ecoEE

Ecologically relevant methods for Google Earth Engine

Matthew R. Helmus

Integrative Ecology Lab, Center for Biodiversity, Department of Biology, Temple University, Philadelphia, PA 19122 USA.

www.iecolab.org

Google Earth Engine (EE) is a "planetary-scale platform for earth science data & analysis." It combines cloud-based supercomputing with a huge spatial data catalog in one platform that can be accessed via a Python and JavaScript API. The latter can be used in a browser window with the Earth Engine Interactive Development Environment (IDE).

The purpose of this repository is to provide relevant primers on the EE APIs and IDE for ecologists and others in the environmental sciences. Each folder is a sub-repository built on JavaScript, R or Python. At this time, only the JavaScript sub-repository has been fully developed and include useful functions and examples. We developed the JavaScript repository first because it allows access to the IDE. The goal of the future Python repository is to reproduce the ecoEE JavaScript functions in Python to be used with the EE Python API. The goal of the future R repository is an R package that takes the ecoEE-js (and eventually ecoEE-py) output and loads it into R for downstream analyses.

Table of Contents

Citation
Installation Instructions
Primer
Notes
Feedback

---

Citation

Helmus, M.R and E. Zangakis. (2019) ecoEE: Ecologically relevant methods for Google Earth Engine. v0_1 https://github.com/ieco-lab/ecoEE DOI 10.5281/zenodo.2398922

Installation Instructions

See the individual code repositories for installation instructions.

Primer

If you are new to EE then we suggest taking a look at our paper LINK TO BE INSERTED that describes EE in the context of ecological research.

Notes

Only ecoEE-js is fully developed. Please contact Matt Helmus if you are interested in helping to develop the ecoEE-py or ecoEE-R repositories.

Feedback

Please read and follow these simple rules before submitting a feature, bug or pull request

(these rules are blatantly copied from here)

• If you have a new idea for how the scripts should be restructured, please open an issue (tagged 'enhancement') to discuss it first before making a pull request.

• If you you've found a bug, open an issue (tagged 'bug') that contains a minimal, complete, and verifiable example. We'll try and get back to you quickly. If you are able to solve the bug on your own, please post the correction.

• If you have a feature request, open an issue (tagged 'enhancement') to discuss it. We're much more likely to be able to do it if you can be clear and concise about what you want, and if you have already written some code that you would like to merge. If you are requesting a complicated analysis technique that is not available, then consider bringing one of the authors of the individual code repositories on as a collaborator.