지도 정보를 활용하기 위한 데이타 구하기

진행하고 있던 프로젝트에서 지도 정보가 필요하여 찾아봤던 자료들 입니다.

 

무료로 좌표계를 받을수 있는 곳을 찾기가 힘들어 고생했던 기억이 있어서 그당시 찾아봤던 site들을 정리해봤습니다.

 

 

결국 위도 경도 정보를 data로 구해야 해서 저는 python panda로 data를 구했었습니다.

 

 

 

https://www.esrikr.com/arcgis-guide/arcgis-pro-master-2/

 

[ArcGIS Pro 완전 정복!] ②기본 | 한국에스리

 

 

 

 

지도 정보 찾기

 

 

 

https://earthdata.nasa.gov/

Earthdata

 

Global Map data archives

 

https://globalmaps.github.io/

Global Map data archives

 

https://globalmaps.github.io/glcnmo.html#code

Land Cover (GLCNMO) - Global version - Global Map

 

 

http://www.diva-gis.org/datadown

Spatial Data Download | DIVA-GIS

 

 

https://datascienceschool.net/view-notebook/ef921dc25e01437b9b5c532ba3b89b02/

Data Science School

pandas

 

 

import geopandas as gpd
import matplotlib.pyplot as plt
import matplotlib.path as mpath
import matplotlib.patches as mpatches

gpd.__version__


def get_pos(PosData) : 
    return PosData[0],PosData[1]


print(gpd.__version__)

countries = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
cities = gpd.read_file(gpd.datasets.get_path('naturalearth_cities'))

#countries.tail(3)

print(countries.name)


china = countries[countries.name == "China"].geometry



china.boundary.squeeze()

china.plot()


rect = china.total_bounds

fig = plt.figure()
ax =fig.add_axes(rect,)

fig.delaxes(ax)
fig.add_axes(ax)


# sub plot

# ax = plt.subplots()   

# pos = [[china.total_bounds[0],china.total_bounds[1]],
#         [china.total_bounds[2],china.total_bounds[1]],
#         [china.total_bounds[2],china.total_bounds[3]],
#         [china.total_bounds[0],china.total_bounds[3]]]
# Path = mpath.Path
# path_data = [
#     (Path.MOVETO, (pos[0])),
#     (Path.LINETO, (pos[1])),
#     (Path.LINETO, (pos[2])),
#     (Path.LINETO, (pos[3])),
#      (Path.CLOSEPOLY, (pos[0])),
#      ] 
# ax.plot(path_data)        
# #    
# codes, verts = zip(*path_data)
# path = mpath.Path(verts, codes)
# patch = mpatches.PathPatch(path, facecolor='r', alpha=0.5)

#  ax.add_patch(patch)

# x, y = zip(*path.vertices)
# line, = ax.plot(x, y, 'go-')
# ax.grid()
# ax.axis('equal')

plt.figimage(fig)
plt.show()


#china.

with open("china_map.txt", mode='wt') as f:
    f.write(china)

print(china)
#ax.set_title("세계 지도")
#ax.set_axis_off()


#print(countries)
i=0
while 1 :
    i+=i

 

 

결과 

result: 

"{\"type\": \"FeatureCollection\", \"features\": [{\"id\": \"139\", \"type\": \"Feature\", \"properties\": {}, \"geometry\": {\"type\": \"MultiPolygon\", \"coordinates\": [[[[109.47520958866365, 18.197700913968575], [108.65520796105616, 18.507681993071387], [108.62621748254044, 19.367887885001906], [109.11905561730804, 19.821038519769345], [110.21159874882281, 20.101253973872033], [110.78655073450221, 20.077534491450052], [111.01005130416458, 19.69592987719072], [110.57064660038677, 19.25587921800927], [110.33918786015147, 18.678395087147592], [109.47520958866365, 18.197700913968575]]], [[[80.2599902688853, 42.34999929459906], [80.1801501809943, 42.92006785742694], [80.86620649610126, 43.18036204688101], [79.96610639844141, 44.91751699480463], [81.9470707539181, 45.31702749285312], [82.45892581576906, 45.539649563166506], [83.18048383986047, 47.33003123635086], [85.16429039911324, 47.0009557155161], [85.72048383987067, 47.452969468773105], [85.7682328633083, 48.45575063739699], [86.59877648310336, 48.549181626980626], [87.35997033076265, 49.21498078062912], [87.75126427607671, 49.297197984405486], [88.01383222855173, 48.599462795600616], [88.85429772334676, 48.069081732772965], [90.28082563676392, 47.69354909930793], ...