README.md
In niknap/slidaRtools: Tools for lidar simulation and lidar processing
slidaRtools
Tools for lidar simulation and lidar processing
Introduction
The slidaRtools package provides a couple of useful functions to simulate and process lidar data of forests.
Lidar simulation means to create discrete lidar point clouds or large footprint waveforms for a given tree list
using their positions, crown properties and a Beer-Lambert light extinction approach. Lidar data processing means
operations like point cloud thinning, conversions between XYZ-tables, rasters, matrices and arrays, spatial indexing,
vertical profile delineation, etc.
Demo
A demo script can be found inside the folder DemoWorkflow, along with a small example dataset.
References
- Knapp, N., Fischer, R., Huth, A., 2018a. Linking lidar and forest modeling to assess biomass estimation across scales and disturbance states. Remote Sens. Environ. 205, 199–209. https://doi.org/10.1016/j.rse.2017.11.018
- Knapp, N., Huth, A., Kugler, F., Papathanassiou, K., Condit, R., Hubbell, S.P., Fischer, R., 2018b. Model-assisted estimation of tropical forest biomass change: A comparison of approaches. Remote Sens. 10, 1–23. https://doi.org/10.3390/rs10050731
- Rödig, E., Knapp, N., Fischer, R., Bohn, F.J., Dubayah, R., Tang, H., Huth, A., 2019. From small-scale forest structure to Amazon-wide carbon estimates. Nat. Commun. 10, 1–7. https://doi.org/10.1038/s41467-019-13063-y
- Fischer, R., Knapp, N., Bohn, F., Shugart, H.H., Huth, A., 2019. The Relevance of Forest Structure for Biomass and Productivity in Temperate Forests: New Perspectives for Remote Sensing. Surv. Geophys. https://doi.org/10.1007/s10712-019-09519-x
- Knapp, N., Huth, A., Fischer, R., 2021. Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing. Remote Sens. 13, 1592. https://doi.org/10.3390/rs13081592
- Bauer, L., Knapp, N., Fischer, R., 2021. Mapping Amazon forest productivity by fusing GEDI lidar waveforms with an individual-based forest model. Remote Sens. 13. https://doi.org/10.3390/rs13224540
- Bruening, J.M., Fischer, R., Bohn, F.J., Armston, J., Armstrong, A.H., Knapp, N., Tang, H., Huth, A., Dubayah, R., 2021. Challenges to aboveground biomass prediction from waveform lidar. Environ. Res. Lett. 16, 125013. https://doi.org/10.1088/1748-9326/ac3cec
niknap/slidaRtools documentation built on Oct. 16, 2024, 3:53 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
slidaRtools
Tools for lidar simulation and lidar processing
Introduction
The slidaRtools package provides a couple of useful functions to simulate and process lidar data of forests. Lidar simulation means to create discrete lidar point clouds or large footprint waveforms for a given tree list using their positions, crown properties and a Beer-Lambert light extinction approach. Lidar data processing means operations like point cloud thinning, conversions between XYZ-tables, rasters, matrices and arrays, spatial indexing, vertical profile delineation, etc.
Demo
A demo script can be found inside the folder DemoWorkflow, along with a small example dataset.
References
- Knapp, N., Fischer, R., Huth, A., 2018a. Linking lidar and forest modeling to assess biomass estimation across scales and disturbance states. Remote Sens. Environ. 205, 199–209. https://doi.org/10.1016/j.rse.2017.11.018
- Knapp, N., Huth, A., Kugler, F., Papathanassiou, K., Condit, R., Hubbell, S.P., Fischer, R., 2018b. Model-assisted estimation of tropical forest biomass change: A comparison of approaches. Remote Sens. 10, 1–23. https://doi.org/10.3390/rs10050731
- Rödig, E., Knapp, N., Fischer, R., Bohn, F.J., Dubayah, R., Tang, H., Huth, A., 2019. From small-scale forest structure to Amazon-wide carbon estimates. Nat. Commun. 10, 1–7. https://doi.org/10.1038/s41467-019-13063-y
- Fischer, R., Knapp, N., Bohn, F., Shugart, H.H., Huth, A., 2019. The Relevance of Forest Structure for Biomass and Productivity in Temperate Forests: New Perspectives for Remote Sensing. Surv. Geophys. https://doi.org/10.1007/s10712-019-09519-x
- Knapp, N., Huth, A., Fischer, R., 2021. Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing. Remote Sens. 13, 1592. https://doi.org/10.3390/rs13081592
- Bauer, L., Knapp, N., Fischer, R., 2021. Mapping Amazon forest productivity by fusing GEDI lidar waveforms with an individual-based forest model. Remote Sens. 13. https://doi.org/10.3390/rs13224540
- Bruening, J.M., Fischer, R., Bohn, F.J., Armston, J., Armstrong, A.H., Knapp, N., Tang, H., Huth, A., Dubayah, R., 2021. Challenges to aboveground biomass prediction from waveform lidar. Environ. Res. Lett. 16, 125013. https://doi.org/10.1088/1748-9326/ac3cec
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.