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import math
import ee
def gba_tile_id(lon: float, lat: float, step_deg: int = 5) -> str:
lon0 = math.floor(lon / step_deg) * step_deg
lat0 = math.floor(lat / step_deg) * step_deg
lon1 = lon0 + step_deg
lat1 = lat0 + step_deg
def fmt_lon(x: int) -> str:
return ("e" if x >= 0 else "w") + f"{abs(x):03d}"
def fmt_lat(x: int) -> str:
return ("n" if x >= 0 else "s") + f"{abs(x):02d}"
return f"{fmt_lon(lon0)}_{fmt_lat(lat1)}_{fmt_lon(lon1)}_{fmt_lat(lat0)}"
def gba_fc_path(tile_id: str) -> str:
return f"projects/sat-io/open-datasets/GLOBAL_BUILDING_ATLAS/{tile_id}"
class GlobalBuildingAtlasHeight:
def __init__(self) -> None:
self._fc_cache = {}
def _get_fc(self, tile_id: str) -> ee.FeatureCollection:
if tile_id not in self._fc_cache:
self._fc_cache[tile_id] = ee.FeatureCollection(gba_fc_path(tile_id))
return self._fc_cache[tile_id]
def get_height_m(self, lat: float, lon: float, buffer_m: float = 20.0, centroid_scale_m: float = 1.0):
tile_id = gba_tile_id(lon, lat)
fc = self._get_fc(tile_id)
pt = ee.Geometry.Point([lon, lat])
search_geom = pt.buffer(buffer_m) if buffer_m and buffer_m > 0 else pt
candidates = (
fc.filterBounds(search_geom)
.filter(ee.Filter.gt("height", 0))
)
def add_dist(f):
f = ee.Feature(f)
d = f.geometry().centroid(centroid_scale_m).distance(pt)
return f.set("dist_m", d)
best = ee.Feature(candidates.map(add_dist).sort("dist_m").first())
count = candidates.size().getInfo()
if count == 0:
return {
"status": "not_found",
"tile_id": tile_id,
"buffer_m": buffer_m,
"predicted_height": None,
}
props = best.toDictionary(["height", "dist_m"]).getInfo()
return {
"status": "success",
"tile_id": tile_id,
"buffer_m": buffer_m,
"predicted_height": props.get("height"),
"distance_m": props.get("dist_m"),
}
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