diff --git a/README.md b/README.md
index 8dfc8e6f..9e086b9c 100644
--- a/README.md
+++ b/README.md
@@ -36,13 +36,11 @@ pyCSEP can be installed in several ways. It can be installed using conda or pip
 source code found in the pyCSEP github repo. Researchers interested in contributing to pyCSEP development should 
 install pyCSEP from source code. pyCSEP depends on the following software packages. 
 These which may be installed automatically, or manually, depending on the installation method used.
-* Python 3.7 or later (https://python.org)
+* Python 3.9 or later (https://python.org)
 * NumPy 1.21.3 or later (https://numpy.org)
 * SciPy 1.7.1 or later (https://scipy.org)
 * pandas 1.3.4 or later (https://pandas.pydata.org)
-* cartopy 0.20.0 or later (https://scitools.org.uk/cartopy/docs/latest)
-* GEOS 3.7.2 or later (https://trac.osgeo.org/geos/)
-* PROJ 8.0.0 or later (https://proj.org/)
+* cartopy 0.22.0 or later (https://scitools.org.uk/cartopy/docs/latest)
 
 Please see the [requirements file](https://github.com/SCECcode/pycsep/blob/master/requirements.yml) for a complete list 
 of requirements. These are installed automatically when using the `conda` distribution.
diff --git a/docs/getting_started/installing.rst b/docs/getting_started/installing.rst
index c37b8a41..d9c0fd07 100644
--- a/docs/getting_started/installing.rst
+++ b/docs/getting_started/installing.rst
@@ -5,7 +5,7 @@ We are working on a ``conda-forge`` recipe and PyPI distribution.
 If you plan on contributing to this package, visit the
 `contribution guidelines <https://github.com/SCECcode/pycsep/blob/master/CONTRIBUTING.md>`_ for installation instructions.
 
-.. note:: This package requires >=Python 3.7.
+.. note:: This package requires >=Python 3.9.
 
 The easiest way to install PyCSEP is using ``conda``. It can also be installed using ``pip`` or built from source.
 
@@ -22,29 +22,25 @@ Before this installation will work, you must **first** install the following sys
 should be installed by the installation script. To help manage dependency issues, we recommend using virtual environments
 like `virtualenv`.
 
-| Python 3.7 or later (https://python.org)
+| Python 3.9 or later (https://python.org)
 |
-| NumPy 1.10 or later (https://numpy.org)
+| NumPy 1.21.3 or later (https://numpy.org)
 |     Python package for scientific computing and numerical calculations.
 |
-| GEOS 3.3.3 or later (https://trac.osgeo.org/geos/)
-|     C++ library for processing geometry.
+| SciPy 1.7.1 or later (https://scipy.org)
+|     Python package that extends NumPy tools.
 |
-| PROJ 4.9.0 or later (https://proj4.org/)
-|     Library for cartographic projections.
-
-Example for Ubuntu: ::
-
-    sudo apt-get install libproj-dev proj-data proj-bin
-    sudo apt-get install libgeos-dev
-    pip install --upgrade pip
-    pip install numpy
+| Pandas 1.3.4 or later (https://pandas.pydata.org)
+|     Python package for data analysis and manipulation.
+|
+| Cartopy 0.22.0 or later (https://scitools.org.uk/cartopy/)
+|     Python package for geospatial data processing.
 
-Example for MacOS: ::
+Example for Ubuntu and MacOS: ::
 
-    brew install proj geos
+    git clone https://github.com/sceccode/pycsep
     pip install --upgrade pip
-    pip install numpy
+    pip install -e .
 
 Installing from Source
 ----------------------
@@ -54,13 +50,13 @@ the latest GitHub commit.
 
 We recommend using virtual environments when installing python packages from source to avoid any dependency conflicts. We prefer
 ``conda`` as the package manager over ``pip``, because ``conda`` does a good job of handling binary distributions of packages
-across multiple platforms. Also, we recommend using the ``miniconda`` installer, because it is lightweight and only includes
+across multiple platforms. Also, we recommend using the ``miniconda`` or the ``miniforge`` (which uses mamba for a faster dependency handling) installers, because it is lightweight and only includes
 necessary pacakages like ``pip`` and ``zlib``.
 
 Using Conda
 ***********
 
-If you don't have ``conda`` on your machine, download and install `Miniconda <https://docs.conda.io/en/latest/miniconda.html>`_. ::
+If you don't have ``conda`` on your machine, download and install `Miniconda <https://docs.conda.io/en/latest/miniconda.html>`_ or `Miniforge <https://github.com/conda-forge/miniforge>`_ ::
 
     git clone https://github.com/SCECcode/pycsep
     cd pycsep