User:Fehrmann/Books/ChatGPT training
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ChatGPT training
- Remote sensing and image processing with open source software
- SNAP Tutorial
- Brief history of forest inventory
- Data and information
- Forest inventory
- Geographical levels of forest inventories
- Forest Definition
- Tree Definition
- Minimum crown cover
- Forest boundary
- Species composition
- Forest Inventory Glossary
- Biomass functions and carbon estimation
- Height curve
- Linear regression
- Volume functions
- Caliper
- Caliper vs. diameter tape
- Crown mirror - densiometer
- Dendrometer
- Diameter tape
- Finn caliper
- Optical caliper
- Relascope
- Walktax
- Wedge prism
- Bark thickness
- Crown attributes
- Diameter increment
- Distance to tree
- Quality
- Stem shape
- Stem volume
- Tree sociological position
- Measuring slope
- Accuracy and precision
- Bias
- Confidence interval
- Inclusion probability
- Independent random sample
- Population
- Random selection
- Relative efficiency
- Sample size
- Sampling design and plot design
- Sampling intensity vs. sample size
- Standard error
- Statistical estimations
- Statistical sampling
- Approaches to populations of sample plots
- Bitterlich sampling
- Cluster sampling
- Comparison of plot designs
- Distance based plots
- Fixed area plots
- Fixed area plots at the stand boundary
- Intracluster Correlation Coefficient
- Line sampling
- Non-response
- Plot design examples
- Slope correction
- Spatial autocorrelation
- Adaptive cluster sampling
- Cluster sampling examples
- Double sampling
- Double sampling with ratio or regression estimator
- Hansen-Hurwitz estimator
- Horvitz-Thompson estimator
- Importance sampling
- List sampling
- Randomized branch sampling
- Ratio estimator
- Sampling with unequal selection probabilities
- Simple random sampling
- Stratified sampling
- Systematic sampling
- Two stage sampling
- Variance issue in systematic sampling
- Estimating forest area
- Estimating number of species
- Estimating the length of the forest edge
- Estimation on changes
- Planning a forest inventory
- Adaptive cluster sampling examples
- Double sampling examples
- Double sampling with ratio or regression estimator examples
- Hansen-Hurwitz estimator examples
- Horvitz-Thompson estimator example
- Pair difference technique example
- Ratio estimator sampling examples
- Simple random sampling examples
- Stratified sampling examples
- Conference of Parties (COP)
- IPCC
- Kyoto Protocol
- Reducing Emissions from Deforestation and Forest Degradation (REDD)
- UNFCCC
- Canopy Height Model based on Airborne Laserscanning using LAStools
- Change detection
- Cloud masking
- Collecting training data
- Course data
- Defining LUC schemes
- Georeferencing (Tutorial)
- Georeferencing of UAV photos
- Image fusion
- Individual Tree Detection (ITC)
- Land Cover/Use Classification using the Semi-Automatic Classification Plugin for QGIS
- Map validation
- Object-based supervised classification
- Per pixel supervised classification
- Principal component analysis
- Region Growing Segmentation
- Spectral indices
- Unsupervised classification
- Co-registration with SNAP
- Installation of SNAP
- Preprocessing Sentinel-2 with SNAP
- Radiometric calibration with SNAP
- SAR change detection with SNAP
- SAR flood mapping with SNAP
