sesame-iesd 1.0.1

A simple Python package for SESAME toolbox

SESAME Project

About

The SESAME project aims to unify key human and non-human (Earth system) datasets into a shared spatially-gridded format. These datasets are often siloed in incompatible formats (eg. csv, tiff, netcdf, shp, etc.); SESAME improves interdisciplinary data discoverability and interoperability for research and modeling the global human system.

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📑 Table of Contents

• Main Tools
• Installation Instructions
• Dependencies
• Human-Earth Atlas
• Software Documentation
• Contact

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Main Tools

• point_2_grid
  Maps point data onto standardized global grids. Supports counting points per cell, summing or averaging associated values, or grouping by class to generate multi-variable datasets.

• line_2_grid
  Maps line data onto global grids by calculating the length of each line segment within grid cells. Supports aggregation methods such as mean, max, or standard deviation through spatial intersections.

• poly_2_grid
  Handles polygon data by computing the fraction or area of each polygon that overlaps with each grid cell. Supports combining multiple polygon types into a multi-variable NetCDF output.

• grid_2_grid
  Converts raster data to a new grid resolution. Ensures global coverage, checks projections, fills in missing cells with NaNs, and supports aggregation methods like sum, mean, max, min, or standard deviation.

• table_2_grid
  Converts jurisdiction-level tabular data into standardized grids using surrogate variables. Accounts for boundary changes over time for accurate spatial representation.

• add_iso3_column
  Standardizes country names by converting them to ISO3 codes. This function is a prerequisite for running table_2_grid.

• grid_2_table
  Reverses the gridding process by aggregating gridded data into summary tables based on predefined regions or countries.

• Built-in plotting functions
  SESAME also includes tools for quick visualization and mapping, such as plot_histogram, plot_scatter, plot_time_series, and plot_hexbin for charts, and plot_map, plot_country for gridded or choropleth maps. These functions help generate both exploratory plots and publication-ready outputs with minimal setup.

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Installation Instructions

If you're using conda to manage your Python environment:

Step 1: Create and activate the environment

# create a new conda environment
conda create -n sesame_env
# activate the environment
conda activate sesame_env
# Install all geospatial dependencies via conda
conda install -c conda-forge gdal rasterio cartopy geopandas h5netcdf matplotlib

# install SESAME from testPyPI
pip install sesame-iesd

Step 2: Add this as a Python code snippet:

import sesame as ssm 

If you are using Windows and encounter the error:

"ERROR: Failed building wheel for cartopy," please follow these steps:

1. Download and install the Microsoft C++ Build Tools from the official website:
   https://visualstudio.microsoft.com/visual-cpp-build-tools/

2. During installation, make sure to select the "Desktop development with C++" workload.
   This is required to build packages like cartopy that depend on C++ extensions.

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Dependencies

• geopandas>=1.0.1
• xarray>=2024.6.0
• h5netcdf>=1.3.0
• rasterio>=1.3.10
• matplotlib>=3.9.1
• seaborn>=0.13.2
• scipy>=1.14.0
• cartopy==0.23.0

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License

MIT License

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Human-Earth Atlas

Data Access:

Faisal, A. A., Kaye, M., Ahmed, M. & Galbraith, E. The SESAME Human-Earth Atlas. figshare https://doi.org/10.6084/m9.figshare.28432499 (2025).

Paper:

Faisal, A.A., Kaye, M., Ahmed, M. et al. (2025).The SESAME Human-Earth Atlas. Scientific Data, 12, 775. https://doi.org/10.1038/s41597-025-05087-5

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Software Documentation

Detailed setup, usage instructions, advanced features, and testing procedures are included in the official software manual:

📄 SESAME Software Manual (v1.1)

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Contact

For questions or inquiries about the SESAME project, please contact [e-mail] or [e-mail].