Using correct data is the most important step in the implementation of any spatial decision support system. It is impossible to provide good decision support using a spatial decision support system without decent data, even if the system is perfect. Therefore, the data need to be as error free as possible to assure reasonable results. The quality of data relies on two main factors: accuracy and currency. Data accuracy indicates how well the data reflect the real world. It involves data acquisition methods, data resolution, data format, and data units. Data currency determines how timely the data are for a particular research project. It is not always true that the more recent XXX data are XXX better. For example, if the data are used in a research project that is focused on the past, they must reflect the XXX truth at that time.
Data preparation and description
For this research, data were acquired from various sources and were of different formats and coordinate systems. In order to analyze all the data in a single system, they had to be properly digitized into the system. XXX ArcView 3.1 was adopted for digitization and feature editing, and Arcinfo 7.2 was used for projection transformation. The raw data collected for this research included the followingX:
To get the data of all the layers within the study area, a rectangular
boundary polygon was created. This rectangle served as a general
outline for the study area and was used to clip all layers
that extended beyond its edges. The specific area for analysis
was determined by the distribution of the mine sites within the general
geographic vicinity, which was of
The study area lies on the border of XXX
Pike County and Warrick County. The revision dates of soil survey
maps of these two counties are 10 years apart. The
Pike County soil map survey was completed in 1989, and the
Warrick County soil survey was completed in 1979. There were
some on going mining activities in
the study area during the time gap between 1979 and 1989.
the geographic locations
of the soil map boundaries of two counties
XXX match perfectly,
the attributes of the soils were discontinuous
along their borders
[Add a paragraph.]
For those mining areas in Warrick County, which were explored between 1979 and 1989, the soil information recorded on the survey map was merely the soil series and properties that existed before mining activities began. To extract useful soil information, then, the data have to reflect either the current conditions or at least the conditions after mining activities began. To compensate for this situation in the study area, and to get one continuous soil map, an assumption was made that the mining areas during that particular mining period XXX were covered with a unique soil series.
First of all, soil map sheets from the two counties were placed side by side, and the study area boundary was drawn on them. With the map registered in a UTM projection, the soil polygons within the boundary were digitized and edited. [Xiao Liu: I talked to Steve Connelly a little about your thesis, and mentioned the prolific use of acronyms. It was his view that they should be defined very clearly, and often, in order that even a lay person can understand what he's reading. I suggest that you may wish to spell out UTM here.] During the editing phase, the map of mine sites was overlaid on XXX the digital soil map. The polygons in the areas that were affected after 1979 in Warrick County were then deleted from the map and the mine site boundary polygon was added to the soil map. [Xiao Liu: in the preceding sentence, does the word map and the words soil map refer to the same map? I would edit it differently depending on the answer.] After all the polygons were edited, soil attributes were added to each of them. The information in the general soil map includes the soil series name, the acidity (pH value), and the K value. In the soil survey maps, the soil reaction (pH value) was recorded as a range of values. However, to use the pH value in calculations, the values must be saved as a single value for each member of the soil series. The average value of the value range for a soil series was taken as the value for that soil series. The attributes for those modified polygons in Warrick County were then imported into the data of similar areas during the same mining period in Pike County. [Xiao Liu: Does this last sentence still mean what you want it to mean?]
The soil layer covers all the soil properties needed in this research.
Acidity data were XXX primary criteria
in the multiple criteria analysis, and the K values were the input for
the RUSLE model. [RSULE
?] It would be quite time-consuming
and most resource demanding if a particular
property was extracted each time it was accessed
in a program. It is much better to have every particular data set
ready as a layer in the database. For this purpose both an
acidity map and a K value map were
generated from the soil map by using region functions provided by ESRI.[
I know this one, but I didn't till you told me. Should you spell
The digital elevation model (DEM) records
XXX information regarding
the terrain. Originally the values in a DEM were
elevations above XXX sea level. The
USGS 7.5 minute DEM, which has
30 meter by 30 meter
ground resolution, was used for this research. [Xiao
Liu: Do you in fact mean meters here, or do you mean minutes?] The
file was stored in USGS DEM format, which
could not be processed directly in ArcInfo or ArcView.
However, there was an import module in ArcView that
allowed the USGS DEM file to be converted
to a grid file. The DEM was mainly used to calculate an
LS [LS ?] value for the calculation
of erosion rate using the RUSLE model.
The streams and lakes layer was acquired
from the Indiana Geological Survey (IGS).
Since XXX pollutants are
carried by water and relocated
along the waterways, the stream layer was
extremely critical in evaluating the potential pollution caused by abandoned
mine sites. This layer, originally stored
in shape file format, was then XXX
clipped by the boundary shape file. Using the ArcInfo file format
conversion function, the Shapefile was eventually converted to ArcInfo
coverage allowing the program to access it
XXX Mine site layer data,
collected and prepared by the IGS, recorded not only the mining
areas but also XXX mining periods. This was
the main source for delineating the analysis
boundary. The intersection of this layer and the general boundary was outlined
as the primary analysis area.
Topographic maps were scanned from the U.S. 7.5 minute topographic maps
as digital images. However, the geographic
information on the map was not kept with the image file when the maps were
scanned; XXX a geo-reference file had to be
created for this purpose. The world
file is one that can record XXX
geographic locations for any image files. Primarily,
the world file keeps the up-left corner coordinates, horizontal and vertical
factor for converting screen units to map units, and rotation factor.
[Xiao Liu: I just don't know what you
mean in this sentence, and am therefore reluctant to try to edit it without
your input.] Topographic maps provided general information
about the area and served as back draft. [I don't
know what back draft is.] They also were a source of verification
for land use and land cover classification
from the satellite images.
The Shapefile is a default file format for ArcView, and its coverage is a default format for ArcInfo. To reduce the amount of calculation in the program, all the layers in Shapefile format generated from ArcView were converted to ArcInfo coverage so that the ArcInfo functions could call up the data directly. This conversion was conducted in ArcInfo using the ‘ShapeArc’ command.
Land use/ land cover classification
System building is another important part of this study, in addition to data collection. To build an appropriate system, the spatial decision support system must be user friendly and functionally rich. XXX
The SDSS application was built in a multiple document interface (MDI) environment (Figure 4.1). The MDI application comprises a main window and XXX many child, or subservient, windows. It allows users to open child windows within the main application window. More than one document or child window can be opened within a single parent window. Another advantage of using the MDI application is that the child windows can share the toolbars or menus of their parents.
The main menu XXX provides entrance to
some typical Windows functions. The "File" menu item contains the functions
to operate files, such as opening a child
window and printing a map. The user can open
a new child window and import any layer for display,
such as the ShapefileXXX coverage and
image file. XXX From the "View"
menu, the user can navigate the map and load
the area of interest by zooming in, by
zooming out, and by
panning. The "Modeling" menu
item is the main function of this system. It covers all the models
used in the system, which include erosion rate information,
stream buffer information, normalization
information, and weight matrix information.
Each model is represented by a tab form [icon
?] in the modeling window, which provides
blanks for the user to operate. By selecting
this item, a user is able to interact with
the system by typing
XXX preferences in a user-friendly environment. The "Windows" menu item controls the layout of child windows within the frame of their parent window. The windows can be arranged as tile, cascade and auto arrange.
Buffering stream proximity
The tab window for the stream proximity calculation XXX comprises four parts (Figure 4.2): a scale bar for values, a scale bar for distance to the stream, a text box, and a panel for the display. A user can assign values to the ranges of the distance to the streams simply by sliding the scale bar. With a click of the "Set" button, the user’s selection can be shown in the small text box below. The "Preview" button sends the user’s assignment to a temporary file and calls ArcInfo functions to calculate the buffering zones. It eventually displays the result in the display panel.
The buffer function of ArcInfo was integrated into the program
to calculate buffering zones. Figure 4.3 illustrates how the function works.
The buffer function creates buffer polygons around specified input coverage
features. The output is a polygon XXX with
a new attribute called "inside" attached to it. After every buffer
function has been called, the output coverage
is converted to a grid for further calculation.
If only one buffer zone is set, it is quite straightforward to use the
buffer function to generate the buffer zones. However, most of the time
multiple buffering zones are requested, and the buffer
function alone cannot handle it.
In this case, other techniques need
to be incorporated.
[Xiao Liu: I just thought a paragraph break here would ease the reader's task.]
The operation of the buffer function, with XXX input of the buffer distance for a stream layer, generates a coverage with three values for the attribute "inside." The values are: 100 for those inside the buffer zone, 0 for those outside the buffer zone, and 1 for those in the "donuts" enclosed by pixels inside the buffer zone. In the case of more than one buffer distanceXX being defined, the buffer function can calculate only the last defined buffer zone XXX correctly. The result is more likely that a value of 100 will be assigned to those pixels in the last defined buffer zone, a value of 0 to those pixels outside XXX the buffer zone, and a value of 1 to those in the donuts (outside the polygons). To redeem the shortcoming of the buffer function, the following scheme was introduced.
For example, the user’s selection is set as:
Erosion rate calculation
The erosion rate window (Figure 4.4) consists of four buttons for conducting the functions. The "Calculate LS" button calls the function that runs the ArcInfo ArcInfo Macro Language (AML) (Appendix A). It generates the grid file for LS values. The "Statistics" button shows the statistical values for the erosion rate, XXX such as maximum, minimum and standard deviation. These values can be used when normalization is needed. The "Calculate A" button operates on all the input files for RUSLE [RUSLE ?]calculations. It also exports of all the files XXX to an output file of erosion rate values. The "Preview" button displays the output erosion rate file.
The RUSLE model expects inputs of five factors, a rainfall factor (R), a soil erosivity factor (K), a slope factor (LS), a cover and management factor (C), and a conservation factor (P).
The R value was acquired from the CITY database which came along with the RUSLE program. This R value was regionally distributed, so it was a constant for the whole study area. The value for the study area is 200 hundred XXX (ft-tonf-in)/(acre-hr-yr)-1. [Xiao Liu: Don't you think this might be clearer?]
The K value was extracted from the general soil maps that had been digitized from the county soil survey maps. Using a regional function in ArcView, the soil map was categorized by this K value. The polygons with the same K value were merged into one region. This file was saved as an ArcInfo coverage and then converted to raster format for calculation. The units for the K value are (ton-acre-hr)/(100-ft-tonf-in).
The P value was not taken into account in this study, since most XXX of the study area has not been restored back to crop fields and therefore no conservation methods were applied.
The C value primarily reflects the coverage conditions of the soil. This layer was generated from the land use/land cover classification extracted from remotely sensed data.
Like the tab form for proximity to streams, the window for acidity (Figure 4.5) contains the same structure. The two scalebars allow the user to assign normalized values to a pH value and the "Set" button saves the assignment into a text file for final calculation. The "Preview" button reads from the text file that stores the settings, and then reclassifies the acidity file to generate the normalized pH value grid file.
On the weight matrix form (Figure 4.6), three scalebars were designed to allow users to enter their preferences, or weights, for each of XXX three variables: erosion rate, proximity to streams, and acidity. After the weights are set, the current weight matrix shows up in the text box. At that time, the " Preview" XXX program calculates the final result according to the weight matrix and reclassifies the result so that the output values are normalized on a scale of 1 to 10 for reclamation priority.
Normalization is a very important step in multiple criteria analysis. It reassigns new values to original values according to the requirements of the problem. Usually XXX normalization values fall within a range of numeric values. This step assures that every criterion is treated equally before any weight or preference is assigned to it.
The highest priority value for reclamation in this research was set to be 10. Therefore, all the criteria values have to be reclassified into XXX values between 1 and 10 before the final calculation can be made. The higher value reflects the higher priority for reclamation. For the instance of proximity to streams and acidity, as the system was designed, the user assigns a normalized value to each range of the original values at the time user interacts with the system. Higher values should be assigned to those areas that are close to streams and have low pH values. All the settings then are saved in a text file. The ArcInfo reclassify function can read from this text file and operate on the grid file to generate a normalized output grid.
In the case of erosion rate, the value calculated from the RUSLE model is not easy to predict and not normalized. Therefore, there needs to be a way to conduct the normalization. At the erosion rate tab form, the user has access to the statistics of the erosion rate result. Based on the statistics, the user is able to get a general idea on how the values are distributed. At the time of normalization, a linear algorithm is used. There are two ways to set the maximum and minimum values for this stretch of XXX data. The default maximum and minimum values from the statistics can be used, or the user can detemine them by analyzing the statistics.
All the operations are conducted behind the screen windows. Therefore, the visualization of and the presentation of XXX results is another important component of the system. Displaying the data allows the user to view the geographical distribution of the attributes of a particular layer. Overlaying XXX two or more layers in a single display panel or window provides more detailed information for assessing the results. Multiple display windows provide the capability for the user to make comparisons. If the user has two or more priority maps resulting from different settings of the weights for some of the criteria, he can compare the results on the screen. A great advantage of multiple display windows XXX is that of allowing the user the option of calling up other data to assist in the comparison.
To run the spatial decision support system properly, the following requirements have to be met.
Hardware : PC compatible, 32MB RAM
Software : Windows 95 or NT platform, 32 bit operating system , and ArcInfo library and license
MapObjects DLLs [DLLs ?]
Regarding the physical storage of data and applications, two considerations need to be taken into account : 1.the directory structure, and 2. the naming convention. To simplify the system, a directory structure was created to avoid forcing the user to find the data path XXX when running the system. It is only necessary that the users XXX copy the whole structure. Since the system accesses a fixed directory structure for all the data files and program files, XXX the structure must be intact to ensure that the system gets correct data and functions (AMLs). Naming convention for this system is critical for XXX users who want to replace the existing data files with their own custom data files. If any of the data file names are changed, the system will not function normally.
All the data, AMLs, and application files must be saved in the same directory as "working directory." In the system, the users have the option of changing the system path to the working directory. The files and directories under the working directory should include:
1. DEM directory for digital elevation model data used to generate LS values for erosion rate model,
2. K_Value directory for K value used in erosion rate model,
3. C_Value directory for C value used in erosion rate model,
4. Stream directory for streams and lakes layer,
5. PhGrid directory for pH values,
6. sl.aml, fil.aml, dn_slope.aml, high_pts.aml, s_length.aml, and ls.aml for LS value calculation algorithm ,and [Whew! What's all this?]
7. SDSS.exe for the executable file of the application.