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README.md

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@@ -10,9 +10,8 @@ Below a short guide to: perform the uncertainty analysis of your own DEMs, retri
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## Uncertainty analysis of your own data with xDEM
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The results of this study are based on routines implemented in [xDEM](https://github.com/GlacioHack/xdem) with
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documentation at [https://xdem.readthedocs.io/](https://xdem.readthedocs.io/). xDEM includes tutorials to perform
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uncertainty analysis of your own DEM data based on this article.
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The methods of this study are implemented in [xDEM](https://github.com/GlacioHack/xdem), in routines that can be used to perform uncertainty analysis of your
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own DEM data.
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There are **three basic examples** with:
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- The detailed steps to [estimate and model the spatial correlation of elevation errors](https://xdem.readthedocs.io/en/latest/advanced_examples/plot_variogram_estimation_modelling.html#sphx-glr-advanced-examples-plot-variogram-estimation-modelling-py),
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- The detailed steps to [standardize elevation differences to use stable terrain as a proxy](https://xdem.readthedocs.io/en/latest/advanced_examples/plot_standardization.html#sphx-glr-advanced-examples-plot-standardization-py).
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The full documentation of xDEM can be found at [https://xdem.readthedocs.io/](https://xdem.readthedocs.io/).
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***Note at the date of 07.11.22:** xDEM is still in development (version 0.0.7), and its documentation in
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construction. Compared to version 0.0.6 used in this repository, several changes were added to xDEM late 2022,
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including:*
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the full distribution of samples, not only the binned estimates of dispersion).
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For plotting figures of your own data, xDEM provides simpler plotting tools of binned data and variograms
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(see [example gallery](https://xdem.readthedocs.io/en/latest/auto_examples/index.html)).
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(see [example gallery](https://xdem.readthedocs.io/en/latest/basic_examples/index.html)).
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Enjoy! :volcano:

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