Appendix 1: Definitions and Methods

This appendix outlines the procedures and definitions used to generate the assess- ment of urban forest resources in the United States. it provides supplementary infor- mation to discussions from chapter 2 of this report.

A place is defined by the U.S. Bureau of the Census as a concentration of people. A place may (incorporated place) or may not (census-designated place) have legally pre- scribed limits, powers, or functions. To be designated as a place, the concentration of population must have a name, be locally recognized, and not be part of any other place (U.S. Department of Commerce, Bureau of the Census 1994b). Of the 23,435 places in all 50 states in the 1990 census, 19,289 were incorporated; 4,146 were census- designated places.

Urbanized areas have a population of 50,000 or more and a minimum population den- sity of 384 people per square kilometer (U.S. Department of Commerce, Bureau of the Census 1994b). Individual places exist both within and outside urbanized areas. Any place with at least 2,500 people and located outside urbanized areas is designated as an urban place (U.S. Department of Commerce, Bureau of the Census 1994b). Rural places are places outside urbanized areas that have a population of less than 2,500.

Urban area (UA) was a designation created for this report to represent the areas where people and their developments are concentrated. Urban area was defined as the area occupied by the union of three census-defined urban designations: (1) urbanized areas, (2) places that contain some urbanized areas within their boundaries, and (3) urban places. Areas totally surrounded by urbanized areas but not within an urbanized area or place boundary also were considered to be urban areas.

A metropolitan area (MA) is a county, or group of counties, containing a large popula- tion nucleus as its core and includes adjacent communities having a high degree of economic and social integration with the core (U.S. Department of Commerce, Bur- eau of the Census 1994b). Metropolitan areas are further classified into metropolitan statistical areas (MSAs), consolidated metropolitan statistical areas (CMSAs), and primary metropolitan statistical areas (PMSAs). Most metropolitan areas in the

Appendix 1: Definitions and Methods

Terminology

Urban Areas

Metropolitan Areas

United States represent a county or group of counties, but metropolitan areas in the six New England states are based on city boundaries. New England county metropoli- tan areas (NECMAs) offer an alternative, county-based definition for metropolitan areas in those states (U.S. Department of Commerce, Bureau of the Census 1994b).

The MSAs consist of one or more counties that contain either a core city of 50,000 or more inhabitants or an urbanized area and have a total population of at least 100,000 (75,000 in New England). In addition to the counties containing the principal concentra- tion of population, other counties are included in the MSA if they meet certain criteria (for example, a specified level of commuting to a principal county, minimum population density, and minimum percentage of the population that is urban).

The CMSAs are larger metropolitan units, consisting of multiple MSAs with a combined population of 1 million or more, that demonstrate strong internal economic and social links with the central core of the larger area. The MSAs within CMSAs are redesignated as PMSAs (U.S. Department of Commerce, Bureau of the Census 1994b).

The NECMAs are metropolitan areas that are county-based representations of city- based metropolitan areas in the six New England states. The NECMAs are defined for MSAs and CMSAs only in these six states (U.S. Department of Commerce, Bureau of the Census 1994b). In this report, reference to metropolitan areas (MAs) includes county-based MSAs, CMSAs, and their PMSA components. In the six New England states, the MA definition incorporates county-based NECMAs as surrogates for the city-based MSAs and CMSAs.

The USDA Natural Resources Conservation Service includes the land cover categories

“urban and built-up land” and “small built-up land” as part of their national resources inventory (NRI). Their urban and built-up definition includes the following land uses of at least 0.1 hectare: airports, playgrounds with permanent structures, cemeteries, public administration sites, commercial sites, residences, golf courses, sanitary land- fills, industrial sites, sewage treatment plants, institutional sites, water control structures and spillways, and parking lots. Highways, railroads, and other transportation facilities were included in this classification if they were surrounded by other urban or built-up areas. Tracts of less than 4.05 hectares (10 acres) not meeting the above definition (for example, water), but that are completely surrounded by urban and built-up land, were included as urban and built-up land (USDA Natural Resources Conservation Service 1994).

The NRI was developed from a stratified, two-stage, sampling scheme of 863,185 second-stage sample points to collect data on tree cover and land use (along with other variables). Tree cover was recorded as the percentage of earth covered with trees in a 0.81-hectare (2-acre) circle around the sample point. Land use type also was recorded at the sample point. Tree cover and land use data (that is, urban, agriculture, and forest) were calculated for every county in the United States by using the appropriate weighting factor for each sample point within the county (USDA Natural Resources Conservation Service 1994).

Although limitations of the NRI have been noted (for example, content, definitions and standards, consistency in data collection, quality-control procedures, and design [USDA Natural Resources Conservation Service 1995]), the NRI provides field and photo data for the entire country, land use data, and a means of nationally cross-comparing tree National Resources

Inventory Urban

Classifications

cover data with our report’s primary tree canopy cover database (USDA Forest Service 1997c). Because NRI data are county based, comparisons can be made only with county and metropolitan area tree cover data.

For the assessment of the national urban forest resource, metropolitan area and urban area definitions were used. In some cases, NRI estimates of urban and built-up land were included for comparison.

Within each urban geographic definition, from states to places, percentage of tree cover was assessed from forest density map data compiled by the USDA Forest Ser- vice, Southern Forest Experiment Station’s Forest Inventory and Analysis (SO-FIA) research unit (USDA Forest Service 1997c, Zhu 1994). Forest density (0 to 100 per- cent) was calculated for each 1-square kilometer pixel by using a statistical model and 1991 advanced very high resolution radiometer (AVHRR) data. Multiple models were developed to correspond with different physiographic settings across the United States.

Each statistical model was developed to predict forest density per square kilometer in an AVHRR pixel based on the proportion of 28.5- by 28.5-meter cells (from Landsat thematic mapper classified data sets) that were forested. Within each urban geograph- ic boundary, tree cover was calculated by using an average of forest density estimates for individual pixels.

Although based on forest data and developed to estimate forest density, the AVHRR data likely yield better assessments of tree cover than of forest density. The spectral images received by the AVHRR from trees in forest and nonforest areas are similar because the statistical models cannot differentiate between forest and nonforest trees within a pixel. Thus, nonforest tall vegetation (orchard trees, urban trees) contribute to the forest density estimate within a pixel. The tree cover data presented in this report were based on the AVHRR forest density estimates.

The AVHRR data were merged with the physical boundaries of various urban entities (places, urbanized areas, MSAs, PMSAs) in a geographic information system (GIS) to calculate tree cover across the United States. The boundaries of some coastal places extend into large areas of water, thereby causing estimates of tree cover in those locations to be artificially low. To adjust for underestimates, tree cover for coastal places and places bordering lakes greater than 416 square kilometers were recalculated

¹

by dividing the tree cover estimate (in square meters) by the census-defined land area (rather than the GIS-calculated total area). These recalculated estimates are noted in the appendices. Although many other cities contain water within their borders, their tree cover was not adjusted, owing to the limitations in matching GIS-calculated areas with census areas. Thus, tree cover of individual places was based predominantly on the total area of a city, rather than on its land area.

Tree cover data interpreted from aerial photographs (Nowak and others 1996) were compared with AVHRR tree cover estimates within selected cities to determine poten- tial inaccuracies in predicting tree cover in an individual city. The NRI tree cover data also were compared with AVHRR data to determine any discrepancies between the two

Tree Cover Assessment

1 Places adjacent to Toledo Bend Reservoir, LA-TX, Lower Red Lake, MN, Flathead Lake, MT, Pyramid Lake, NV, and Leech Lake, MN, and lakes less than 416 square kilometers were not recalculated because data were not available.

databases. Because NRI data do not include Federal lands, comparisons between the two databases were limited to counties with less than 5 percent Federal land. Differ- ences between tree cover estimates based on NRI and those developed from AVHRR data are expected in analyses at the county level. Both databases have limitations that increase the uncertainty of the tree cover estimate at a fine spatial scale (that is, county level analyses and smaller). To identify potential problems in the tree cover data, states with average differences between AVHRR and NRI tree cover estimates of greater than 10 percent (t-test; alpha = 0.02) were noted.

Potential factors affecting tree cover in urban areas were explored by using Pearson correlation and regression analyses. The analyses included the following factors: eco- region, population, and city size characteristics. Land use effects could not be analyzed owing to data limitations.

Two potential limitations to the estimates of tree canopy cover were identified in this assessment. The first related to differences between the AVHRR and NRI tree cover data; the second related to an increased uncertainty of estimates as the area of analy- sis becomes smaller. In comparisons of AVHRR and NRI tree cover estimates, states in three regions exhibited average differences greater than 10 percent: (1) the central plains (Illinois, Indiana, Iowa, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota), (2) New England (Connecticut, Maine, New Hampshire, Rhode Island), and (3) New Jersey. For the central plains and New Jersey, AVHRR estimates of tree canopy cover were significantly higher than those generated from NRI data. The maxi- mum average difference between AVHRR and NRI tree cover estimates was 30 per- cent (Iowa). In New England, AVHRR estimates were significantly less than NRI esti- mates, with the maximum average difference (21 percent) in Connecticut.

Because both data sets have limitations, determining the general degree of accuracy nationwide was difficult. Limitations were most obvious for analyses at the county level owing to a small sample size with NRI data and the increased uncertainty of statistical model estimates from the AVHRR data for small areas. Validated field data against which to compare these estimates unfortunately are limited. Further investigations are needed to determine specific inaccuracies for each of these databases, the reasons for these discrepancies, and which database is most appropriate for use in particular instances.

Potential reasons for the inaccuracy of the AVHRR data in the regions identified above are that (1) AVHRR may classify tall crops in the central plains as tree cover and (2) inadequate calibration of the thematic mapper (TM) data used to develop statistical models for large physiographic regions. During certain seasons, other tall vegetation (tall grass and meadow shrub lands) may have spectral signals that the statistical models identify as tree cover. Thus, the “AVHRR spectral classifications often yield mixed results in sparsely forested regions (for example, the Plains States) or over small areas (for example, a county)” (Zhu 1994).

The possibility exists that the statistical model for AVHRR data may be miscalibrated for the Northeastern highlands physiographic region. Another explanation might be that the relatively high degree of coastline and water in this area leads to underestimating Potential Data

Limitations for Estimates

of Tree Canopy Cover

tree cover. New Jersey is the northern-most state in the Mississippi River and coastal flood plains physiographic region, which was calibrated with TM data from Florida and Louisiana; it may be too distant from the calibration areas for accurate use of the statistical models.

It is also possible that tree cover estimates from the AVHRR data are accurate in these regions and the inaccuracies lie within the NRI data set. Potential problems with the NRI data may result from a small sample size at the county level or from sample design and data collection problems (USDA Natural Resources Conservation Service 1995).

Regardless, additional analyses of both data sets are warranted.

Because the tree cover estimates are based on predictive equations, the accuracy of the estimate will decrease as the area for which the prediction is made becomes smaller (that is, the degree of uncertainty in predicting tree cover for an individual pixel is relatively high). In addition, even after adjusting for water, tree cover estimates for cities with boundaries extending into water bodies appear to be low. Users must be cautious about tree cover estimates for coastal places.

In comparing AVHRR data with photointerpreted tree cover data for individual cities, no significant difference (paired t-test, alpha = 0.05) between the two data sets was found for cities in forest or desert areas; for cities in grassland areas, however, AVHRR esti- mates tended to predict city tree cover at a rate lower than photointerpreted predictions by 5.6 percent. Overall, individual city tree cover predictions from the two methods dif- fered by up to 24 percent. Of the 60 cities compared, 37 percent had AVHRR estimates within 5 percent of photointerpreted estimates; 48 percent were within 5 to 15 percent;

and 15 percent were greater than 15 percent. These differences most likely were due to AVHRR limitations in relatively small areas, AVHRR pixel data not exactly matching the borders of the analyzed area, bodies of water within the analyzed area, and sam- pling variation in the photointerpretation methods.

The AVHRR cover data can be used for relative comparisons of tree cover among urban places within a region, but they have more limited use for individual tree cover estimates in a particular urban area, owing to the increased degree of uncertainty at this level of detail. Cover analyses (for example, aerial photo interpretation or field surveys) of individual urban places generally will provide a more reliable estimate of tree cover in a particular urban area and are recommended for that purpose when available.

To determine the amount of forest land within and around urban and metropolitan areas, the USDA Forest Service FIA database retrieval system was used (USDA For- est Service 1997a). For each state, the percentage of land area in forest land, acres of forest land, acres of forest land in urban counties, and percentage of forest land in urban counties were calculated. To illustrate the amount of forest land in and around urban areas, total forest land area, percentage of total land area in forest and timber- land, and percentage of timberland ownership by various groups within 80.5-, 160.9-, and 241.4-kilometer (50-, 100-, and 150-mile) radii were calculated for 53 major cities.

These cities generally represent the central or “core” cities of CMSAs for which suffi- cient data on forest land were available. The definition of forest land and timberland are as follows (USDA Forest Service 1997a):

Forest Analyses

Forest land: Land currently growing forest trees of any size with a total stocking value of at least 16.7; or lands formerly forested, currently capable of becoming forest land, and not currently developed for nonforest uses. These lands must be a minimum of 0.4 hectare (1 acre) in area. Roadside, streamside, and shelterbelt strips of timber must have a crown width of at least 36.6 meters (120 ft) to qualify as forest land. Unim- proved roads, trails, streams, and clearings within forest areas are classified as forest land if they are less than 36.6 meters wide. Recently clearcut areas that are currently nonstocked are classed as forest land unless they are being used for a nonforest use such as agriculture. Forest land is divided into two categories (timberland and other forest land), and both categories may be further classified as reserved if harvesting of trees is prohibited by statutory or administrative restrictions.

Timberland: Forest land that is producing or capable of producing crops of industrial wood. This land should be capable of producing 1.4 cubic meters of industrial wood per hectare (20 ft

³

/acre) per year. This definition includes all land formerly called com- mercial forest land.

Information regarding population and land characteristics was compiled for places, ur- banized areas, counties, metropolitan areas, and states based on U.S. population cen- sus data (U.S. Department of Commerce, Bureau of the Census 1992a, 1992b, 1992c;

Geolytics, Inc. 1996). The following population and land characteristics were obtained for places and urbanized areas: population (1990), population density (1990), age (1990), race or ethnicity (1990), median household income (1990), educational attain- ment (1990), and land and water area (urban places, 1990; urbanized areas, 1994).

Data collected for counties and metropolitan areas included population (1990, 1996), percentage of population change from 1990 to 1996, population density (1996), land area, and water area. The percentages of total white, black, Native American, Asian- Pacific islander, and Hispanic origin populations (1990) also were obtained for counties and metropolitan areas. County population growth trends (1990-96) by population size and population density were analyzed to identify patterns of association between population growth and these factors.

To assess the total urban forest resource in the United States, the percentage of tree cover for all urban areas was determined from the AVHRR data and multiplied by its associated land and water area (U.S. Department of Commerce, Bureau of the Census 1992c) to calculate total area of tree cover (in hectares).

The average number of trees

²

per hectare of tree cover in urban areas was calculated from published and unpublished

³

urban forest assessments that encompassed all land uses within a city (Nowak 1991, 1994). The average tree cover density (that is, the number of trees per hectare of tree cover) was calculated for each city by dividing the city’s tree density (trees per hectare) by its average percentage of tree cover. This cal- culation was done for seven selected cities (table 14). The average tree cover density

Population Characteristics

National Urban Forest Assessment

2 Including 2.54-centimeter (1-in) minimum d.b.h. trees and shrubs in tree form (single stemmed).

3 Unpublished field data. On file with: D.J. Nowak, USDA Forest Service, Northeastern Research Station, c/o SUNY- CESF, 5 Moon Library, Syracuse, NY 13210.

for urban areas in the United States (504 trees per hectare of tree cover) represents an average of the tree cover density values for these cities. This value was multiplied by the total hectares of tree cover in urban areas to estimate the total number of urban trees in the United States (see table 4).

Estimating the total trees in metropolitan areas involved adding two separate calcula- tions: (1) total trees in urban areas within a metropolitan area, and (2) total trees in non- UA parts of the metropolitan area. To estimate the trees in the non-UA portion of metro- politan areas, information on the amount of forest land (including both timberland and other forest land) and tree density in timberland was obtained from the FIA database retrieval system for metropolitan areas in each state (USDA Forest Service 1997a). To estimate tree density of other forest land, the average ratio of tree density in other for- est land to that in timberland in New York State (0.46)

⁴

was applied to the timberland density estimate. For states not having forest inventory data, tree density values from an adjacent state were used. The total trees in non-UA parts of metropolitan areas was calculated by multiplying the tree cover (in hectares) in these areas by the timberland and other forest land tree density values, proportional to the amount of land each forest type occupied in the metropolitan area. The total tree population in metropolitan areas of the United States represented the sum of the tree population in urban areas and the total number of trees in the non-UA portion of metropolitan areas.

Table 14—Average trees per hectare of tree cover for 7 U.S. cities

City Tree density Tree cover

^a

Tree cover density Reference

Trees/ha Percent Trees/ha

Atlanta, GA 275.8 36.7 751 Nowak

^b

Baltimore, MD 109.2 21.5 508 Nowak

^b

Boston, MA 82.9 22.3 372 Nowak

^b

Chicago, IL 68 11.0 618 Nowak 1994

New York City, NY 65.2 20.9 312 Nowak

^b

Oakland, CA 119.8 21.0 570 Nowak 1991

Philadelphia, PA 61.9 15.7 394 Nowak

^b

Average 504

a Tree cover estimated from 0.04-hectare field plots, except for Chicago and Oakland where data are based on aerial photo sampling of tree cover. Data are based on field sampling of all land uses within a city.

b Nowak, D.J. 1998. Unpublished field data. On file with: USDA Forest Service, Northeastern Research Station, c/o SUNY-CESF, 5 Moon Library, Syracuse, NY 13210.

4 Unpublished field data. On file with: USDA Forest Service, Northeastern Research Station, 11 Campus Boulevard, Suite 200, Newtown Square, PA 19073.

114 Tables 15 through 62—Percentage of tree cover, land and water area, land use, and population characteristics, by county, by state

221 Tables 63—Percentage of tree cover, land and water area, land use, and population characteristics by county-based metropolitan area (MA)

228 Table 64—Percentage of tree cover, land and water area, land use, and population characteristics by county-based consolidated metropolitan statistical area (CMSA) 230 Table 65—Percentage of tree cover, total area (land and water), total population,

and population density of consolidated metropolitan statistical areas (CMSA), primary metropolitan statistical areas (PMSA), and urbanized areas for the central cities of CMSAs

231 Table 66—Percentage of tree cover, land and water area, and 1990 population characteristics (total population and population density) within urbanized areas 239 Tables 67 through 114—Percentage of tree cover, land and water area, total

population, and population density for urban places and places within urbanized areas, by state

Appendix 2: Supplemental

Table For Chapter 2

T able 15—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Alabama

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers– – – – – Percent – – – – –%km2– – – – – – Percent – – – – – – Autauga*56.71,544220.526.864.63.434,22240,06117.126.079.520.00.00.30.7 Baldwin*46.14,1351,1150.313.771.24.998,280123,02325.229.886.012.80.90.20.9 Barbour52.62,292510.726.465.02.625,41726,4754.211.655.444.10.20.20.3 Bibb85.21,612815.28.386.41.816,57618,1429.511.378.921.10.00.00.3 Blount*67.21,672130.032.556.14.739,24843,39210.626.097.51.50.40.10.7 Bullock55.61,61930.040.955.51.011,04211,1881.36.927.572.20.00.30.3 Butler71.12,01230.014.879.00.421,89221,530-1.710.759.640.20.10.00.6 Calhoun*74.91,5761021.519.963.99.8116,034113,511-2.272.080.118.70.30.71.0 Chambers68.21,547151.715.678.63.236,87636,748-0.423.863.935.90.10.00.3 Cherokee68.21,4331210.431.254.12.719,54321,1708.314.893.26.50.20.00.5 Chilton69.21,798175.119.873.32.832,45835,3238.819.788.511.30.20.00.2 Choctaw78.02,366190.95.186.82.116,01815,714-1.96.655.744.20.00.00.5 Clarke78.93,208370.14.888.61.627,24027,9822.78.756.842.90.00.20.4 Clay80.51,567216.511.482.91.813,25213,5442.28.683.416.30.00.20.2 Cleburne90.81,451226.211.382.51.312,73013,4455.69.394.84.70.40.10.0 Coffee38.81,75933.842.849.32.440,24041,9104.223.881.217.30.50.81.1 Colbert*64.11,540750.724.559.96.051,66652,4901.634.182.716.60.40.20.3 Conecuh73.52,20440.014.081.30.914,05414,1120.46.457.742.20.00.00.3 Coosa77.91,690360.04.890.41.211,06311,4443.46.865.534.10.40.00.0 Covington56.92,680248.124.567.31.936,47837,2632.213.986.313.10.30.20.3 Crenshaw55.91,57930.019.075.71.313,63513,514-0.98.673.726.00.00.00.3 Cullman58.21,913420.043.345.44.367,61373,2748.438.398.80.80.20.10.3 Dale*41.11,453412.234.858.53.549,63349,167-0.933.879.217.70.61.52.3 Dallas54.82,540330.440.249.52.048,13047,362-1.618.641.957.90.00.20.1 DeKalb60.72,01520.038.651.43.854,65157,1654.628.496.81.90.90.30.5 Elmore*51.21,610920.124.058.76.749,21058,46018.836.376.722.50.50.20.6 Escambia62.82,454144.811.383.02.435,51835,6200.314.568.628.13.00.20.6 Etowah*66.71,385360.029.253.19.699,840102,1292.373.785.113.90.40.50.4 Fayette84.91,62640.016.778.30.817,96217,944-0.111.087.212.30.00.10.7 Franklin76.61,646280.330.658.64.127,81429,2535.217.894.94.60.20.20.3 Geneva24.21,49370.156.336.33.123,64724,6184.116.587.211.90.40.20.7 Greene67.51,673361.124.265.81.210,1539,947-2.06.019.480.60.00.00.2 Hale66.91,667337.135.658.41.415,49816,2885.19.840.359.30.20.20.6 Henry33.21,455170.334.856.82.015,37415,232-0.910.564.535.10.30.00.3 Houston*17.71,50330.049.937.36.581,33183,7783.055.775.923.20.30.50.5 Jackson76.02,7941240.127.260.52.147,79650,4285.518.192.94.12.60.40.5 Jefferson*77.32,882290.06.762.824.2651,525661,9271.6229.764.135.00.20.60.4

T able 15—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Alabama (continued)

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers– – – – – Percent – – – – –%km2– – – – – – Percent – – – – – – Lamar84.01,56720.016.576.42.215,71515,591-0.810.087.911.80.20.20.4 Lauderdale*52.21,7341280.351.031.46.579,66183,5934.948.289.79.60.50.20.3 Lawrence*60.71,7966419.655.332.63.431,51333,0374.818.478.115.26.70.00.0 Lee57.81,577180.018.167.68.987,14695,0389.160.374.523.50.11.70.7 Limestone*45.61,4711013.662.320.06.354,13559,84410.640.786.313.00.30.40.3 Lowndes50.11,860180.448.945.71.312,65812,8111.26.925.274.70.10.00.6 Macon55.41,58172.925.766.01.924,92823,563-5.514.913.785.90.00.30.2 Madison*55.72,085217.745.734.813.9238,912270,30913.1129.777.320.10.61.71.2 Marengo68.92,531150.132.661.62.023,08423,4301.59.349.050.90.00.00.1 Marion82.81,92060.014.477.13.229,83030,7183.016.096.43.10.30.20.2 Marshall54.51,4691450.037.541.18.370,83279,15911.853.998.01.50.30.10.5 Mobile*45.93,1941,0640.016.161.514.9378,643395,9524.6124.067.331.10.60.90.9 Monroe70.22,657220.311.283.21.123,96823,874-0.49.059.639.11.10.30.2 Montgomery*39.82,046260.740.538.911.4209,085216,4343.5105.857.141.70.20.70.8 Morgan*61.71,508441.740.842.58.9100,043106,9426.970.989.210.00.40.20.5 Perry69.91,864127.235.959.10.512,75912,717-0.36.835.064.20.70.00.4 Pickens79.72,283221.09.884.81.220,69920,8640.89.157.742.10.10.00.0 Pike47.51,73830.030.165.61.527,59528,4643.216.464.434.70.30.50.5 Randolph72.91,50580.015.175.92.219,88120,0731.013.376.223.70.20.00.3 Russell*52.21,661163.024.264.15.146,86051,4399.831.060.838.50.30.10.8 St. Clair*76.91,642510.012.273.26.250,00959,21818.436.190.49.10.40.00.2 Shelby*77.92,059380.011.972.59.499,358130,16531.063.291.37.70.40.60.5 Sumter68.22,344221.333.957.31.116,17416,1740.06.929.570.20.00.30.6 Talladega65.71,916549.725.662.26.374,10776,3693.139.968.730.80.30.20.4 Tallapoosa70.01,8601250.411.573.43.138,82639,8102.521.473.326.30.10.20.2 Tuscaloosa*77.83,432691.65.083.05.4150,522158,7795.546.372.925.90.20.80.6 Walker80.42,058280.016.372.95.167,67069,6863.033.993.36.40.10.20.3 Washington77.72,799200.08.088.11.116,69417,3413.96.265.927.76.30.00.3 Wilcox67.92,302490.418.276.10.113,56813,515-0.45.931.068.90.00.00.1 Winston83.51,5924522.014.772.82.722,05323,6027.014.899.50.20.20.10.5 * Indicates an urban county that belongs to a metropolitan area (U.S. Department of Commerce, Bureau of the Census 1997). a Percentage of state area that is Federal land (USDA Natural Resources Conservation Service 1995). b Percentage of state area used for agricultural purposes, including horticultural, row crops, close-grown crops, hayland, rangeland, and pastureland (Agr.); forest, including grazed and ungrazed (For.); and urban and built-up areas (Urb.) (USDA Natural Resources Conservation Service 1995). c 1990 and 1996 population (U.S. Department of Commerce, Bureau of the Census 1992c, 1997), percentage of change in population from 1990 to 1996 (Chng.) and 1996 population density (Dens.) (people/km2). d Percentage of total 1990 population that is White (W), Black (B), Native American (NA), Asian Pacific (AP), and of Hispanic origin (H) (U.S. Department of Commerce, Bureau of the Census 1992c).

T able 16—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Arizona

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers – – – – – Percent – – – – –%km2 – – – – – – Percent – – – – – – Apache17.329,023359.562.433.00.561,59169,08712.22.420.30.277.60.03.9 Cochise11.415,98012825.494.90.83.497,624110,35813.06.981.55.21.22.228.4 Coconino*17.548,22411239.781.24.10.296,591112,26016.22.364.51.329.30.810.1 Gila35.412,3497358.677.716.51.540,21647,33817.73.876.60.213.10.318.4 Graham16.411,9913136.984.18.20.826,55430,78015.92.677.61.714.70.624.6 Greenlee36.74,784479.580.10.00.88,0089,33016.52.086.40.31.90.642.8 La Paz2.311,6543678.882.00.42.713,84414,4974.71.274.70.317.70.624.7 Maricopa*7.123,8385455.177.50.012.12,122,1012,611,32723.1109.584.93.51.81.716.0 Mohave*12.834,47940967.361.828.61.393,497126,29435.13.795.30.22.30.75.0 Navajo13.225,780179.673.117.91.477,65892,08618.63.644.01.152.20.37.1 Pima*14.623,794629.089.20.06.1666,880767,87315.132.378.93.13.01.824.2 Pinal*15.613,9081217.990.40.02.4116,379135,37616.39.774.93.19.60.629.4 Santa Cruz33.43,206153.587.00.08.929,67636,95224.511.574.90.20.20.477.2 Yavapai23.021,0401245.790.71.61.6107,714139,36829.46.695.80.21.60.56.4 Yuma*1.714,2821383.665.10.03.6106,895125,14217.18.875.72.81.51.341.8 * Indicates an urban county that belongs to a metropolitan area (U.S. Department of Commerce, Bureau of the Census 1997). a Percentage of state area that is Federal land (USDA Natural Resources Conservation Service 1995). b Percentage of state area used for agricultural purposes, including horticultural, row crops, close-grown crops, hayland, rangeland, and pastureland (Agr.); forest, including grazed and ungrazed (For.); and urban and built-up areas (Urb.) (USDA Natural Resources Conservation Service 1995). c 1990 and 1996 population (U.S. Department of Commerce, Bureau of the Census 1992c, 1997), percentage of change in population from 1990 to 1996 (Chng.) and 1996 population density (Dens.) (people/km2). d Percentage of total 1990 population that is White (W), Black (B), Native American (NA), Asian Pacific (AP), and of Hispanic origin (H) (U.S. Department of Commerce, Bureau of the Census 1992c).

T able 17—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Arkansas

TreeAreaLand usebTotal populationcRace and ethnicityd CountyCoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers – – – – – Percent – – – – –%km2 – – – – – – Percent – – – – – – Arkansas18.12,5601179.072.321.70.121,65321,046-2.88.278.121.70.10.00.3 Ashley46.42,386465.430.365.20.424,31924,5430.910.371.927.30.30.01.2 Baxter54.11,4368426.140.142.65.431,18636,38216.725.399.20.00.40.30.7 Benton*23.52,184873.954.729.47.897,499125,95629.257.797.10.01.80.41.4 Boone38.11,531282.053.739.81.628,29731,90612.820.899.10.00.60.20.6 Bradley63.41,685104.39.188.50.011,79311,617-1.56.968.331.00.00.01.0 Calhoun64.41,627110.03.592.01.65,8265,714-1.93.575.124.80.00.00.0 Carroll43.11,642220.556.836.92.318,65422,49220.613.798.90.00.90.10.9 Chicot8.71,6681210.079.99.00.915,71315,130-3.79.142.556.50.40.01.4 Clark61.52,242442.020.573.41.221,43722,0873.09.976.423.00.30.20.7 Clay6.51,65650.785.310.70.918,10717,588-2.910.699.70.00.20.00.4 Cleburne47.01,4331011.935.052.43.519,41122,44715.615.799.30.00.50.00.5 Cleveland66.01,54830.08.089.70.27,7818,3377.25.486.113.70.10.11.0 Columbia69.21,98420.06.588.42.525,69125,469-0.912.864.535.10.10.30.2 Conway42.11,441271.947.346.62.019,15119,8853.813.884.415.00.20.30.6 Craighead*3.31,84160.678.311.95.468,95676,15510.441.493.35.60.30.60.7 Crawford*52.81,5422322.748.541.43.742,49349,07415.531.896.50.72.00.70.7 Crittenden*5.51,581681.481.96.81.849,93949,604-0.731.456.342.90.40.30.6 Cross5.31,595170.088.67.90.919,22519,3630.712.174.724.90.20.00.6 Dallas69.31,72920.04.093.00.69,6149,335-2.95.460.538.50.00.31.1 Desha17.61,9811415.758.030.50.016,79815,513-7.77.856.841.80.01.10.6 Drew42.02,145190.027.868.31.117,36917,8632.88.371.827.30.40.00.6 Faulkner*38.01,677432.256.832.74.860,00673,90923.244.191.07.80.60.50.7 Franklin48.61,5792630.560.928.72.614,89716,45310.510.498.70.40.70.11.1 Fulton40.31,60160.652.144.70.010,03710,7086.76.798.90.20.90.00.2 Garland56.91,75614627.08.059.913.773,39782,03811.846.791.17.60.70.31.1 Grant63.11,63630.06.489.32.113,94815,46310.99.596.62.70.20.20.6 Greene6.71,49660.182.111.72.631,80435,03710.223.499.50.10.20.00.5 Hempstead48.51,888330.036.357.11.321,62122,0642.111.768.529.90.20.41.8 Hot Spring57.31,593191.312.380.43.226,11528,2428.117.788.211.00.60.00.4 Howard56.41,522203.121.971.50.013,56913,8822.39.178.121.50.20.00.9 Independence34.21,978200.058.335.82.331,19233,0035.816.797.31.70.20.70.2 Izard55.21,50490.045.949.12.211,36412,79412.68.598.90.00.50.40.8 Jackson4.61,641210.786.18.01.618,94418,485-2.411.385.114.60.30.00.2 Jefferson*24.22,292752.857.330.55.185,48783,007-2.936.256.143.10.50.30.4 Johnson62.21,7155340.836.951.42.118,22120,89814.712.296.71.70.80.41.5 Lafayette50.01,364480.333.058.90.79,6439,231-4.36.861.238.60.10.10.4 Lawrence16.01,519150.073.122.01.517,45717,436-0.111.598.50.50.90.20.2 Lee9.91,558463.073.718.21.113,05312,802-1.98.241.857.30.00.60.9 Lincoln25.91,454280.352.040.20.813,69014,3094.59.863.336.20.10.01.1 Little River43.21,377860.346.241.71.513,96613,333-4.59.777.021.01.40.00.9

T able 17—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Arkansas (continued)

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers – – – – – Percent – – – – –%km2 – – – – – – Percent – – – – – – Logan50.81,8395622.948.245.11.720,55721,1883.111.597.31.20.70.30.6 Lonoke*10.41,983960.073.516.02.939,26847,58321.224.090.29.10.30.30.4 Madison54.92,16809.039.058.70.711,61813,09412.76.098.70.01.10.00.9 Marion48.51,54811014.638.149.30.812,00114,29819.19.299.20.00.40.30.3 Miller*41.91,616350.049.639.33.038,46738,9501.324.176.522.40.40.41.0 Mississippi3.22,327562.487.25.11.857,52550,606-12.021.870.727.90.40.51.1 Monroe18.31,571386.276.916.71.211,33310,381-8.46.660.639.30.00.10.2 Montgomery69.12,0235065.025.158.51.67,8418,4487.74.298.60.01.30.00.9 Nevada63.21,60620.014.383.00.310,10110,067-0.36.368.031.50.50.00.0 Newton76.02,132045.624.772.90.27,6667,9663.93.799.30.00.70.00.2 Ouachita66.41,897190.06.586.32.430,57428,374-7.215.064.435.20.30.10.5 Perry64.81,4272526.314.280.80.07,9699,31216.96.597.02.10.60.40.8 Phillips9.21,794904.473.816.61.428,83827,906-3.215.644.74.50.10.50.7 Pike65.01,562283.018.176.60.610,08610,4854.06.795.73.90.40.00.5 Poinsett4.11,963151.183.710.40.824,66424,7200.212.692.07.50.30.10.4 Polk73.82,226836.426.967.81.717,34719,33611.58.798.40.00.70.32.1 Pope57.32,1034936.756.532.06.645,88351,32611.924.496.22.40.70.40.8 Prairie12.01,673771.075.417.31.19,5189,273-2.65.586.013.60.50.00.2 Pulaski*37.71,997961.733.037.218.3349,660352,3050.8176.472.226.40.40.71.1 Randolph31.71,688110.057.737.72.116,55817,7427.210.598.80.90.20.10.3 St. Francis8.51,642220.178.413.82.528,49728,348-0.517.351.647.70.20.40.6 Saline*59.61,8771511.511.074.09.264,18374,55516.239.796.82.00.50.40.8 Scott73.92,3151162.550.743.31.410,20510,7755.64.798.20.00.71.00.3 Searcy58.11,728413.034.363.40.47,8417,728-1.44.599.20.10.40.00.7 Sebastian*39.81,3892521.946.335.213.399,590105,8276.376.289.15.61.63.21.1 Sevier57.91,461452.927.864.20.213,63714,7548.210.188.45.71.90.14.3 Sharp51.21,56550.033.361.22.614,10916,46716.710.598.60.11.00.10.3 Stone64.21,571715.723.872.00.89,77510,87711.36.999.10.00.90.00.5 Union70.42,691424.26.086.02.146,71946,036-1.517.169.230.10.40.20.3 Van Buren62.41,843337.419.874.01.914,00815,3259.48.399.10.10.70.00.6 Washington*37.32,461153.748.544.24.4113,409134,98419.054.995.91.41.40.91.3 White27.02,678210.066.227.72.554,67661,95413.323.195.93.10.50.20.9 Woodruff6.71,519193.174.619.91.49,5209,203-3.36.169.829.80.20.20.2 Yell59.22,4035439.942.850.01.117,75919,0007.07.996.12.20.70.80.8 * Indicates an urban county that belongs to a metropolitan area (U.S. Department of Commerce, Bureau of the Census 1997). a Percentage of state area that is Federal land (USDA Natural Resources Conservation Service 1995). b Percentage of state area used for agricultural purposes, including horticultural, row crops, close-grown crops, hayland, rangeland, and pastureland (Agr.); forest, including grazed and ungrazed (For.); and urban and built-up areas (Urb.) (USDA Natural Resources Conservation Service 1995). c 1990 and 1996 population (U.S. Department of Commerce, Bureau of the Census 1992c, 1997), percentage of change in population from 1990 to 1996 (Chng.) and 1996 population density (Dens.) (people/km2). d Percentage of total 1990 population that is White (W), Black (B), Native American (NA), Asian Pacific (AP), and of Hispanic origin (H) (U.S. Department of Commerce, Bureau of the Census 1992c).

T able 18—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in California

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers – – – – – Percent – – – – –%km2 – – – – – – Percent – – – – – – Alameda*14.71,9102172.733.623.026.71,279,1821,328,1393.8695.359.617.90.715.113.8 Alpine67.21,9131287.760.222.30.21,1131,23210.70.673.40.025.30.54.9 Amador45.81,5353022.047.041.45.730,03933,31510.921.789.45.62.00.76.9 Butte*44.84,2479715.345.040.23.9182,120192,5075.745.390.81.21.92.87.4 Calaveras50.62,6424321.537.355.62.431,99838,43720.114.696.00.52.10.55.4 Colusa16.42,9811415.282.612.40.216,27518,22312.06.176.40.62.22.632.4 Contra Costa*13.01,8662122.846.714.126.8803,732881,4909.7472.576.19.30.79.611.2 Del Norte91.82,61057570.33.080.33.623,46026,94714.910.386.53.66.61.710.3 El Dorado*71.84,43320739.717.965.87.7125,995151,70620.434.294.80.31.12.06.6 Fresno*19.915,44514238.879.412.15.1667,490751,27212.648.663.54.91.18.634.7 Glenn25.33,4063224.976.017.70.824,79826,2025.77.785.70.82.03.019.9 Humboldt84.49,2541,24220.310.284.41.6119,118123,0233.313.390.70.75.52.04.0 Imperial4.610,81379563.319.70.03.4109,303142,65130.513.267.42.61.72.065.3 Inyo5.126,3979292.255.70.61.318,28118,4330.80.786.70.310.11.58.2 Kern*7.321,0875332.079.913.23.0543,477622,72914.629.569.85.51.33.027.7 Kings0.73,59952.993.30.02.4101,469113,35111.731.563.98.31.53.633.4 Lake61.33,25918445.248.430.54.050,63155,2619.117.091.81.62.50.97.2 Lassen51.411,80442254.657.231.40.627,59831,43113.92.788.06.23.11.010.5 Los Angeles*16.110,5151,79332.941.65.147.68,863,1649,127,7513.0868.056.911.20.510.837.3 Madera*27.45,5393936.069.623.44.088,090110,48125.420.072.22.91.51.434.2 Marin*38.31,34679923.340.325.210.7230,096233,2301.4173.388.93.50.44.07.4 Mariposa44.83,7593052.255.433.74.114,30215,86911.04.292.41.14.50.94.8 Mendocino71.79,08995613.313.481.51.980,34583,2983.79.289.90.74.20.99.8 Merced*2.04,9961126.485.23.92.5178,403192,3117.838.567.54.90.98.332.0 Modoc50.010,21667162.966.321.00.09,6789,6930.21.090.71.05.00.65.5 Mono34.47,88522686.357.18.71.79,95610,4975.41.392.70.24.60.711.3 Monterey*27.48,6041,16328.566.027.03.3355,660339,047-4.739.463.96.40.97.832.7 Napa*41.11,953898.434.749.76.1110,765116,5125.259.789.11.00.73.414.2 Nevada73.72,4804429.911.967.97.878,51089,01613.435.997.10.31.20.74.4 Orange*14.12,04541014.827.83.765.72,410,5562,636,8889.41289.378.71.70.510.423.1 Placer*64.13,63724836.327.242.29.6172,796213,22723.458.693.60.51.32.37.7 Plumas84.36,61515558.76.085.91.719,73920,5974.43.194.21.03.00.74.5 Riverside*8.118,66924854.245.65.612.81,170,4131,417,42521.175.976.65.41.03.625.8 Sacramento*4.02,501782.367.90.420.71,041,2191,117,2757.3446.775.29.31.29.311.4 San Benito17.83,598414.587.410.80.736,69744,50321.312.470.10.51.22.145.4 San Bernardino*2.651,96111673.557.50.57.71,418,3801,598,35812.730.873.18.11.04.126.3 San Diego*25.610,89083324.141.212.715.62,498,0162,655,4636.3243.975.16.30.98.020.0 San Francisco*1.612148010.30.30.038.7723,959735,3151.66079.253.610.90.529.213.4 San Joaquin*10.33,624701.082.34.47.3480,628533,39211.0147.273.55.61.212.422.7

T able 18—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in California (continued)

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers – – – – – Percent – – – – –%km2 – – – – – – Percent – – – – – – San Luis- Obispo*18.68,55980616.868.723.73.0217,162229,4375.726.889.22.61.12.912.4 San Mateo*45.51,1637560.528.727.719.9649,623686,9095.7590.572.05.30.516.817.4 Santa Barbara*35.47,0932,72243.165.720.46.5369,608385,5734.354.477.22.81.14.526.3 Santa Clara*37.43,344341.437.936.721.01,497,5771,599,6046.8478.369.13.70.617.520.5 Santa Cruz*68.61,1544190.113.068.213.3229,734237,8213.5206.084.11.00.83.820.0 Shasta*73.99,80516040.029.559.55.4147,036161,74010.016.594.10.82.71.83.7 Sierra83.22,4692269.322.872.31.03,3183,4092.71.495.30.02.20.05.9 Siskiyou77.516,28415761.529.862.51.543,53144,1931.52.792.21.44.51.15.5 Solano*5.92,1452043.154.17.58.5340,421365,5367.4170.466.713.51.012.812.9 Sonoma*44.64,0824982.836.146.911.2388,222420,8728.4103.190.71.41.22.810.2 Stanislaus*8.83,871520.974.116.35.6370,522415,78612.2107.480.41.61.25.121.6 Sutter*4.41,561160.988.62.23.364,41575,65017.448.577.21.51.59.515.5 Tehama39.87,6432923.460.634.92.549,62554,1089.07.191.70.71.90.910.1 Trinity92.98,2337574.52.589.50.813,06313,4182.71.692.90.55.00.53.5 Tulare*29.012,4953948.779.715.02.6311,921349,92212.228.065.91.51.34.438.2 Tuolumne55.05,79010174.836.649.64.248,45652,1967.79.090.63.12.20.88.0 Ventura*29.94,78193950.977.03.514.4669,016714,7336.8149.579.22.40.85.126.2 Yolo*7.72,622274.384.43.95.8141,092149,9256.357.276.12.21.38.419.8 Yuba*34.81,6333418.464.020.45.158,22860,9054.637.378.44.12.98.611.2 * Indicates an urban county that belongs to a metropolitan area (U.S. Department of Commerce, Bureau of the Census 1997). a Percentage of state area that is Federal land (USDA Natural Resources Conservation Service 1995). b Percentage of state area used for agricultural purposes, including horticultural, row crops, close-grown crops, hayland, rangeland, and pastureland (Agr.); forest, including grazed and ungrazed (For.); and urban and built-up areas (Urb.) (USDA Natural Resources Conservation Service 1995). c 1990 and 1996 population (U.S. Department of Commerce, Bureau of the Census 1992c, 1997), percentage of change in population from 1990 to 1996 (Chng.) and 1996 population density (Dens.) (people/km2). d Percentage of total 1990 population that is White (W), Black (B), Native American (NA), Asian Pacific (AP), and of Hispanic origin (H) (U.S. Department of Commerce, Bureau of the Census 1992c).

T able 19—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Colorado

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers – – – – – Percent – – – – –%km2 – – – – – – Percent – – – – – – Adams*1.33,087152.581.00.014.2265,038309,92816.9100.486.93.20.92.518.3 Alamosa10.71,872220.093.20.41.213,61714,3005.07.682.30.41.40.637.9 Arapahoe*1.82,08062.481.80.215.3391,511455,03516.2218.789.35.90.52.95.6 Archuleta57.23,4951450.640.648.44.45,3457,95348.82.387.80.01.70.423.3 Baca0.36,620412.697.30.00.04,5564,491-1.40.795.30.01.40.05.1 Bent1.43,921711.096.00.00.35,0485,4788.51.491.50.50.30.727.2 Boulder*46.41,9232335.736.721.120.9225,339258,23414.6134.393.50.70.62.56.7 Chaffee42.32,625478.159.226.05.212,68414,67215.75.695.41.41.20.210.0 Cheyenne0.74,61400.098.70.00.22,3972,323-3.10.597.70.00.00.24.0 Clear Creek64.91,024370.75.875.26.97,6198,44810.98.297.50.50.30.73.0 Conejos29.43,334958.288.76.01.27,4537,8695.62.485.50.40.30.360.3 Costilla33.13,17890.072.320.30.63,1903,56711.81.184.00.60.31.677.4 Crowley1.02,044290.997.70.00.03,9464,2006.42.087.55.92.40.723.8 Custer43.21,914339.079.611.87.01,9263,06259.01.697.50.01.90.31.8 Delta28.12,9581756.477.511.40.420,98025,56321.88.696.00.20.80.28.7 Denver*9.339740.00.00.00.0467,610497,8406.51,254.072.212.91.12.322.8 Dolores42.22,764357.682.315.20.01,5041,67711.50.696.70.02.70.11.3 Douglas*33.92,176727.469.111.214.560,391111,64784.951.396.90.80.51.13.2 Eagle53.94,3721076.353.623.07.521,92830,52539.27.091.50.20.40.413.4 Elbert2.94,79400.095.51.91.09,64616,20968.03.496.60.81.80.62.7 El Paso*13.35,508815.380.93.812.8397,014472,92419.185.986.27.10.92.48.4 Fremont35.33,971345.058.037.22.432,27341,69429.210.595.02.61.00.38.6 Garfield43.17,6342262.365.218.52.129,97436,49921.84.896.90.40.90.35.7 Gilpin75.8388142.74.278.94.43,0703,72521.39.697.70.40.70.92.7 Grand62.14,7915269.848.938.85.97,9669,53619.72.097.70.20.20.32.8 Gunnison47.88,3895478.766.724.72.110,27312,14818.31.497.30.90.50.92.9 Hinsdale53.92,8951494.244.631.54.546766642.60.299.60.00.40.00.6 Huerfano25.24,120620.878.420.20.16,0096,5649.21.693.80.21.20.241.5 Jackson44.54,1782052.375.919.40.31,6051,521-5.20.494.30.02.80.03.6 Jefferson*48.02,0001523.720.235.732.5438,430492,52812.3246.394.80.60.51.76.8 Kiowa0.24,587380.797.90.00.11,6881,646-2.50.497.20.00.80.03.3 Kit Carson1.35,59720.098.30.00.07,1407,2181.11.394.90.50.30.07.1 Lake54.59761875.236.732.43.56,0076,2123.46.491.50.01.10.124.2 La Plata44.44,3832038.966.123.94.232,28439,45322.29.089.90.24.90.611.1 Larimer*47.06,7388447.862.924.66.9186,136221,72519.132.994.70.60.61.56.4 Las Animas16.312,362711.877.019.40.413,76514,4855.21.287.40.31.40.343.3 Lincoln0.76,69800.198.80.00.04,5295,57823.20.898.00.11.10.01.7 Logan2.74,762160.096.50.30.217,56718,0212.63.895.80.00.40.37.9 Mesa*31.08,6193569.863.016.42.993,145108,37116.412.694.90.40.80.57.8

T able 19—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Colorado (continued)

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers – – – – – Percent – – – – –%km2 – – – – – – Percent – – – – – – Mineral59.12,268593.370.710.84.555868122.00.399.10.00.40.00.9 Moffat13.412,2832254.489.54.50.311,35712,0866.41.096.50.01.40.26.1 Montezuma27.15,276842.682.43.70.518,67221,99917.84.285.10.011.70.28.9 Montrose30.25,804566.770.718.90.524,42329,60121.25.196.00.20.40.511.1 Morgan3.73,329220.695.20.10.821,93924,78813.07.487.90.20.80.518.0 Otero2.13,2711821.195.20.01.120,18520,9013.66.482.70.51.10.935.2 Ouray45.71,404048.952.736.21.92,2953,14036.82.297.50.00.40.25.2 Park36.45,7002651.373.017.21.67,17411,60261.72.097.90.51.20.42.9 Phillips1.91,78100.097.70.00.04,1894,3403.62.499.40.00.20.43.3 Pitkin58.02,513782.868.113.712.012,66113,4896.55.496.60.50.61.34.6 Prowers1.44,249100.096.00.50.613,34713,6892.63.285.40.31.10.022.9 Pueblo*5.66,187238.890.12.82.8123,051131,2176.621.284.81.70.90.735.7 Rio Blanco33.48,343572.787.79.40.55,9726,3486.30.897.60.00.30.44.3 Rio Grande30.22,364159.392.32.22.110,77011,3195.14.890.50.00.70.040.5 Routt56.86,1171743.581.915.40.814,08816,97520.52.898.70.00.60.32.7 Saguache32.48,207566.090.42.90.34,6195,78425.20.780.20.02.80.246.1 San Juan48.41,004288.236.717.45.8745564-24.30.699.20.30.00.012.4 San Miguel33.03,332558.663.725.01.93,6535,20842.61.699.00.00.20.33.2 Sedgwick2.91,42040.095.50.50.52,6902,651-1.51.997.50.21.00.59.3 Summit65.11,5752980.232.431.118.312,88117,89638.911.497.50.30.80.72.5 Teller54.81,443545.728.854.86.012,46818,71750.113.097.70.00.70.32.7 Washington0.66,53080.097.90.00.24,8124,673-2.90.798.90.00.20.01.6 Weld*3.810,341758.395.70.01.2131,821152,18915.514.789.00.40.61.020.8 Yuma3.46,12880.498.10.00.38,9549,2843.71.598.50.00.30.22.3 * Indicates an urban county that belongs to a metropolitan area (U.S. Department of Commerce, Bureau of the Census 1997). a Percentage of state area that is Federal land (USDA Natural Resources Conservation Service 1995). b Percentage of state area used for agricultural purposes, including horticultural, row crops, close-grown crops, hayland, rangeland, and pastureland (Agr.); forest, including grazed and ungrazed (For.); and urban and built-up areas (Urb.) (USDA Natural Resources Conservation Service 1995). c 1990 and 1996 population (U.S. Department of Commerce, Bureau of the Census 1992c, 1997), percentage of change in population from 1990 to 1996 (Chng.) and 1996 population density (Dens.) (people/km2). d Percentage of total 1990 population that is White (W), Black (B), Native American (NA), Asian Pacific (AP), and of Hispanic origin (H) (U.S. Department of Commerce, Bureau of the Census 1992c).

T able 20—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Connecticut

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers– – – – – Percent – – – – –%km2– – – – – – Percent – – – – – – Fairfield*30.41,6215470.25.536.448.0827,645833,7610.7514.384.89.90.12.08.1 Hartford*33.11,905390.016.939.636.3851,783831,694-2.4436.683.710.20.21.58.2 Litchfield63.72,383641.113.068.19.0174,092180,3393.675.797.90.90.20.81.1 Middlesex*50.09561810.012.556.218.1143,196148,1433.5155.094.14.20.21.01.8 New Haven*33.81,5696640.17.645.538.3804,219794,672-1.2506.585.610.20.21.26.0 New London*46.51,7252740.612.261.313.0254,957250,735-1.7145.391.84.80.61.43.2 Tolland*53.41,062180.610.766.614.7128,699130,2651.2122.795.32.00.22.01.6 Windham47.91,328230.612.470.910.4102,525104,6292.178.895.81.10.40.84.1 * Indicates an urban county that belongs to a metropolitan area (U.S. Department of Commerce, Bureau of the Census 1997). a Percentage of state area that is Federal land (USDA Natural Resources Conservation Service 1995). b Percentage of state area used for agricultural purposes, including horticultural, row crops, close-grown crops, hayland, rangeland, and pastureland (Agr.); forest, including grazed and ungrazed (For.); and urban and built-up areas (Urb.) (USDA Natural Resources Conservation Service 1995). c 1990 and 1996 population (U.S. Department of Commerce, Bureau of the Census 1992c, 1997), percentage of change in population from 1990 to 1996 (Chng.) and 1996 population density (Dens.) (people/km2). d Percentage of total 1990 population that is White (W), Black (B), Native American (NA), Asian Pacific (AP), and of Hispanic origin (H) (U.S. Department of Commerce, Bureau of the Census 1992c).

T able 21—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Delaware

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers– – – – – Percent – – – – –%km2– – – – – – Percent – – – – – – Kent*48.81,5305434.447.426.69.7110,993122,24410.179.978.718.60.61.22.6 New Castle*54.31,1041742.233.916.231.9441,946471,4176.7427.080.516.40.21.52.5 Sussex39.52,4296681.544.033.78.1113,229131,18115.954.081.516.80.70.51.1 * Indicates an urban county that belongs to a metropolitan area (U.S. Department of Commerce, Bureau of the Census 1997). a Percentage of state area that is Federal land (USDA Natural Resources Conservation Service 1995). b Percentage of state area used for agricultural purposes, including horticultural, row crops, close-grown crops, hayland, rangeland, and pastureland (Agr.); forest, including grazed and ungrazed (For.); and urban and built-up areas (Urb.) (USDA Natural Resources Conservation Service 1995). c 1990 and 1996 population (U.S. Department of Commerce, Bureau of the Census 1992c, 1997), percentage of change in population from 1990 to 1996 (Chng.) and 1996 population density (Dens.) (people/km2). d Percentage of total 1990 population that is White (W), Black (B), Native American (NA), Asian Pacific (AP), and of Hispanic origin (H) (U.S. Department of Commerce, Bureau of the Census 1992c).

T able 22—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Florida

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers– – – – – Percent – – – – –%km2– – – – – –Percent – – – – – – Alachua*38.92,2642460.034.143.910.4181,596196,5258.286.877.619.00.22.53.7 Baker66.81,5161028.15.486.94.318,48620,55611.213.684.514.60.30.30.9 Bay*64.31,9786985.30.970.111.0126,994144,63713.973.186.510.50.81.81.9 Bradford48.1759180.017.466.910.522,51524,1307.231.878.820.40.50.31.4 Brevard*35.92,6381,39513.349.33.714.5398,978453,99813.8172.189.97.80.41.33.1 Broward*12.63,1312870.28.70.023.21,255,4881,438,22814.6459.381.815.40.21.38.4 Calhoun60.81,470180.014.081.51.511,01112,21711.08.383.115.11.20.21.9 Charlotte*12.61,7974290.054.73.416.6110,975130,42617.572.694.93.80.30.82.2 Citrus25.71,5124917.115.539.618.693,515109,38917.072.396.42.20.70.61.6 Clay*44.51,5571100.02.975.38.9105,986128,91221.682.892.25.20.41.72.9 Collier*19.25,24672442.661.511.34.8152,099188,18723.735.991.54.60.40.413.3 Columbia58.62,0651015.225.465.84.842,61349,29115.723.980.518.10.30.61.2 Dade*10.55,0371,25633.29.81.828.21,937,0942,076,1757.2412.273.120.60.21.349.0 DeSoto25.91,65160.083.45.24.723,86525,2535.815.380.115.80.50.78.1 Dixie48.21,8244146.21.384.73.910,58512,35216.76.890.98.70.30.00.8 Duval*47.42,0043744.86.550.229.1672,971721,1397.2259.872.724.40.41.92.4 Escambia*50.41,7195962.313.351.716.8262,798277,6345.7161.576.620.01.01.81.8 Flagler*67.11,2562220.07.969.68.228,70142,14246.833.689.77.90.41.14.5 Franklin72.51,3831,2759.40.079.93.78,96710,27114.57.486.712.60.50.01.1 Gadsden*57.71,337320.014.571.85.041,10543,7876.532.840.658.10.20.21.8 Gilchrist29.4904170.024.163.36.59,66712,87133.114.291.08.50.40.01.6 Glades14.22,0035510.068.85.20.97,5917,8513.43.978.712.35.70.46.6 Gulf71.01,4644940.313.466.53.011,50413,32715.99.180.718.80.50.00.3 Hamilton61.01,334120.014.676.90.410,93012,28812.49.259.439.00.20.42.4 Hardee23.21,65130.079.616.61.319,49920,1303.212.283.85.70.40.123.0 Hendry11.02,985960.091.02.81.525,77329,82115.710.072.016.82.30.422.0 Hernando*25.11,2392873.413.648.420.6101,115121,26619.997.994.93.80.50.42.7 Highlands24.92,6642027.871.811.16.768,43274,8369.428.187.49.80.50.55.0 Hillsborough*18.82,7225580.939.419.331.5834,054897,5227.6329.782.913.20.31.312.6 Holmes57.11,250160.036.457.81.615,77818,17415.214.593.24.81.60.01.4 Indian River39.41,3032950.058.18.89.290,20896,4907.074.089.88.60.30.83.0 Jackson40.42,3721012.141.846.95.541,37544,7288.118.972.626.20.50.32.3 Jefferson60.41,5481012.114.080.70.811,29613,26017.48.656.043.00.30.21.6 Lafayette60.61,406130.09.386.90.15,5786,23711.84.483.014.10.20.04.2 Lake*32.72,46952711.337.817.711.3152,104186,63122.775.689.29.30.30.42.7 Lee*8.62,0811,0580.931.19.324.2335,113380,00113.4182.691.36.60.30.54.4 Leon*60.31,7279123.314.459.716.6192,493215,59312.0124.873.624.20.31.42.6 Levy39.12,8977613.011.068.54.725,92330,29616.910.486.612.40.40.51.7 Liberty71.82,1651949.34.991.40.05,5696,54217.53.082.017.00.50.01.4

T able 22—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Florida (continued)

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers– – – – – Percent – – – – –%km2– – – – – –Percent – – – – – – Madison57.41,792620.025.767.51.116,56917,5135.79.857.641.80.40.00.9 Manatee*15.11,9203930.064.311.913.3211,707232,2859.7121.089.97.80.40.64.4 Marion*43.54,09021825.931.635.918.9194,833230,06818.156.285.612.80.50.52.9 Martin*17.31,4395110.263.72.610.9100,900112,52711.578.291.26.00.20.64.4 Monroe16.22,5837,09754.40.023.910.378,02480,7303.531.291.65.50.41.011.9 Nassau*52.41,6881920.06.868.89.243,94152,07918.530.889.010.30.30.40.8 Okaloosa*51.92,42437937.420.350.714.0143,776165,87315.468.487.19.00.62.52.9 Okeechobee22.72,0063050.070.94.75.429,62730,8944.315.484.66.20.60.311.9 Orange*29.32,3512500.342.619.823.2677,491758,98012.0322.879.615.20.32.19.3 Osceola*36.83,4244780.062.519.24.9107,728135,81226.139.789.35.50.31.511.9 Palm Beach*10.15,26991213.045.70.521.6863,518992,84015.0188.484.912.40.21.17.5 Pasco*24.91,9303190.050.122.715.9281,131311,55610.8161.496.31.90.40.53.2 Pinellas*7.97268480.02.94.970.6851,659868,8872.01,196.890.57.60.31.22.2 Polk*23.04,8563502.244.714.911.8405,382440,9548.890.884.413.40.40.63.8 Putnam49.51,8702725.418.357.96.665,07069,7047.137.379.918.60.20.42.3 St. Johns*62.21,5775500.010.162.510.483,829106,50327.167.590.38.40.30.52.9 St. Lucie*22.61,4833000.061.75.419.8150,171174,72816.4117.881.916.30.20.53.6 Santa Rosa*55.62,63136110.717.958.87.481,608108,18632.641.193.54.01.01.21.7 Sarasota*21.71,4813980.055.27.925.7277,776296,5186.8200.294.74.30.20.52.1 Seminole*22.3798950.021.220.837.0287,529335,86816.8420.988.28.30.41.76.5 Sumter40.31,413900.152.928.93.631,57735,94813.825.482.316.21.00.02.6 Suwannee39.71,781110.048.445.13.126,78030,90115.417.383.614.80.50.31.9 Taylor63.32,6994920.23.786.71.617,11118,1736.26.780.517.81.00.70.5 Union64.5622240.018.074.82.610,25212,45121.520.075.523.20.40.52.8 Volusia*48.42,8648464.18.457.415.5370,712414,32211.8144.788.79.00.30.64.0 Wakulla72.11,57133455.65.667.15.114,20218,10527.511.585.212.91.40.40.6 Walton55.12,73946720.615.763.66.027,76035,25527.012.991.46.61.80.21.3 Washington53.21,502930.015.069.26.116,91919,21213.612.882.714.71.70.50.8 * Indicates an urban county that belongs to a metropolitan area (U.S. Department of Commerce, Bureau of the Census 1997). a Percentage of state area that is Federal land (USDA Natural Resources Conservation Service 1995). b Percentage of state area used for agricultural purposes, including horticultural, row crops, close-grown crops, hayland, rangeland, and pastureland (Agr.); forest, including grazed and ungrazed (For.); and urban and built-up areas (Urb.) (USDA Natural Resources Conservation Service 1995). c 1990 and 1996 population (U.S. Department of Commerce, Bureau of the Census 1992c, 1997), percentage of change in population from 1990 to 1996 (Chng.) and 1996 population density (Dens.) (people/km2). d Percentage of total 1990 population that is White (W), Black (B), Native American (NA), Asian Pacific (AP), and of Hispanic origin (H) (U.S. Department of Commerce, Bureau of the Census 1992c).

T able 23—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Georgia

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers– – – – – Percent – – – – –%km2– – – – – – Percent – – – – – – Appling60.21,31890.027.168.02.015,74416,3333.712.478.620.80.40.00.3 Atkinson67.4876160.021.275.60.56,2137,02213.08.071.526.90.00.01.7 Bacon61.273830.035.660.91.89,56610,3448.114.084.015.40.40.01.0 Baker41.6889150.045.951.80.23,6153,6862.04.248.351.70.00.00.3 Baldwin67.7669230.021.463.88.739,53041,9476.162.756.742.40.10.70.8 Banks78.260500.520.173.63.410,30811,91815.619.795.53.50.20.21.1 Barrow*68.042020.034.648.113.829,72137,40725.989.087.511.40.30.51.0 Bartow*72.71,191283.517.568.57.455,91166,29318.655.789.99.20.40.30.6 Ben Hill49.265260.030.659.15.516,24517,3226.626.668.331.30.20.10.7 Berrien55.51,172140.037.559.00.614,15315,78411.513.588.111.60.10.11.6 Bibb*54.1648130.413.442.934.3149,967155,5733.7240.357.641.70.10.50.4 Bleckley41.256340.048.048.01.410,43010,9304.819.477.122.40.10.40.3 Brantley69.01,15180.010.286.61.311,07713,04817.811.394.44.61.00.10.3 Brooks45.81,279110.059.036.00.115,39815,8202.712.457.141.50.70.21.3 Bryan*70.51,1443336.66.167.74.915,43822,28644.419.584.814.90.00.30.9 Bulloch51.51,768160.044.346.93.043,12549,32814.427.973.026.00.20.60.5 Burke49.62,151120.037.459.30.820,57921,5424.710.047.452.20.10.00.5 Butts74.248390.022.263.98.215,32616,5838.234.364.135.50.20.00.5 Calhoun43.872690.048.148.70.85,0134,844-3.46.741.158.90.00.00.0 Camden53.81,63239511.40.062.04.630,16742,79841.926.277.120.20.61.42.6 Candler51.264050.040.352.62.57,7448,67612.013.668.630.90.00.21.7 Carroll*68.31,293120.027.954.712.471,42279,30711.061.384.015.50.10.10.6 Catoosa*67.142015.436.141.218.842,46448,54114.3115.598.40.90.30.40.4 Charlton71.02,022635.74.294.20.08,4969,2939.44.671.727.11.10.00.7 Chatham*45.11,1415338.32.321.923.2216,935226,9614.6199.060.238.00.31.11.2 Chattahoochee*75.6644677.28.282.55.716,93416,137-4.725.059.630.90.52.910.1 Chattooga82.081309.629.560.58.122,24222,9533.228.390.88.60.30.10.2 Cherokee*83.91,098274.215.170.08.590,204121,49634.7110.797.01.80.40.41.2 Clarke*68.631310.119.141.635.887,59490,6023.4289.570.826.20.12.41.8 Clay48.8506561.722.463.31.33,3643,360-0.16.738.860.80.20.20.3 Clayton*61.036941.65.431.060.3182,052202,42711.2547.972.523.80.32.72.0 Clinch84.82,096393.73.294.61.06,1606,5826.93.172.627.30.20.00.8 Cobb*67.1881115.24.121.769.8447,745538,83220.3611.587.69.80.21.72.0 Coffee49.31,55290.039.152.65.129,59233,18812.221.472.925.50.10.41.5 Colquitt35.01,430110.051.739.63.436,64538,9606.327.273.824.20.30.24.0 Columbia*72.1751465.78.659.419.166,03186,17330.5114.786.310.90.22.51.4 Cook41.6593110.049.841.14.613,45614,3516.724.269.529.90.50.01.8 Coweta*78.61,14880.018.968.98.853,85376,29541.766.577.022.60.00.20.4 Crawford68.384230.022.374.01.58,99110,51416.912.567.730.70.80.01.3

T able 23—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Georgia (continued)

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers– – – – – Percent – – – – –%km2– – – – – – Percent – – – – – – Crisp27.4709190.050.934.47.520,01120,6433.229.158.940.70.20.20.1 Dade*90.745000.622.367.37.513,14714,48610.232.299.10.40.30.20.5 Dawson90.654785.67.984.92.79,42913,01638.023.898.50.31.20.00.4 Decatur40.81,546681.736.951.33.225,51126,5294.017.259.839.50.40.21.6 DeKalb*67.569570.03.319.972.4545,837589,7968.1848.853.642.20.22.92.7 Dodge52.91,29770.032.362.81.717,60717,9361.913.872.227.60.00.00.7 Dooly30.01,018110.064.231.11.59,90110,4165.210.250.449.00.00.50.5 Dougherty*51.0854131.530.846.618.496,31196,5810.3113.148.850.20.30.50.9 Douglas*83.151620.08.360.827.371,12084,46318.8163.691.17.60.40.61.2 Early40.41,324130.053.442.61.311,85412,1492.59.255.544.10.40.00.8 Echols83.71,047430.04.195.00.02,3342,325-0.42.286.011.51.70.21.5 Effingham*70.41,24290.012.979.83.225,68733,36329.926.985.314.00.40.20.4 Elbert72.1955155.824.165.10.418,94919,2861.820.269.230.00.10.71.0 Emanuel63.11,777110.031.562.42.220,54621,0302.411.866.832.60.20.50.4 Evans57.1479513.739.053.44.68,7249,5199.119.965.333.90.00.01.2 Fannin96.49991542.515.472.46.315,99217,74511.017.899.70.00.10.10.1 Fayette*75.751150.014.445.233.462,41581,89131.2160.292.35.10.01.91.5 Floyd77.81,329142.023.863.09.981,25184,4223.963.585.513.60.20.40.8 Forsyth*61.4585563.331.543.715.244,08369,12756.8118.299.00.00.40.00.8 Franklin57.968280.627.665.03.216,65018,1849.226.789.39.90.50.30.1 Fulton*73.91,369150.813.331.252.0648,951718,33610.7524.647.849.90.21.32.1 Gilmer98.21,1051321.05.989.40.613,36816,86826.215.399.10.30.50.00.9 Glascock64.637300.018.775.90.72,3572,4293.16.587.312.70.00.00.2 Glynn60.01,0944160.61.341.613.362,49665,6085.060.073.725.60.20.40.8 Gordon68.292063.632.652.410.935,07239,36912.342.895.53.80.20.30.5 Grady42.91,18760.040.350.54.920,27921,4545.818.167.531.50.60.01.4 Greene86.71,0064610.017.473.62.211,79313,01010.312.949.849.90.30.00.7 Gwinnett*73.61,121100.59.141.245.2352,910478,00135.5426.491.15.10.32.82.3 Habersham78.7721322.529.359.55.927,62130,79411.542.791.65.40.32.11.1 Hall53.21,020924.027.040.219.195,428113,03318.5110.987.48.50.20.64.2 Hancock81.51,226140.010.485.61.08,9089,0231.37.420.279.60.10.00.0 Haralson86.573130.021.467.76.421,96623,8718.732.793.16.50.20.20.4 Harris*74.01,201240.08.380.85.717,78821,30319.817.773.825.50.40.20.4 Hart38.8601633.850.629.15.419,71221,0056.634.979.320.40.10.10.3 Heard81.8767134.311.882.30.28,6289,85514.212.986.113.40.00.50.1

T able 23—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Georgia (continued)

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers– – – – – Percent – – – – –%km2– – – – – – Percent – – – – – – Henry*71.183650.018.963.812.558,74190,96954.9108.888.710.20.20.70.8 Houston*43.997683.642.535.517.089,208101,38413.7103.976.421.80.31.11.5 Irwin38.1924150.062.632.50.58,6498,8712.69.669.230.50.00.20.0 Jackson72.188720.039.252.95.030,00535,23017.439.789.80.60.30.20.3 Jasper82.7960814.319.273.52.58,4539,55613.110.064.334.80.40.01.0 Jeff Davis55.086450.030.564.91.412,03212,6124.814.684.215.40.00.00.7 Jefferson52.21,36750.737.057.42.617,40817,8602.613.144.055.90.00.00.1 Jenkins60.690670.033.262.11.98,2478,4712.79.458.241.50.00.10.2 Johnson55.178850.037.557.71.98,3298,252-0.910.565.733.90.00.40.5 Jones*80.91,020417.925.366.64.920,73922,3307.721.974.025.60.20.20.0 Lamar68.747930.027.164.05.613,03814,0297.629.365.74.00.20.00.3 Lanier73.5484345.317.574.23.25,5316,61019.513.773.126.60.30.00.7 Laurens47.12,105150.037.854.94.439,98843,3428.420.666.233.30.00.40.3 Lee*41.0922160.047.346.93.016,25020,70527.422.580.219.20.30.01.2 Liberty67.91,34521631.51.545.712.752,74559,06312.043.954.839.20.52.25.6 Lincoln52.854712014.421.643.82.37,4428,0267.914.761.838.20.00.00.4 Long70.91,039612.16.189.82.96,2028,15131.47.975.621.80.30.82.9 Lowndes59.51,306173.128.156.611.675,98183,98210.564.366.531.90.50.81.2 Lumpkin92.6737131.419.275.83.014,57317,28618.623.595.91.42.10.50.6 McDuffie*65.2673177.318.667.26.320,11921,4746.731.963.236.40.30.00.4 McIntosh60.91,1233664.40.958.32.68,6349,59211.18.556.743.30.00.00.6 Macon43.91,04570.234.860.62.113,11413,1410.212.640.158.70.20.30.6 Madison*62.473730.033.161.81.821,05024,19214.932.891.08.30.10.40.5 Marion63.195110.015.881.80.95,5906,34513.56.757.641.31.10.00.5 Meriwether69.81,30450.014.976.44.822,41122,9442.417.655.144.60.00.10.4 Miller22.573320.263.332.50.76,2806,144-2.28.472.227.50.40.00.4 Mitchell32.31,32650.055.839.81.520,27520,9903.515.851.447.90.10.00.9 Monroe80.91,02560.09.281.23.617,11319,36813.218.967.731.80.30.20.6 Montgomery56.463550.028.967.11.37,1637,7007.512.169.928.30.10.22.0 Morgan69.4906130.237.354.93.312,88314,17110.015.764.834.70.10.30.6 Murray82.6892624.314.674.87.426,14730,77717.734.599.30.30.10.20.8 Muscogee*60.45601235.211.343.039.6179,278183,3942.3327.459.038.00.31.42.9 Newton*73.271670.029.148.816.141,80852,70926.173.677.222.40.00.20.6 Oconee*68.748100.822.462.810.017,61822,41027.246.692.17.40.40.20.8 Oglethorpe81.71,14331.320.777.00.09,76310,89911.69.574.824.70.30.00.4

T able 23—Percentage of tree cover , land and water area, land use, and population characteristics, by county , in Georgia (continued)

TreeAreaLand usebTotal populationcRace and ethnicityd CountycoverLandWaterFed.aAgr.For.Urb.19901996Chng.Dens.WBNAAPH People/ %Square kilometers– – – – – Percent – – – – –%km2– – – – – – Percent – – – – – – Paulding*89.381240.012.678.25.541,61164,07254.078.995.23.90.40.30.5 Peach*38.339111.244.542.77.821,18923,52911.060.150.747.50.40.51.4 Pickens*89.060120.05.785.95.614,43217,57021.729.298.01.50.30.00.3 Pierce61.288820.026.666.23.913,32815,27014.617.287.711.70.10.00.7 Pike59.556630.039.753.13.510,22411,70214.520.779.420.00.40.20.3 Polk79.280630.022.867.76.133,81535,3704.643.984.514.30.10.11.6 Pulaski40.864160.038.455.42.98,1088,2682.012.965.732.50.00.32.0 Putnam76.28924215.011.278.23.414,13716,51116.818.565.332.80.01.10.9 Quitman75.8393240.18.480.70.02,2092,46311.56.349.549.90.50.10.0 Rabun89.79611561.44.677.311.411,64813,01311.713.599.00.40.40.00.5 Randolph55.01,11240.027.369.62.08,0237,989-0.47.241.258.20.10.50.0 Richmond*46.78391120.513.144.235.8189,719193,7842.1230.955.042.00.31.81.9 Rockdale*78.733940.013.345.832.154,09165,21920.6192.790.48.00.40.80.9 Schley59.443400.014.483.60.23,5883,7634.98.764.834.10.20.01.0 Screven57.91,680180.035.259.41.413,84214,2863.28.554.844.70.00.50.1 Seminole28.7617483.256.624.82.89,0109,2522.715.067.032.70.00.26.1 Spalding*66.351340.012.656.325.954,45757,7136.0112.670.329.10.20.40.5 Stephens75.24641320.319.260.611.023,25725,2468.654.487.411.80.10.30.9 Stewart77.21,188121.515.579.60.05,6545,532-2.24.736.363.50.20.00.2 Sumter40.71,257190.043.148.63.730,22830,6681.524.452.446.50.30.60.7 Talbot78.01,01940.06.789.41.76,5246,8655.26.737.562.30.10.00.8 Taliaferro94.950600.06.591.90.01,9151,861-2.83.738.261.40.00.40.4 Tattnall52.91,253121.733.758.44.017,72218,7285.715.068.429.20.10.12.6 Taylor54.497860.018.677.61.37,6428,1897.28.456.643.20.00.00.3 Telfair60.71,14380.019.376.50.711,00011,6626.010.265.434.50.00.00.1 Terrell42.486960.059.835.81.210,65311,0924.112.840.059.90.00.00.2 Thomas44.21,420100.046.246.93.538,98641,9087.529.561.337.90.20.00.9 Tift29.2687100.054.029.29.934,99836,8505.353.771.326.70.10.53.3 Toombs51.095050.041.250.03.624,07225,4635.826.873.623.40.30.43.0 Towns94.74311452.417.958.012.36,7547,99018.318.599.50.00.30.20.3 Treutlen64.852040.031.665.20.65,9945,903-1.511.466.833.10.10.00.0 Troup68.11,072837.914.358.214.555,53658,5685.554.669.230.00.10.50.4 Turner31.2741100.045.547.42.78,7039,0033.512.258.940.70.00.40.1 Twiggs*67.593370.09.084.42.29,8069,8730.710.653.945.90.10.00.1 Union92.68361746.329.755.66.411,99314,92324.417.999.50.10.30.20.2 Upson70.384360.017.871.46.726,30026,9232.431.971.827.80.00.30.3 Walker*79.11,15617.123.962.111.658,34061,1634.852.995.73.70.30.30.3 Walton71.285320.038.444.98.838,58649,30727.857.880.918.40.10.40.7