Code and Data for the paper "A Multi-Level Bayesian Analysis of Urban and Rural Warming Trends Across Global Climates"

作者：Panagiotis Sismanidis, Benjamin Bechtel · 发表于：Open MIND · 年份：2026 · DOI：10.5281/zenodo.19470768 · 被引用次数：1 · 研究领域：Environmental science、Climatology、Meteorology、Geography、Environmental resource management、Computer science、Remote sensing

This repository contains code and data supporting the analysis reported in "A Multi-Level Bayesian Analysis of Urban and Rural Warming Trends Across Global Climates" (preprint title: "Urban and Rural Warming Trends from MODIS are Statistically Indistinguishable") The study uses MODIS Land Surface Temperature (LST) data together with a multi-level Bayesian model to quantify warming rates across densely populated climate zones and to assess the effect of urbanization.