Datasets:
Formats:
csv
Size:
1K - 10K
ArXiv:
Tags:
causal-inference
earth-observation
satellite-imagery
geospatial
observational-data
research-data
License:
File size: 1,834 Bytes
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---
dataset:
- name: Replication Data for Integrating Earth Observation Data into Causal Inference
tags:
- causal-inference
- earth-observation
- satellite-imagery
- geospatial
- observational-data
- research-data
configs:
- config_name: default
data_files:
- split: train
path: YandW_mat.csv # Default 'train' split in the viewer
license: mit
---
[](https://github.com/cjerzak/causalimages-software)
**Replication Data for:** Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities
**Details:**
`YandW_mat.csv` contains individual-level observational data. In the dataset, `LONGITUDE` and `LATITUDE` refer to the approximate geo-referenced long/lat of observational units. Experimental outcomes are stored in `Yobs`. The treatment variable is stored in `Wobs`. The unique image key for each observational unit is saved in `UNIQUE_ID`.
Geo-referenced satellite images are saved in
`./Nigeria2000_processed/%s_BAND%s.csv`, where the first "`%s`" refers to the image key associated with each observation (saved in `UNIQUE_ID` in `YandW_mat.csv`) and `BAND%s` refers to one of 3 bands in the satellite imagery.
**Code Link:** https://github.com/cjerzak/causalimages-software/
**Paper Reference:** Connor T. Jerzak, Fredrik Johansson, Adel Daoud. Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities. ArXiv Preprint, 2023. [[PDF]](https://arxiv.org/pdf/2301.12985)
For more information: [**PlanetaryCausalInference.org**](https://planetarycausalinference.org/).
[<img src="https://i0.wp.com/connorjerzak.com/wp-content/uploads/2024/08/EO_WorkflowVizV52.png?resize=1187%2C1536&ssl=1">](https://connorjerzak.com/gci-overview/)
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