Overview

Overview#

Software Tools#

In this course, we will use essential software tools that streamline development, version control, and geospatial analysis. Make sure you have these installed and configured:

  • Visual Studio Code: A lightweight, highly customizable code editor with robust extensions for Python development.

  • Git: A version control system for tracking code changes and collaborating on projects.

  • Miniconda or Anaconda: Python distribution platforms that simplify environment management and package installation.

  • QGIS: An open-source GIS software that complements Python tools for geospatial data visualization and analysis.

Tip: If you’re new to any of these tools, refer to their official documentation for setup guides or seek tutorials in the course Software Tools section.

Cloud Computing Platforms#

Geospatial analysis often involves large datasets and computationally intensive tasks. Cloud platforms provide scalable solutions to handle these efficiently. Here are some popular options:

  • Google Colab: A free Jupyter notebook environment with pre-installed Python packages, ideal for coding on the go. We will primarily use this platform in the course.

  • Google Earth Engine: A cloud-based platform for processing geospatial data, especially remote sensing imagery.

  • Amazon SageMaker Studio Lab: Offers free cloud computing resources for Python-based machine learning and data analysis.

  • Microsoft Planetary Computer: Provides geospatial datasets and APIs for large-scale environmental analysis.

Why Use Google Colab?#

  • Accessibility: Works entirely in the browser, so no setup is required.

  • Free Resources: Includes free access to GPUs/TPUs for advanced computations.

  • Integration: Supports popular geospatial libraries like GeoPandas, Shapely, and Leafmap out of the box.

To get started, visit colab.research.google.com and sign in with your Google account.

Install Python Packages#

There are different ways to install Python packages. The most common methods are using pip or conda. Here are some examples:

To install packages using pip:

pip install leafmap

To install packages using conda:

conda install leafmap -c conda-forge

To install packages from a GitHub repository:

pip install git+https://github.com/opengeos/leafmap.git

To install packages from a requirements.txt file:

pip install -r requirements.txt
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