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cussen-geo

License: MIT Python 3.10+

Framework Cussen — Geospatial indices for marine, volcanic, fire, agricultural, forestry, geology and space mining domains.

A reproducible, citable Python implementation of the Framework Cussen (FC), a collection of remote-sensing-based indices designed to quantify environmental processes across seven domains:

Code Domain Indices
MAR Marine / Coastal CO₂ solubility (K₀), Kelp Habitat Affinity (KHAI), …
VOL Volcanology thermal anomalies, ash plumes, …
FIR Fire burn severity, smoke detection, …
AGR Agriculture crop water stress, yield estimation, …
FOR Forestry canopy structure, biomass, blue carbon, …
GEO Geology / Geomorphology hazard mapping, kriging, …
SP Space Mining CLPI, CMPI, CAPI, CASI

Status

🚧 Alpha — under active development. v0.2 ships two domain modules:

MAR — Marine / Coastal:

  • MAR.01 k0_weiss — CO₂ solubility (Weiss 1974)
  • MAR.02 khai — Kelp Habitat Affinity Index (proposed)

SP — Space Mining / Planetary Prospection:

  • CLPI (M3 / Moon): mri, hpi, opi
  • CMPI (CRISM / Mars): hmi, cbi, ahi
  • CAPI (Sentinel-2 / ASTER analog sites): mas, evi, haz
  • CASI (NEO VNIR spectroscopy): vmi, mmi, mvi

Installation

pip install cussen-geo

For raster / vector / lidar workflows:

pip install "cussen-geo[all]"

Quick start

Marine (MAR)

import numpy as np
from cussen_geo.mar import k0_weiss, khai

# CO2 solubility at 12 °C, salinity 33 psu
k0 = k0_weiss(12.0, 33.0)
print(f"K0 = {k0:.2f} mmol/(L·atm)")
# K0 = 42.63 mmol/(L·atm)

# Kelp Habitat Affinity Index (triangular, T_opt = 12 °C, ΔT = 4 °C)
sst_grid = np.array([10.0, 12.0, 14.0, 17.0])
habitat = khai(sst_grid)
print(habitat)
# [0.5, 1.0, 0.5, 0.0]

Space mining (SP)

import numpy as np
from cussen_geo.sp import vmi, mvi

# Asteroid VNIR features
hydration = np.array([0.08, 0.01])  # C-type vs S-type
slope     = np.array([-0.1, 0.5])
bd1_depth = np.array([0.0, 0.30])

vmi_scores = vmi(hydration, slope, bd1_depth)
print(vmi_scores.round(2))
# [0.95 0.20]

# Mission viability with delta-v penalty
mvi_scores = mvi(vmi_scores, np.zeros(2), delta_v=np.array([4.5, 4.5]))
print(mvi_scores.round(2))
# [0.95 0.2 ]

Citation

If you use cussen-geo in academic work, please cite:

@software{cussen_geo,
  author = {Cussen Eltit, Pablo},
  title  = {cussen-geo: Framework Cussen geospatial indices},
  year   = {2026},
  url    = {https://github.com/pablocussen/cussen-geo},
  note   = {ORCID: 0009-0008-4853-4200}
}

License

MIT © 2026 Pablo Cussen Eltit

Metadata

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