Spatial Process VS. Non-spatial Process. Landscape Process

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1 Spatial Process VS. Non-spatial Process A process is non-spatial if it is NOT a function of spatial pattern = A process is spatial if it is a function of spatial pattern Landscape Process If there is no spatial process, then landscape pattern does not matter. Otherwise, landscape pattern analysis is necessary Causes of landscape pattern Consequences of landscape pattern Quantify landscape pattern 1

2 Caveats for Landscape Pattern Analysis Do not fall into a trap of generating a lot of numbers than we can understand Must have a clear idea of purpose and limitations of landscape data and metrics that quantify landscape pattern Quantifying Landscape Patterns by Remote Sensing: Pixels vs. Patches 2

3 Concepts of Digital Image With raster data structure, each image is treated as an array of values of the pixels. Image data is organized as rows and columns (or lines and pixels). Each pixel is treated as a separate unite. 3

4 Defining a Patch Digitizing: Using remote sensing data, one can delineate polygon boundaries (patches) visually. Remote Sensing Image Vector GIS Coverage Defining a Patch Aggregation: Using remote sensing data and GIS grid data one can combine all adjacent pixels/cells that have the same (or similar) value into one patch 4

5 Quantifying Landscape Patterns by Remote Sensing: Pixels vs. Patches Traditionally, creating land cover or vegetation maps from aerial photography has relied on human interpreters inherent ability to group together areas of similar characteristics. Digital remote sensing imagery divides the sensed area into arbitrary small squares, i.e. Pixels. Information about each pixel is recorded and analyzed as an individual unit. Patch Characteristics AREA/SIZE - sensitive to the unit of measurement PERIMETER - actual length also dependent upon the unit of measurement SHAPE COMPLEXITY - many methods available for measurement 5

6 Finer spatial resolution remote sensing data can be in meter or submeter levels. On one hand people need high spatial resolution to identify spatial details to illustrate the landscape. On the other hand, increase spatial resolution separates the space into finer sized pixels. 10/10/1997 Landsat TM Data 10/10/1997 Digital Multispectral Videography Data 2-meter spatial resolution 6

7 Ecological Scaling: Definitions Grain = minimum resolution of the data, defined by the cell size (for raster data) or minimum polygon size (vector data). Extent = the scope or domain of the data, defined as the size of the landscape or the duration of time under consideration. Ecological Scaling: Definitions Grain in Vector Data Grain = minimum resolution of the data, i.e., minimum mapping unit. 7

8 Data Format and Grain Size (for example) Data Format Grain Vector Data Edge = 1000 Edge = 100 Raster Data Coarsegrained Finegrained Edge = 1500 Edge = meter Spatial Resolution 2-meter spatial resolution 8

9 High spatial resolution data are not representative averages of land cover or vegetation types, which presents challenges to the user communities. Appropriate measures must be taken to avoid problems of using pixel data in landscape characterization. 2-meter spatial resolution 9

10 An Example of Savanna Ecosystem in mid-west USA: Savanna: A grassland with scattered trees. Trees are characteristically oaks, well spaced in clusters, 10%-50% canopy cover (Packard and Mutel, 1998). Landscape Reality: Savanna 30-m Spatial Resolution Data: Savanna/Prairie? 2-meter Spatial Resolution Data: Forest/Woodland/Savanna/Prairie? 10

11 Traditional photo interpretation is a grouping or lumping process Digital image processing is a splitting process 11

12 Pixels and subpixels: A perspective from different spatial resolutions GIS Aggregation Rule For Example: The Majority Rule 12

13 2-meter Spatial Resolution After 5x5 Spatial Filtering 30-meter Spatial Resolution After 5x5 Spatial Filtering 13

14 Scale Issues: 1. Understanding the impact of scale 2. Determining appropriate scale 3. Scaling up/down Impact of Changing Scale 1. Effects of changing scale on landscape patterns 2. Effects of spatial resolution on landscape measurements 14

15 Effects of thematic resolution on landscape pattern analysis (USGS Level II) Effects of thematic resolution on landscape pattern analysis (USGS Level I) 15

16 Effects of thematic resolution on landscape pattern analysis Thematic resolution of mapped data determines the amount of detail of geospatial information, and influences various aspects of landscape classification and the relevance of derived pattern attributes to particular ecological questions. Changing thematic resolution may significantly affect landscape metrics and in turn their ability to detect landscape changes. The effects of thematic resolution must be considered in landscape pattern analysis. Modifiable Aerial Unit Problem (MAUP) 1. MAUP represents the sensitivity of analytical results to the definition of data collection units. The selection of spatial units for analysis is often arbitrary and they may not correspond to meaningful entities of interest. 2. MAUP may affect the results of landscape analysis. 16

17 Determination of Optical Scales Ecological processes possess an inherent scale at which they occur over the landscape (Carlile et al., 1989) Scaling Up / Down Scaling is transferring data from one spatial scale to another. It requires an understanding of the organization of the landscape where different patterns and processes are linked to specific scales of observation and finding appropriate transition rules across scales. 17

18 Data preparation is important toward a meaningful landscape quantification 18