|
| 1 | +import argparse |
| 2 | +import os |
| 3 | +import warnings |
| 4 | + |
| 5 | +import geopandas as gpd |
| 6 | +import pandas as pd |
| 7 | +import rasterio |
| 8 | +import requests |
| 9 | +from exactextract import exact_extract |
| 10 | +from tqdm import tqdm |
| 11 | + |
| 12 | +warnings.filterwarnings("ignore") |
| 13 | + |
| 14 | + |
| 15 | +def project_list(id_file): |
| 16 | + """Reads Mapswipe project IDs from the user input file""" |
| 17 | + |
| 18 | + with open(id_file, "r") as file: |
| 19 | + ids = file.read().strip() |
| 20 | + |
| 21 | + project_list = ids.split(",") |
| 22 | + project_list = [id.strip() for id in project_list] |
| 23 | + |
| 24 | + return project_list |
| 25 | + |
| 26 | + |
| 27 | +def population_raster_download(): |
| 28 | + """Downloads 1km resolution global population raster for 2020 from WorldPop to the current working directory.""" |
| 29 | + |
| 30 | + url = "https://data.worldpop.org/GIS/Population/Global_2000_2020/2020/0_Mosaicked/ppp_2020_1km_Aggregated.tif" |
| 31 | + |
| 32 | + output_file = "ppp_2020_1km_Aggregated.tif" |
| 33 | + |
| 34 | + output_file_path = os.path.join(os.getcwd(), output_file) |
| 35 | + |
| 36 | + if os.path.exists(output_file_path): |
| 37 | + |
| 38 | + print("Population raster already exists. Moving to next steps......") |
| 39 | + return output_file_path |
| 40 | + |
| 41 | + else: |
| 42 | + |
| 43 | + response = requests.get(url, stream=True) |
| 44 | + size = int(response.headers.get("content-length", 0)) |
| 45 | + block_size = 1024 |
| 46 | + try: |
| 47 | + with open(output_file, "wb") as file, tqdm( |
| 48 | + desc="Downloading population raster", |
| 49 | + total=size, |
| 50 | + unit="B", |
| 51 | + unit_scale=True, |
| 52 | + unit_divisor=1024, |
| 53 | + ) as bar: |
| 54 | + for chunk in response.iter_content(block_size): |
| 55 | + if chunk: |
| 56 | + file.write(chunk) |
| 57 | + bar.update(len(chunk)) |
| 58 | + |
| 59 | + print("Download complete:", output_file_path) |
| 60 | + return output_file_path |
| 61 | + |
| 62 | + except requests.RequestException as e: |
| 63 | + print(f"Error downloading data: {e}") |
| 64 | + |
| 65 | + |
| 66 | +def population_count(list, dir, raster): |
| 67 | + """Gets boundary data for projects from Mapswipe API and calculates zonal statistics |
| 68 | + with global population raster and individual project boundaries.""" |
| 69 | + |
| 70 | + dict = {} |
| 71 | + worldpop = rasterio.open(raster) |
| 72 | + |
| 73 | + for id in list: |
| 74 | + url = f"https://apps.mapswipe.org/api/project_geometries/project_geom_{id}.geojson" |
| 75 | + response = requests.get(url) |
| 76 | + |
| 77 | + try: |
| 78 | + geojson = response.json() |
| 79 | + for feature in geojson["features"]: |
| 80 | + geometry = feature.get("geometry", {}) |
| 81 | + if "coordinates" in geometry: |
| 82 | + if geometry["type"] == "Polygon": |
| 83 | + geometry["coordinates"] = [ |
| 84 | + [[coord[0], coord[1]] for coord in polygon] |
| 85 | + for polygon in geometry["coordinates"] |
| 86 | + ] |
| 87 | + elif geometry["type"] == "MultiPolygon": |
| 88 | + geometry["coordinates"] = [ |
| 89 | + [ |
| 90 | + [[coord[0], coord[1]] for coord in polygon] |
| 91 | + for polygon in multipolygon |
| 92 | + ] |
| 93 | + for multipolygon in geometry["coordinates"] |
| 94 | + ] |
| 95 | + gdf = gpd.GeoDataFrame.from_features(geojson["features"]) |
| 96 | + gdf.set_crs("EPSG:4326", inplace=True) |
| 97 | + no_of_people = exact_extract(worldpop, gdf, "sum") |
| 98 | + no_of_people = round(no_of_people[0]["properties"]["sum"]) |
| 99 | + |
| 100 | + dict[id] = no_of_people |
| 101 | + |
| 102 | + except requests.RequestException as e: |
| 103 | + print(f"Error in retrieval of project boundary from Mapswipe: {e}") |
| 104 | + |
| 105 | + df = pd.DataFrame( |
| 106 | + dict.items(), columns=["Project_IDs", "Number of people impacted"] |
| 107 | + ) |
| 108 | + |
| 109 | + df["Project_IDs"] = "https://mapswipe.org/en/projects/" + df["Project_IDs"] |
| 110 | + |
| 111 | + df.to_csv(f"{dir}/projects_population.csv") |
| 112 | + |
| 113 | + print(f"CSV file successfully created at {dir}/number_of_people_impacted.csv") |
| 114 | + |
| 115 | + |
| 116 | +if __name__ == "__main__": |
| 117 | + """Generates population stats for individual Mapswipe projects""" |
| 118 | + parser = argparse.ArgumentParser() |
| 119 | + parser.add_argument( |
| 120 | + "-t", |
| 121 | + "--text_file", |
| 122 | + help=( |
| 123 | + "Path to the text file containing project IDs from Mapswipe. The file should contain IDs in this manner: " |
| 124 | + "-O8kulfxD4zRYQ2T1aXf, -O8kyOCreRGklW15n8RU, -O8kzSy9105axIPOAJjO, -OAwWv9rnJqPXTpWxO8-, " |
| 125 | + "-OB-tettI2np7t3Gpu-k" |
| 126 | + ), |
| 127 | + type=str, |
| 128 | + required=True, |
| 129 | + ) |
| 130 | + parser.add_argument( |
| 131 | + "-o", |
| 132 | + "--output_directory", |
| 133 | + help="Path to the directory to store the output", |
| 134 | + type=str, |
| 135 | + required=True, |
| 136 | + ) |
| 137 | + args = parser.parse_args() |
| 138 | + |
| 139 | + population_count( |
| 140 | + project_list(args.text_file), |
| 141 | + args.output_directory, |
| 142 | + population_raster_download(), |
| 143 | + ) |
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