Montana Range High Points Shapefile

mt_highpoints.py

import os
import csv
import requests
import time
import geopandas
from shapely.geometry import Point

"""
Montana State Library: Montana's Tallest Peaks by Mountain Range
https://msl.mt.gov/geoinfo/geography/geography_facts/montanaxs_tallest_peaks_by_mountain_range

Pulling most of these by GNIS name lookup and filling in the missing values under MISSING
by finding the peak with the MSL link and getting coordinates from Google Earth.
"""

WATERDATA_API_URL = "https://dashboard.waterdata.usgs.gov/service/geocoder/get/location/1.0"
STATE_ABBREVIATION = "MT"
REQUEST_TIMEOUT = 15
DELAY_BETWEEN_REQUESTS = 2.0

MISSING = {'Bears Paw Mountains': (48.148593, -109.65075),

           # Beartooth Mountains GNIS lookup gets first result from Tobacco Root
           'Beartooth Mountains': (45.1841, -109.79129),

           # exact point of Beaverhead Mtns HP is in Idaho
           'Beaverhead Mountains': (44.447227, -112.996476),

           # Bighorn's Montana HP is drive-up
           # 'Bighorn Mountains': (45.00098, -107.91139),
           # Bighorn Overall HP is Cloud Peak
           'Bighorn Mountains': (44.382147, -107.173951),

           'Big Sheep Mountains': (47.044020, -105.730260),

           # not sure why this one finds a bad coordinate pair
           'Bitteroot Range': (45.88965, -114.2981),

           'Blacktail Mountains': (44.987672, -112.578531),
           'Castle Mountains': (46.452622, -110.753254),

           # not sure why this one finds a bad coordinate pair
           'Chalk Buttes': (45.708559, -104.734215),
           'Gravelly Range': (44.90425, -111.85563),
           'Henrys Lake Mountains': (44.7633, -111.3906),
           'Highland Mountains': (45.742484, -112.461789),
           'John Long Mountains': (46.479171, -113.680506),
           'Little Snowy Mountains': (46.752222, -109.173333),
           'Lewis and Clark Range': (47.11654, -112.738643),
           'Long Pines': (45.639974, -104.184526),
           'North Moccasin Mountains': (47.31448, -109.46758),
           'Ruby Range': (45.312778, -112.228056),
           'South Moccasin Mountains': (47.1725, -109.523889),
           'Sweet Grass Hills': (48.931379, -111.532198),
           'Wolf Mountains': (45.03603, -107.19281)}


def get_coordinates_from_gnis(mountain_name):
    params = {
        "term": mountain_name,
        "include": "gnis",
        "states": STATE_ABBREVIATION,
        "maxSuggestions": 1
    }
    headers = {}
    response = requests.get(WATERDATA_API_URL, params=params, headers=headers, timeout=REQUEST_TIMEOUT)
    response.raise_for_status()
    data = response.json()

    if data and len(data) > 0:
        location = data[0]
        if location.get("Source") == "gnis" and "Latitude" in location and "Longitude" in location:
            print(f'{mountain_name}: {location["Latitude"]:.2f}, {location["Longitude"]:.2f}')
            return location["Latitude"], location["Longitude"]
    else:
        raise ValueError


def process_mountains_csv(input_csv_filepath, output_csv_filepath, output_shapefile_filepath):
    processed_mountains_for_csv = []
    mountains_for_geodataframe = []

    with open(input_csv_filepath, mode='r', encoding='utf-8-sig') as infile:
        reader = csv.DictReader(infile)

        for row_number, row_dict in enumerate(reader, 1):
            name_from_csv = row_dict.get('Name')
            climbed = row_dict.get('done')
            range = row_dict.get('range')
            elev_ft = row_dict.get('elev_ft')
            status_msg = ""
            lat, lon = None, None

            current_attributes = dict(row_dict)

            if name_from_csv and name_from_csv.strip():
                stripped_name = name_from_csv.strip()
                current_attributes['Name'] = stripped_name

                if range in MISSING:
                    loc = MISSING[range]
                    print(f'{stripped_name}: {loc[0]:.2f}, {loc[1]:.2f}')
                else:
                    loc = get_coordinates_from_gnis(stripped_name)

                lat, lon = loc[0], loc[1]
                time.sleep(DELAY_BETWEEN_REQUESTS)

                status_msg = "Success"
                point_data = current_attributes.copy()

                point_data['geometry'] = Point(float(lon), float(lat))
                point_data['latitude'] = float(lat)
                point_data['longitude'] = float(lon)

                point_data['status'] = status_msg
                mountains_for_geodataframe.append(point_data)

            else:
                status_msg = "Skipped - Empty name in CSV"
                current_attributes['Name'] = name_from_csv if name_from_csv else ''

            csv_entry = {
                'name': current_attributes['Name'],
                'latitude': lat if lat is not None else 'N/A',
                'longitude': lon if lon is not None else 'N/A',
                'range': range,
                'elev_ft': elev_ft,
                'done': climbed
            }
            processed_mountains_for_csv.append(csv_entry)

    if processed_mountains_for_csv:
        with open(output_csv_filepath, mode='w', newline='', encoding='utf-8') as outfile:
            fieldnames = list(csv_entry.keys())
            writer = csv.DictWriter(outfile, fieldnames=fieldnames)
            writer.writeheader()
            writer.writerows(processed_mountains_for_csv)

    if mountains_for_geodataframe:
        gdf = geopandas.GeoDataFrame(mountains_for_geodataframe, crs="EPSG:4326")

        sanitized_columns = {}

        for col_name in gdf.columns:
            if col_name == 'geometry':
                sanitized_columns[col_name] = 'geometry'
                continue

            s_name = str(col_name).replace(' ', '_').replace('.', '_').replace('-', '_')
            s_name = s_name[:10]

            original_s_name = s_name
            count = 1
            while s_name in sanitized_columns.values():
                s_name = original_s_name[:10 - len(str(count))] + str(count)
                count += 1
            sanitized_columns[col_name] = s_name

        gdf.rename(columns=sanitized_columns, inplace=True)
        gdf.to_file(output_shapefile_filepath, driver='ESRI Shapefile')

if __name__ == "__main__":

    d = os.path.expanduser('~')

    input_file = os.path.join(d, 'mt_highpoints_noCoords.csv')
    output_csv = os.path.join(d, 'mt_highpoints.csv')
    output_shp = os.path.join(d, 'mt_highpoints.shp')

    process_mountains_csv(input_file, output_csv, output_shp)

# ========================= EOF ====================================================================

mt_highpoints_noCoords.csv