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Geospatial Information Technology
Remotely Sensed Data
Instantaneous Field of View (IFOV) at Nadir (Resolution on the Ground)
IKONOS ORBIMAGE (GeoEye)
QuickBird The SPOT (System Probatori D’Observation de la Terre)
MODIS (Moderate Resolution Imaging Spectroradiometer)
ASTER (Advanced Spaceborne Thermal Emission and Reflection radiometer)
Active Remotely Sensed Data
Radar Lidar
Derived Remotely Sensed Data
Vegetation Indices The Tasseled Cap Transformation
Geographic Information Systems (GIS)
Thematic Data Layers
Geospatial Data Conversion
Using ERDAS-IMAGINE Software Using ARCINFO Software Select Area of Interest (Study Site)
Topographic Data
Global Positioning System (GPS)
GPS Services The GPS Satellite System and Fact GPS Applications
References
Data Sampling Methods and Applications
Data Representation Data Collection and Source of Errors
Data Types
Sampling Methods and Applications Sampling Designs
Simple Random Sampling Stratified Random Sampling Systematic Sampling Nonaligned Systematic Sample Cluster Sampling Multiphase (Double) Sampling
Double Sampling and Mapping Accuracy
Pixel Nested Plot (PNP): Case Study
Plot Design
Issues Characteristics of Different Plot Shapes Plot Size
References
Spatial Pattern and Correlation Statistics
Scale Spatial Sampling
Errors in Spatial Analysis Spatial Variability and Method of Prediction
Spatial Pattern
Spatial Point Pattern
Linear Correlation Statistic
Case Study Statistical Example
Spatial Correlation Statistics
Moran’s I and Geary’s C Cross-Correlation Statistic Inverse Distance Weighting (IDW)
Statistical Example
References
Geospatial Analysis and Modeling–Mapping
Stepwise Regression
Statistical Example
Ordinary Least Squares (OLS)
Variogram and Kriging
Ordinary Kriging Simple Kriging Universal Kriging Developing Variogram Model and Kriging to Predict Plant Diversity at GSENM, Utah
Spatial Autoregressive (SAR)
Statistical Example
Binary Classification Tree (BCTs)
Cokriging Geospatial Models for Presence and Absence Data
GARP Model Maxent Model Logistic Regression Classification and Regression Tree (CART)
Envelope Model
References
R Statistical Package
Overview of R Statistics (R)
What Is R?
Strengths of R/S The R Environment Scripts Working with R on Your COMPUTER Begin to Use R
Statistical Analysis Examples Using R
Common Statistics Common Graphics Common Programming Create and Examine a Logical Vector Working on Graphical Display of Data (Data distributions)
Develop a Histogram Data Comparison between the Data and an Expected Normal Distribution More Statistical Analysis Reading New Variable (Enter new data set, WEIGHT)
Plotting Weight and Height Test of Association Some Basic Regression Analysis
Case Study
Test for Spatial Autocorrelation Using Moran’s I Test for Spatial Autocorrelation Using Geary’s C Test for Spatial Cross-Correlation Using Bi-Moran’s I
Trend Surface Analysis
Test for Spatial Autocorrelation of the Residuals Test for Moran’s I for Residuals Using Spatial AR Model without Regression Using Spatial AR with Regression (Using All Independent Variables as with OLS Model)
Analysis of Residuals Develop Variogram Model (Modeling Fine Scale Variability)
Plotting Variogram Model
References
Working with Geospatial Information Data
Exercise 1: Working with Remotely Sensed Data Exercise 2: Derived Remote Sensing Data and Digital Elevation Model (DEM)
Deriving Slope and Aspect from DEM Data Resample GRID
Exercise 3: Geospatial Information Data Extraction
Deriving SLOPE and ASPECT from DEM Data (ELEVATION)
Resample GRID Select Area of Interest (Study Site)
Data Extraction Steps for Converting the Geospatial Model to a Thematic Map Product Working with Vegetation Indices and Tasseled Cap Transformation Develop Thematic Layer in ARCVIEW or ARCMAP Map Layout
References
Index
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