understand the impact on water quality and biodiversity.

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Development of Population Density and Land Use Based Regression Model

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  1. Development of a Population Density and Land Use Based Regression Model to Calculate the Amount of Imperviousness Anna Chabaeva, Daniel L. Civco & Sandy Prisloe Department of Natural Resources Management & Engineering The University of Connecticut U-4087, Room 308, 1376 Storrs Road Storrs, CT 06269-4087 May 26, 2004

  2. Primary • Develop, assess, and refine a regression-based modeling technique to be used with National Land Cover Data (NLCD) and population density to predict percent imperviousness Secondary • Interpolate population density value for Connecticut watersheds • Estimate percent imperviousness for Connecticut Census tracts and watersheds Objectives 2

  3. Rooftops Transportation System • Roads • Sidewalks • Driveways • Parking lots • Buildings • Pools • Patios Impervious Surface The imprint of land development on the landscape: 3

  4. Flow dynamics – high flows low flows • Sedimentation load • Temperature regime • Pollution profile of storm water runoff • Stream biodiversity Impact of Imperviousness Limits the infiltration of water into soil and changes: 4

  5. 80 70 60 50 40 30 20 10 0 DEGRADED Watershed Imperviousness (%) Watershed Water Quality IMPACTED PROTECTED Adapted from Schueler, et al., 1994 Watershed Impacts 5

  6. Measuring the Amount of Imperviousness • Interpretive Approach • Spectral Approach • Modeling Approach 6

  7. Measuring the Amount of Imperviousness Interpretive Approach Image data are processed by the human analyst who visually interprets and manually extracts necessary information • Digitizing • Cover Tool 7

  8. Measuring the Amount of Imperviousness Spectral Approach Uses computer-based image processing to assess the spectral characteristics of a multispectral imagery • Sub-pixel Classification • Artificial Neural Networks • Classification and Regression Tree (CART) • Normalized Difference Vegetation Index (NDVI) • Vegetation-Impervious Surface-Soil (VIS) Model 8

  9. Measuring the Amount of Imperviousness Modeling Approach Employs numerical or statistical models to data derived from remote sensing imagery and/or ancillary spatial information • Population Density Based • Impervious Surface Analysis Tool (ISAT) • Regression Model 9

  10. Study Area MA Suffield North Castle West Hartford Marlborough CT RI Mount Vernon Waterford Woodbridge Stonington NY Groton Milford Stamford Eleven towns in Connecticut and New York. The town of Amherst, MA is located in northern Massachusetts and is omitted from the figure 10

  11. Data Requirements All datasets are in Connecticut State Plane feet, NAD83 coordinates • Planimetric data • National Land Cover Data (NLCD) 1992 • Census tracts 1990 data • Census blocks 2000 data • CT watershed boundary data • Town boundary data 11

  12. CT: Groton Marlborough Milford Stamford Stonington Suffield West Hartford Waterford Woodbridge MA: Amherst NY: Mount Vernon North Castle Impervious footprint of features derived from aerial photography Planimetric Data 12

  13. National Land Cover Data (NLCD) 100’x100’ grid cells 13

  14. Accuracy Report for NLCD Classes Overall Accuracy – 0.46; NR – not reported 14

  15. Town Boundary Data (Town of Milford, CT Example) Including large waterbodies Excluding large waterbodies Obtained from: Map and Geographic Information Center (MAGIC) – CT boundary data Local town managers – NY and MA town boundary data 15

  16. 108 Census tracts Obtained from: Cartographic Boundaries section of the U.S. Census Bureau Census Tract Data Original (green) and edited (red) tract data 16

  17. Planimetric Data Based Impervious Surface Coefficients Calculation (West Hartford Example) Step 1. Cut CT NLCD grid to the extent of the town Step 2. Convert NLCD grid to shapefile Step 3. Clip shapefiles to the town boundary limits Step 4. Define Imperviousness field for planimetric data set Step 5. Combine planimetric and land cover data Step 6. Create Frequency tables Step 7. Calculate impervious surface percentage 17

  18. Analysis Map Calculator + West Hartford, CT area Step 1. Cut CT NLCD Grid to the Extent of the Town West Hartford Area West Hartford, CT area NLCD grid CT NLCD grid 18

  19. Grid2Shape Script West Hartford, CT area NLCD shapefile Step 2. Convert NLCD Grid to Shapefile West Hartford, CT area NLCD grid Note: Grid2Shape Script converts Grid cells to square polygons while Convert to Grid… command transforms square Grid cells into triangular polygons 19

  20. Geoprocessing Clip West Hartford, CT NLCD shapefile West Hartford, CT imperviousness shapefile Step 3. Clip Shapefiles to the Town Boundary West Hartford, CT area NLCD shapefile West Hartford, CT area imperviousness shapefile 20

  21. Step 4. Define Imperviousness Field for Planimetric Dataset Impervious Surface = 1 Pervious Surface = 0 21

  22. Union West Hartford, CT LULC and imperviousness shapefile Deciduous Forest Impervious Step 5. Combine Planimetric and Land Cover Data + West Hartford, CT NLCD shapefile West Hartford, CT imperviousness shapefile 22

  23. Xtools Extension Table Frequency Frequency Fields: Gridcode Imperv_y_n Summary Field: Area West Hartford, CT imperviousness area by LULC class table Step 6. Create Frequency Tables Summary Impervious Area Table for Each LULC class West Hartford, CT LULC and imperviousness attribute table 23

  24. Xtools Extension Table Frequency West Hartford, CT total area by LULC class table Frequency Field: Gridcode Summary Field: Area Step 6. Create Frequency Tables Summary Total Area Table for Each LULC class West Hartford, CT LULC and imperviousness attribute table 24

  25. Step 7. Calculate Impervious Surface Percentage Join + West Hartford Imperviousness Area by LULC class Table West Hartford, CT total and imperviousness area by LULC class table West Hartford Total Area by LULC class Table Add New Field  Calculate  [Area] \ [lulc_area] * 100 25

  26. Planimetric Data Based Summary Information at the Town Level Town Total Area (ac) Total Impervious Surface Area (ac) Percent Impervious Surface (%) Total Population (people) Population Density (people per sq. mi) Amherst, MA 17759.68 1509.03 8.5 35228 1270 Groton, CT 20004.32 2564.91 12.8 40110 1283 Marlborough, CT 15004.81 517.50 3.4 5535 236 Milford, CT 14101.03 3422.69 24.0 49938 2267 Mount Vernon, NY 2807.01 1294.77 46.1 67072 15292 North Castle, NY 16718.37 1231.50 7.4 10061 385 Stamford, CT 24590.05 5326.63 21.7 108050 2812 Stonington, CT 25048.85 1758.37 7.0 16919 432 Suffield, CT 27755.36 1018.00 3.7 11427 263 Waterford, CT 21908.28 1529.03 7.0 17930 524 West Hartford, CT 14335.33 3165.28 22.1 60105 2683 Woodbridge, CT 12283.42 943.20 7.7 7924 413 26

  27. Clip + West Hartford, CT Census tracts 1990 West Hartford, CT LULC and imperviousness by Census tract 1990 Calculate Impervious Surface Percentage per Census Tract West Hartford,CT LULC and imperviousness 27

  28. Planimetric Data Based Summary Information at the Tract Level Tract # Total Area (ac) Total Impervious Surface Area (ac) Percent Impervious Surface (%) Total Population (people) Population Density (people per sq. mi) West Hartford, CT 4961 756.54 376.62 49.8 4721 3994 4962 685.35 224.66 32.8 3554 3319 4963 559.25 166.93 29.8 3825 4377 4964 707.71 179.33 25.3 3810 3445 4965 338.11 136.92 40.5 2335 4420 4966 892.88 135.70 15.2 4350 3118 4967 295.78 124.50 42.1 4048 8759 4968 333.10 99.84 30.0 2340 4496 4969 521.14 223.01 42.8 6079 7466 4970 591.13 167.43 28.3 2715 2939 4971 326.62 127.42 39.0 3379 6621 4972 433.76 107.15 24.7 2335 3445 4973 1270.31 227.90 17.9 3277 1651 4974 1005.66 225.43 22.4 3027 1926 4975 947.15 206.68 21.8 3150 2128 4976 442.49 118.28 26.7 2546 3682 4977 4226.74 317.30 7.5 4589 695 28

  29. Percent Imperviousness vs. Population Density at the Tract (n=108) Level 29

  30. Regression Model Input Variables Total percent imperviousness based on planimetric data Population density % A11 – percent of Open Water class area % A21 – percent of Low Intensity Residential class area % A22 – percent of High Intensity Residential class area % A23 – percent of Commercial/Industrial/Transportation class area % A31 – percent of Bare Rock/Sand/Clay class area % A32 – percent of Quarries/Strip Mines/Gravel Pits class area % A33 – percent of Transitional class area % A41 – percent of Deciduous Forest class area % A42 – percent of Coniferous Forest class area % A43 – percent of Mixed Forest class area % A51 – percent of Shrubland class area % A61 – percent of Orchards/Vineyards/Other class area % A81 – percent of Pasture/Hay class area % A82 – percent of Row Crops class area % A85 – percent of Urban/Recreational Grasses class area % A91 – percent of Woody Wetlands class area % A92 – percent of Emergent Herbaceous Wetlands class area 30

  31. Percent Imperviousness, % A11, % A21, …, % A91 sqrt(% A11), sqrt(% A21), …, sqrt(% A91) Population Density Log10(Population Density) Regression Model Normality Shapiro-Wilk’s W Test Transformed Input Variables 31

  32. Input Data Validation Data 20 % - 23 tracts 80 % - 85 tracts Regression Model 108 Census tracts where - b1 is an intercept - b2, b3, … b19 are the regression coefficients - PopDenis the Population density - %A22, %A23, %A31,…%A92 are the percent of the NLCD category area within the tract 32

  33. Regression Model Coefficients 33

  34. JMP Stepwise Fit Analysis Output Variables with no coefficient reported were determined not to be significant contributors (probability value less then 0.25) and were omitted from the final model 34

  35. Regression Model Validation Applied to validation data – RMSE < 6% 35

  36. Regression Model Validation Applied to all 108 tracts – RMSE < 4.5% 36

  37. Tract # PI ac PI pr Diff Predicted minus Actual %IS -25 to -20 1501 38.0 37.7 -0.3 -20 to -15 1502 22.0 28.1 6.1 -15 to -10 -10 to -5 1503 36.0 34.0 -2.0 -5 to -3 1504 37.0 36.6 -0.4 -3 to -2 -2 to -1 1505 16.0 16.2 0.2 -1 to 0 1506 18.0 16.7 -1.3 0 to 1 1507 13.0 14.9 1.9 1 to 2 2 to 3 1508 31.0 28.4 -2.6 3 to 5 1509 25.0 25.3 0.3 5 to 10 10 to 15 1510 29.0 36.8 7.8 15 to 20 1511 33.0 31.2 -1.8 20 to 25 1512 30.0 28.6 -1.4 Difference between Regression Model Based and Actual Percent Imperviousness (Town of Milford, CT Example) 37

  38. Predicted minus Actual %IS Tract # PI ac PI pr Diff -25 to -20 7021 5.7 3.0 -2.7 -20 to -15 -15 to -10 7022 10.5 11.1 0.6 -10 to -5 7023 22.6 25.6 3.0 -5 to -3 -3 to -2 7024 28.9 31.2 2.3 -2 to -1 7025 38.5 38.1 -0.4 -1 to 0 7026 49.1 26.7 -22.4 0 to 1 1 to 2 7027 22.1 22.0 -0.1 2 to 3 7028 8.8 10.2 1.4 3 to 5 5 to 10 7029 10.4 8.2 -2.2 10 to 15 7030 14.7 11.9 -2.8 15 to 20 20 to 25 Difference between Regression Model Based and Actual Percent Imperviousness (Town of Groton, CT Example) 38

  39. Planimetric Data NLCD DOQQ Underestimation of Actual Percent Imperviousness (Town of Groton, CT, Tract 7026 Example) 39

  40. Predicted minus Actual %IS -25 to -20 -20 to -15 -15 to -10 -10 to -5 -5 to -3 -3 to -2 -2 to -1 -1 to 0 0 to 1 1 to 2 2 to 3 3 to 5 5 to 10 10 to 15 15 to 20 20 to 25 Difference between Regression Model Based and Actual Percent Imperviousness (Town of Stamford, CT Example) 40

  41. DOQQ Planimetric Data NLCD Overestimation of Actual Percent Imperviousness (Town of Stamford, CT, Tract 220 Example) 41

  42. Regression Based Percent Impervious Surface for Connecticut Tracts Percent Impervious Surface 0.0 - 1.0 10.1 - 15.0 1.1 - 2.0 15.1 - 20.0 2.1 - 3.0 20.1 - 25.0 3.1 - 5.0 25.1 - 30.0 5.1 - 10.0 30.1 - 100.0 42

  43. Watersheds that fall completely within the town boundary and have planimetric data available CT watersheds 236 watersheds in Connecticut Planimetric Data Based Impervious Surface Coefficients for CT Watersheds (West Hartford, CT Example) 43

  44. Impervious Percent Impervious Basin # Town Total Area (ac) Area (ac) Surface (%) 4403 - 00 - 1* West Hartford 252.70 55.04 21.8 4403 - 00 - 1 - L2 West Hartford 81.56 9.33 11.4 4403 - 00 - 2 - R1 West Hartford 1021.42 222.30 21.8 4403 - 00 - 2 - R2 West Hartford 2253.73 733 .89 32.6 4403 - 00 - 2 - R3 West Hartford 774.78 270.55 34.9 4403 - 03 - 1 West Hartford 54.50 3.00 5.5 4403 - 03 - 1 - L1 West Hartford 727.98 4.37 0.6 4403 - 03 - 1 - L2 West Hartford 176.73 4.65 2.6 4403 - 04 - 1* West Hartford 117.20 14.23 12.1 4403 - 04 - 2 - R1 West Hartford 136.52 29.44 21.6 4403 - 05 - 1 West Hartford 259.77 38.34 14.8 4403 - 06 - 1 West Hartford 1384.46 230.00 16.6 4403 - 07 - 1 West Hartford 1326.76 395.92 29.8 4404 - 11 - 1 West Hartford 268.96 41.10 15.3 Planimetric Data Based Impervious Surface Coefficients for CT Watersheds (West Hartford Example) 44

  45. Estimating Total Population Value per CT Watershed Convert to Grid… NLCD grid Spatial Extent properties • Census block 2000 grid Census block 2000 shapefile 45

  46. Estimating Total Population Value per CT Watershed Analysis Summarize Zones CT Watersheds Field defining the zones – Basin_no (Basin Number) Theme containing variable to summarize – Census Blocks 2000 Grid 46

  47. Estimating Total Population Value per CT Watershed Join Attribute Table for CT Watersheds Shapefile Statistics Table for Population Value 47

  48. Calculating Total Area of Each LULC Class per CT Watershed Analysis Tabulated Areas CT Watersheds Row Theme NLCD Column Theme 48

  49. Regression Model based Predicted vs. Actual Percent Imperviousness for Selected Connecticut Watersheds (n = 236) RMSE = 4% 49

  50. Percent Impervious Surface 0.0 - 1.0 1.1 - 2.0 2.1 - 3.0 3.1 - 5.0 5.1 - 10.0 10.1 - 15.0 15.1 - 20.0 20.1 - 25.0 25.1 - 30.0 30.1 - 100.0 Regression Based Percent Impervious Surface for Connecticut Watersheds (n = 6711) 50

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