DOI: 10.5061/dryad.1925k
title: Data from: Integrating remotely sensed fires for predicting deforestation for REDD+

description: Fire is an important tool in tropical forest management, as it alters
 forest composition, structure, and the carbon budget. The United Nations
 program on Reducing Emissions from Deforestation and Forest Degradation
 (REDD+) aims to sustainably manage forests, as well as conserve and
 enhance their carbon stocks. Despite the crucial role of fire management,
 decision-making on REDD+ interventions fails to systematically include
 fires. Here, we address this critical knowledge gap in two ways. First, we
 review REDD+ projects and programs to assess the inclusion of fires in
 monitoring, reporting and verification (MRV) systems. Second, we model the
 relationship between fire and forest for a pilot site in Colombia using
 near-real-time (NRT) fire monitoring data derived from the Moderate
 Resolution Imaging Spectroradiometer (MODIS). The literature review
 revealed fire remains to be incorporated as a key component of MRV
 systems. Spatially-explicit modeling of land use change showed the
 probability of deforestation declined sharply with increasing distance to
 the nearest fire the preceding year (multi-year model area under the curve
 [AUC] 0.82). Deforestation predictions based on the model performed better
 than the official REDD early-warning system. The model AUC for 2013 and
 2014 was 0.81 compared to 0.52 for the early warning system in 2013 and
 0.68 in 2014. This demonstrates NRT fire monitoring is a powerful tool to
 predict sites of forest deforestation. Applying new, publicly available,
 and open-access NRT fire data should be an essential element of
 early-warning systems to detect and prevent deforestation. Our results
 provide tools for improving both the current MRV systems, and the
 deforestation early-warning system in Colombia.
description: Spatial grid with fire
 and forest loss dataSpatial grid with fire
 and forest loss data, pixels are in decimal degrees. def = deforestation 0
 no 1 loss, yloss = year of loss, fire =fire recorded 0 no 1 yes, yfire =
 year of fire, disedge09 = distance to forest edge in
 2009.bothgridandfire.csvVeredas de ColombiaSubmunicipal geographic units of Colombia (veredas) in shapefile format.Veredas_de_Colombia.zipR script for INLA deforestation modelingR script to organize data and fit deforestation models, creates first version of file fires.Rdata to be analyzed further downstream requires files bothgridandfire.csv and Veredas_de_Colombia.shp in the same folder. Unzip Veredas_de_Colombia.zip to recreate the shapefile data.fires.RR script to make predictions based on INLA modelingR script to make plots and predictions. Takes file fires.Rdata generated by fires.R and continues analyses, calculates AUC, makes plots.predict.RR script to compare models to forest loss alert systemR script to compare to the "Alertas Tempranas" system. Data from "Alertas Tempranas" are in a folder called /raster_alertas. Takes file fires.Rdata from predict.R and compares those results to results from the national deforestation alert system.compare.R2013 and 2014 early warning system alertsZipped folder with 2013 and 2014 early warning alerts for the region of analysis in Colombia. Place folder in the folder with compare.R script to replicate analysis.raster_alertas.zip