Welcome to STIMP's documentation!
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The python repository ``STIMP`` (`GitHub repository <https://github.com/YangLabHKUST/STIMP>`_) implements the methods in the **STIMP** paper.
STIMP an advanced AI framework to impute and predict Chl_a across a broad spatiotemporal scale in coastal oceans. 
STIMP's results can be utilized to diagnose and analyze the ecosystem health of coastal oceans based on the remote sensing measurement.


In this tutorial website, we provide guidelines for using ``STIMP`` along with remote sensing Chl_a data analysis examples, including imputation and prediction.
The source code for building the website can be found at https://github.com/Ryanfzhang/STIMP-tutorials.

Contents
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.. toctree::
   :maxdepth: 3

   installation.rst
   usage.rst
   baselines.rst
   analysis/index.rst
   supplementary/index.rst

Reference
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If you find the ``STIMP`` package or any of the source code in this repository useful for your work, please cite:

   | AI-powered spatiotemporal imputation and prediction of chlorophyll-a concentration in coastal ecosystems.
   | Fan Zhang, Hiuseut Kung, Fa Zhang, Can Yang and Jianping Gan.
   | 2025.

Development
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The python repository ``STIMP`` is developed and maintained by `Fan Zhang <https://ryanfzhang.github.io>`_.

Contact
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Please feel free to contact `Fan Zhang <mafzhang@ust.hk>`_, `Prof. Can Yang <macyang@ust.hk>`_, or `Prof. Jianping Gan <magan@ust.hk>`_ if any inquiries.