worldclim-extract

Using the CLI Script

A reusable Python script is provided at {baseDir}/extract_worldclim.py:

# Extract BIO1 (annual mean temp) and BIO12 (annual precipitation) — default
python3 {baseDir}/extract_worldclim.py \
  -i samples.xlsx \
  -o samples_with_climate.xlsx
Extract all 19 bioclimatic variables
python3 {baseDir}/extract_worldclim.py \
  -i samples.xlsx \
  -o samples_all_bio.xlsx \
  --bios 1-19
Extract specific variables with custom column names
python3 {baseDir}/extract_worldclim.py \
  -i coords.csv \
  -o result.xlsx \
  --bios 1,5,6,12,13 \
  --res 2.5m \
  --lon longitude \
  --lat latitude

Using Python Directly

For custom integration or programmatic use:

import pandas as pd
import rasterio
def extract_bio(tif_path, lon, lat):
    """Extract a single value from a GeoTIFF at given coordinates."""
    with rasterio.open(tif_path) as src:
        value = next(src.sample([(lon, lat)]))[0]
    return value
Read sample coordinates
df = pd.read_excel("samples.xlsx")
coords = list(zip(df["经度"], df["纬度"]))
Extract BIO1 (Annual Mean Temperature)
with rasterio.open("wc2.1_10m_bio_1.tif") as src:
    df["年均温度_C"] = [v[0] for v in src.sample(coords)]
Extract BIO12 (Annual Precipitation)
with rasterio.open("wc2.1_10m_bio_12.tif") as src:
    df["年降水量_mm"] = [v[0] for v in src.sample(coords)]
df.to_excel("samples_with_climate.xlsx", index=False)