Building Regularization¶

Install package¶

To use the geoai-py package, ensure it is installed in your environment. Uncomment the command below if needed.

In [1]:

# %pip install geoai-py

# %pip install geoai-py

Import package¶

In [2]:

import geoai

import geoai

Download sample data¶

In [3]:

naip_url = (
    "https://huggingface.co/datasets/giswqs/geospatial/resolve/main/naip_train.tif"
)
masks_url = "https://huggingface.co/datasets/giswqs/geospatial/resolve/main/naip_building_masks.tif"

naip_url = ( "https://huggingface.co/datasets/giswqs/geospatial/resolve/main/naip_train.tif" ) masks_url = "https://huggingface.co/datasets/giswqs/geospatial/resolve/main/naip_building_masks.tif"

In [4]:

masks_path = geoai.download_file(masks_url)
naip_path = geoai.download_file(naip_url)

masks_path = geoai.download_file(masks_url) naip_path = geoai.download_file(naip_url)

naip_building_masks.tif:   0%|          | 0.00/61.6k [00:00<?, ?B/s]

naip_building_masks.tif: 100%|██████████| 61.6k/61.6k [00:00<00:00, 4.38MB/s]

naip_train.tif:   0%|          | 0.00/12.1M [00:00<?, ?B/s]

naip_train.tif:  52%|█████▏    | 6.25M/12.1M [00:00<00:00, 65.5MB/s]

naip_train.tif: 100%|██████████| 12.1M/12.1M [00:00<00:00, 81.2MB/s]

In [5]:

geoai.view_image(masks_path, figsize=(18, 10))

geoai.view_image(masks_path, figsize=(18, 10))

In [6]:

geoai.create_split_map(
    left_layer=masks_url,
    right_layer=naip_url,
    left_label="Building Masks",
    right_label="NAIP Imagery",
    left_args={
        "colormap": {"255": "#0000ff"},
        "opacity": 0.5,
    },
    basemap=naip_url,
)

geoai.create_split_map( left_layer=masks_url, right_layer=naip_url, left_label="Building Masks", right_label="NAIP Imagery", left_args={ "colormap": {"255": "#0000ff"}, "opacity": 0.5, }, basemap=naip_url, )

Out[6]:

Convert raster to vector¶

In [7]:

gdf = geoai.raster_to_vector(masks_path, output_path="naip_building_masks.geojson")

gdf = geoai.raster_to_vector(masks_path, output_path="naip_building_masks.geojson")

Vectorized data saved to naip_building_masks.geojson

In [8]:

geoai.view_vector_interactive(
    gdf, style_kwds={"color": "blue", "fillOpacity": 0.4}, tiles=naip_url
)

geoai.view_vector_interactive( gdf, style_kwds={"color": "blue", "fillOpacity": 0.4}, tiles=naip_url )

Out[8]:

Make this Notebook Trusted to load map: File -> Trust Notebook

In [9]:

geoai.create_split_map(
    left_layer=gdf,
    right_layer=naip_url,
    left_label="Buildings",
    right_label="NAIP Imagery",
    left_args={"style": {"color": "blue"}, "fillOpacity": 0.4},
    basemap=naip_url,
)

geoai.create_split_map( left_layer=gdf, right_layer=naip_url, left_label="Buildings", right_label="NAIP Imagery", left_args={"style": {"color": "blue"}, "fillOpacity": 0.4}, basemap=naip_url, )

Out[9]:

Building regularization¶

In [10]:

gdf_regularized = geoai.regularization(
    building_polygons=gdf,
    angle_tolerance=10,
    simplify_tolerance=0.5,
    orthogonalize=True,
    preserve_topology=True,
)

gdf_regularized = geoai.regularization( building_polygons=gdf, angle_tolerance=10, simplify_tolerance=0.5, orthogonalize=True, preserve_topology=True, )

In [11]:

geoai.view_vector_interactive(
    gdf_regularized, style_kwds={"color": "red", "fillOpacity": 0.4}, tiles=naip_url
)

geoai.view_vector_interactive( gdf_regularized, style_kwds={"color": "red", "fillOpacity": 0.4}, tiles=naip_url )

Out[11]:

Make this Notebook Trusted to load map: File -> Trust Notebook

In [12]:

geoai.create_split_map(
    left_layer=gdf_regularized,
    right_layer=naip_url,
    left_label="Regularized Buildings",
    right_label="NAIP Imagery",
    left_args={"style": {"color": "red"}, "fillOpacity": 0.4},
    basemap=naip_url,
)

geoai.create_split_map( left_layer=gdf_regularized, right_layer=naip_url, left_label="Regularized Buildings", right_label="NAIP Imagery", left_args={"style": {"color": "red"}, "fillOpacity": 0.4}, basemap=naip_url, )

Out[12]:

Hybrid regularization¶

In [13]:

gdf_hybrid = geoai.hybrid_regularization(gdf)

gdf_hybrid = geoai.hybrid_regularization(gdf)

In [14]:

geoai.view_vector_interactive(
    gdf_hybrid, style_kwds={"color": "green", "fillOpacity": 0.4}, tiles=naip_url
)

geoai.view_vector_interactive( gdf_hybrid, style_kwds={"color": "green", "fillOpacity": 0.4}, tiles=naip_url )

Out[14]:

Make this Notebook Trusted to load map: File -> Trust Notebook

In [15]:

geoai.create_split_map(
    left_layer=gdf_regularized,
    right_layer=naip_url,
    left_label="Regularized Buildings",
    right_label="NAIP Imagery",
    left_args={"style": {"color": "green", "fillOpacity": 0.4}},
    basemap=naip_url,
)

geoai.create_split_map( left_layer=gdf_regularized, right_layer=naip_url, left_label="Regularized Buildings", right_label="NAIP Imagery", left_args={"style": {"color": "green", "fillOpacity": 0.4}}, basemap=naip_url, )

Out[15]:

Adaptive regularization¶

In [16]:

gdf_adaptive = geoai.adaptive_regularization(
    building_polygons=gdf,
    simplify_tolerance=0.5,
    area_threshold=0.9,
    preserve_shape=True,
)

gdf_adaptive = geoai.adaptive_regularization( building_polygons=gdf, simplify_tolerance=0.5, area_threshold=0.9, preserve_shape=True, )

In [17]:

geoai.view_vector_interactive(
    gdf_adaptive, style_kwds={"color": "yellow", "fillOpacity": 0.4}, tiles=naip_url
)

geoai.view_vector_interactive( gdf_adaptive, style_kwds={"color": "yellow", "fillOpacity": 0.4}, tiles=naip_url )

Out[17]:

Make this Notebook Trusted to load map: File -> Trust Notebook

In [18]:

geoai.create_split_map(
    left_layer=gdf_adaptive,
    right_layer=naip_url,
    left_label="Adaptive Regularization Buildings",
    right_label="NAIP Imagery",
    left_args={"style": {"color": "yellow", "fillOpacity": 0.4}},
    basemap=naip_url,
)

geoai.create_split_map( left_layer=gdf_adaptive, right_layer=naip_url, left_label="Adaptive Regularization Buildings", right_label="NAIP Imagery", left_args={"style": {"color": "yellow", "fillOpacity": 0.4}}, basemap=naip_url, )

Out[18]:

Compare regularization methods¶

In [19]:

import leafmap.foliumap as leafmap

import leafmap.foliumap as leafmap

In [20]:

m = leafmap.Map()
m.add_basemap("SATELLITE")
m.add_gdf(gdf, layer_name="Original")
m.add_gdf(
    gdf_regularized, style={"color": "red", "fillOpacity": 0}, layer_name="Regularized"
)
m.add_gdf(gdf_hybrid, style={"color": "green", "fillOpacity": 0}, layer_name="Hybrid")
m.add_gdf(
    gdf_adaptive, style={"color": "yellow", "fillOpacity": 0}, layer_name="Adaptive"
)
legend = {
    "Original": "blue",
    "Regularized": "red",
    "Hybrid": "green",
    "Adaptive": "yellow",
}
m.add_legend(title="Building Footprints", legend_dict=legend)
m

m = leafmap.Map() m.add_basemap("SATELLITE") m.add_gdf(gdf, layer_name="Original") m.add_gdf( gdf_regularized, style={"color": "red", "fillOpacity": 0}, layer_name="Regularized" ) m.add_gdf(gdf_hybrid, style={"color": "green", "fillOpacity": 0}, layer_name="Hybrid") m.add_gdf( gdf_adaptive, style={"color": "yellow", "fillOpacity": 0}, layer_name="Adaptive" ) legend = { "Original": "blue", "Regularized": "red", "Hybrid": "green", "Adaptive": "yellow", } m.add_legend(title="Building Footprints", legend_dict=legend) m

Out[20]: