fix broken links, use https

Author: Conengmo

docs/advanced_guide/geodedetic_image_overlay.md

@@ -102,6 +102,6 @@ TODO: Try [rasterio](https://github.com/mapbox/rasterio/blob/ca75cf0a842943c1b3d
 
 ## Compare to original
 
-From https://scitools.org.uk/cartopy/docs/latest/gallery/waves.html
+From https://scitools.org.uk/cartopy/docs/latest/gallery/scalar_data/waves.html
 
 ![](https://scitools.org.uk/cartopy/docs/latest/_images/sphx_glr_waves_001.png)

docs/advanced_guide/polygons_from_list_of_points.md

@@ -193,7 +193,7 @@ my_envelope_map
 ```
 
 ## Concave hull (alpha shape)
-In some cases the convex hull does not yield good results - this is when the shape of the polygon should be concave instead of convex. The solution is a concave hull that is also called alpha shape. Yet, there is no ready to go, off the shelve solution for this but there are great resources (see: http://blog.thehumangeo.com/2014/05/12/drawing-boundaries-in-python/, accessed 04.01.2019 or https://towardsdatascience.com/the-concave-hull-c649795c0f0f, accessed 29.12.2018).
+In some cases the convex hull does not yield good results - this is when the shape of the polygon should be concave instead of convex. The solution is a concave hull that is also called alpha shape. Yet, there is no ready to go, off the shelve solution for this but there are great resources (see: https://web.archive.org/web/20191207074940/http://blog.thehumangeo.com/2014/05/12/drawing-boundaries-in-python/, accessed 04.01.2019 or https://towardsdatascience.com/the-concave-hull-c649795c0f0f, accessed 29.12.2018).
 
 
 ## Putting it together
@@ -259,14 +259,12 @@ my_map_global
 
 ## Sources:
 
-* http://blog.yhat.com/posts/interactive-geospatial-analysis.html, accessed 28.12.2018
+* https://web.archive.org/web/20200222150431/http://blog.yhat.com/posts/interactive-geospatial-analysis.html, accessed 28.12.2018
 
 * https://docs.scipy.org/doc/scipy-0.19.0/reference/generated/scipy.spatial.ConvexHull.html, accessed 29.12.2018
 
-* https://www.oreilly.com/ideas/an-elegant-solution-to-the-convex-hull-problem, accessed 29.12.2018
-
 * https://medium.com/@vworri/simple-geospacial-mapping-with-geopandas-and-the-usual-suspects-77f46d40e807, accessed 29.12.2018
 
 * https://towardsdatascience.com/the-concave-hull-c649795c0f0f, accessed 29.12.2018
 
-* http://blog.thehumangeo.com/2014/05/12/drawing-boundaries-in-python/, accessed 04.01.2019
+* https://web.archive.org/web/20191207074940/http://blog.thehumangeo.com/2014/05/12/drawing-boundaries-in-python/, accessed 04.01.2019

docs/getting_started.md

@@ -68,7 +68,7 @@ You can also pass any tileset as a url template. Choose one from https://leaflet
 and pass the url and attribution. For example:
 
 ```
-folium.Map(tiles='http://{s}.tiles.example.com/{z}/{x}/{y}.png', attr='My Data Attribution')
+folium.Map(tiles='https://{s}.tiles.example.com/{z}/{x}/{y}.png', attr='My Data Attribution')
 ```
 
 Folium also accepts objects from the [xyzservices package](https://github.com/geopandas/xyzservices).

docs/user_guide/geojson/geojson.md

@@ -102,8 +102,8 @@ You can provide a function of the form `lambda feature: {}` that sets the style
 
 For possible options, see:
 
-* For `Point` and `MultiPoint`, see http://leafletjs.com/reference.html#marker
-* For other features, see http://leafletjs.com/reference.html#path-options and http://leafletjs.com/reference.html#polyline-options
+* For `Point` and `MultiPoint`, see https://leafletjs.com/reference.html#marker
+* For other features, see https://leafletjs.com/reference.html#path and https://leafletjs.com/reference.html#polyline
 
 ```{code-cell} ipython3
 m = folium.Map([43, -100], zoom_start=4)

docs/user_guide/geojson/geopandas_and_geo_interface.md

@@ -7,14 +7,13 @@ import folium
 
 # Using GeoPandas.GeoDataFrame in folium
 
-GeoPandas is a project to add support for geographic data to [pandas](http://pandas.pydata.org) objects.
+GeoPandas is a project to add support for geographic data to [pandas](https://pandas.pydata.org) objects.
 (See https://github.com/geopandas/geopandas)
 
 It provides (among other cool things) a `GeoDataFrame` object that represents a Feature collection.
 When you have one, you may be willing to use it on a folium map. Here's the simplest way to do so.
 
-In this example, we'll use the same file as GeoPandas demo ; it's containing
-[the boroughs of New York City](http://www.nyc.gov/html/dcp/download/bytes/nybb_14aav.zip).
+In this example, we'll use the same file as GeoPandas demo ; it's containing the boroughs of New York City.
 
 ```{code-cell} ipython3
 boros = folium.example_data.new_york_boroughs_geodataframe()

docs/user_guide/plugins/locate_control.md

@@ -9,8 +9,7 @@ import folium.plugins
 ## LocateControl
 
 Adds a control button that when clicked, the user device geolocation is displayed.
-For list of all possible keyword options see:
-https://github.com/domoritz/leaflet-locatecontrol#possible-options
+For list of all possible keyword options see 'Possible options' on https://github.com/domoritz/leaflet-locatecontrol.
 
 To work properly in production, the connection needs to be encrypted (HTTPS),
 otherwise the browser will not allow users to share their location.

docs/user_guide/plugins/search.md

@@ -56,7 +56,7 @@ mean = round(states["density"].mean(), 2)
 print(f"minimum: {minimum}", f"maximum: {maximum}", f"Mean: {mean}", sep="\n\n")
 ```
 
-This looks better. Our min and max values for the colorscale are much closer to the mean value now. Let's run with these values, and make a colorscale. I'm just going to use a sequential light-to-dark color palette from the [ColorBrewer](https://colorbrewer2.org/#type=sequential&scheme=Purples&n=5).
+This looks better. Our min and max values for the colorscale are much closer to the mean value now. Let's run with these values, and make a colorscale. I'm just going to use a sequential light-to-dark color palette from the [ColorBrewer](https://colorbrewer2.org/?type=sequential&scheme=Purples&n=5).
 
 ```{code-cell} ipython3
 import branca

docs/user_guide/raster_layers/tiles.md

@@ -40,16 +40,16 @@ folium.Map(location=[lat, lon], tiles="Cartodb dark_matter", zoom_start=zoom_sta
 
 ```{code-cell} ipython3
 attr = (
-    '&copy; <a href="http://www.openstreetmap.org/copyright">OpenStreetMap</a> '
-    'contributors, &copy; <a href="http://cartodb.com/attributions">CartoDB</a>'
+    '&copy; <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> '
+    'contributors, &copy; <a href="https://cartodb.com/attributions">CartoDB</a>'
 )
-tiles = "http://{s}.basemaps.cartocdn.com/light_nolabels/{z}/{x}/{y}.png"
+tiles = "https://{s}.basemaps.cartocdn.com/light_nolabels/{z}/{x}/{y}.png"
 
 folium.Map(location=[lat, lon], tiles=tiles, attr=attr, zoom_start=zoom_start)
 ```
 
 ### Other tilesets
 
-For a list of many more tile providers go to http://leaflet-extras.github.io/leaflet-providers/preview/.
+For a list of many more tile providers go to https://leaflet-extras.github.io/leaflet-providers/preview/.
 
 You can also use the xyzservices package: https://github.com/geopandas/xyzservices.

docs/user_guide/raster_layers/wms_tile_layer.md

@@ -11,7 +11,7 @@ import folium
 m = folium.Map(location=[41, -70], zoom_start=5, tiles="cartodb positron")
 
 folium.WmsTileLayer(
-    url="http://mesonet.agron.iastate.edu/cgi-bin/wms/nexrad/n0r.cgi",
+    url="https://mesonet.agron.iastate.edu/cgi-bin/wms/nexrad/n0r.cgi",
     name="test",
     fmt="image/png",
     layers="nexrad-n0r-900913",

docs/user_guide/vector_layers/polyline.md

@@ -8,9 +8,7 @@ import folium
 # PolyLine
 
 ```{code-cell} ipython3
-# Coordinates are 15 points on the great circle from Boston to
-# San Francisco.
-# Reference: http://williams.best.vwh.net/avform.htm#Intermediate
+# Coordinates are 15 points on the great circle from Boston to San Francisco.
 coordinates = [
     [42.3581, -71.0636],
     [42.82995815, -74.78991444],