play_arrowdatasetViewer.description
Knowing and quantifying forest resources (forests and natural vegetation) was one of the priority tasks of Chilean forestry policy in the 90s, given the importance that society assigns to forests and natural vegetation, not only in terms of timber production, but also in all the environmental services they offer, including water production, soil protection, carbon sequestration, wildlife habitat and recreation.
Along these lines, this collection contains the cadastre of land use and vegetation at the regional level in Chile. It includes land use, altitude range, cover and species.
Data is current as of July 2021.
play_arrowdatasetViewer.preview
datasetViewer.previewCollectionInfo
| Nombre de Región | Código |
|---|
| Magallanes y la Antártica Chilena | 12REG_2005_WGS18SUR |
| Tarapacá | Catastro_RV_R01_2016 |
| Antofagasta | Catastro_RV_R02_1997 |
| Atacama | Catastro_RV_R03_1997 |
| Coquimbo | Catastro_RV_R04_2014 |
| ··· | ··· |
| Aysén | Catastro_RV_R11_2011 |
| Metropolitana | Catastro_RV_R13_2013 |
| Arica y Parinacota | Catastro_RV_R15_2015 |
| Los Lagos | CBN_10REG_2013 |
| Los Ríos | CBN_XIV_2013 |
play_arrowdatasetViewer.download
datasetViewer.download1 datasetViewer.here. datasetViewer.download3
play_arrowdatasetViewer.programaticAccess
datasetViewer.programaticAccess1 itrend-ds:CA917686FAA0724
datasetViewer.programaticAccess2 Código
datasetViewer.programaticAccess3 datasetViewer.programaticAccess4 datasetViewer.programaticAccess5 datasetViewer.here
```python
import pytrend
import pandas as pd
session = pytrend.itrend_developer_tools()
session.set_credentials(
access_key_id = '', # Type your access_key_id
secret_access_key = '' # Type your secret_access_key
)
# Dataset
dataset_id = 'itrend-ds:CA917686FAA0724'
collection_id = 'Código'
# Get available formats
dataset_formats = session.get_dataset_formats(dataset_id)
fmt = dataset_formats[0] # Choose your preferred format: dataset_formats = [csv]
# Download file
response = session.download_file(dataset_id, fmt)
# Download an element
filename = response.get('filename')
delimiter = response.get('delimiter')
df = pd.read_csv(filename, delimiter)
element_formats = session.get_element_formats(dataset_id)
efmt = element_formats[0] # Choose your preferred format: element_formats = [shp, geojson]
for r, row in df.iterrows():
element_id = row[collection_id]
element_response = session.download_file(dataset_id, efmt, element_id)
break
```
play_arrowdatasetViewer.attribution
datasetViewer.attributionMessage1
datasetViewer.attribution1 National Forestry Corporation, «Use of soil and vegetation». datasetViewer.attribution2
file_copy
datasetViewer.attributionMessage2
datasetViewer.attribution3 National Forestry Corporation («Use of soil and vegetation»), datasetViewer.attribution4
file_copy
play_arrowdatasetViewer.permanentLink
datasetViewer.permanentLinkDescription
https://www.plataformadedatos.cl/datasets/en/CA917686FAA0724
file_copy
play_arrowdatasetViewer.metadata
datasetViewer.noMetadata
