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Analytical Tools Interface for Landscape Assessments (ATtILA)

User Guide

Version 2.0

DRAFT

Lead programmer: Donald W. Ebert1

Programmer: Timothy G. Wade1

In cooperation with: James E. Harrison2

Dennis H. Yankee3

 

1U.S. Environmental Protection Agency
2U.S. Environmental Protection Agency

Office of Research and Development Region 4

National Exposure Research Laboratory Sam Nunn Federal Center

Environmental Sciences Division 61 Forsyth St., S.W.

Landscape Ecology Branch Atlanta, GA 30303

Box 93478

Las Vegas, NV 89193

 

3Tennessee Valley Authority

Environmental Research Center

17 Ridgeway Road

Norris, TN 37828

 

I. Background 1

II. System Requirements 2

A. Hardware 2

B. Software 2

III. Installation 2

IV. Data Requirements 3

V. The Indicators 4

A. Landscape Characteristics 6

B. Human Stresses 8

C. Physical Characteristics 10

D. Riparian Characteristics 11

E. Other Indicators 11

VI. Display 12

VII. Other Tools 14

Appendix 1 - Indicator Glossary 15

Appendix 2 - Default coding schemes 17

Appendix 3 - Technical Notes 20

 

I. Background

Environmental management practices are trending away from simple, local-scale assessments toward complex, multiple-stressor regional assessments. Landscape ecology provides the theory behind these assessments while geographic information systems (GIS) supply the tools to implement them. A common application of GIS is the generation of landscape indicators, which are quantitative measurements of the environmental condition or vulnerability of an area (e.g., ecological region or watershed). Generation of these indicators can be a difficult, lengthy process, requiring substantial GIS experience. The goal behind ATtILA is to provide an interface that allows users to easily calculate many common landscape indicators regardless of their level of GIS knowledge. Four indicator groups are currently included in the package. After indicator values have been generated, there are four display options to view results. ATtILA runs within ArcView as an extension. It is written in Avenue, ArcView's programming language, and is designed to be flexible enough to accommodate spatial data from a variety of sources. Finally, this is a work in progress. Please report bugs and forward comments to us at (ebert.donald@epa.gov or wade.timothy@epa.gov).

II. System Requirements

A. Hardware

Because of the size of landscape data sets and the complexity of the calculations to generate some indicators, we recommend a minimum of a Pentium II 266 MHz (or equivalent) with 32 MB of memory. A preferred system would be a Pentium II 400MHz (or equivalent) with 64MB of memory and a fast (<8 ms) hard drive or better.

B. Software

To use the ATtILA, you will need ArcView 3.1 and the Spatial Analyst extension. Both UNIX and Windows (95, 98 and NT) environments are supported.


III. Installation

To load the extension, copy the attila.avx file to your extensions directory. The Windows default location is C:\ESRI\AV_GIS30\ARCVIEW\EXT32, the location varies on UNIX systems, but will be called "ext" in the ArcView installation directory (you may require root privileges to do this). In ArcView, make the project window active, go to the File menu, click on Extensions, and turn on ATtILA. This will add a new menu to the view GUI called "ATtILA".

 

IV. Data Requirements

Different indicators require different input data. To run the entire suite of indicators, you will need the data sets described below. The extension assumes all your data is in the same projection and datum with the same map units. Vector themes may be Arc/Info coverages or ArcView shapefiles. Raster themes must be in Arc/Info GRID format.

 

Reporting units

A polygon theme that may define any area of interest (watersheds, ecological regions, counties, etc.). Note: users must have write permission to this theme's attribute table to store indicator values.

 

Land use/Land cover

Land use must be an integer grid. Land use codes must be known to correctly generate indicators. Land use data will soon be available nationwide through the Multi-Resolution Landscape Characterization (MRLC) program. Another source is the GAP program, which also publishes data on the web.

 

Elevation and slope

Elevation and slope must also be grids, either integer of floating point. It is possible to generate slope from a DEM within ArcView using Spatial Analyst. You will need to know if the slope represents percent or degree slope. DEMs are available from the USGS website in several scales. It is recommended you choose a DEM resolution similar to your land use resolution.

 

Streams

Streams must be a line theme. Stream order may be used if it is present in your data, but it is not necessary. Stream data is available from the USGS (SDTS format) or from the US EPA (RF3).

 

Roads

Roads must also be a line theme. A class attribute may be used if it is present in your data, but it is not necessary. The item or field name may be anything, but should contain numeric or character values representing road classes (i.e., interstate, state highway or surface street). Road data is available from the USGS (SDTS format), as well as many commercial companies.

 

Population

Population must be a polygon theme. Any level of data is acceptable (county, tract, block, etc.), although you will want to use an appropriate level for the scale of your reporting units. Population data is available from the Census Bureau.


Precipitation

Precipitation must be in grid format. Precipitation data is available from Oregon State University as part of the PRISM Climate Mapping Program. Data is distributed by state, region or the entire coterminous US.


V. The Indicators

There are four indicator categories listed in the ATtILA menu and each includes several related indicators. Making a selection displays one or more dialogs in which you enter information such as the indicators to calculate and what data sets to use.

Coding Schemes

In three of the indicator categories, land use is the core input. You must tell ATtILA what land use is represented by each code in your data. Several common schemes are available, along with a custom option. Once the scheme has been entered, it will remain in effect throughout the session. For example, if you have MRLC data, and select that option in Landscape Characteristics, ATtILA will also use MRLC codes when you go to Riparian Characteristics, unless you change the selection.

Select the coding scheme of your land use data: Anderson level I or II, MRLC, SAA (Southern Appalachian Assessment), or Custom. This tells the program what land use is represented by each code in the grid. A description of the selected scheme is available by clicking the middle button on the bottom of the custom dialog (see below).

Selecting Custom or clicking the advanced button brings up a new dialog (shown below) that allows you to view and edit which codes represent each type of land use. If you have data that uses codes other than Anderson, MRLC or SAA, you will need to enter the codes for each land use by clicking on the appropriate values (hold the shift key to select more than one). For example, if forest is coded as 7, 8, and 9 in your data, shift-click those values in the Forest list. This same technique can be used to modify Anderson, MRLC or SAA defaults. Shift-clicking a code toggles it from on to off or vice-versa. If any of the predefined schemas were selected before choosing custom, the previous schema values will remain. You may edit these or use the "Clear All" button to start from scratch. Clicking "Custom" again after making edits will reset to values when the dialog was opened.

User defined is a custom category that can be defined as any combination of land uses in your data.

You may save a custom classification for future use with the save custom button. This will create a file with a ".cds" extension in a location of your choice. To recall the classification, use the "Load Custom" button. At any time, you may select a core definition (e.g., MRLC) to reset values to that definition. When all the codes have been entered, click "Done".

A. Landscape Characteristics

This family of indicator deals with proportions of land use.  Be sure to choose a coding scheme before proceeding.

 

Source Data

Land cover, reporting unit, and id field must be filled in to proceed. The program will search the themes in the view and attempt to make a logical choice as the default selection (see appendix 3 for further information). The ID field should contain a unique value for each area (e.g., watershed name or number) in the reporting unit theme.

 

Indicators

Land Use Proportion Indicators

Calculate the percentages and total area (reported in map units of the land use grid) of any land use types by checking the appropriate boxes. You may also generate U-index (all human use), N-index (all natural cover), and percentage of agriculture on steep slopes.

Slope Indicators

Calculating the amount of agriculture on steep slopes requires you to enter a slope grid and a threshold value. It is recommended you use slope measured in percent (instead of degrees) and a threshold of 3. Studies have shown this to be a level where soil erosion begins to increase. You may compute the amount of crop land, pasture, total agriculture and/or the user defined category (if defined) on steep slopes.

Output Options

"Indicator values only" will not save any intermediate data sets required for the calculations. Values will be added to new fields in the reporting unit attribute table, or overwrite values if the field already exists. Any fields that are overwritten will be displayed in a list when processing is complete.

Indicator values and binary maps will generate and save values as above, but will also create new themes for user specified or all (if possible) selected indicators. These options are most useful for the slope aggregate indicators, where a 1 represents crops, pasture or all agriculture on steep slopes, a 0 elsewhere.


Notes: Percentages of land use calculations exclude water from total area. For example, Pfor = area of forest / (total area - area of water), or the percentage of terrestrial area that has forest cover. This is significant only in areas with large lakes or reservoirs. Therefore, it is important that codes for water be entered in the water code list and only that list (i.e., do not include it as part of N-index).

The percent overlap between land use and reporting unit is calculated and written to a field named LC_Overlap. If this value is substantially below 100 for a reporting unit, you may wish to exclude it from analyses, as values may not be representative of the entire reporting unit. Likewise, the overlap between slope, land use and reporting unit is calculated and written to a field named SL_Overlap.

 

B. Human Stresses

Indicators in this group are primarily related to population and roads, including length of roads near streams and road/stream crossings. 

 

Source Data

Reporting unit and ID field must be entered, population, stream, and road information (the program sets initial values - see appendix 3) are optional depending on the indicators you want to generate.

For road related indicators, your data should include an attribute relating to road class (e.g., interstate highway or surface street). If your data does not have this information, use the "None" option. This will treat all roads as a single class, but will generate valid results. RDDENS/RDLEN must be checked if you want to calculate PCTIA_RD or STPRD.

Indicators

Phosphorus and Nitrogen Loadings (P_Load and N_Load)

Phosphorus and nitrogen loadings are based on amounts of land certain use types. Weightings in the input boxes are measured in kg per hectare per year. For example, each hectare of urban land use contributes 1.2 kg of phosphorus and 5.5 kg of nitrogen per year to the watershed. Default numbers are based on literature, and may be changed. The abbreviations used are: URB = urban, PAS = pasture, RC = row crop, NRC = non-row crop agriculture (e.g., orchards), FOR = forest, and User = user defined (optional). Results are in kg/Ha/year.

Population Density and Change

For population density, you need to enter the theme name for Census1 and the associated field (Pop field) containing population values. When reporting units contain partial census units, population is apportioned by area-weighting. That is, if 50% of the census unit is within the reporting unit, 50% of the population is assigned to that reporting unit. A new field with the same name as the population field is added to the reporting unit attribute table. It contains the total area-weighted population.

To compute population change, you also need to set theme and field name for Census2 (this information can be in the same theme, in different fields). Population density is reported as number of people per km2. Population change is reported as absolute change in population by reporting unit.

Impervious Surface (PCTIA_LC and PCTIA_RD)

Impervious surface is calculated two ways. The first (PCTIA_LC) is based on percent cover of certain land uses. By default, 2% of forest, 60% of high intensity residential, 40% of low intensity residential, 10% of other grasses, and 90% of high intensity commercial are considered impervious, based on previous studies. These values may be altered manually. Total impervious surface by reporting unit is calculated by multiplying the percentages by amount of area for each associated land use, then summed over all land uses. Results are reported both as total area, as well as percent impervious cover.

PCTIA_RD uses road density as the independent variable in a linear regression model to calculate impervious surface. Road density is calculated as km of road per km2 of reporting unit area. Due to the nature of the regression equation used for PCTIA_RD, values below 1.8 are assigned a value of 0, values above 11 km/km2 are considered invalid and will be reported as -1.

Road Density Indicators

Total road length (RDLEN) is reported in map units (usually meters). Road density (RDDENS) is reported as total road length in km divided by area of reporting unit in km2.

Streams in proximity to roads (STPRD) requires a buffer distance, measured in projected map units if the view is projected, or native map units if not. In most cases, map units will be meters. This is the total length of roads within the buffer distance divided by the total length of stream in the reporting unit, both lengths measured in map units (e.g., m of road/m of stream).

Stream/Road crossings (STXRD) are reported as the number of stream/road crossings per kilometer of streams in the reporting unit.

Note: STPRD is extremely computationally intensive. You may want to run few selected reporting units as a test before using your entire data set.

C. Physical Characteristics

These indicators provide general physical descriptions of reporting units. Required inputs are Reporting Unit and ID Field. Optional inputs are elevation, slope, streams, stream order, and a point cover which will usually be sample site locations.


Common statistical measurements such as range, minimum, maximum, mean and standard deviation, may be calculated for precipitation, topography and/or slope. If desired, elevation at each location in a point coverage (Sites input box) may also be calculated. Output for the SITE_ELEV indicator is a new table. You have the option to join the new table to the Sites point theme attribute table.

Stream density (STRMDENS) and total stream length (STRMLEN) may be calculated by stream order for each reporting unit. If stream order information isn't available, use the "None" option, and values will be generated using all streams in the reporting unit. Total stream length is reported in map units. Stream density is reported as total stream length in km divided by area of reporting unit in km2.


D. Riparian Characteristics

This category is very similar to the landscape characteristics indicators (see section "A. Landscape Characteristics" for more detailed instructions), but focuses on proportions of land use adjacent to and near streams. Required inputs are identical to those in the landscape characteristics dialog, with the addition of a streams input. Initial theme names are chosen in the same manner as the landscape characteristics dialog (see appendix 3).

You will enter stream buffer distances for which land use percentages will be generated. You may enter up to two values, measured in number of cells. For example, if your land use grid has a 30 meter cell size, entering a 1 will buffer the streams by 30 meters on each side. Default values are one and four cells. A value must be used in the first buffer distance. To turn off the second buffer, set the value to zero or blank. By default, land use adjacent to streams is always calculated (buffer distance of zero). Percentages and total area of each selected land use located within the buffer(s) will be calculated. Area is reported in the map units of the land use grid.  Output options are identical to those in the Landscape Characteristics dialog.

E. Other Indicators

This section not yet implemented, but may include such measures as perimeter/area ratio, average patch size, contagion, etc.

VI. Display

There are four ways to display results in the extension: Atlas-like maps, an indicator index, column charts of selected indicators, and indicator histograms. Be sure your reporting unit theme is active when you select any of these display options. Atlas and index values are calculated using all reporting units, regardless of whether any units are selected.

The Create indicator atlas option displays a scrolling list of indicators in the active theme's attribute table. Select those you would like to include in the atlas. Next, you will be asked how many quantiles to use in the legend. The default is 5, but you may enter any integer from 2 to 64. The number of quantiles is the number of classes used in the legend, where each class contains the same number of features (reporting units in this case). For each indicator you choose, a new theme is added to your view. Reporting units are ranked based on their indicator values and displayed using colors from red (worst condition, high rank value) to green (best condition, low rank value). Rankings are relative. A low ranking does not necessarily represent poor conditions, just worse conditions than other areas in your data.

Create indicator index is a way of combining many indicators into one value. The atlas maps are valuable for viewing single indicators at a time, but it is difficult to analyze many indicators simultaneously. To make an index you will select up to 18 indicators from the same list used in create atlas. You must enter a number of quantiles (any integer between 2 and 64, the initial setting is 5). This value is used to rank the reporting units, similar to the create atlas function, and to display the index (see appendix 3 for details on index creation methodology).

Checking the "Save quantile rankings..." box will add a new field to the reporting unit attribute table for each indicator. The field name is the same as the indicator code with a "_q" and the number of quantiles appended (e.g., Pfor with 5 quantiles becomes Pfor_q5). You may change the name of the index in the "Index name" box. By default, the name is "Index". A new field will be added to the reporting unit attribute table with the name you enter to hold index values. If the field already exists, values are overwritten.

Each selected indicator has an input box in the dialog to accept a weight which may be any number less than 10. For each reporting unit, all indicator rank values are multiplied by the related indicator weight. The index is the sum of all the weighted values. A new theme is added to the view and displayed using the specified number of quantiles. Again, rankings are relative. The equation used to calculate the index is stored in the index theme properties' comments.

Create indicator column charts also displays a list of available indicators. A chart is generated that shows each selected indicator grouped by reporting unit. The maximum number of columns cannot exceed 100 (i.e., number of indicators * number of reporting units must be less than 100). You may need to select a subset of reporting units or only run this option on one indicator at a time. This limitation is the default in ArcView. It was maintained because charts larger than this are difficult to decipher. You may get a warning stating: CHART: There is not enough space to plot the chart; check the format parameters and/or resize the chart. Click OK on the warning dialog. Making the chart window larger will usually fix this problem.

Create indicator histogram displays a same list of available indicators, but in this case, only one may be chosen. A histogram is then created for the selected indicator. This option creates a new dbf file in your working directory (usually C:\temp on PCs or the user's home directory on UNIX) called histo.dbf. It is overwritten when a new histogram is created. Because of this, when several histograms are created, all of them will be listed in the project window under charts, but only the most recent will be correct.

VII. Other Tools

There are several tools included in the extension. All are located at the bottom of the ATtILA menu.

The first, "Update area, length and perimeter", will recalculate area and perimeter for polygon themes and length for line themes. If you project your data within ArcView, these values are not automatically updated and need to be recalculated to represent correct measurements in the new projection space.

Second is "Delete multiple fields from table". Because ATtILA creates many new fields in the reporting unit table, this tool allows you to efficiently remove unwanted fields. A list of all fields in the attribute table for the active theme will be displayed when you choose this tool. Select the fields you want to delete and click OK.

The third tool is "Get grid values at points". Make a point theme active before choosing this option. A list will display the grids in the view, select those that you want information for. The result is a permanent table (you are given a choice of where it is stored on disk) of values at each point in the active theme for each selected grid. Finally, you are given the choice of joining the grid information to the point attribute table.

Fourth is "Get elevation profile along line...". You must have a line theme active, with one or more lines selected. Although the most common use of this tool is an elevation profile along a stream, you can get information along a line or transect for any grid in your view (e.g., slope, aspect, or vegetation cover). Select the grid you want to profile from the list. Next the selected line(s) in the active theme will be split into equal length segments for display in a graph. The default number of segments is 10, you may change that value in the dialog. A permanent table is created by this tool. A final dialog allows you to choose where to store this table. The original script was written by Bill Eichenlaub and is used with his permission. Minor modifications were made to incorporate the script into ATtILA.

The fifth tool is "Find intersections of two themes...". This tool prompts you for two themes (any combination of line and poly) and creates a theme with points at the intersections of the two inputs. This tool is used in ATtILA to find road/stream crossings.

The script for this tool was written by Jarko Laine and is used with his permission. Minor modifications were made to incorporate the script into ATtILA.

Appendix 1 - Indicator Glossary

The following is a list all the possible indicators that can be generated, including the code which is used in the dialogs and as the field name that is added to the reporting unit table.

Landscape Characteristics

Pagc - Percentage of crop land

Pagp - Percentage of pasture

Pagt - Percentage of all agricultural use

Pbar - Percentage of barren

Pfor - Percentage of forest

Purb - Percentage of urban

Pusr1 - Percentage of user defined class

Pwetl - Percentage of wetland

N_index - Percentage of all natural land use

U_index - Percentage of all human land use

AgcSL - Agricultural crop land on steep slopes

AgpSL - Agricultural pasture on steep slopes

AgtSL - Total agricultural land use on steep slopes

Usr1SL - User defined class on steep slopes

Each of the above will also have a field with _A appended (e.g. Pfor_A) representing total area in map units.

Human Stresses

P_LOAD - Phosphorus loading

N_LOAD - Nitrogen loading

POPDENS - Population density

POPCHG - Change in total population

PCTIA_LC - Impervious cover, based on land use

RDDENS* - Road density by road class

RDLEN* - Total road length by class

STXRD* - Number of road/stream crossings by road class

PCTIA_RD - Percentage of impervious cover, based on road density

STPRD* - Length of roads in close proximity to streams (user defined distance) by class

* If a road class is used in the indicator computation, the output field name will have "C<CLASS>" appended. For example, for road class 1, the density name will be RDDENSC1.

Physical Characteristics

PRCPRNG - Precipitation range

PRCPMIN - Minimum precipitation

PRCPMAX - Maximum precipitation

PRCPMEAN - Average precipitation

PRCPSTD - Standard deviation of precipitation

ELEVRNG - Elevation range

ELEVMIN - Minimum elevation

ELEVMAX - Maximum elevation

ELEVMEAN - Average elevation

ELEVSTD - Standard deviation of elevation

SITE_ELEV - Elevation at point locations

SLPRNG - Slope range

SLPMIN - Minimum slope

SLPMAX - Maximum slope

SLPMEAN - Average slope

SLPSTD - Standard deviation of slope

STRMDENS* - Stream density

STRMLEN* - Total stream length

* If an stream order is used in the indicator computation, the output field name will have "O<ORDER>" appended. For example, for stream order 1, the density name will be STRMDENS1.

Riparian Characteristics

Ragc - Percentage of stream length adjacent to cropland

Ragp - Percentage of stream length adjacent to pasture

Ragt - Percentage of stream length adjacent to all agricultural use

Rbar - Percentage of stream length adjacent to barren

Rfor - Percentage of stream length adjacent to forest

Rurb - Percentage of stream length adjacent to urban

Rusr1 - Percentage of stream length adjacent to user defined class

Rwetl - Percentage of stream length adjacent to wetland

Rnat - Percentage of stream length adjacent to all natural land use

Rhum - Percentage of stream length adjacent to all human land use

Each of the above can also have a number following the code representing a buffer distance. For example, Rfor30 is the percentage of forest in a 30 (map units) stream buffer area. If the buffer distance was a real number, it is rounded to the nearest integer.

Appendix 2 - Default coding schemes

Anderson level 1

Land use category Codes included in this category
Urban 1
Low density residential None
High density residential None
High intensity commercial None
Agriculture - crops None
Agriculture - pasture None
Agriculture - total 2
Urban grasses None
Forest 4
Shrubland None
Water 5,9
Wetland 6
Barren 7
U-index 1,2
N-index 3,4,6,8

Note: Because barren can be a mix of natural and anthropogenic use, it is not included in either N- or U-index. To include it in either indicator, add it's code to the appropriate list in the custom dialog box manually.

Anderson level 2

Land use category Codes included in this category
Urban 11,12,13,14,15,16,17
Low density residential None
High density residential 11
High intensity commercial 12,13,14,15,16
Agriculture - crops None
Agriculture - pasture None
Agriculture - total 21,22,23,24
Urban grasses 17
Forest 41,42,43
Shrubland None
Water 51,52,53,54,91,92
Wetland 61,62
Barren 71,72,73,74,75,76,77,83
U-index 11,12,13,14,15,16,17,21,22,23,24,75,76
N-index 31,32,33,41,42,43,61,62,71,72,73,74,77,81,82,83,84,85

Note: Rangeland (codes 31-33) and tundra (codes 81-85) are included in N-index, but are not used as individual indicators (i.e., percentage of rangeland). Code 83 (bare ground tundra) is included in the barren indicator.

MRLC

Land use category Codes included in this category
Urban 21,22,23
Low density residential 21
High density residential 22
High intensity commercial 23
Agriculture - total 61,81,82,83,84,85
Agriculture - pasture 81
Agriculture - crops 61,82,83,84,85
Urban grasses 85
Forest 41,42,43
Shrubland Urban grasses
Water 11,12
Wetland 91,92
Barren 31,32,33
U-index 21,22,23,32,33,61,81,82,83,84,85
N-index 31,41,42,43,51,52,53,71,91,92

Note: Natural shrubland (codes 51-53) and grassland (code 71) are included in N-index, and urban grasses (code 85) is included in U-index, but are not used as individual indicators (i.e., percentage of shrubland).

SAA

Land use category Codes included in this category
Urban 15
Low density residential None
High density residential None
High intensity commercial None
Agriculture - crops 13
Agriculture - pasture 12
Agriculture - total 12,13
Urban grasses None
Forest 1,2,3,4,5,6,7,8,9
Shrubland None
Water 16
Wetland 14
Barren 11
U-index 11,12,13,15
N-index 1,2,3,4,5,6,7,8,9,10,14

Note: Herbaceous (code 10) is included in N-index, but is not used as an individual indicator (i.e., percentage of herbaceous).

Appendix 3 - Technical Notes

All dialogs - Default theme and field selections in input boxes

Most of the dialogs require some user input. For theme inputs, the program searches the names of all themes in the view and attempts to choose the most logical theme for each input. Once theme inputs have been chosen, the program searches fields within their attribute tables for logical choices for field inputs (if required). In both cases, the first pass looks only for exact pattern matches, a second for partial matches. The search strings are listed below. If no matches are found, the program selects the first valid theme in the table of contents or field in the attribute table. The user may override program choices by manually selecting from the scrolling list.

Dialog(s) Input field name Search strings (in order of precedence)
Landscape Characteristics, Human Stresses, Riparian Characteristics Reporting unit huc, reporting unit, reporting, unit, watershed, wtrshd, basin, subbasin, shed
Landscape Characteristics, Human Stresses, Riparian Characteristics Reporting unit field huc, basin, subbasin, shed, -id, label, name, recno, id
Landscape Characteristics, Riparian Characteristics Landcover landcover, landcov, lndcvr, land, cover, lc, lnd
Landscape Characteristics Slope slope, slp, gradient
Human Stresses Census1, Census2 population, pop, census, blockgroup, blkgrp, block, tract
Human Stresses Pop field pop, census, count
Human Stresses, Riparian Characteristics Streams stream, streams, strm, river, rivers
Human Stresses Roads roads, road, rds, highway, hwy, trans
Human Stresses Class field class, code, type

All indicator categories

When reporting units have multi-part polygons, ATtILA will perform a spatial merge based on reporting unit ID. Indicators will be calculated using this theme, and results appended back to the original reporting unit table. Each record of any multi-part reporting unit will contain indicator values based on the entire reporting unit, not the individual piece.

Landscape Characteristics

Calculations of land use percentages use terrestrial area only. Water areas are not included in the total area for the reporting unit. This is also true for the N-index and U-index, (i.e., water should not be included in the N-index selection list).

Create Indicator Atlas and Create Indicator Index

If you are working with a small number of reporting units (create atlas) or a small number of indicators (create index), there may be very few unique indicator/index values. The number of quantiles cannot exceed the number of unique values. If you choose more quantiles than are valid, the program automatically uses the number of unique values instead. When this occurs, a message box will inform you and the resultant theme will have fewer quantiles than you requested. This may be a concern in creating an index, as indicators may not all have the same range of values (values are equal to quantile ranks in index creation).

Create Indicator Index

The index calculation process is best described using an example. A reporting unit has a large amount of total forest cover, but also has a large amount of riparian zone agriculture. We create an index with percentage of forest (Pfor) and percentage of agriculture within 30 meters of streams (Ragt30), using 5 quantiles. Weights of 1.0 and 2.3 are assigned to Pfor and Ragt30, respectively. Given the high amount of total forest and riparian zone agriculture, this reporting unit would likely be assigned a rank of 1 (best), for Pfor, but a 5 for Ragt100. The index value for this unit would be calculated as follows:

1 (Pfor rank) * 1.0 (Pfor weight) + 5 (Ragt30 rank) * 2.3 (Ragt30 weight) = 1 + 11.5 = 12.5

Index values for all other reporting units would be calculated in the same manner, and those values would then be used to rank the reporting units in the index display. Note that because of the weights chosen in the example, riparian agriculture has much more impact on the index value than forest cover.

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