Recent Releases of multilc_areaestimation_uq
multilc_areaestimation_uq - MultiLC_AreaEstimation_UQ - v1.0.1
This release provides a tool for conducting accuracy assessments, area estimations, and uncertainty quantifications for multi-class land cover maps. The included graphical user interface (GUI) facilitates data input, displays results, and allows users to save results for further analysis. This tool follows the methods and best practices for accuracy assessment and area estimation as outlined in:
- Olofsson et al. (2013): Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote Sensing of Environment, 129, 122-131. https://doi.org/10.1016/j.rse.2012.10.031
- Olofsson et al. (2014): Good practices for estimating area and assessing accuracy of land change. Remote Sensing of Environment, 148, 42-57. https://doi.org/10.1016/j.rse.2014.02.015
Key Features - Interactive GUI: Easily input pixel size, error matrix values, and mapped pixel counts with tooltips for guidance. - Accuracy Metrics: Calculates user’s accuracy, producer’s accuracy, and overall accuracy for each land cover class. - Area Estimation: Provides error-adjusted area estimates per class. - Uncertainty Quantification: Computes standard errors and 95% confidence intervals for each metric. - CSV Export: Option to save results to a CSV file for further analysis.
For detailed instructions, please refer to the README file in the repository.
- Python
Published by ccgeoinformatics over 1 year ago
multilc_areaestimation_uq - MultiLC_AreaEstimation_UQ - v1.0.0
This release provides a tool for conducting accuracy assessments, area estimations, and uncertainty quantifications for multi-class land cover maps. The included graphical user interface (GUI) facilitates data input, displays results, and allows users to save results for further analysis. This tool follows the methods and best practices for accuracy assessment and area estimation as outlined in:
- Olofsson et al. (2013): Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote Sensing of Environment, 129, 122-131. https://doi.org/10.1016/j.rse.2012.10.031
- Olofsson et al. (2014): Good practices for estimating area and assessing accuracy of land change. Remote Sensing of Environment, 148, 42-57. https://doi.org/10.1016/j.rse.2014.02.015
Key Features - Interactive GUI: Easily input pixel size, error matrix values, and mapped pixel counts with tooltips for guidance. - Accuracy Metrics: Calculates user’s accuracy, producer’s accuracy, and overall accuracy for each land cover class. - Area Estimation: Provides error-adjusted area estimates per class. - Uncertainty Quantification: Computes standard errors and 95% confidence intervals for each metric. - CSV Export: Option to save results to a CSV file for further analysis.
For detailed instructions, please refer to the README file in the repository.
- Python
Published by ccgeoinformatics over 1 year ago