Metadata-Version: 2.1
Name: cartolidar
Version: 0.0.dev1
Summary: Lidar processing focused on Spanish PNOA datasets (https://pnoa.ign.es/el-proyecto-pnoa-lidar)
Home-page: https://github.com/cartolid/cartolidar
Author: Jose Bengoa
Author-email: cartolidar@gmail.com
License: GNU GPLv3
Project-URL: Source, https://github.com/cartolid/cartolidar/issues
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: End Users/Desktop
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: Spanish
Classifier: Natural Language :: English
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: GIS
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE

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CartoLidar
----------

Python tools for Lidar processing focused on Spanish PNOA Lidar datasets (https://pnoa.ign.es/el-proyecto-pnoa-lidar)

Herramientas python para procesado de datos Lidar del PNOA (https://pnoa.ign.es/el-proyecto-pnoa-lidar)

Introduction
------------

CartoLidar es una coleción de herramientas destinadas a procesar ficheros
lidar (las y laz) y generar a partir de los rasters obtenidos otros productos
de utilidad en selvicultura y otras area de gestión del medio natural.

El proyecto está en fase alpha e incluye únicamente la herramienta "clidtwins".

clidtwins está destinada a buscar zonas similares a una(s) de referencia en
términos de determinadas variables dasoLidar (DLVs).

DLV: variable Lidar que describe algún aspecto de la estructura de una
     formación arbolada, arbustiva o de matorral.
-------------------------------------------------------------------------------

CartoLidar is a collection of tools to process lidar files "las" and "laz" and
generate other products aimed to forestry and natural environment management.

This project is in alpha version and includes only the "clidtwins" tool.

"clidtwins" searchs for similar areas to a reference one in terms of dasoLidar Variables (DLVs)
DLV: Lidar variables that describe or characterize forest structure (or vegetation in general).


Consultar documentación en: [cartolidar.org](http://cartolidar.org)
Documentation available at [cartolidar.org](http://cartolidar.org)
[Read the Docs](http://cartolidar.readthedocs.io/en/latest/)


Install
--------

1. Instalation of official version from [pypi - cartolidar](https://pypi.org/project/cartolidar/):
```
$ pip install cartolidar
```

2. Download of development version from [github - cartolidar](https://github.com/cartolid/cartolidar)

This version can be instaled in lib/site-packages (ie, using cmd in Windows):
```
$ cd path_to_project
$ pip install .
```

or the olther way (not recommendable):
```
$ cd path_to_project
$ python setup.py install
```

where:
  path_to_project is the path that contains setup.py


Requeriments
------------
cartolidar requires Python 3.7 or higher. See requirements.txt.


Use
--------
## Uso de cartolidar
### Uso en linea de comandos

1. Ejecutar el paquete cartolidar:
```
$ python -m cartolidar [ options ]
```
Se inicia un menu con modulos que usan las herramientas de cartolidar, como qlidtwins.py)

&nbsp;&nbsp;&nbsp;&nbsp;options:

...


2. Importar desde un script (.py) o desde el interprete interactivo; hay varias opciones:
```
import cartolidar
from cartolidar import clidtools
from cartolidar.clidtools import clidtwins
from cartolidar.clidtools.clidtwins import DasoLidarSource
```


to be continued...



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