remote sensing theory & background iii geog370 instructor: yang shao
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Remote Sensing Theory & Background IIIGEOG370Instructor: Yang Shao
Vegetation InformationNormalized Difference Vegetation Index
dNIR
dNIR
RRRRNDVI
Re
Re
NDVI: [-1.0, 1.0]
Often, the more the leaves of vegetation present, the bigger theContrast in reflectance in the red and near-infrared spectra.
2. Feature space and image classification Imagine you have available image data from a multi-spectral scanner that has two narrow spectral bands. One is centered on 0.65 and the other on 1.0 wavelength. Suppose the corresponding region on the earth’s surface consists of water, vegetation and soil.
Construct a graph with two axes, one representing the brightness of a pixel in the 0.65 band and the other representing the brightness of the pixel in the 1.0 band. In this show where you would expect to find vegetation pixels, soil pixels and water pixels.
An Example
“Sorting incoming Fish on a conveyor according to species using optical sensing”
Sea bassSpecies
Salmon
Problem Analysis
Set up a camera and take some sample images to extract features
• Length• Lightness• Width• Number and shape of fins• Position of the mouth, etc…
Classification
Select the length of the fish as a possible feature for discrimination
The length is a poor feature alone!
Select the lightness as a possible feature.
Image classification
“Labeling image pixels according to land use/cover classes using spectral signals”
vegetationLand use/cover classes urban water soil
1 1 1 1 1 1 1 11 1 1 1 1 1 1 11 1 2 2 2 2 2 21 1 2 2 2 2 2 21 1 1 2 2 1 1 11 1 1 1 1 1 1 11 1 1 1 1 1 1 11 1 1 1 1 1 1 1
Forest: 1Non-forest: 2
1 1 1 1 1 1 1 11 1 1 1 1 1 1 11 1 2 2 2 2 2 21 1 2 2 2 2 2 21 1 1 2 2 1 1 11 1 1 1 1 1 1 11 1 1 1 1 1 1 11 1 1 1 1 1 1 1
1 1 1 1 1 1 1 11 1 1 1 1 1 1 12 2 2 2 2 2 2 22 2 2 2 2 2 2 22 2 2 2 2 1 1 12 2 2 2 1 1 1 11 1 1 1 1 1 1 11 1 1 1 1 1 1 1
Forest: 1Non-forest: 2
1990 image 2000 image
1. The rate of land use/cover change
2. The pattern of land use/cover change (e.g., large/small patch, along road/stream)
3. What are the drivers of land use/cover change?
4. What are the environmental, social, economic, and human health consequences of current and potential land-use and land-cover change
Fragmentation Statistics
Landscape CompositionProportional Abundance of each Class
Landscape ConfigurationPatch size distribution and densityPatch shape complexityIsolation/Proximity
See Fragstats website: http://www.umass.edu/landeco/research/fragstats/fragstats.html
Remote sensing applications Deforestation
Urban growth mapping
Coastal wetlands vegetation
Geology (mineral identification)
Precision Agriculture
Sea surface temperature
Identify invasive species
Wrapping up: You should know
What is remote sensing?How it works?Remote sensing data characteristicsNDVIHow image classification worksSome applications (e.g., biodiversity and conservation)
Remote sensing for biodiversity
1. Two approaches - direct and indirect approaches 2. Challenges - spatial/spectral resolution - data analysis
Elementary Spatial Analysis
OverviewSpatial Analysis
Flowcharting
Query
Defining spatial characteristics
Spatial Analysis
Spatial analysis: Way in which we turn raw data into useful information
A set of techniques whose results are dependent on the locations of the objects being analyzed
Variety of methods
Powerful computers
Intelligent users
Preparing a Spatial Analysis: Flowcharting
Flowchart tools provided by: ESRI’s Model Builder, ERDAS’s GIS Modeler, etc.)
Objective – systematizing thinking and documenting procedures about a GIS application/project
Input OutputOperation
(Plus conditions)
General form of most GIS flowcharts:
From Fundamentals of Geographic Information Systems, Demers (2005)
GIS Data Query
ImportantWhy?
Narrowing down informationBetter understanding of map
What might you want to know?Which features occur most oftenHow often they occurWhere are they located?
Vector dataSelect by attributesSelect by location
Raster dataRaster calculator
GIS Data Query: Vector and rater data
GIS Data QueryWhat is it?
Using tools to find records meeting specific criteriaHow?
Select criteriaUse operators to
define expression• Simple • Complex
And: Intersection of setsEx.: ([area] > 1500) and ( [b_room] > 3)
Or: Union of setsEx: ([age] < 18 or [age] > 65)
Not: Subtracts one set from another setEx.: ([sub_region] = "N Eng") and ( not ( [state_name] = "Maine"))
Raster calculator
Examining vector entities’ attributes
Check spatial objects’ properties•Using identify tool•Using find tool •Performing queries
GIS Data Query: Vector
GIS Data Query: Raster
Examining raster attributes
Unique colors assigned to attribute values
Tabulating results # of grid cells in each category• For those interested in landscape ecology
fragmentation statistics