Merge pull request #186 from Deltares/#134-integrate-roads-script-in-…

…code-base

#134 integrate roads script in code base

docs/api/api_index.rst

@@ -23,7 +23,7 @@ Build components
    fiat.FiatModel.setup_basemaps
    fiat.FiatModel.setup_vulnerability
    fiat.FiatModel.setup_vulnerability_from_csv
-   fiat.FiatModel.setup_exposure_vector
+   fiat.FiatModel.setup_exposure_buildings
    fiat.FiatModel.setup_hazard
    fiat.FiatModel.setup_social_vulnerability_index
 

docs/data/hazus.rst

@@ -16,7 +16,7 @@ by providing the following values in the configuration file::
     vulnerability_identifiers_and_linking_fn = "default_hazus_iwr_linking"
     unit = "ft"
 
-    [setup_exposure_vector]
+    [setup_exposure_buildings]
     max_potential_damage = "hazus_max_potential_damages"
     unit = "m"
 

docs/data/jrc.rst

@@ -14,7 +14,7 @@ by providing the following values in the configuration file::
     vulnerability_identifiers_and_linking_fn = "jrc_vulnerability_curves_linking"
     unit = "m"
 
-    [setup_exposure_vector]
+    [setup_exposure_buildings]
     max_potential_damage = "jrc_damage_values"
     unit = "m"
 

docs/data/national_structure_inventory.rst

@@ -8,7 +8,7 @@ For projects in the United States, users of **HydroMT-FIAT** can directly and ea
 of the `National Structure Inventory <https://www.hec.usace.army.mil/confluence/nsi>`_ (NSI). The 
 user can access the data through providing 'NSI' in the configuration file as such::
 
-    [setup_exposure_vector]
+    [setup_exposure_buildings]
     asset_locations = "NSI"
     occupancy_type = "NSI"
     max_potential_damage = "NSI"

docs/data/openstreetmap.rst

@@ -7,7 +7,7 @@ OpenStreetMap Building Footprints and Land Use
 Users of **HydroMT-FIAT** can directly and easily make use of the `OpenStreetMap <https://www.openstreetmap.org/about>`_ 
 (OSM) initiative. The user can access the data through providing 'OSM' in the configuration file as such::
 
-    [setup_exposure_vector]
+    [setup_exposure_buildings]
     asset_locations = "OSM"
     occupancy_type = "OSM"
 

docs/user_guide/user_guide_overview.rst

@@ -32,9 +32,9 @@ to local data on the user's machine. The `asset_locations`, `occupancy_type`, an
 data should be provided as a vector file (e.g. *.shp* or *.gpkg*). The `ground_floor_height` can currently 
 only be set to a single value (this will be updated soon!). The `damage_types` should be provided as a 
 list of strings (e.g. ["structure", "content"]). The `unit` should be provided as a string (e.g. "m"). 
-See below how the `setup_exposure_vector` method can be used to build or update the exposure data::
+See below how the `setup_exposure_buildings` method can be used to build or update the exposure data::
 
-   [setup_exposure_vector]
+   [setup_exposure_buildings]
    asset_locations = <Key in the Data Catalog, data API key, or path to local data>
    occupancy_type = <Key in the Data Catalog, data API key, or path to local data>
    damage_types = <List of damage types, e.g. ["structure", "content"]>
@@ -45,7 +45,7 @@ See below how the `setup_exposure_vector` method can be used to build or update
 The following method is used to build or update the **exposure** data:
 
 .. autosummary::
-   FiatModel.setup_exposure_vector
+   FiatModel.setup_exposure_buildings
 
 For more information, see the :ref:`exposure_vector`.
 

examples/global_OSM_JRC.ipynb

@@ -242,7 +242,7 @@
     "        \"continent\": continent,\n",
     "        \"unit\": unit,\n",
     "    },\n",
-    "    \"setup_exposure_vector\": {\n",
+    "    \"setup_exposure_buildings\": {\n",
     "        \"asset_locations\": asset_locations,\n",
     "        \"occupancy_type\": occupancy_type,\n",
     "        \"max_potential_damage\": max_potential_damage,\n",

hydromt_fiat/api/data_types.py

@@ -85,4 +85,4 @@ class ConfigIni(BaseModel):
     setup_config: ModelIni
     setup_hazard: HazardIni
     setup_vulnerability: VulnerabilityIni
-    setup_exposure_vector: ExposureVectorIni
+    setup_exposure_buildings: ExposureVectorIni

hydromt_fiat/api/hydromt_fiat_vm.py

@@ -73,7 +73,7 @@ def build_config_ini(self):
             setup_config=self.model_vm.config_model,
             setup_hazard=self.hazard_vm.hazard_model,
             setup_vulnerability=self.vulnerability_vm.vulnerability_model,
-            setup_exposure_vector=self.exposure_vm.exposure_model,
+            setup_exposure_buildings=self.exposure_vm.exposure_model,
         )
 
         database_path = self.__class__.database.drive

hydromt_fiat/data/hydromt_fiat_catalog_USA.yml

@@ -1,45 +1,57 @@
 
 NSI:
-    path: "https://nsi.sec.usace.army.mil/nsiapi/structures?fmt=fc"
-    data_type: GeoDataFrame
-    driver: vector
-    crs: 4326
-    translation_fn: "attribute_linking/NSI_attributes_to_FIAT.json"
-    meta:
-      category: exposure
+  path: "https://nsi.sec.usace.army.mil/nsiapi/structures?fmt=fc"
+  data_type: GeoDataFrame
+  driver: vector
+  crs: 4326
+  translation_fn: "attribute_linking/NSI_attributes_to_FIAT.json"
+  meta:
+    category: exposure
 
 default_vulnerability_curves:
-    path: damage_functions/flooding/Hazus_IWR_curves.csv
-    data_type: DataFrame
-    driver: csv
-    meta:
-      category: vulnerability
-      source: HAZUS SQL database, USACE-IWR and FEMA expert elicitation curves. The source of these curves is the Draft Report Nonresidential Flood Depth-Damage Functions Derived from Expert Elicitation, April 2009, Revised 2013. FEMA Contract Number HSFEHQ-06-D-0162. Task Order HSFEHQ-08-J-0014. Not for distribution, but data shared by USACE.
+  path: damage_functions/flooding/Hazus_IWR_curves.csv
+  data_type: DataFrame
+  driver: csv
+  meta:
+    unit: ft
+    category: vulnerability
+    source: HAZUS SQL database, USACE-IWR and FEMA expert elicitation curves. The source of these curves is the Draft Report Nonresidential Flood Depth-Damage Functions Derived from Expert Elicitation, April 2009, Revised 2013. FEMA Contract Number HSFEHQ-06-D-0162. Task Order HSFEHQ-08-J-0014. Not for distribution, but data shared by USACE.
 
 jrc_vulnerability_curves:
-    path: damage_functions/flooding/JRC_damage_functions.xlsx
-    data_type: DataFrame
-    driver: xlsx
-    meta:
-      category: vulnerability
+  path: damage_functions/flooding/JRC_damage_functions.xlsx
+  data_type: DataFrame
+  driver: xlsx
+  meta:
+    unit: m
+    category: vulnerability
 
 hazus_max_potential_damages:
-    path: max_potential_damages/damage_values_fema_hazus-inventory-technical-manual-4.2.3.xlsx
-    data_type: DataFrame
-    driver: xlsx
-    meta:
-      category: vulnerability
+  path: max_potential_damages/damage_values_fema_hazus-inventory-technical-manual-4.2.3.xlsx
+  data_type: DataFrame
+  driver: xlsx
+  meta:
+    unit: ft
+    category: vulnerability
 
 social_vulnerability:
-    path: social_vulnerability/census_vulnerability_data_codebook.xlsx
-    data_type: DataFrame
-    driver: xlsx
-    meta:
-      category: social_vulnerability
+  path: social_vulnerability/census_vulnerability_data_codebook.xlsx
+  data_type: DataFrame
+  driver: xlsx
+  meta:
+    category: social_vulnerability
 
 default_hazus_iwr_linking:
   path: vulnerability_linking/default_hazus_iwr_curve_linking.csv
   data_type: DataFrame
   driver: csv
   meta:
-    category: vulnerability
+    category: vulnerability
+
+default_road_max_potential_damages:
+  path: max_potential_damages/us_road_damage.csv
+  data_type: DataFrame
+  driver: csv
+  meta:
+    unit: ft
+    category: exposure
+    source: Bouwer, Laurens & Haasnoot, Marjolijn & Wagenaar, Dennis & Roscoe, Kathryn. (2018). Assessment of alternative flood mitigation strategies for the C-7 Basin in Miami, Florida. 

hydromt_fiat/data/max_potential_damages/us_road_damage.csv

@@ -0,0 +1,7 @@
+lanes,cost [USD/ft]
+1,240
+2,240
+3,360
+4,480
+5,600
+6,720

hydromt_fiat/data_apis/open_street_maps.py

@@ -1,16 +1,17 @@
 import osmnx as ox
 import logging
 from shapely.geometry import Polygon
+import geopandas as gpd
+from typing import Union, List
 
 
-def get_assets_from_osm(polygon: Polygon):
+def get_assets_from_osm(polygon: Polygon) -> gpd.GeoDataFrame:
     tags = {"building": True}  # this is the tag we use to find the correct OSM data
     footprints = ox.features.features_from_polygon(
         polygon, tags
     )  # then we query the data
 
     if footprints.empty:
-        logging.warning("No buildings found from OSM")
         return None
 
     logging.info(f"Total number of buildings found from OSM: {len(footprints)}")
@@ -25,7 +26,38 @@ def get_assets_from_osm(polygon: Polygon):
     return footprints
 
 
-def get_landuse_from_osm(polygon: Polygon):
+def get_roads_from_osm(
+    polygon: Polygon,
+    road_types: Union[str, List[str], bool] = True,
+) -> gpd.GeoDataFrame:
+    if isinstance(road_types, str):
+        road_types = [road_types]
+
+    tag = {
+        "highway": road_types
+    }  # this is the tag we use to find the correct OSM data
+
+    roads = ox.features.features_from_polygon(
+        polygon, tags=tag
+    )  # then we query the data
+
+    if roads.empty:
+        return None
+
+    logging.info(f"Total number of roads found from OSM: {len(roads)}")
+
+    # Not sure if this is needed here and maybe filter for the columns that we need
+    roads = roads.loc[
+        (roads.geometry.type == "LineString")
+        | (roads.geometry.type == "MultiLineString")
+    ]
+    roads = roads.reset_index(drop=True)
+    roads = roads.loc[:, ["highway", "name", "lanes", "geometry"]]
+
+    return roads
+
+
+def get_landuse_from_osm(polygon: Polygon) -> gpd.GeoDataFrame:
     tags = {"landuse": True}  # this is the tag we use to find the correct OSM data
     landuse = ox.features.features_from_polygon(polygon, tags)  # then we query the data
 
@@ -45,18 +77,6 @@ def get_landuse_from_osm(polygon: Polygon):
     return landuse
 
 
-if __name__ == "__main__":
-    _polygon = Polygon(
-        [
-            [-80.21997289327112, 25.83897611793664],
-            [-80.21997289327112, 25.86427542636784],
-            [-80.24609330530801, 25.86427542636784],
-            [-80.24609330530801, 25.83897611793664],
-            [-80.21997289327112, 25.83897611793664],
-        ]
-    )
-    get_landuse_from_osm(_polygon)
-
 # # Do a spatial join to connect the buildings with the classes
 # # (here we use a buffer area of 100 m around the classes in case there buildings falling completely out of the classes)
 # # a more comprehensive spatial join to account for overlapping area can be used as well

hydromt_fiat/fiat.py

@@ -244,13 +244,35 @@ def setup_vulnerability_from_csv(self, csv_fn: Union[str, Path], unit: str) -> N
                 (e.g. meter).
         """
         # Process the vulnerability data
-        self.vulnerability = Vulnerability(
-            unit,
-            self.logger,
-        )
+        if not self.vulnerability:
+            self.vulnerability = Vulnerability(
+                unit,
+                self.logger,
+            )
         self.vulnerability.from_csv(csv_fn)
 
-    def setup_exposure_vector(
+    def setup_road_vulnerability(
+        self,
+        vertical_unit: str,
+        threshold_value: float = 0.6,
+        min_hazard_value: float = 0,
+        max_hazard_value: float = 10,
+        step_hazard_value: float = 1.0,
+    ):
+        if not self.vulnerability:
+            self.vulnerability = Vulnerability(
+                vertical_unit,
+                self.logger,
+            )
+        self.vulnerability.create_step_function(
+            "roads",
+            threshold_value,
+            min_hazard_value,
+            max_hazard_value,
+            step_hazard_value,
+        )
+
+    def setup_exposure_buildings(
         self,
         asset_locations: Union[str, Path],
         occupancy_type: Union[str, Path],
@@ -262,7 +284,7 @@ def setup_exposure_vector(
         damage_types: Union[List[str], None] = ["structure", "content"],
         country: Union[str, None] = None,
     ) -> None:
-        """Setup vector exposure data for Delft-FIAT.
+        """Setup building exposure (vector) data for Delft-FIAT.
 
         Parameters
         ----------
@@ -322,7 +344,7 @@ def setup_exposure_vector(
         except AssertionError:
             logging.error(
                 "Please call the 'setup_vulnerability' function before "
-                "the 'setup_exposure_vector' function. Error message: {e}"
+                "the 'setup_exposure_buildings' function. Error message: {e}"
             )
         self.exposure.link_exposure_vulnerability(
             self.vf_ids_and_linking_df, damage_types
@@ -334,6 +356,30 @@ def setup_exposure_vector(
         self.set_config("exposure.geom.crs", self.exposure.crs)
         self.set_config("exposure.geom.unit", unit)
 
+    def setup_exposure_roads(
+        self,
+        roads_fn: Union[str, Path],
+        road_damage: Union[str, Path],
+        road_types: Union[str, List[str], bool] = True,
+        unit: str = "m",
+    ):
+        """Setup road exposure data for Delft-FIAT.
+
+        Parameters
+        ----------
+        roads_fn : Union[str, Path]
+            Path to the road network source (e.g., OSM) or file.
+        road_types : Union[str, List[str], bool], optional
+            List of road types to include in the exposure data, by default True
+        """
+        if not self.exposure:
+            self.exposure = ExposureVector(self.data_catalog, self.logger, self.region, unit=unit)
+        self.exposure.setup_roads(roads_fn, road_damage, road_types)
+
+        # Link to vulnerability curves
+
+        # Combine the exposure database with pre-existing exposure data if available
+
     def setup_exposure_raster(self):
         """Setup raster exposure data for Delft-FIAT.
         This function will be implemented at a later stage.