GithubHelp home page GithubHelp logo

e-baynerd's Introduction

e-BayNeRD

Enhanced Bayesian Network for Raster Data

  • The e-BayNeRD model is an enhanced version of the BayNeRD (Bayesian Network for Raster Data) model, which was developed by Mello et al (2013):

MELLO, M. et al. Bayesian Networks for Raster Data (BayNeRD): Plausible Reasoning from Observations. Remote Sensing, v. 5, n. 11, p. 5999–6025, 15 nov. 2013. link

  • The implemented improvements are described in the following conference paper:

SILVA, A. C. O.; MELLO, M. P.; FONSECA, L. M. G. Enhancements to the Bayesian Network for Raster Data (BayNeRD). XV Brazilian Symposium on GeoInformatics (2014). Proceedings of the Brazilian Symposium on GeoInformatics, Campos do Jordão, São Paulo, Brazil. link

  • To cite the e-BayNeRD model, please refer to the following papers

SILVA, A. C. O.; FONSECA, L. M. G.; KORTING, T. S.; ESCADA, M. I. S.. A spatio-temporal Bayesian Network approach for deforestation prediction in an Amazon rainforest expansion frontier. Spatial Statistics, v. 35, p. 100393, mar. 2020. link

SILVA, A. C. O.; FONSECA, L. M. G.; KORTING, T. S.. Bayesian network model to predict areas for sugarcane expansion in Brazilian Cerrado. Brazilian Journal of Cartography (2017), Nº 69/5, Special Issue GEOINFO 2017: 857-867. Brazilian Society of Cartography, Geodesy, Photgrammetry and Remote Sense ISSN: 1808-0936. link

  • Papers that employed the e-BayNeRD model:

NG, W. T. et al. Ensemble approach for potential habitat mapping of invasive Prosopis spp. in Turkana, Kenya. Ecology and Evolution, v. 8, n. 23, p. 11921–11931, 2018. link

To run

To run the e-BayNeRD model:

  • Download the e-BayNeRD.r file to your working folder.
  • In the RGui, set the working folder:
setwd("./your_working_folder")
  • And run the following command to activate the e-BayNeRD menu in R (as highlighted in the image below).
source("e-BayNeRD.r")

e-baynerd

e-baynerd's People

Contributors

alexsandrocandido avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.