Use case · greenfield triage
Undeveloped, accessible, low-relief candidate land.
Rank MH-36 clusters that are not yet built, are sparsely populated, sit on cropland / grassland / shrubland LULC, and are still reachable by road.
§1 The buyer's question
“Where in Maharashtra are the next 50 candidate parcels for a manufacturing park, a logistics hub, a solar farm, or a township — undeveloped, low-relief, low-population, with a road already nearby?”
§2 The cube columns it touches
scope : mh36
cube_fp : dcc1845460cbd47c…
weights : built_fraction -0.40 (penalise existing build)
pop_density_per_km2 -0.20 (penalise dense population)
road_length_km +0.20 (reward existing road access)
terrain_elev_m -0.10 (mild penalty on hills)
ndvi_p50 +0.10 (cropland/grass cover ok)
filter : lulc_class_primary IN (40 cropland, 30 grassland, 20 shrubland, 60 bare/sparse)
min_witnesses ≥ 3§3 Worked example — live from the cube
Cells scored
209,058
Districts in scope
35
Top-K returned
10
LULC kept
40/30/20/60
cropland · grass · shrub · bare
| # | Anchor | District | LULC | built | road km | pop /km² | elev m | score |
|---|---|---|---|---|---|---|---|---|
| 1 | 491:4910004966 | Raigad | 40 cropland | 0.003 | 17.75 | 698.5 | 3 | 1.19 |
| 2 | 486:4860003213 | Nandurbar | 40 cropland | 0.004 | 14.54 | 0 | 169 | 1.09 |
| 3 | 665:6650000041 | Palghar | 40 cropland | — | 14.60 | 286.3 | 24 | 1.07 |
| 4 | 469:4690001179 | Chhatrapati Sambhajinagar | 30 grassland | 0.001 | 16.01 | 0 | 508 | 0.96 |
| 5 | 469:4690003223 | Chhatrapati Sambhajinagar | 40 cropland | 0.000 | 15.68 | 0 | 590 | 0.93 |
| 6 | 665:6650000432 | Palghar | 40 cropland | — | 11.84 | 79.6 | 12 | 0.87 |
| 7 | 486:4860003132 | Nandurbar | 40 cropland | 0.000 | 9.12 | 0 | 162 | 0.87 |
| 8 | 469:4690003120 | Chhatrapati Sambhajinagar | 40 cropland | 0.009 | 16.88 | 348.2 | 586 | 0.85 |
| 9 | 491:4910004917 | Raigad | 40 cropland | 0.014 | 16.32 | 1,784.4 | 2 | 0.83 |
| 10 | 491:4910001809 | Raigad | 30 grassland | 0.003 | 6.46 | 36.8 | 170 | 0.82 |
Top cell — full evidence record
Raigad · 491:4910004966
lat 18.9150 · lon 73.0050
Built fraction
0.003
Building count
27
Building height p50
0.01 m
Road length
17.75 km
Population density
699 /km²
NDVI p50
0.233
Terrain elevation
2.5 m
§4 The workflow in Explorer
Step 2
Filter to one district at a time
Use the admin filter to surface candidates inside a target district (e.g. Pune, Aurangabad).
Step 3
Compare candidates head-to-head
Pick two top hits and use Compare to see per-column deltas with floor-key chips inline.
§5 Talk to us about a pilot
Public-sector teams and developers get bulk parquet + the GeoJSON export of any custom-scored top-N.