Accepted paper in IEEE-JSTARS
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The paper, "A Badging System for Reproducibility and Replicability in Remote Sensing Research",

by Alejandro C. Frery (LaCCAN—Laboratório de Computação Científica e Análise Numérica, Universidade

Federal de Alagoas, Maceió, Brazil) , Luis Gomez (CTIM, Universidad de Las Palmas de Gran Canaria,

Las Palmas de Gran Canaria, Spain) and Atonio M. Souza (LaCCAN—Laboratório de Computação

Científica e Análise Numérica, Universidade Federal de Alagoas, Maceió, Brazil), has been accepted for

publication in IEEE-JSTARS (in press).


The works summarizes the research done to promote the reproducibility in the area of Remote Sensing

(see the abstract below).


IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing is an indexed

Journal with Impact Factor of 3.827 (according to Journal Citation Reports), specially devoted to

applications in Earth observations and remote sensing. These include biodiversity, health and climate.

Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers,

signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS.

Thus, the Journal attracts a broad range of interests that serves both present members in new ways

and expands the IEEE visibility into new areas.


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A Badging System for Reproducibility and Replicability in Remote Sensing Research

Alejandro C. Frery, Senior Member, IEEE, Luis Gomez, Senior Member, IEEE, and Antonio C. Medeiros


Abstract—Remote Sensing is both an active research area and the source of valuable information

for decision-making. Many actors play a fundamental role in Remote Sensing, from industry

(public or private) to large or small research groups. From that intensive activity, methods,

algorithms, and techniques are continuously published or broadcasted through papers, conference

presentations, repositories, patents, standards, and other means. The consumers of that information

need it to be readily available and dependable. Reproducible research can handle those needs.

In this paper, we discuss two concepts: reproducibility and replicability in the context of Remote Sensing

research. We propose a badging system suited to the specifics of the Remote Sensing community.

Such a system aims at both recognizing the level of the reproducibility of the research, and to help

increase its visibility. We show examples of reproducible research and provide clues to make easier

the transition to the inevitable new times that embrace contemporary Science and Technology.

Index Terms—Reproducibility, Replicability, Remote Sensing