Datamonger

Covertype

Browse datasets

uci:covertype@1 · Registry 1.4.0. Default version in this registry.

Forest cover types for 581,012 cells measuring 30 by 30 meters in four wilderness areas of the Roosevelt National Forest in northern Colorado. The 54 cartographic features comprise 10 quantitative measurements, four binary wilderness indicators, and 40 binary soil-type indicators. Cover_Type codes 1 through 7 denote spruce/fir, lodgepole pine, ponderosa pine, cottonwood/willow, aspen, Douglas-fir, and krummholz, respectively.

Dimensions and tasks

Task

Type

Split

Samples

Predictors

default

classification

—

581,012

54

Predictor counts follow each task's feature selection and exclude targets and identifiers. Sample counts are reported separately for each split.

Retrieve

These examples pin both the dataset version and the registry's exact index. An uncached dataset requires network access to its source. The CLI retrieves verified artifacts. The language clients also decode them.

Python

from datamonger import Registry, fetch_data

registry = Registry(
    release="1.4.0",
    index_sha256="ef83679266af9fcbb9ea194acdfb9bb6c380b440a574fc2ee7292899c5102909",
    index_url="https://github.com/jolars/datamonger/releases/download/registry-v1.4.0/index.json",
)
data = fetch_data("uci:covertype@1", registry=registry)

R

library(datamonger)

registry <- registry_selector(
  release = "1.4.0",
  index_sha256 = "ef83679266af9fcbb9ea194acdfb9bb6c380b440a574fc2ee7292899c5102909",
  index_url = "https://github.com/jolars/datamonger/releases/download/registry-v1.4.0/index.json"
)
data <- fetch_data("uci:covertype@1", registry = registry)

Julia

using Datamonger

registry = registry_selector(
    "1.4.0",
    "ef83679266af9fcbb9ea194acdfb9bb6c380b440a574fc2ee7292899c5102909",
    "https://github.com/jolars/datamonger/releases/download/registry-v1.4.0/index.json",
)
data = fetch_data("uci:covertype@1"; registry=registry)

CLI

cat > datamonger-registry.json <<'JSON'
{
  "index_sha256": "ef83679266af9fcbb9ea194acdfb9bb6c380b440a574fc2ee7292899c5102909",
  "index_url": "https://github.com/jolars/datamonger/releases/download/registry-v1.4.0/index.json",
  "release": "1.4.0",
  "schema_version": 1
}
JSON
datamonger --selector datamonger-registry.json fetch 'uci:covertype@1'

Representation and variables

Tabular data with a dense representation. Decoder: delimited-text version 1.

Component

Kind

Type

Shape

Elevation

vector

int64

581,012

Aspect

vector

int64

581,012

Slope

vector

int64

581,012

Horizontal_Distance_To_Hydrology

vector

int64

581,012

Vertical_Distance_To_Hydrology

vector

int64

581,012

Horizontal_Distance_To_Roadways

vector

int64

581,012

Hillshade_9am

vector

int64

581,012

Hillshade_Noon

vector

int64

581,012

Hillshade_3pm

vector

int64

581,012

Horizontal_Distance_To_Fire_Points

vector

int64

581,012

Wilderness_Area1

vector

int64

581,012

Wilderness_Area2

vector

int64

581,012

Wilderness_Area3

vector

int64

581,012

Wilderness_Area4

vector

int64

581,012

Soil_Type1

vector

int64

581,012

Soil_Type2

vector

int64

581,012

Soil_Type3

vector

int64

581,012

Soil_Type4

vector

int64

581,012

Soil_Type5

vector

int64

581,012

Soil_Type6

vector

int64

581,012

Soil_Type7

vector

int64

581,012

Soil_Type8

vector

int64

581,012

Soil_Type9

vector

int64

581,012

Soil_Type10

vector

int64

581,012

Soil_Type11

vector

int64

581,012

Soil_Type12

vector

int64

581,012

Soil_Type13

vector

int64

581,012

Soil_Type14

vector

int64

581,012

Soil_Type15

vector

int64

581,012

Soil_Type16

vector

int64

581,012

Showing 30 of 55 components. The complete registry record contains every variable name and task binding.

Preprocessing

Upstream

Status: documented.

The provider documents unscaled data with no missing values. The original study used the first 11,340 records for training, the next 3,780 for validation, and the last 565,892 for testing. The upstream CSV contains the full table; this entry retains its source order and does not materialize separate split artifacts.

feature-encoding. The provider represents wilderness area and soil type using four and 40 binary indicator columns, respectively.

Parameters: absence: 0; presence: 1; soil_columns: Soil_Type1 through Soil_Type40; wilderness_columns: Wilderness_Area1 through Wilderness_Area4.

Evidence: https://archive.ics.uci.edu/dataset/31/covertype, https://archive.ics.uci.edu/ml/machine-learning-databases/covtype/covtype.info

Datamonger

Status: none.

Datamonger decodes the provider artifact without additional statistical preprocessing.

Evidence: spec/decoders/delimited-text-v1.md

Provenance and citation

Provider: UCI Machine Learning Repository. Upstream name: Covertype. Retrieved: 2026-10-26.

Original source

Authors: Jock Blackard.

Blackard, J. (1998). Covertype [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C50K5N.

Cite the UCI dataset DOI and retain the copyright notice for Jock A. Blackard and Colorado State University, as requested in covtype.info.

License

CC-BY-4.0

License information

The UCI landing page at https://archive.ics.uci.edu/dataset/31/covertype states that the dataset is licensed under CC BY 4.0. The original covtype.info permits unlimited reuse with retention of the copyright notice for Jock A. Blackard and Colorado State University.

Artifacts

Total download: 72.2 MiB. Sizes describe the distributed files, including any compression.

Artifact

Format

Compression

Size

Distribution

Preservation

data

csv

none

72.2 MiB

upstream-only

unknown

data: upstream

Versions in this registry

1 (default)

Registry record

Download the complete registry record, registry selector, or full registry index.

Index SHA-256: ef83679266af9fcbb9ea194acdfb9bb6c380b440a574fc2ee7292899c5102909.