Biol 515 Landscape Ecology and Management



Biol 515 Landscape Ecology and Management, Fall 2011

Lab #1

Introduction to Geographic Information Systems: Viewing and Analyzing Spatial Data in

ArcGIS Desktop

Lab Exercise: Today you will be introduced to using a Geographic Information System (GIS) for viewing, manipulating and modifying spatial data for a region in East Africa. You will complete several exercises in ArcGIS and apply skills to answer a few questions regarding the African landscape. Your answers are due Monday, Sept 12th at beginning of lab.

Objectives:

1. Understand how landscape features can be represented and qualitatively analyzed in a GIS,

2. Become familiar with viewing spatial data in ArcMap which is the display portion of the Geographic Information System, ArcGIS Desktop,

3. Learn how to query and modify the appearance of vector and raster data within a GIS

Overview of Lab 1:

At the end of this lab, you should understand and be able to do the items below to address the questions at the end of the lab. Next week you will build on these skills using ArcCatalog and ArcToolbox and the Geoprocessing functions in ArcGIS. The techniques in the labs build on each other, so it’s useful to keep your previous labs and bring them to class.

Tasks in ArcMap

- create a Map document file (.mdx) so you can save your work from week to week

- work in the ArcMap Interface using the Table of Contents and Map Display Area

- add spatial data (layers), understand precedence, zoom and be able to pan around in the map display area

- change your data legends, edit attribute classes, measure distances, identify features

- understand the spatial/attribute connection, query data

Introduction to Spatial Data

Some digital ways of representing a landscape

Points - Features that are represented only as an X, Y coordinate in space, such as the latitude/longitude location of the center of a study plot. Information about the point (e.g., its size, elevation and dominant vegetation cover type) can be stored along with its location.

Lines - Features that are represented by a series of connected X,Y coordinates. Information on the type of line (i.e. road size, stream order) and line length can be stored.

Polygons - Areal features that are bounded by a series of connected X,Y coordinates, such as a study area. Information about the area and length of bounding perimeter are stored, along with any associated characteristics (e.g., average elevation, dominant vegetation type). Polygon data are particularly useful for landscapes where boundaries are finite.

Cells – Conceptually, cells are created by placing a grid over the landscape and assigning a value to each grid unit (cell) to represent the underlying characteristics. For example, each cell could be designated as “within the study plot” or “outside the study plot.” The spatial resolution of the cells, i.e., their X and Y dimensions, can be set to any size. Cell based data are Raster Data.

ArcGIS Data Models

Vector data model – Vector data are point, line and polygon data and their associated relationships or topology. There are many types of vector files, but the files types used in ArcGIS are coverages, shapefiles and feature classes. The shapefile is the ArcView vector file that are actually a group of files that work together (.shx, .shp and .dbf). Arc coverages are vector files created in Arc Workstation, and area also actually two separate files (coverage and info). Feature classes are the newest form of vector data and most suited to use with ArcGIS Desktop. Vector files with many features classes (i.e. points and lines as example) are feature datasets. Geodatabases are a collection of feature datasets.

Raster data model - Grids are the raster data. Grids consist of two files that do not function if they are separated. The first file is the name of the grid and the second file is the ‘info’ file. ArcGIS can handle other forms of raster data but we will only use raster grids in this lab.

Study Area Landscape

The study area is a portion of East Africa that is termed Maasailand. This was the traditional area of the Maasai people who herded cattle nomadically across the savanna. Maasailand stretches from Lake Victoria eastward to the Kenyan and Tanzanian coastal plain. Included in Maasailand are the Greater Serengeti Ecosystem, the Rift Valley, and Mount Kilimanjaro. The large cities such as Nairobi are also within Maasailand. Our study area includes two districts in the Kenyan portion of Maasailand that are centered on nature reserves. The Narok District includes the Maasai Mara Reserve and represents the northern portion of the Greater Serengeti Ecosystem. The Kajiado District lies just north of Mt Kilimanjaro and includes Amboseli National Park.

The landscapes here are typical of East African savanna. Total annual rainfall varies from 250-1800 mm, falling in two rainy seasons. Elevations range from 1300-2500 m. Soils are principally young, weathered, recently formed mixtures of volcanics, Tertiary igneous rocks, Quarternary sediments and older basement complex. Soil texture varies from stony sands on hilltops to heavy cracking clays at the lower end of catenas. Small patches of forest cover some hilltops and the slopes of Kilimanjaro. These forests grade into mid-elevation woodlands (now mostly cultivated) to lowland rangelands, dominated by bushland, grassland, and patches of dry woodland. Major water bodies include the Mara, Ewuaso Ngiro, and Olekejuado Rivers; Lake Magadi; and the swamps of Engare Ngiro and those that ring the northern flanks of Kilimanjaro.

This region, and that in neighboring Tanzania, is home to the most diverse remnant of the Pleistocene fauna left on earth, supporting some 31 species of large grazing mammals (Yellowstone has 7). Throughout the 20th century, this area was also home to the two largest migrations of wildebeest and zebra in East Africa: the Serengeti-Mara and the Athi-Kaputiei (in Kajiado) migrations. Elephants also migrate throughout Narok and in southern Kajiado districts. Colonial and Kenyan governments established Amboseli National Park and Mara National Reserve between the 1940-1970’s in the dry season grazing areas of both wildlife and livestock; however, in the late 1980’s more than half the wildlife was outside conservation areas.

The Maasai people arrived in this region in about the 1600’s. They roamed over the savanna with their cattle and coexisted well with wildlife. In 1911, the British colonial government and Maasai leaders agreed to create a ‘Maasai reserve’ in what is now these two districts, to be used principally by the Maasai. In the 1970’s, the land was divided into communally owned group ranches, and, in 1986, some of these group ranches near Nairobi converted to private land ownership. Today, land ownership is private in the wetter areas and near towns, and still under communal land tenure in group ranches in the driest areas far from towns. However, this is rapidly changing, with many more of the group ranches converting to private ownership since 1999. As Maasai sell land to other peoples, urban centers like Nairobi are spreading into pastoral areas and farming families are ploughing more and more land for food crops, starting in the highest potential areas. In areas below 600 mm rainfall, farmers have good crops only 1 out of every 5 years, so the potential for widespread cultivation is currently limited. Important exceptions are the wet rangelands (800-1000 mm rainfall) north of the Mara reserve, and the swamps around the edge of Kilimanjaro. In-migration and local growth has more than quadrupled human population from 5 to 23 people km2 in Kajiado and 8 to 39 people km2 in Narok between 1960 to 2000. Most of these districts are thinly populated except near the population centers of Nairobi, Loitokitok and Narok, with few people in the driest areas. Current livestock populations (late 1990’s) average 28 TLU (tropical livestock units) km2 in Kajiado and 60 TLU km2 in Narok districts.

There is concern about the effects of this land use intensification on wildlife, especially mammal species that migrate out of the protected areas seasonally. Several studies found that many of the large mammal species in this region have declined in abundance over the past 30 years, some by as much as 75%. Hansen et al. (2006, unpublished report) found that presence of agriculture and human population density were significantly associated with the population declines, but climate and plant productivity factors were generally not significant. They conclude that recent changes in human uses are having strong negative effects on several large mammal species in the study area, not only in unprotected areas that are undergoing land use intensification, but also in protected areas.

Introduction to the ArcGIS Desktop software package

Open ArcGIS and create a new Map Document (.mdx).

1) Go to Start, All Programs, ArcGIS, ArcMap (or use the shortcut on the desktop).

2) When the “ArcMap – Getting Started” box appears, click “Blank Map” since we are creating a map document from scratch, and “OK”

Copy the folder ‘lab12011’ from a flash drive or CD (provided in class) to c:\users\biol5\My Documents\ArcGIS.

This is the ArcMap Document screen. The box on the left is the Table of Contents (TOC), which shows what spatial data you have available to work with. You obviously have none at this point. The right window is the Map Display Area (MDA), where your geographic data will be visible. The middle section of this screen might show the ArcToolbox. We will use ArcToolbox next week, so if it appears in the middle of your screen, close out of it for now (click top right “x”).

3) Click on “File, Save As”, and save your project in c:\users\biol515\lab1yourinitials. IMPORTANT: Name your project in less than 9 characters, with NO SPACES OR HYPHENS. Now you can open that file up anytime after closing ArcMap and find your previous work.

Add spatial data to your MDA

Spatial data is viewed in the MDA within the Map document.

1) To add spatial data to the project, click on ‘File, Add Data’ (note the button in the future). Browse and select “c:\users\biol515\lab12011\eacountry.shp” and click “Add”. Repeat these steps and add all files in the “c:\users\biol515\lab12011” folder.

Seven spatial files should be visible in the TOC, and a map should be visible in the MDA.

Turn these themes on and off by clicking the small box to the left of the theme name. This is the East African study area you read about. Note the different symbols used to represent the different data types (points, lines, polygons and cells).

Understand View Precedence

2) Re-order the themes so that the “earivers” is on top. Do this by clicking on rivers and dragging it above the other files, or dragging the other files below the earivers file. View the MDA. Now drag parks to the top. View MDA. Now drag the ‘eaelevation’ to the top. Note that the other files are not visible.

This demonstrates conceptually how a GIS handles data by overlaying data layers. It also demonstrates the precendence of data such that points are single x,y locations, polygons are enclosed and have area. Lines have no area but have length. Raster data are continuous, meaning they occupy all area in their Map Extent, or geographic space.

NOTE: To work with raster data in ArcGIS, we must use an ArcGIS “extension” called Spatial Analyst. If you are ever unable to use your raster data in the future, go to “Tools, Extensions” and click “Spatial Analyst” on. We will use other ArcGIS extensions later in the class.

3) Since the continuous elevation (raster) data is on top of your vector data, reorder the data again so that the vector data have precedence and are visible in the MDA (i.e. drag elevation down to the bottom of the view menu).

Changing Data Symbology

Open the Layer Properties and modify the appearance of your data

Now you will change the symbols of the data to make the spatial data appear to your liking. You will first change the colors and symbols in the line, point and polygon files and then for the raster Grid.

1) Double click on the eatowns.shp file in the TOC. This brings up the Layer Properties dialogue box.

In the Symbology tab, double click the elevated point and choose a color, size and symbol of your choice. Click OK and look at your changes in your map. Do the same for all the line files (eacountry, eariver).

2) Now double click on the polygon file, eaparks, double click on the colored polygon rectangle, and choose a fill color and outline color, and click “OK”. Now go to the tab, at the top of the dialogue box called “ Display” and make the fill 45% transparent. Click “OK” and note the transparency of the parks. This allows you to see the roads and towns (and later elevation) inside the parks

Now we will manipulate the elevation classes in the Grid data with three different classification schemes. There are too many values of elevation to ever use the ‘unique values’ scheme as each elevation value would have a different color. We will explore using three popular schemes: Natural Breaks, Equal Interval and Manual options, defined below.

• Natural breaks—identifies groupings of values that are inherent in your data. This is the default method because it is appropriate for most data.

• Equal interval—this method is like a ruler: the interval between each class is the same. For example, you might have classes with intervals of 10 percent (1-10%, 11-20%, 21-30%, etc.)

• Manual—each class has the range you specify. This method is useful when you want the classes to reflect specific criteria or data. For example, if you have temperature data, you might want to specify a break between classes at 32 degrees Fahrenheit (freezing point).

1) Double click on the elevation grid to open its Layer Properties and select the symbology tab. Now click on “classified” under Show: and click on classify under ‘Classification”.

You will see a histogram of the values in the elevation grid, a box of classification statistics, and other information on the elevation values. The best classification scheme depends on the distribution of your raster data, and what you want to convey with the appearance. The next few steps are intended to demonstrate this.

2) Choose the “Equal Interval” classification method in the pulldown menu, and look at the way this classification scheme breaks down the elevation classes. Click “OK” and choose another color from the color ramp, and click “Apply”, and OK. Look at your map.

Using the “equal interval” classification, all values in the grid are spread equally over the full range of elevation values. There are very few cells/areas that are found at these highest elevation classes. This masks the variability in the lower elevation classes. To address this issue, we will use a better classification method for elevation in our specific study area.

3) Open Layer Properties, classify again and now choose the “Natural Breaks” method, OK and OK. See how this improves representation of the lower elevation classes. This illustrates how important the display of values can be when looking at spatial data.

Getting around in the ArcGIS Map Display Area

Now we will explore using ArcMap Tools to get around in the MDA and to become familiar with the data and our study area. Make sure this toolbar is available, by going to Customize, Toolbars and making sure that there is a check next to “Tools”. Check out all the available toolbars for future reference. Your Tools toolbar might be represented by buttons on the top of the ArcGIS window, or it could be ‘undocked’ on the outside of the ArcMap window.

1) Put your cursor on top of the tool button that looks like a magnifying glass with a plus sign (without clicking) and a button name will appear in a yellow text box. The table below describes the functions of the buttons and brief instructions regarding their use. Find the icons representing each of the tools below.

2) Use the ‘zoom in’ button to zoom into your data (click the button, and drag a box over the map). Zoom in until you see the individual raster cells of the elevation data. Use the measure tool to determine the resolution, or smallest unit, of the elevation file.

Become familiar with the buttons below to explore your data.

|Tool |Action |Instruction |

|Identify |Opens table of attribute values at that |Click on button, click on the area of interest in the MDS and note options|

|(i) |location for the active dataset |for selecting the layer to get the attribute values (i.e. click on a town|

| | |with eatown.shp active) |

|Zoom in (plus |Zooms in (larger/broader scale) to MDA |Click button and then in MDA, or drag a box |

|sign) | | |

|Zoom out (minus |Zooms out (smaller/finer scale) to MDA |Click button and then in MDA, or drag a box |

|sign) | | |

|Pan (hand) |Moves around the MDA |Click button and then in MDA, hold down button and drag |

|Measure (ruler) |Measures distance of two points or a line |Click button, click in MDA, move cursor, click again and see distance |

| |segment |units in the dialogue box- Double click to end |

|Full extent |Zooms to the full extent of ALL dataset in |Click button |

|(earth) |the MDA | |

Using Attribute Data

So far we’ve used spatial data associated within our study area. Another very important type of data supported in the GIS environment is the attribute data. Attribute data is the information associated with the points, lines, polygons or cells.

Working with Attribute data in Tables

1) To look at the attribute data associated with each file, right click on the data (i.e. eaparks) and go to “Open attribute table”. Click on a box on the very left in the table (left of a FID value). This makes each record active and highlights it on the MDA. You might have to move or minimize the attribute table to see the MDA. The columns of data are all the data associated with each spatial reference. For the eaparks dataset, the park name, size, country are all contained with the attribute file. Close the attribute table.

Select by Attribute

The query builder is an invaluable tool to help select attribute features that meet specified criteria.

1) Open the “Select by Attributes” dialogue box, under Selection. Select the eaparks layer, and create a statement to select parks that are greater than 220,000 square meters in size. Do this by double clicking on the “size” attribute in the attribute list (scroll down), clicking the greater than or equal to (>=) button, and typing 220000. Note the query equation is built in the lower box. Click Apply and these parks should appear highlighted (the default selection for polygons is aqua blue outline). Close the dialogue box.

2) Select by Attributes for grids, by right clicking the elevation grid, choose Open Attribute table. This shows the elevation value (value) and frequency of that value (count). Click on “Table Options” in upper left pulldown menu, and select “Select by attributes”. Double click “Value” >= 2000. In the MDA you will see all grid cells, greater than 2000m highlighted. Scroll down in the attribute table and see the values greater than 2000 are also highlighted. Now right click on the “count” column and choose “statistics”. The Count provides how many cell values are selected that meet your criteria and the Sum provides how many cells meet your criteria. If you know how big each cell is, you can use this information to calculate the geographic area of your selection. Close the statistics box, choose options again and ‘clear selection’. Close the attribute box.

Lab 1 Exercise portion Complete!

Tools for Manipulating Your Data to Answer Questions

In this lab, (lab 1), tools were introduced to help view and gain information from spatial data. As an example, the first tool, the Layer Properties would allow you to change the class values and class colors of data groupings in datasets (i.e. making the highest elevation class a different color for recognition). Another tool, the ‘Select by Attributes’ tool would allow you for formulate true statements about a vector file or grid, to select records (i.e. Park = “Serengeti”, would select any polygon that was named Serengeti). Use these tools and other strategies that you learned in lab today to answer the following questions, Due at the beginning of the next lab.

1) What town is closest to the Amboseli National Park? What is this distance? What tools did you use to obtain this information?

2) What portion of the study area (as defined by the Grid extent) is higher in elevation than 5000m? What park is located here? (FYI – one grid cell is 90 square meters)

3) Traveling from the town of Iguna to the town of Mangola using Class C roads only, what cities, in order, do you pass through? (zoom in and note that there is a road-break between Mkalama and Dongobesh that must be avoided)

4) In this study area, what is the oldest and youngest park in Tanzania? In Kenya? (hint: the year attribute indicates the park’s first year and you can sort ascending or descending by right-clicking the attribute name)

5) What is the latitude and longitude of the park “Maswa” as defined in the attribute table? Is this an accurate way to represent the location of polygon data? Explain.

6) What is the elevation range in the bottom 10% of elevation values and the top 10% of elevation values (as defined by the Grid extent)? (hint: the Legend Editor allows you to split classes into equal interval classes and 10 classes gives you 10% of values)

Next week:

Tasks in ArcCatalog

- browse, manage and document geographic data

- read and understand metadata

- create connections from your computer to the catalog

Tasks in ArcToolbox

- work in the arctoolbox, and explore some of the processing options available

- create your own toolbox with your own set of regularly used tools

- search for a tool

- do simple geoprocessing using the ArcToolbox

Tasks in ArcMap

- Create a jazzy looking map with your geoprocessing output (above)

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