size_categories:1K<n<10K format:parquet modality:image library:datasets library:dask library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype: image
  splits:
  - name: train
    num_bytes: 2511244176.0
    num_examples: 6400
  - name: validation
    num_bytes: 252535598.0
    num_examples: 653
  - name: test
    num_bytes: 495070953.5
    num_examples: 1286
  download_size: 1200019345
  dataset_size: 3258850727.5
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---
# Alaskan Dead Tree Dataset

## Dataset Details

This dataset consists of high resolution aerial images of forest from the Kenai peninsula area of Alaska taken by [NASA Goddard's G-LiHT](https://gliht.gsfc.nasa.gov/) instrument. 

Pixel-wise annotations were created using k-means clustering augmented by a Gray Level Co-occurrence Matrix (GLCM). A value of 1 denotes a dead tree, and 0 denotes everything else. The masks and images were tiled into 256x256 pixel squares and paired together, then any empty masks (entirely 0 or 1) were removed.  

## Dataset Structure

The dataset is split into 3 subsets: training set, validation set, test set. The training set contains 1286 images, the validation set contains 653 images, and the test set contains 1286.


### Data categories

| id | category |
| --- | ---- |
| 0 | background |
| 1 | dead tree |


