Parcels
Retrieves parcel and footprints data based on one or more U.S. location inputs. The data extraction is parcel based, meaning it retrieves data on all the buildings within the parcel at the requested location.
GET https://us-api.geox.ai/v1/parcels
Query Parameters
The request can contain up to 100 locations.
| Name | Type | Description |
|---|---|---|
location | string | Required. The location to search for. Can be an address or coordinates. |
Input Formats
- Address: Free text format. Ideally:
[Street Number] [Street Name], [City], [State/Province] [Postal Code], [Country]. - Coordinates: Lat/Lng format:
lat, lng(e.g.,42.937, -71.413). - Multiple Locations: Append additional locations using the
&location=parameter.
Response Schema
The response returns a list of locations, each containing a parcel object and an array of footprints.
{
"data": [
{
"parcel": { ...Parcel Object },
"footprints": [{ ...Footprint Object }]
}
]
}Example Usage
Example Request
- cURL
- JavaScript
- Python
curl --location 'https://us-api.geox.ai/v1/parcels?location=1600+Amphitheatre+Parkway,+Mountain+View,+CA' \
--header 'Authorization: Bearer YOUR_TOKEN'
fetch('https://us-api.geox.ai/v1/parcels?location=1600+Amphitheatre+Parkway,+Mountain+View,+CA', {
method: 'GET',
headers: {
'Authorization': 'Bearer YOUR_TOKEN'
}
})
.then(response => response.json())
.then(data => console.log(data));
import requests
url = "https://us-api.geox.ai/v1/parcels"
params = {
"location": "1600 Amphitheatre Parkway, Mountain View, CA"
}
headers = {
"Authorization": "Bearer YOUR_TOKEN"
}
response = requests.get(url, params=params, headers=headers)
print(response.json())
Example Response
{
"data": [
{
"parcel": {
"parcel_id": "3301100116618",
"pool_count": 0,
"pool_enclosure_count": 0,
"temporary_pool_count": 0,
"trampoline_count": 0,
"number_of_buildings_in_parcel": 32
},
"footprints": [
{
"parcel_id": "3301100116618",
"footprint_id": "33011001166183110000",
"center_long": -71.41314975284693,
"center_lat": 42.93783754514559,
"state": "New Hampshire",
"county": "Hillsborough",
"crs": 4326,
"footprint_area": 2820.45,
"year_built": null,
"occupancy": null,
"occupancy_of_closest_building": null,
"land_use_description": null,
"roof_type": "gable",
"roof_material": "shingle",
"roof_condition": "fair",
"tarp_evidence": false,
"flat_area": 0,
"hip_area": 678.02,
"rust_area": 0,
"ponding_area": 0,
"discoloration_area": 669.31,
"solar_panel_area": 0,
"air_conditioner_count": 0,
"building_height": null,
"ground_height_amsl": null,
"number_of_stories": null,
"square_footage": null,
"tree_overhang_percent": 0,
"distance_to_tree": 48.88,
"distance_to_shrub": 18.5,
"distance_to_vegetation": 18.5,
"tree_zone_1": 0,
"tree_zone_2": 0,
"tree_zone_3": 0,
"tree_zone_4": 2.24,
"shrub_zone_1": 0,
"shrub_zone_2": 0.88,
"shrub_zone_3": 21.54,
"shrub_zone_4": 40.69,
"vegetation_zone_1": 0,
"vegetation_zone_2": 0.88,
"vegetation_zone_3": 21.54,
"vegetation_zone_4": 40.91,
"distance_to_coast": 27.46,
"distance_to_water_body": 0.51,
"distance_to_fire_station": 0.95,
"distance_to_closest_building": 101.21,
"image_date": "2024-04-25T00:00:00.000Z",
"model_run_date": "2024-12-08T00:00:00.000Z",
"geometry": "0103000020E6100000010000000B00000058EBD62B70DA51C0E8F6F4390D7845409FE103AE6FDA51C0A40DCF290978454009DDFE946EDA51C0A17D4E7509784540A4B9D13B6EDA51C026C66A92067845404C17A7E96FDA51C08A5D411B06784540C469FC1B70DA51C0080DB3BE077845407A4488D470DA51C0FB5C5E8C077845406028E6F170DA51C04274B17F087845409C6596D871DA51C0EDF4F844087845402A7FE65F72DA51C080C9C2A90C78454058EBD62B70DA51C0E8F6F4390D784540"
}
]
}
]
}
Error Responses
| Code | Meaning | Description |
|---|---|---|
400 | Bad Request | Missing or malformed address query parameter |
401 | Unauthorized | Missing or invalid authentication token |
404 | Not Found | No parcels matched the provided address(es) |
429 | Too Many Requests | Usage limit exceeded. Includes X-Usage-Left and X-User-Id headers |
500 | Internal Server Error | Query timeout (over 15 seconds) or unexpected backend error |