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Copy pathHyperlink_Panna.py
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Hyperlink_Panna.py
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# ---
# jupyter:
# jupytext:
# formats: ipynb,py:percent
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.14.0
# kernelspec:
# display_name: Python 3 (ipykernel)
# language: python
# name: python3
# ---
# %%
import pandas as pd
import folium
from osgeo import gdal
from folium import plugins,Vega
from folium import raster_layers
#from matplotlib import cm
import numpy as np
import branca.colormap as cm
#import branca
import matplotlib
from matplotlib import colors
import matplotlib.pyplot as plt
from folium.plugins import MarkerCluster,FloatImage, Draw, MeasureControl
# import osmnx as ox
# import geopandas
# import vincent
# from vincent import Bar,AxisProperties, PropertySet, ValueRef
import geopandas as gpd
import os
# import plotly.graph_objects as go
# import branca
# import plotly.io as pio
# from plotly.subplots import make_subplots
from matplotlib import colors
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
# %%
def get_rooted(stem):
return "D:\\Panna\\" + stem
def read_df_UT(stem):
return gpd.read_file(get_rooted(stem)).to_crs(epsg = 4326)
# %% [markdown]
# ## Hyperlink - Panna District
# %% [markdown]
# ### Features
# %%
# %%
_shp_district = read_df_UT("forest\\Panna\\panna_dst.shp")
_shp_district.to_file('_shp_district.json', driver='GeoJSON')
_shp_district = os.path.join('', '_shp_district.json')
roads_prim_sec_ter = gpd.read_file("D:\\Panna\\roads_prim_sec_ter.shp")
def regioncolors(roads_prim_sec_ter):
if roads_prim_sec_ter['highway'] == 'primary':
return '#df2a29'
elif roads_prim_sec_ter['highway'] == 'secondary':
return '#E97C78'
elif roads_prim_sec_ter['highway'] == 'tertiary':
return '#f0b8b3'
roads_prim_sec_ter["color"] = roads_prim_sec_ter.apply(regioncolors, axis=1)
roads_prim_sec_ter.to_file('roads_prim_sec_ter.json', driver='GeoJSON')
roads_prim_sec_ter = os.path.join('', 'roads_prim_sec_ter.json')
substations =gpd.read_file("D:\\Hasten Ventures\\Features\\Substations\\Substations.shp")
substations.to_file('substations.json', driver='GeoJSON')
substations = os.path.join('', 'substations.json')
Forest_reserve =gpd.read_file("D:\Hasten Ventures\Features\Forest_reserve\\Forest_reserve.shp")
Forest_reserve = Forest_reserve.round({"area_hect":0})
Forest_reserve["area_hect"] = Forest_reserve["area_hect"].replace([0],["< 1"])
Forest_reserve.to_file('Forest_reserve.json', driver='GeoJSON')
Forest_reserve = os.path.join('', 'Forest_reserve.json')
outfile = 'D:\\Panna\\workdir\\slope.tif'
#Open raster file
driver=gdal.GetDriverByName('GTiff')
driver.Register()
ds1 = gdal.Open(outfile)
if ds1 is None:
print('Could not open')
band=ds1.GetRasterBand(1)
data= band.ReadAsArray()
#Get coordinates, cols and rows
geotransform = ds1.GetGeoTransform()
cols2 = ds1.RasterXSize
rows2 = ds1.RasterYSize
#Get extent
xmin2=geotransform[0]
ymax2=geotransform[3]
xmax2=xmin2+cols2*geotransform[1]
ymin2=ymax2+rows2*geotransform[5]
#Get Central point
centerx=(xmin2+xmax2)/2
centery=(ymin2+ymax2)/2
a = np.nanmax(data)
b = np.nanmin(data)
print(a,b)
def get_color_slope(x):
if 0<= x <= 45:
return (240,240,240,1)
elif 45 < x <= 90 :
return (195,195,195,1)
elif 90 < x <=135 :
return (150,150,150,1)
elif 135 < x <= 180:
return (104,104,104,0.7)
elif 180 < x <=225 :
return (104,104,104,1)
else:
return (255,0,0,0)
# AVC_grey = LinearSegmentedColormap.from_list('testcmap1', colors=['#686868', '#969696', '#c3c3c3', '#F0F0F0'], N=256)
m= folium.Map(location=[24.436933515, 80.20336914], zoom_start=8)
g2 = folium.plugins.FeatureGroupSubGroup(m, 'Slope',show=False)
g3 = folium.plugins.FeatureGroupSubGroup(m, 'Substations',show=False)
g4 = folium.plugins.FeatureGroupSubGroup(m, 'Roads',show=False)
g5 = folium.plugins.FeatureGroupSubGroup(m, 'Forest reserve',show=False)
m.add_child(g2)
m.add_child(g3)
m.add_child(g4)
m.add_child(g5)
tile = folium.TileLayer(
tiles = 'https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}',
attr = 'Esri',
name = 'Esri Satellite',
overlay = False,
control = True
).add_to(m)
loc = 'District features'
title_html = '''
<h3 align="center" style="font-size:16px"><b>{}</b></h3>
'''.format(loc)
m.get_root().html.add_child(folium.Element(title_html))
cm2 = cm.LinearColormap(['#F0F0F0','#c3c3c3','#969696','#686868'], vmin=0, vmax=225, caption='Elevation in meters')
m.add_child(cm2)
folium.GeoJson(
_shp_district,
name='dist_boundary',
show = True,
control = False,
style_function=lambda feature: {
'fillColor': "none",
'color' : "black",
'weight' : 1,
'fillOpacity' : 0.5,
},
# highlight_function=lambda x: {'weight':5,'color':'yellow'},
# tooltip=folium.features.GeoJsonTooltip(fields=['AREA'],labels=False, toLocaleString=True)
#smooth_factor=2.0
).add_to(m)
g2.add_child(raster_layers.ImageOverlay(
image=data,
show=False,
name = 'Slope',
bounds=[[ymin2, xmin2], [ymax2, xmax2]],
colormap=lambda x: get_color_slope(x),
interactive=True,
mercator_project = True,
opacity=1
))#.add_to(m)
# ###Reference
folium.GeoJson(
substations,
name='Substations',
show = False,
# style_function=lambda feature: {
# 'fillColor': "#FBB034",
# 'color' : "#FBB034",
# 'weight' : 3,
# 'fillOpacity' : 0.5,
# },
highlight_function=lambda x: {'weight':5,'color':'yellow'},
tooltip=folium.features.GeoJsonTooltip(fields=['name'],aliases=["Name:"],labels=True, toLocaleString=True)
#smooth_factor=2.0
).add_to(g3)
folium.GeoJson(
roads_prim_sec_ter,
name='Roads',
show = False,
style_function=lambda feature: {
'fillColor': feature['properties']['color'],
'color' : feature['properties']['color'],
'weight' : 3,
'fillOpacity' : 0.5,
},
highlight_function=lambda x: {'weight':5,'color':'yellow'},
tooltip=folium.features.GeoJsonTooltip(fields=['highway'],aliases=["Type :"] ,labels=True, toLocaleString=True)
#smooth_factor=2.0
).add_to(g4)
folium.GeoJson(
Forest_reserve,
name='Forest Reserve',
show = False,
style_function=lambda feature: {
'fillColor': "#048160",
'color' : "#048160",
'weight' : 3,
'fillOpacity' : 0.5,
},
highlight_function=lambda x: {'weight':5,'color':'yellow'},
tooltip=folium.features.GeoJsonTooltip(fields=['area_hect'],aliases =["Area (hect) :"],labels=True, toLocaleString=True)
#smooth_factor=2.0
).add_to(g5)
plugins.Fullscreen(
position="topright",
title="Expand me",
title_cancel="Exit me",
force_separate_button=True,
).add_to(m)
minimap = plugins.MiniMap()
m.add_child(minimap)
# Add drawinf controls
draw = Draw()
draw.add_to(m)
m.add_child(MeasureControl())
folium.LayerControl().add_to(m)
#plugins.Geocoder().add_to(m)
m.save('D:\\Panna\\workdir\\Features.html')
# %% [markdown]
# ### Land Cover
# %%
_shp_district = read_df_UT("forest\\Panna\\panna_dst.shp")
_shp_district.to_file('_shp_district.json', driver='GeoJSON')
_shp_district = os.path.join('', '_shp_district.json')
filename = 'D:\\Panna\\workdir\\tempo.tif'
#Open raster file
driver=gdal.GetDriverByName('GTiff')
driver.Register()
ds = gdal.Open(filename)
if ds is None:
print('Could not open')
#Get coordinates, cols and rows
geotransform = ds.GetGeoTransform()
cols = ds.RasterXSize
rows = ds.RasterYSize
#Get extent
xmin=geotransform[0]
ymax=geotransform[3]
xmax=xmin+cols*geotransform[1]
ymin=ymax+rows*geotransform[5]
#Get Central point
centerx=(xmin+xmax)/2
centery=(ymin+ymax)/2
#Raster convert to array in numpy
bands = ds.RasterCount
band=ds.GetRasterBand(1)
dataset= band.ReadAsArray(0,0,cols,rows)
dataimage=dataset
color_labels = np.unique(dataset)
print(color_labels)
#dataimage1=np.where(dataset==100, 7, dataimage1)
# extract clouds
#dataimage1=np.where(dataset==100, 1, 0)
# extract unclassified
dataimage2=np.where(dataset==0, 100, 0)
#extract Barren
dataimage3=np.where(dataset==1, 1, 0)
#extract Sparse Vegetation
dataimage4=np.where(dataset==2, 2, 0)
#extract CropLand
dataimage5=np.where(dataset==3, 3, 0)
#extract Forests
dataimage6=np.where(dataset==4, 4, 0)
#extract Water
dataimage7=np.where(dataset==5, 5, 0)
#extract Urban
dataimage8=np.where(dataset==6, 6, 0)
m= folium.Map(location=[24.436933515, 80.20336914], zoom_start=8)
g2 = folium.plugins.FeatureGroupSubGroup(m, 'Unused',show=False)
g3 = folium.plugins.FeatureGroupSubGroup(m, 'Sparse vegetation',show=False)
g4 = folium.plugins.FeatureGroupSubGroup(m, 'Cropland',show=False)
g5 = folium.plugins.FeatureGroupSubGroup(m, 'Forest',show=False)
g6 = folium.plugins.FeatureGroupSubGroup(m, 'Water',show=False)
g7 = folium.plugins.FeatureGroupSubGroup(m, 'Built-up',show=False)
m.add_child(g2)
m.add_child(g3)
m.add_child(g4)
m.add_child(g5)
m.add_child(g6)
m.add_child(g7)
tile = folium.TileLayer(
tiles = 'https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}',
attr = 'Esri',
name = 'Esri Satellite',
overlay = False,
control = True
).add_to(m)
loc = 'Land cover map'
title_html = '''
<h3 align="center" style="font-size:16px"><b>{}</b></h3>
'''.format(loc)
m.get_root().html.add_child(folium.Element(title_html))
folium.GeoJson(
_shp_district,
name='dist_boundary',
show = True,
control = False,
style_function=lambda feature: {
'fillColor': "none",
'color' : "black",
'weight' : 1,
'fillOpacity' : 0.5,
},
# highlight_function=lambda x: {'weight':5,'color':'yellow'},
# tooltip=folium.features.GeoJsonTooltip(fields=['AREA'],labels=False, toLocaleString=True)
#smooth_factor=2.0
).add_to(m)
g2.add_child(raster_layers.ImageOverlay(
image=dataimage3,
show=False,
name = 'Unused',
bounds=[[ymin, xmin], [ymax, xmax]],
colormap=lambda x: (1-x,1-x, 1-x,0+x*255),#R,G,B,red: (255,0,0)
interactive=True,
mercator_project = True,
opacity=1
))#.add_to(m)
g3.add_child(raster_layers.ImageOverlay(
image=dataimage4,
show=False,
name = 'Sparse Vegetation',
bounds=[[ymin, xmin], [ymax, xmax]],
colormap=lambda x: (253+x,0,253+x,0+x*127),#R,G,B,alpha Yellow: (255,255,0) (255,0,255)
interactive=True,
mercator_project = True,
opacity=1
))#.add_to(m)
g4.add_child(raster_layers.ImageOverlay(
image=dataimage5,
show=False,
name = 'CropLand',
bounds=[[ymin, xmin], [ymax, xmax]],
colormap=lambda x: (3-x,13-x, 3-x,0+x*85),#R,G,B,alpha Lime Green (0,255,0)(0,10,0)
interactive=True,
mercator_project = True,
opacity=1
))#.add_to(m)
g5.add_child(raster_layers.ImageOverlay(
image=dataimage6,
show=False,
name = 'Forest',
bounds=[[ymin, xmin], [ymax, xmax]],
colormap=lambda x: (4-x,251+x,4-x,0+x*63),#R,G,B,alpha Dark Green (0,10,0)(0,255,0)
interactive=True,
mercator_project = True,
opacity=1
))#.add_to(m)
g6.add_child(raster_layers.ImageOverlay(
image=dataimage7,
show=False,
name = 'Water',
bounds=[[ymin, xmin], [ymax, xmax]],
colormap=lambda x: (5-x,250+x, 250+x,0+x*51),#R,G,B,alpha Blue (0, 255, 255)
interactive=True,
mercator_project = True,
opacity=1
))#.add_to(m)
g7.add_child(raster_layers.ImageOverlay(
image=dataimage8,
show=False,
name = 'Urban',
bounds=[[ymin, xmin], [ymax, xmax]],
colormap=lambda x: (249+x,6-x,6-x,0+x*42),#R,G,B,alpha Fuchsia (255,0,255)(255,0,0)
interactive=True,
mercator_project = True,
opacity=1
))#.add_to(m)
plugins.Fullscreen(
position="topright",
title="Expand me",
title_cancel="Exit me",
force_separate_button=True,
).add_to(m)
minimap = plugins.MiniMap()
m.add_child(minimap)
# Add drawinf controls
draw = Draw()
draw.add_to(m)
m.add_child(MeasureControl())
folium.LayerControl().add_to(m)
#plugins.Geocoder().add_to(m)
m.save('D:\\Panna\\workdir\\Landcover.html')
# %% [markdown]
# ### Competing use
# %%
_shp_merge_tech_water = gpd.read_file("D:\\Hasten Ventures\\Competing Use\\CompetingUse_w_Water\\CompetingUse_w_Water.shp")
_shp_merge_tech_water = _shp_merge_tech_water.round({"area_hect":0})
_shp_merge_tech_water.to_file('_shp_merge_tech_water.json', driver='GeoJSON')
_shp_merge_tech_water = os.path.join('', '_shp_merge_tech_water.json')
lc_tech = gpd.read_file("D:\\Hasten Ventures\\Technical Suitability\\Technical_Potential\\Technical_Potential.shp")
lc_tech = lc_tech.to_crs(4326)
def regioncolors(lc_tech):
if lc_tech['area_class'] == 'A':
return '#455555'
elif lc_tech['area_class'] == 'B':
return '#157e5c'
elif lc_tech['area_class'] == 'C':
return '#54ad64'
elif lc_tech['area_class'] == 'D':
return '#99cc66'
lc_tech["color"] = lc_tech.apply(regioncolors, axis=1)
lc_tech = lc_tech.round({"area_hect":0})
lc_tech["area_class"] = lc_tech["area_class"].replace(['A','B','C','D'],['Small area','Medium area','Large area','Very Large Area'])
lc_tech.to_file('lc_tech.json', driver='GeoJSON')
lc_tech = os.path.join('', 'lc_tech.json')
_shp_district = read_df_UT("forest\\Panna\\panna_dst.shp")
_shp_district.to_file('_shp_district.json', driver='GeoJSON')
_shp_district = os.path.join('', '_shp_district.json')
m= folium.Map(location=[24.436933515, 80.20336914], zoom_start=8)
loc = 'Competing land-use for climate action'
title_html = '''
<h3 align="center" style="font-size:16px"><b>{}</b></h3>
'''.format(loc)
m.get_root().html.add_child(folium.Element(title_html))
tile = folium.TileLayer(
tiles = 'https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}',
attr = 'Esri',
name = 'Esri Satellite',
overlay = False,
control = True
).add_to(m)
folium.GeoJson(
lc_tech,
name='Forest Technical Potential',
show = False,
style_function=lambda feature: {
'fillColor': feature['properties']['color'],
'color' : feature['properties']['color'],
'weight' : 3,
'fillOpacity' : 0.5,
},
highlight_function=lambda x: {'weight':5,'color':'yellow'},
tooltip=folium.features.GeoJsonTooltip(fields=['area_hect','area_class'],aliases =["Area (hect) :","Class :"],labels=True, toLocaleString=True)
#smooth_factor=2.0
).add_to(m)
folium.GeoJson(
_shp_merge_tech_water,
name='Water Harvesting Potential',
show = False,
style_function=lambda feature: {
'fillColor': "#00B9F2",
'color' : "#00B9F2",
'weight' : 3,
'fillOpacity' : 0.5,
},
highlight_function=lambda x: {'weight':5,'color':'yellow'},
tooltip=folium.features.GeoJsonTooltip(fields=['area_hect'],aliases=["Overlap Area (hect) :"],labels=True, toLocaleString=True)
#smooth_factor=2.0
).add_to(m)
folium.GeoJson(
_shp_district,
name='dist_boundary',
show = False,
control = False,
style_function=lambda feature: {
'fillColor': "none",
'color' : "black",
'weight' : 1,
'fillOpacity' : 0.5,
},
# highlight_function=lambda x: {'weight':5,'color':'yellow'},
# tooltip=folium.features.GeoJsonTooltip(fields=['AREA'],labels=False, toLocaleString=True)
#smooth_factor=2.0
).add_to(m)
plugins.Fullscreen(
position="topright",
title="Expand me",
title_cancel="Exit me",
force_separate_button=True,
).add_to(m)
minimap = plugins.MiniMap()
m.add_child(minimap)
# Add drawinf controls
draw = Draw()
draw.add_to(m)
m.add_child(MeasureControl())
folium.LayerControl().add_to(m)
m.save('D:\\Panna\\workdir\\Competinguse.html')
# %% [markdown]
# ## Land Suitability
# %% [markdown]
# ### No potential File
# %%
# _shp_district = read_df_UT("forest\\Panna\\panna_dst.shp")
# _shp_district.to_file('_shp_district.json', driver='GeoJSON')
# _shp_district = os.path.join('', '_shp_district.json')
# lc_tech = gpd.read_file("D:\\Hasten Ventures\\Technical Suitability\\Technical_Potential\\Technical_Potential.shp")
# lc_tech = lc_tech.to_crs(4326)
# def regioncolors(lc_tech):
# if lc_tech['area_class'] == 'A':
# return '#455555'
# elif lc_tech['area_class'] == 'B':
# return '#157e5c'
# elif lc_tech['area_class'] == 'C':
# return '#54ad64'
# elif lc_tech['area_class'] == 'D':
# return '#99cc66'
# lc_tech["color"] = lc_tech.apply(regioncolors, axis=1)
# lc_tech = lc_tech.round({"area_hect":0})
# lc_tech["area_class"] = lc_tech["area_class"].replace(['A','B','C','D'],['Small area','Medium area','Large area','Very Large Area'])
# lc_tech.to_file('lc_tech.json', driver='GeoJSON')
# lc_tech = os.path.join('', 'lc_tech.json')
# # filename = 'D:\\Panna\\workdir\\tempo.tif'
# # #Open raster file
# # driver=gdal.GetDriverByName('GTiff')
# # driver.Register()
# # ds = gdal.Open(filename)
# # if ds is None:
# # print('Could not open')
# # #Get coordinates, cols and rows
# # geotransform = ds.GetGeoTransform()
# # cols = ds.RasterXSize
# # rows = ds.RasterYSize
# # #Get extent
# # xmin=geotransform[0]
# # ymax=geotransform[3]
# # xmax=xmin+cols*geotransform[1]
# # ymin=ymax+rows*geotransform[5]
# # #Get Central point
# # centerx=(xmin+xmax)/2
# # centery=(ymin+ymax)/2
# # #Raster convert to array in numpy
# # bands = ds.RasterCount
# # band=ds.GetRasterBand(1)
# # dataset= band.ReadAsArray(0,0,cols,rows)
# # dataimage=dataset
# # color_labels = np.unique(dataset)
# # print(color_labels)
# # #dataimage1=np.where(dataset==100, 7, dataimage1)
# # # extract clouds
# # #dataimage1=np.where(dataset==100, 1, 0)
# # # extract unclassified
# # # dataimage2=np.where(dataset==0, 100, 0)
# # #extract Barren
# # dataimage3=np.where(dataset==1, 1, 0)
# No_potential = gpd.read_file("D:\\Hasten Ventures\\Technical Suitability\\No_Potential\\test_no_potential.shp")
# No_potential = No_potential.to_crs(4326)
# # No_potential = No_potential.round({"area_hect":0})
# # No_potential["area_hect"] = No_potential["area_hect"].replace([0],['< 1'])
# No_potential.to_file('No_potential.json', driver='GeoJSON')
# No_potential = os.path.join('', 'No_potential.json')
# theo_only = gpd.read_file("D:\\Hasten Ventures\\Technical Suitability\\\Only_theoretical\\\Only_theoretical.shp")
# theo_only = theo_only.round({"area_hect":0})
# theo_only["area_hect"] = theo_only["area_hect"].replace([0],["< 1"])
# theo_only.to_file('theo_only.json', driver='GeoJSON')
# theo_only = os.path.join('', 'theo_only.json')
# med = gpd.read_file("D:\\Hasten Ventures\\High Potential\\Medium_Potential\\Medium_Potential.shp")
# med = gpd.GeoDataFrame(med)
# med = med.to_crs(4326)
# med = med.round({"area_hect":0})
# med.to_file('med.json', driver='GeoJSON')
# med = os.path.join('', 'med.json')
# low = gpd.read_file("D:\\Hasten Ventures\\High Potential\\Low_Potential\\Low_Potential.shp")
# low = low.to_crs(4326)
# low = low.round({"area_hect":0})
# low.to_file('low.json', driver='GeoJSON')
# low = os.path.join('', 'low.json')
# # high = gpd.read_file("D:\\Hasten Ventures\\High Potential\\High_Potential\\High_Potential.shp")
# # high = high[["geometry","area_hect"]]
# # high = gpd.GeoDataFrame(high)
# # high = high.to_crs(4326)
# # high = high.round({"area_hect":0})
# # high.to_file('high.json', driver='GeoJSON')
# # high = os.path.join('', 'high.json')
# m= folium.Map(location=[24.436933515, 80.20336914], zoom_start=8)
# tile = folium.TileLayer(
# tiles = 'https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}',
# attr = 'Esri',
# name = 'Esri Satellite',
# overlay = False,
# control = True
# ).add_to(m)
# loc = 'Land potential and distribution by size'
# title_html = '''
# <h3 align="center" style="font-size:16px"><b>{}</b></h3>
# '''.format(loc)
# m.get_root().html.add_child(folium.Element(title_html))
# folium.GeoJson(
# _shp_district,
# name='dist_boundary',
# show = False,
# control = False,
# style_function=lambda feature: {
# 'fillColor': "none",
# 'color' : "black",
# 'weight' : 1,
# 'fillOpacity' : 0.5,
# },
# # highlight_function=lambda x: {'weight':5,'color':'yellow'},
# # tooltip=folium.features.GeoJsonTooltip(fields=['AREA'],labels=False, toLocaleString=True)
# #smooth_factor=2.0
# ).add_to(m)
# folium.GeoJson(
# No_potential,
# name='No potential',
# show = False,
# style_function=lambda feature: {
# 'fillColor': "#424242",
# 'color' : "#424242",
# 'weight' : 3,
# 'fillOpacity' : 0.5,
# },
# # highlight_function=lambda x: {'weight':5,'color':'yellow'},
# # tooltip=folium.features.GeoJsonTooltip(fields=['area_hect'],aliases =["Area (hect) :"],labels=True, toLocaleString=True),
# smooth_factor=1000
# ).add_to(m)
# # m.add_child(raster_layers.ImageOverlay(
# # image=dataimage3,
# # show=False,
# # name = 'No Potential',
# # bounds=[[ymin, xmin], [ymax, xmax]],
# # colormap=lambda x: (1-x,1-x, 1-x,0+x*255),#R,G,B,red: (255,0,0)
# # interactive=True,
# # mercator_project = True,
# # opacity=1
# # ))#.add_to(m)
# folium.GeoJson(
# theo_only,
# name='Theoritical potential',
# show = False,
# style_function=lambda feature: {
# 'fillColor':"#15915C",
# 'color' : "#15915C",
# 'weight' : 3,
# 'fillOpacity' : 0.5,
# },
# highlight_function=lambda x: {'weight':5,'color':'yellow'},
# tooltip=folium.features.GeoJsonTooltip(fields=['area_hect'],aliases =["Area (hect) :"],labels=True, toLocaleString=True),
# smooth_factor=2.0
# ).add_to(m)
# folium.GeoJson(
# lc_tech,
# name='Technical potential',
# show = False,
# style_function=lambda feature: {
# 'fillColor':feature['properties']['color'],
# 'color' : feature['properties']['color'],
# 'weight' : 3,
# 'fillOpacity' : 0.5,
# },
# highlight_function=lambda x: {'weight':5,'color':'yellow'},
# tooltip=folium.features.GeoJsonTooltip(fields=['area_hect','area_class'],aliases =["Area (hect) :","Class :"],labels=True, toLocaleString=True),
# smooth_factor=2.0
# ).add_to(m)
# folium.GeoJson(
# low,
# name='Low technical potential',
# show = False,
# style_function=lambda feature: {
# 'fillColor': "#21583B",
# 'color' : "#21583B",
# 'weight' : 3,
# 'fillOpacity' : 0.5,
# },
# highlight_function=lambda x: {'weight':5,'color':'yellow'},
# tooltip=folium.features.GeoJsonTooltip(fields=['area_hect'],aliases =["Area (hect) :"],labels=True, toLocaleString=True),
# smooth_factor=2.0
# ).add_to(m)
# folium.GeoJson(
# med,
# name='Medium technical potential',
# show = False,
# style_function=lambda feature: {
# 'fillColor': "#009541",
# 'color' : "#009541",
# 'weight' : 3,
# 'fillOpacity' : 0.5,
# },
# highlight_function=lambda x: {'weight':5,'color':'yellow'},
# tooltip=folium.features.GeoJsonTooltip(fields=['area_hect'],aliases =["Area (hect) :"],labels=True, toLocaleString=True),
# smooth_factor=2.0
# ).add_to(m)
# # folium.GeoJson(
# # high,
# # name='High technical potential',
# # show = False,
# # style_function=lambda feature: {
# # 'fillColor': "#99CC66",
# # 'color' : "#99CC66",
# # 'weight' : 3,
# # 'fillOpacity' : 0.5,
# # },
# # highlight_function=lambda x: {'weight':5,'color':'yellow'},
# # tooltip=folium.features.GeoJsonTooltip(fields=['area_hect'],aliases =["Area (hect) :"],labels=True, toLocaleString=True),
# # smooth_factor=2.0
# # ).add_to(m)
# # m.add_child(folium.ClickForMarker(popup='point added'))
# # #m.add_child(folium.LatLngPopup())
# # folium.LatLngPopup().add_to(m)
# # folium.LayerControl(collapsed = False).add_to(m)
# plugins.Fullscreen(
# position="topright",
# title="Expand me",
# title_cancel="Exit me",
# force_separate_button=True,
# ).add_to(m)
# minimap = plugins.MiniMap()
# m.add_child(minimap)
# # Add drawinf controls
# draw = Draw()
# draw.add_to(m)
# m.add_child(MeasureControl())
# folium.LayerControl().add_to(m)
# # plugins.Geocoder().add_to(m)
# m.save('D:\\Panna\\workdir\\Landsuitability.html')
# %% [markdown]
# ### Un Used Lands
# %%
_shp_district = read_df_UT("forest\\Panna\\panna_dst.shp")
_shp_district.to_file('_shp_district.json', driver='GeoJSON')
_shp_district = os.path.join('', '_shp_district.json')
lc_tech = gpd.read_file("D:\\Hasten Ventures\\Technical Suitability\\Technical_Potential\\Technical_Potential.shp")
lc_tech = lc_tech.to_crs(4326)
def regioncolors(lc_tech):
if lc_tech['area_class'] == 'A':
return '#455555'
elif lc_tech['area_class'] == 'B':
return '#157e5c'
elif lc_tech['area_class'] == 'C':
return '#54ad64'
elif lc_tech['area_class'] == 'D':
return '#99cc66'
lc_tech["color"] = lc_tech.apply(regioncolors, axis=1)
lc_tech = lc_tech.round({"area_hect":0})
lc_tech["area_hect"] = lc_tech["area_hect"].replace([0],["< 1"])
lc_tech["area_class"] = lc_tech["area_class"].replace(['A','B','C','D'],['Small area','Medium area','Large area','Very Large Area'])
lc_tech.to_file('lc_tech.json', driver='GeoJSON')
lc_tech = os.path.join('', 'lc_tech.json')
filename = 'D:\\Panna\\workdir\\tempo.tif'