Notes: GIS Applications in Fire Ecology & Management One of the - - PDF document

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NR406 Notes: GIS Applications in Fire Ecology & Management One of the many strengths of a GIS is that you can stack Lesson 2 - Overlay Analysis in GI S several data layers on top of each other for visualization or Gathering Information


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SLIDE 1

NR406

GIS Applications in Fire Ecology & Management Lesson 2 - Overlay Analysis in GI S Gathering Information from Multiple Data Layers

Notes:

One of the many strengths of a GIS is that you can stack several data layers on top of each other for visualization or

  • analysis. For example, if you overlay a map of the habitat for

an endangered species and a land stewardship layer you can find out who is managing the land where the species exists. The concept of overlay analysis is easy, however it can get complicated because real world objects in a GIS can be represented by different features such as points, polygons, lines and pixels. Each type of overlay requires a unique analysis procedure in a GIS. For example point over polygon

  • verlay is different from point over pixel overlay etc.

NR406: GIS Applications in Fire Ecology and Management

Vector Data Vector Data

  • Coordinate-based data structures comm only used to represent

map objects. Each object is represented as a list of X,Y coordinates

  • Examples - tree, poles, roads, housing developments, zoning

districts

Points Polygons Lines

Notes:

Remember the three types of vector data: points, polygons and lines?

NR406: GIS Applications in Fire Ecology and Management

Raster Data Raster Data

  • Cell-based representation of map features. Each cell has a
  • value. A group of cells with the same value represent a

feature.

  • Examples - satellite imagery, aerial photography and some

come from software packages like GRID and ERDAS.

Notes:

….and then there is raster data where the real world features are represented by pixels (cells)….

NR406: GIS Applications in Fire Ecology and Management

Point / Polygon overlay Point / Polygon overlay

Notes:

This map illustrates a point over polygon overlay. The polygons here represent different vegetation types created via aerial photo interpretation. The points are GPS coordinates for vegetation plots characterizing the vegetation in the area. The GPS points will be used to estimate how accurate the photo interpreted map is.

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SLIDE 2

NR406: GIS Applications in Fire Ecology and Management

Point / GRI D overlay Point / GRI D overlay

Notes:

This is a similar map where the vegetation layer was created via image analysis of a satellite image resulting in a raster dataset (grid) where all green pixels represent vegetation type 1, the brown pixels vegetation type 2 etc. Again, the orange points are GPS locations for ground control points.

NR406: GIS Applications in Fire Ecology and Management

  • Multiple layers of data are in

relative position with one another

  • inserting a "digital pin" through

the stack of overlayed data.

  • This allows questions to be

answered concerning everything

  • ccurring at a particular location.
  • This view of the world limits

focus to a particular point and precludes wide-area landscape analysis.

“Piercing Needle” Approach “Piercing Needle” Approach

Notes:

Two overlay analysis principles will be described here: 1 – the piercing needle approach 2 – the cookie cutter approach. Both methods involves extracting data from multiple GIS data layers at locations of interest. In the ‘piercing needle approach’ information from one or more data layers are extracted at one single point (point – polygon overlay). For example, you may want to know the habitat type and canopy cover at bird nest locations. In this case the bird nests are represented by a point layer and the habitat type, elevation and canopy cover is represented by individual polygon data

  • layers. The result of such an analysis will be a table that

contains the habitat type and canopy cover for each bird nest location in your dataset.

NR406: GIS Applications in Fire Ecology and Management

GI S Overlay Analysis - Points GI S Overlay Analysis - Points

GRID: sample Spatial Analyst: Raster Calculator Toolbox – Spatial Analyst Tools- Extraction-Extract by Points or Sample Spatial Analyst: Analysis – Tabulate Areas

  • r

Script: samplegrids.ave

Point to Grid

Arc: identity Join and Relates: Join – Join data based on spatial location Geoprocessing Wizard – Spatial Join

Point to Polygon ArcInfo Workstation ArcGIS 9x ArcView 3x Overlay type

Notes:

This table gives you information on what tool in ArcGIS (or ArcView 3.x or ArcInfo) you can use to create a point to polygon or point to grid overlay. For example in a point/polygon overlay, to find the polygon characteristics of the locations where the points are located, use the Join and Relates features. In Exercise 2 which is part of this lesson you will perform these different kinds of overlay analyses.

NR406: GIS Applications in Fire Ecology and Management

What covertypes burned in the Selway- Bitterrot Wilderness in year 2000? Fire perimeters 2000

Polygon Overlays – on polygons or grids Polygon Overlays – on polygons or grids

Notes:

Sometimes we want to overlay a polygon layer over another polygon layer or a raster. In the map above the polygons

  • utlined in black represent fire perimeters and the raster map

represents different cover types. An overlay analysis can here tell you the cover types within the fire perimeters.

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SLIDE 3

NR406: GIS Applications in Fire Ecology and Management

Vector data

  • Clip
  • Intersect – Union

Raster data

  • GRID clip (masking)
  • Zonal statistics (GRID)
  • Combine

Region W ide: "Cookie Cutter Approach" Region W ide: "Cookie Cutter Approach"

Notes:

The other overlay approach is the ‘cookie cutter approach’ . This is an example of a polygon to polygon overlay analysis. Going back to the bird nest example, rather than extracting data from the exact bird nest location it might be interesting to analyze the conditions within a 100 meter buffer around the bird nest. The first step in such an analysis would be to create a 100 m buffer around the points (nests). The buffers will be represented in a new polygon layer in GIS. Next you would clip or intersect the habitat and canopy cover layers with the buffer layer and finally summarize the habitat types and canopy cover classes within the buffers. If your habitat and canopy cover layers are represented by raster data you would use the raster tools masking, zonal statistics or combine rather than the vector tools clip and intersect.

NR406: GIS Applications in Fire Ecology and Management

Vector Overlay Table Vector Overlay Table

ArcInfo ArcGIS 9x ArcView 3x Overlay type

GRID: combine Spatial Analyst: Raster Calculator Combine(grid1, grid2) Spatial Analyst: Analysis – Zonal- Tabulate Areas Spatial Analyst: Analysis – Tabulate Areas

  • r

Extension: Grid Transformation Tools – Transform Grids - Combine

Grid to Grid

GRID: zonalstats Convert the polygon cover to a grid or the grid to a polygon Spatial Analyst – Zonal Statistics Spatial Analyst: Analysis – Tabulate Areas Spatial Analyst – Zonal Statistics

Poly to Grid

Arc: intersect Arc: union Arc: identity Toolbox – Analysis Tools – Overlay – Union or Intersect Geoprocessing Wizard – Intersect

  • r Union

Poly to Poly

Notes:

The table above guides you as to what tool to use when performing a polygon to polygon overlay (vector overlay) or a poly to grid or grid to grid overlay. We will work with these tools in the lab exercise for this lesson.

NR406: GIS Applications in Fire Ecology and Management

# # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # #

Ve g e U rb a n Ag ric u ltu re N a tiv e g ra s se s Ex o tic g ra s se s H e rb a ce o u s cle a rc u t W e t la n d s/ w e t m e a d o w s Ot h e r s h ru bs Sa g e b ru sh / ra b b itb ru sh Bro a d le a f f o res ts X eric c o n ife ro u s M e sic c o n ife ro u s W a t e r R ip a ria n Ba rre n L an d Alp in e m e a d o w Sn o w , Ic e, C lo u d s Bro a d le a f /c on if e ro u s m ix ed Bu rn e d , s ta n d in g t im b e r N o D a ta # fire st art lo c a tio n s

200 200 M iles

Fires > 640 acres 1986-1992

S N E W

Fire Start Locations & Vegetation ( GAP) Fire Start Locations & Vegetation ( GAP)

Notes:

This map shows the vegetation cover types of Idaho

  • verlayed with the fire start locations for fires larger than 640

acres during the time period 1986-1992. What cover types do you think has the most fire starts (> 640 acres)? When you estimate the relative abundance of fire in different cover type you must consider how much of each cover type there is in the state. If the entire state was in the sagebrush cover type we would expect all fires to start in sagebrush. If half the state was sagebrush and half was forest you would expect half the fires to start in sagebrush and half in forest if the start of fires was a random event. Is it?

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SLIDE 4

NR406: GIS Applications in Fire Ecology and Management

Vegetation classes Relative abundan

10 20 30 40

fire frequency vegetation Agriculture Native g Exotic gr Wetland Other sh Sagebrush Broadleaf Xeric co Mesic c Riparian

Fires > 640 acres I daho State 1 9 8 6 -1 9 9 2 , Fire and Vegetation I daho State 1 9 8 6 -1 9 9 2 , Fire and Vegetation

Notes:

This graph shows data extracted from an overlay analysis of the two layers in the previous map (cover types and fire start locations). First, the black bars here show the distribution of vegetative cover types in Idaho. For example ~14% is in agriculture, 8% in native grasses, 3% in exotic grasses etc. Second, the red bars show the proportion of fires (> 640 acre) that started in these cover types. If the red and the black bar are the same height, the number of fires started are in proportion to the land area covered by that vegetation type,

  • ie. random. If the red bars are taller than the black bars there

are more fires than expected started in that cover type (more than random). What cover types have a higher proportion of large fires than you would expect if the distribution was random? Answer: (Native grasses, exotic grasses, other shrub, sagebrush)

NR406: GIS Applications in Fire Ecology and Management

Large fires ( > 64 0 aacres) by aspect class Large fires ( > 64 0 aacres) by aspect class

Notes:

In this graph the start locations of large fires in Idaho (1986- 1992) are compared to aspect. On what aspects do large fires

  • ccur more often than would be expected if the distribution

was random? Answer: south, southwest, west

NR406: GIS Applications in Fire Ecology and Management Exam ple of Fire- Atlas Data: Selw ay – Bitterroot W ilderness Exam ple of Fire- Atlas Data: Selw ay – Bitterroot W ilderness

Notes:

In exercise to you will perform a few different types of overlay analysis for the Selway-Bitterroot Wilderness area in Idaho.

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SLIDE 5

NR406: GIS Applications in Fire Ecology and Management

  • W estern redcedar
  • Douglas-fir
  • Grand Fir
  • Low er Subalpine Dry
  • Low er Subalpine

Moist

  • Upper Subalpine Dry
  • Upper Subalpine

Moist

  • Rock/ Alpine/ Barren

Land

Potential Vegetation Types Potential Vegetation Types

Notes:

This map displays the potential vegetation types in the Selway-Bitterroot Wilderness. What is a potential vegetation type? Answer: A potential vegetation type is a habitat type, i.e. represents the climax vegetation in an area. How is cover type different from potential vegetation type (habitat type)? Answer: The potential vegetation type (PVT) always represents the climax vegetation while the cover type is the vegetative cover currently occurring in an area. The cover type on a Douglas-fir PVT may be grasses or shrubs a few years after a fire, however, given time Douglas-fir will dominate the site.

NR406: GIS Applications in Fire Ecology and Management

Statistics are calculated for each zone in a zone dataset based on values from another dataset

in ArcGIS

Example: Calculate mean elevation within forest stands Zone dataset: forest stands Value dataset: elevation

Spatial Analyst in ArcGI S Spatial Analyst in ArcGI S

Notes:

Zonal statistics is a tool that is used for overlay analysis in

  • GIS. This tool is part of the Spatial Analyst extension. You

can here find out what the mean elevation is for forest stands.

NR406: GIS Applications in Fire Ecology and Management

Zone Layer Value Layer The output table can be joined to the zone layer to display a statistic per zone

Zonal Statistics Explained Zonal Statistics Explained

Notes:

The Zone layer is in this case the forest stands while the Value layer is the elevation layer. The output table will show the mean, max, min etc elevation within each forest stand.

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SLIDE 6

NR406: GIS Applications in Fire Ecology and Management

  • Zones can be continuous or non-continuous
  • The zone layer can be raster or vector
  • The value layer must be a RASTER
  • Many statistics are computed: mean,

median, standard deviation, min, max, variety, majority, range

  • Selected statistic can be charted

Zonal statistics Zonal statistics

Notes:

The use of zonal statistics will be illustrated in Exercise 2.

NR406: GIS Applications in Fire Ecology and Management

Tabulate Areas in Spatial Analyst Tabulate Areas in Spatial Analyst

Notes:

Another useful overlay analysis tool is Tabulate Areas in the Spatial Analyst Tools in ArcToolbox. You can here create a cross tabulation based on two data layers. Let’s say that you would like to know how much there is of each landcover type in the watersheds within a study area. You must input the two data layers (watersheds and landcover) in this case, but you must also tell the tool what field in the attribute table that you want to tabulate.

NR406: GIS Applications in Fire Ecology and Management

Output from Tabulate Area Output from Tabulate Area

1001 45

W atershed 4

920 100 300

W atershed 3

5 123

W atershed 2

893 543 200

W atershed 1

Agriculture Grassland Forest

Notes:

The output table describes how much area there is of each land cover type in each watershed. The results are in square meter (the numbers above are just an example – these watersheds would be extremely small!) After completion of Exercise 2 you will master all types of

  • verlay analysis in ArcMap and ArcToolbox!