/planttech

Primary LanguageJupyter Notebook

Outline

The following include the process to extract the Leaf Inclination Angle (LIA) with respect to zenith, the Leaf Area Index (LAI), and the Leaf Area Density (LAD) of a point cloud (PC). We test our pipeline using a mockup point cloud generated in Blensor software. This process is outlined below:

  • LiDAR simulation on mockup trees with BLENSOR

    • Toy tree and sensor specifications
    • Data structure
    • Leaf Inclination Angle (LIA) estimation
    • Leaf Area Density (LAD) estimation

  • Aplication on Kiwkifruit LiDAR dataset

Instalation

When creating the list of requirements use:

conda env export -n <env-name> --no-builds> requirements.yml

and to create the environment use:

conda env create -f path/to/environment.yml

Remember to change the last line if needed with the correct path of your anaconda/miniconda distro:

prefix: /Users/tardis/opt/anaconda3/envs/plant-env

If getting the issue ResolvePackageNotFound just move these packages under 'pip'. Install laspy with

$ conda install -c conda-forge laspy

If getting issue No LazBackend selected, cannot decompress data simply install:

$ pip install laszip

create kernel for env

Before login to our new conda env plant-env, we download the ipykernel repo,

pip install ipykernel

then, we create a kernel with based on the plant-env env,

python -m ipykernel install --user --name=plant-env

Finally, we make sure it was created with:

jupyter kernelspec list