Developing an Interactive GIS Tool for Stream

Classification in Northeast Puerto Rico

Lauren Stachowiak

Advanced Topics in GIS

Spring 2012 1

Table of Contents: In-Situ Model-----------------------------------------------

1. Model Introduction – Page 7

2. Branch 1: Flow Hydrology – Pages 8-9

3. Creating Waterhseds – Page 10

4. Branch 2: Meshing Polygons – Page 11

5. Final Steps: Stream Classification – Page 12

6. ArcScene 10 Screenshots – Pages 13-14

Table of Contents: Project Introduction------------------------------------- 1. Project Overview – Page 3

2. The Study Area – Page 4

3. The Datasets Used – Pages 5-6

Table of Contents: Upstream Model------------------------------------------ 1. Model Introduction – Page 15

2. Isolating Subclasses – Page 16

3. Draining and Calculating Dominance – Pages 17-18

4. Final Steps: Stream Classification – Page 19

5. ArcScene 10 Screenshots – Pages 20-21

The Wrap Up: Conclusions and Weaknesses (22-24)----------------

ArcScene 10: Landscape Flyovers (25)---------------------------------------- 2

Project Overview-------------------------------------------------------------------------

3

This project aimed to answer basic environmental questions about a tropical montane ecosystem.

Two models were created to classify streams flowing within the study area based on specific

environmental parameters used as inputs. The output of each model is a derived vector stream

network, which has as data within the attribute table the identification of each parameter, given as

inputs, on a per stream reach basis. The input parameters used for each model were a bedrock

lithology layer and a vegetation layer. For the first model, the in situ environment surrounding the

stream reach was used to classify each stream. For the second model, the upstream dominance of

each parameter (bedrock and forest type) were applied to the downstream channel reaches. Both

models relied on vector and raster data as inputs.

This GIS project was tailored around my MES thesis and was used to enhance the methodology

and techniques section of the final paper. The main goal behind this project was to generate a more

applied GIS focus to my thesis and to better understand the flow hydrology toolset. In addition, I

wanted to investigate how models could be created to automate certain processes. The focus of my

thesis revolved around potential influences in drainage density patterns as influenced by bedrock

and vegetation, which is why I have chosen those particular datasets for this project. Lastly, I have

chosen to create my final project for this class in a .pptx format because it contains many graphics,

which are better displayed and oriented in a slide rather than in a word document.

The following sections within this document describe how a potential user can execute the model

and steps to take for proper model use. To begin, a brief overview of the study area and data used

in the model creation is explained.

4

The Study Area--------------------------------------------------------------------------- The study area for this project is the Luquillo Mountains located in

northeast Puerto Rico. It is classified as a humid, tropical montane

ecosystem.

The geographic coordinates are: Lat: 18 15 N and Long: 66 30 W.

Quick Stats:

• Peaks at 1060 m

• >5000mm of

precip/year

• Average annual

temp. of 73° F

• Only tropical

forest in USFS

5

The Datasets: Introduction--------------------------------------------------------- This project begins with three base data layers, which are then used to generate several

consecutive layers of data. The data are composed of a digital elevation model (DEM), a polygon

shapefile of vegetation boundaries, and a polygon shapefile delineating bedrock lithology. The

following images show these data layers and the corresponding attribute tables.

Base Layer 1: DEM---------------------------------------------------------------------

This DEM is a raster data layer based on a 10 meter cell resolution. Since the cells are

floating point integers in raw form, there is no attribute table. However, the region as a

total of 1051 m relief, with a peak of 1060 meters and lowland of 9 meters. The data was

acquired from Miguel Leon and the LCZO research group.

This layer will be

used to derive the

vector stream

network in later

steps.

HIGH

LOW

6

Base Layer 2: Vegetation------------------------------------------------------------- The attribute table

represents information for

each feature in the polygon

shapefile. The vegetation

consists of 4 classes:

tabonuco (red), colorado

(yellow), elfin (dark green),

and palm (light green). The

forests occupy a total of 42

watersheds.

Base Layer 2: Bedrock Lithology------------------------------------------------ As you can see, this

shapefile is very similar to

the vegetation layer. There

are three geology classes

including: volcanic (purple),

quartz diorite (green), and

hornfels (blue). There are

42 watersheds in this area

as well. Area was calculated

here as well in (m/ha)

Both vector layers above have been overlayed with a hillshade layer to better show relief.

Symbology of each layer will be kept constant throughout this document.

7

In Situ Cartographic Model--------------------------------------------------------- This first model assigns environmental classifications to stream reaches within the immediate surrounding area

(polygonal boundaries) of each corresponding bedrock/vegetation parameter. Essentially, those polygons

through which the streams flow will be the ones whose classifications will be applied to each reach.

The following pages explain in more detail the below steps written in the tool:

I. Generating the stream network with stream order preserved using a DEM of the study area.

II. Generating a watershed shapefile consisting of a constant surface of polygons

III. Meshing Polygons and Classifying Streams

The below model is shrunk to show completely on this slide. It will be broken down in the following slides.

Model Inputs:

1. DEM

2. Watershed Data; allows the user to

define their own watersheds based on

site-specific field observations.

3. Two environmental parameters. Each

must be polygon vector files and must

occupy the same “space” as the DEM

and watershed layers.

*This is what the tool looks like in ArcMap

8

I. Deriving A Vector Stream Network-----------------------------------------

All flow “sinks” in the original DEM

were filled with the Fill tool to make

this output file.

Flow Direction was calculated for each

cell giving values representing cardinal

directions.

Flow Accumulation was calculated

from the direction raster to find flow

channels.

A threshold of 50 was set to limit

the network using Raster Calculator.

Stream Order was calculated giving

each stream a reference number.

A vector file was created using the

Stream to Feature tool.

A

F E D

B C

A B C D E F

The tools used in this first branch of the model are shown in bold.

9

A Closer look at Flow Direction-------------------------------------------------- Considering that many future operations in this model and the second model rely on this raster data layer, it is

worth taking a closer look at this hydrology operation. Essentially, this tool looks at the DEM (or the filled

DEM) on a pixel-by-pixel basis and assigns each cell a value based on the direction to the steepest immediate

neighbor. The new cell values will be one of eight cardinal directions.

Below the flow direction raster from the previous page is shown in planimetric and perspective view (from

ArcScene). On the right, is the direction raster converted to points and symbolized with rotating arrows to

better show what the computer “sees” when it uses the direction raster for the next step in flow accumulation. It

has been overlayed on a DEM to simply show background perspective (so the arrows aren’t floating in space).

Notice distinct V-shape valleys on all three pictures.

II. Creating a Site-Specific Watershed Layer------------------------------- A point shapefile of pour points was

manually created (green circles) to

represent where the water drains.

These represent the outlets of each

watershed. The pour points were

placed at the junctions of bifuracted

streams outside of the park to

generate a constant surface

throughout the entire study area.

The watershed tool requires the

direction raster and the pour points

for operation.

The watershed layer was converted

to a vector polygon file and the

attribute table to the left shows the

features in the layer. The final

watershed count for this particular

study area was a total of 42

watersheds.

*Your watershed layer would look

different than this one. 10

11

III. Meshing Polygons----------------------------------------------------------------- V

ege

tatio

n

Geo

logy

W

aters

hed

s

These three vector layers, shown on the left, are

“meshed” together into a single polygon layer. This is

done by a series of nested intersections, which allow

this final polygon layer (shown below) to assume the

classifications of each of the three starting layers.

Just as a reminder, when running this model for your

particular study area, this final polygon layer will look

different based on your own data.

12

IV. Final Steps: Stream Classification------------------------------------------ The final stream network,

shown in red to the left,

has been intersected with

the polygon layer from

the previous page. It was

overlayed with a semi-

transparent hillshade and

watershed layer to show

individual basins and

relief. The attribute table

shown below is for the

stream reaches selected

from the network (shown

in light blue on the map).

13

ArcScene 10 Screenshots------------------------------------------------------------

The following images are a sample of screenshots taken throughout the creation of this model.

They are meant to give better visual representation of the study area and the different layers used as

inputs and those created during model execution.

This is a schematic made with layered raster

datasets created in the flow hydrology branch

of the model. The bottom is a DEM and the

top is the derived stream network.

The top image is an oblique view of the

stream network with the geology layer. The

bottom is the classified streams draped on

a 3D landscape (the filled DEM).

14

Above is the same example as the geology

layer, but now with vegetation.

The top right and bottom images are views of the study area. The top image is a bird’s

eye view from the NE looking SW, the bottom is at a horizon level looking due north.

15

Upstream Cartographic Flow Model------------------------------------------- This second model classifies stream reaches based on the dominance of bedrock and vegetation

types from the upstream catchment areas. Essentially, each environmental subclass is “drained”

down the DEM surface and total accumulation values are calculated on a pixel basis. These values

are then attributed to stream reaches on a majority ranking system, where each stream is given the

bedrock and vegetation type most dominant upstream. The flow hydrology branch of the model is

the same as the first model, so it will not be described again here.

As you can see, this model is more complicated and requires many more steps. The

following procedures will be discussed in the following pages:

I. Isolating the environmental parameters based on subclasses of data

II. Draining these isolated subclasses and accumulating flows

III. Calculating Upstream Dominance and Classifying Streams

16

I. Isolating Environmental Parameters---------------------------------------- Each input vector polygon layer must be broken up into individual data layers based on their

subclasses. This step in the model is done after the polygons have been converted to raster, by way

of a series of reclassifications. The output rasters are 0/1 grids with 1s representing previously

defined subclass extents and 0s being those areas previously belonging to the other subclasses.

(ie. in the geology layer there are three subclasses, so three 0/1 grids are generated).

From left to right the three grids immediately above are volcaniclastic, quartz

diorite, and hornfels. Red = 0, and Blue = 1 for all three grids.

The tools to take the vector polygon layer of bedrock lithology

distributions to the left and get the three 0/1 grids below are as

follows (the steps are the same for vegetation):

1. Convert to Raster

2. Reclassify. This was done 3 times for geology and 4 times

for vegetation (not shown) for a total of 7 reclassifications.

17

II. Draining and Accumulating Subclasses---------------------------------- Each of the seven 0/1 grids created in the isolation operations from the previous page were then

drained down the DEM landscape using the flow accumulation operation. The flow direction raster

is used and each 0/1 grid is used as the weight raster.

Each of the flow accumulation grids on the left have

cell values representing total upstream cell counts

attributed to that rock type. Using Cell Statistics, the 3

datasets are added together to get total upstream cell

counts for all rock types. The flow accumulation grids

are overlayed with the transparent geology layer.

18

III. Calculating Dominance Values Per Subclass------------------------ The first step to determining dominance is

to calculate the relative percentage of total

upstream accumulation belonging to each

rock type. This is done three times with the

expression shown in the dialogue box.

The next step is to take each raster

calculator output, here labeled

“catch_ROCKTYPE”, and run the highest

position operation. The output shown

below has cell values which identify which

rock type is most dominant on a pixel-by-

pixel basis.

Order of inputs is

important here.

19

IV. Stream Classifications------------------------------------------------------------ The stream classification steps are similar to those in the first model. Each highest position output

grid from the previous page for both initial input datasets (bedrock and vegetation) are then

converted to polygons. These two polygon layers are first intersected with each other, and then to

the stream network derived from the flow hydrology branch.

Polygons

on the left

create the

networks

to the right.

The streams to the right are symbolized

based on the dominant upstream rock

type (top) and vegetation (bottom).

20

ArcScene 10 Screenshots------------------------------------------------------------ The left image is taken from the

N looking S. It shows tabonuco

(red), colorado (yellow), palm

(light green), and elfin (dark

green) streams. Notice how some

streams “bleed” outside of the

natural distributions of their

bedrock type. Both colorado and

palm streams are shown in the

tabonuco boundary. The bottom

image is a landscape view taken

from a horizon perspective

looking due north.

21

The image to the left was taken

in Arcscene showing a stream

layer that has been overlayed

with a transparent geology layer.

Again, notice how the hornfel

(blue) streams are found in

quartz diorite (green) and

volcaniclastic (red) distributions.

The bottom image is a landscape

view of the stream network taken

from the NW looking SE. You

can see here also, how the

streams flow further downslope.

22

The Wrap Up: Conclusions-------------------------------------------------------- Below are the output stream networks from both models. Shown are stream reaches based on

geology and vegetation separately to compare some areas where the networks differ.

MODEL 2

VE

GE

TA

TIO

N

GE

OL

OG

Y

MODEL 1

The Wrap Up: Model Weaknesses--------------------------------------------

1. Environmental Data must be in the form of vector polygons

2. The second parameter is required. The model must compare two separate

parameters. It would be beneficial to make the second optional.

3. The critical contributing area threshold must be known before model is run and

currently the area is set as all cells with an accumulation cut-off of ln(4) or higher.

I. MODEL 1

24

II. MODEL 2

1. This model also requires vector polygons as inputs for the environmental parameters.

2. As of right now, a big weakness is that one parameter must have four variables, and the other

must have three, and they must be used as the right input parameter for the tool.

1 2 As you can see, this

model was built

specifically with the

bedrock and vegetation

data in mind so that it

would ultimately run

properly. However, as a

result of this,

environmental

parameter 1 must have

exactly 3 subclasses and

environmental

parameter 2 can have

only 4 subclasses of

data. This really is not a

practical assumption to

make of some other

user’s future data.

25

ArcScene 10 Study Area Flyover-------------------------------------------------

Here is where the flyover video would be if

it were not over 20 MB in size. Because I

can only send emails with a max size of

25MB, I will email the video to you

separately. The flyover is of the first model

with the stream network symbolized by both

bedrock and vegetation (3 rock types and 4

vegetation types = 12 possible combinations

of subclasses). There are twelve different

color schemes, one for each possible

rock/veg combination. The video transects

the study area from the SW over one river

valley into a second in the NE.