INPE¶

In [16]:

import io

import geopandas as gpd
from owslib.wfs import WebFeatureService

import io import geopandas as gpd from owslib.wfs import WebFeatureService

In [ ]:

wfs = WebFeatureService(
    #
    url='https://terrabrasilis.dpi.inpe.br/geoserver/ows',
    version='2.0.0',
)

wfs = WebFeatureService( # url='https://terrabrasilis.dpi.inpe.br/geoserver/ows', version='2.0.0', )

---

Listas Layers¶

In [18]:

list_layers = list(wfs.contents)
list_layers.sort()

print(f"Existem {len(list_layers)} camadas disponíveis no serviço WFS.")

# Display the first 10 layers
list_layers[0:10]

list_layers = list(wfs.contents) list_layers.sort() print(f"Existem {len(list_layers)} camadas disponíveis no serviço WFS.") # Display the first 10 layers list_layers[0:10]

Existem 214 camadas disponíveis no serviço WFS.

Out[18]:

['ams1:active-fire',
 'ams1:biome_border',
 'ams1:cs_150km_diff_view',
 'ams1:cs_150km_view',
 'ams1:cs_25km_diff_view',
 'ams1:cs_25km_view',
 'ams1:cs_5km_diff_view',
 'ams1:cs_5km_view',
 'ams1:deter-ams',
 'ams1:last_date']

In [19]:

set([layer.split(':')[0] for layer in list_layers])

set([layer.split(':')[0] for layer in list_layers])

Out[19]:

{'ams1',
 'ams1_auth',
 'ams1h',
 'ams1h_auth',
 'ams2',
 'ams2_auth',
 'deter-amz',
 'deter-cerrado-nb',
 'prodes-amazon-nb',
 'prodes-brasil-nb',
 'prodes-caatinga-nb',
 'prodes-cerrado-nb',
 'prodes-legal-amz',
 'prodes-mata-atlantica-nb',
 'prodes-pampa-nb',
 'prodes-pantanal-nb',
 'tcc-samples',
 'vegetation-cerrado'}

---

Obter Layers¶

In [20]:

# Obter os dados no formato GeoJSON (ou outro formato suportado)
response = wfs.getfeature(
    typename='tcc-samples:depressao_carstica_do_sao_francisco',
    # bbox=(173700, 440400, 178700, 441400),
    # srsname='EPSG:28992'
    # srsname='EPSG:4326',
    srsname='EPSG:4674',
    outputFormat='application/json',
)
response

# Obter os dados no formato GeoJSON (ou outro formato suportado) response = wfs.getfeature( typename='tcc-samples:depressao_carstica_do_sao_francisco', # bbox=(173700, 440400, 178700, 441400), # srsname='EPSG:28992' # srsname='EPSG:4326', srsname='EPSG:4674', outputFormat='application/json', ) response

Out[20]:

<_io.BytesIO at 0x246b9e0fb50>

---

Geopandas¶

In [21]:

gdf = gpd.read_file(filename=io.BytesIO(response.read()))
gdf.info()
gdf.head()

gdf = gpd.read_file(filename=io.BytesIO(response.read())) gdf.info() gdf.head()

<class 'geopandas.geodataframe.GeoDataFrame'>
RangeIndex: 1 entries, 0 to 0
Data columns (total 3 columns):
 #   Column    Non-Null Count  Dtype   
---  ------    --------------  -----   
 0   id        1 non-null      object  
 1   name      1 non-null      object  
 2   geometry  1 non-null      geometry
dtypes: geometry(1), object(2)
memory usage: 156.0+ bytes

Out[21]:

	id	name	geometry
0	depressao_carstica_do_sao_francisco.11	Depressão Cárstica do São Francisco	MULTIPOLYGON (((-43.8257 -16.383, -43.8249 -16...

In [22]:

gdf.crs

gdf.crs

Out[22]:

<Geographic 2D CRS: EPSG:4674>
Name: SIRGAS 2000
Axis Info [ellipsoidal]:
- Lat[north]: Geodetic latitude (degree)
- Lon[east]: Geodetic longitude (degree)
Area of Use:
- name: Latin America - Central America and South America - onshore and offshore. Brazil - onshore and offshore.
- bounds: (-122.19, -59.87, -25.28, 32.72)
Datum: Sistema de Referencia Geocentrico para las AmericaS 2000
- Ellipsoid: GRS 1980
- Prime Meridian: Greenwich

In [23]:

gdf.explore()

gdf.explore()

Out[23]:

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