Next Article in Journal
The Semantics of Web Services: An Examination in GIScience Applications
Previous Article in Journal
An Improved Neural Network Training Algorithm for Wi-Fi Fingerprinting Positioning
Article Menu

Export Article

Open AccessArticle

A Suite of Tools for ROC Analysis of Spatial Models

Centro de Investigaciones en Geografía Ambiental, Universidad Nacional Autónoma de México, Antigua Carretera a Pátzcuaro 8701, Col. Ex-Hacienda de San José de La Huerta, Morelia C.P. 58190, MIC, Mexico
Centro de Sensoriamento Remoto, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte-MG, 31270-901, Brazil
Graduate School of Geography, Clark University, 950 Main Street, Worcester, MA 01610-1477, USA
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2013, 2(3), 869-887;
Received: 25 July 2013 / Revised: 13 August 2013 / Accepted: 29 August 2013 / Published: 10 September 2013
PDF [637 KB, uploaded 11 September 2013]


The Receiver Operating Characteristic (ROC) is widely used for assessing the performance of classification algorithms. In GIScience, ROC has been applied to assess models aimed at predicting events, such as land use/cover change (LUCC), species distribution and disease risk. However, GIS software packages offer few statistical tests and guidance tools for ROC analysis and interpretation. This paper presents a suite of GIS tools designed to facilitate ROC curve analysis for GIS users by applying proper statistical tests and analysis procedures. The tools are freely available as models and submodels of Dinamica EGO freeware. The tools give the ROC curve, the area under the curve (AUC), partial AUC, lower and upper AUCs, the confidence interval of AUC, the density of event in probability bins and tests to evaluate the difference between the AUCs of two models. We present first the procedures and statistical tests implemented in Dinamica EGO, then the application of the tools to assess LUCC and species distribution models. Finally, we interpret and discuss the ROC-related statistics resulting from various case studies. View Full-Text
Keywords: accuracy; AUC; Dinamica EGO; LUCC; prediction; ROC; species distribution modeling; uncertainty; validation accuracy; AUC; Dinamica EGO; LUCC; prediction; ROC; species distribution modeling; uncertainty; validation

Figure 1

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Mas, J.-F.; Soares Filho, B.; Pontius, R.G.; Farfán Gutiérrez, M.; Rodrigues, H. A Suite of Tools for ROC Analysis of Spatial Models. ISPRS Int. J. Geo-Inf. 2013, 2, 869-887.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top