Research data: A parsimonious Markov chain framework for national land-use and emissions scenarios — New Zealand 2022–2050

This dataset contains the research data supporting the manuscript "A Parsimonious Markov Chain Framework for National Land-Use and Emissions Scenarios: Implications for Climate Mitigation in New Zealand" submitted to Land Use Policy (Elsevier). The data were generated as part of an independent study undertaken after completing a PhD degree programme in New Zealand, and is not directly affiliated with that doctoral research. The research applies a Markov chain modelling framework to project national land-use dynamics and associated greenhouse gas emission trajectories under four climate policy scenarios through 2050, calibrated entirely on publicly available secondary data from New Zealand's institutional data architecture. Contents: Transition probability matrices; multinomial variance-covariance estimates; scenario-modified transition matrices; emission coefficients (IPCC AR5 GWP100 basis); baseline land-use areas; projected land-use areas and net LULUCF emissions 2022–2050; Monte Carlo credible intervals; one-at-a-time sensitivity analysis results; and stationarity test outputs.