model.aez
Project Drawdown Land Utilities for Solutions. There are three kinds of land divisions recognized within Project Drawdown:
- Regions: these are the geo-political regions such as OECD90 and Latin America
- Thermal-Moisture Regimes, aka TMR: designations such as Boreal-Humid, etc.
- AEZs: this is a custom PD analysis of land areas combining land type, soil quality and slope steepness
Geographical analysis to create a cross-correlation between these three dimensions has been done, and the original work is available at [https://github.com/ProjectDrawdown/spatial-aez].
Land-type solutions are usually only applicable within certain TMRs. Within a given TMR, multiple land solutions might compete for the same land. PD has established a priority between multiple solutions within AEZ types, and from that prioritization, determined a maximum available land allocation for each solution within each political region/TMR area. This is known as the "Total Land Allocation" or TLA, and it works analagously to the "Total Available Market" in other solutions.
The TLA is established by the integration process in integrationsez_land_integration.py
. The integration
process is run periodically to create updated TLAs which are stored in the data
directory.
Individuals may run the integration process themselves to replicate that work, or experiment with alternatives.
Currently PD models land types as unchanging over time. Future research may include forecasts of land changes over time, e.g. due to climate change modeling.
This module contains the classes for solution-specific land allocations.
See the module world_land
for global land data.
The AEZ object holds various land-based information applicable to a solution, including the allocated TLA
Args
- solution_name: full name of the solution (as returned by scenario.name)
- cohort: which land allocation series to use, defaults to most recent
- regimes: list of string names of thermal moisture regimes to use, defaults to standard
- max_tla: If true, the maximum suitable land available is returned, instead of the allocated land
The most granular version of land allocation. A dictionary mapping TMR names to Dataframes, which themselves are indexed by region and have AEZ zones as columns, and allocations for this solution as values.
Land allocation broken down by region and TMR. This is the result returned by get_land_distribution
and
commonly referred to as the TLA.