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---
language:
- en
size_categories:
- 10M<n<100M
pretty_name: Project Resilience Emissions from Land-Use Change Dataset
tags:
- climate
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: ELUC_diff
dtype: float32
- name: c3ann
dtype: float32
- name: c3ann_diff
dtype: float32
- name: c3nfx
dtype: float32
- name: c3nfx_diff
dtype: float32
- name: c3per
dtype: float32
- name: c3per_diff
dtype: float32
- name: c4ann
dtype: float32
- name: c4ann_diff
dtype: float32
- name: c4per
dtype: float32
- name: c4per_diff
dtype: float32
- name: cell_area_diff
dtype: float32
- name: pastr
dtype: float32
- name: pastr_diff
dtype: float32
- name: primf
dtype: float32
- name: primf_diff
dtype: float32
- name: primn
dtype: float32
- name: primn_diff
dtype: float32
- name: range
dtype: float32
- name: range_diff
dtype: float32
- name: secdf
dtype: float32
- name: secdf_diff
dtype: float32
- name: secdn
dtype: float32
- name: secdn_diff
dtype: float32
- name: urban
dtype: float32
- name: urban_diff
dtype: float32
- name: ELUC
dtype: float32
- name: cell_area
dtype: float32
- name: country
dtype: float64
- name: crop
dtype: float32
- name: crop_diff
dtype: float32
- name: country_name
dtype: string
- name: time
dtype: int64
- name: lat
dtype: float64
- name: lon
dtype: float64
splits:
- name: train
num_bytes: 6797746584
num_examples: 41387985
download_size: 3176214475
dataset_size: 6797746584
---
# Project Resilience Emissions from Land-Use Change Dataset
### Project Resilience
To contribute to this project see [Project Resilience](https://www.itu.int/en/ITU-T/extcoop/ai-data-commons/Pages/project-resilience.aspx) ([Github Repo](https://github.com/Project-Resilience/mvp))
Land Use Change data is provided by the [Land Use Harmonization Project](https://doi.org/10.5194/gmd-2019-360), providing land-use changes from 850-2100
Emissions from Land-Use Change (ELUC) data is provided by the [Global Carbon Budget 2023](https://doi.org/10.5194/essd-15-5301-2023) Bookkeeping of Land-Use Emissions (BLUE) model.
Data was used in [Discovering Effective Policies for Land-Use Planning](https://doi.org/10.48550/arXiv.2311.12304) at [NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning](https://www.climatechange.ai/events/neurips2023)
### Land Use Types
- Primary: Vegetation that is untouched by humans
- primf: Primary forest
- primn: Primary nonforest vegetation
- Secondary: Vegetation that has been touched by humans
- secdf: Secondary forest
- secdn: Secondary nonforest vegetation
- Urban
- Crop
- c3ann: Annual C3 crops (e.g. wheat)
- c4ann: Annual C4 crops (e.g. maize)
- c3per: Perennial C3 crops (e.g. banana)
- c4per: Perennial C4 crops (e.g. sugarcane)
- c3nfx: Nitrogen fixing C3 crops (e.g. soybean)
- Pasture
- pastr: Managed pasture land
- range: Natural grassland/savannah/desert/etc.
### Dataset
The dataset is indexed by latitude, longitude, and time, with each row consisting of the land use of a given year, the land-use change from year to year+1, and the committed ELUC at the end of year in tons of carbon per hectare (tC/ha).
Committed ELUC means the sum of all simulated future emissions due to a land-use change.
In addition, the cell area of the cell in hectares and the name of the country the cell is located in are provided.
A crop and crop_diff column consisting of the sums of all the crop types and crop type diffs is provided as well as the BLUE model treats all crop types the same.
Raw data files are provided as: `merged_aggregated_dataset_1850_2022.zarr.zip` and `BLUE_LUH2-GCB2022_ELUC-committed_gridded_net_1850-2021.nc`, which are the land-use changes and the committed emissions respectively.
---
dataset_info:
features:
- name: ELUC_diff
dtype: float32
- name: c3ann
dtype: float32
- name: c3ann_diff
dtype: float32
- name: c3nfx
dtype: float32
- name: c3nfx_diff
dtype: float32
- name: c3per
dtype: float32
- name: c3per_diff
dtype: float32
- name: c4ann
dtype: float32
- name: c4ann_diff
dtype: float32
- name: c4per
dtype: float32
- name: c4per_diff
dtype: float32
- name: cell_area_diff
dtype: float32
- name: pastr
dtype: float32
- name: pastr_diff
dtype: float32
- name: primf
dtype: float32
- name: primf_diff
dtype: float32
- name: primn
dtype: float32
- name: primn_diff
dtype: float32
- name: range
dtype: float32
- name: range_diff
dtype: float32
- name: secdf
dtype: float32
- name: secdf_diff
dtype: float32
- name: secdn
dtype: float32
- name: secdn_diff
dtype: float32
- name: urban
dtype: float32
- name: urban_diff
dtype: float32
- name: ELUC
dtype: float32
- name: cell_area
dtype: float32
- name: country
dtype: float64
- name: crop
dtype: float32
- name: crop_diff
dtype: float32
- name: country_name
dtype: string
- name: time
dtype: int64
- name: lat
dtype: float64
- name: lon
dtype: float64
splits:
- name: train
num_bytes: 6837499488
num_examples: 41630020
download_size: 3195082319
dataset_size: 6837499488
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
--- |