@Article{ArcanjoLuzFazeRamo:2016:MeEvVo,
author = "Arcanjo, Jeferson de Souza and Luz, Eduardo F. P. and Fazenda,
{\'A}lvaro L. and Ramos, Fernando Manuel",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {National
Center for Monitoring and Early Warning of Natural Disasters
(Cemaden)} and {Universidade Federal de S{\~a}o Paulo (UNIFESP)}
and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Methods for evaluating volunteers’ contributions in a
deforestation detection citizen science project",
journal = "Future Generation Computer Systems",
year = "2016",
volume = "56",
pages = "550--557",
month = "Mar.",
keywords = "Citizen science, Data analysis and validation, Forest
monitoring.",
abstract = "Today, due to the availability of free remote sensing data,
efficient algorithms for image classification and increased
connectivity and computing power, together with international
policy initiatives, such as the United Nations Programme on
Reducing Emissions from Deforestation and Forest Degradation
(UN-REDD), more and more countries are investing in their own
national forest monitoring schemes. However, tropical forests
remain under threat worldwide. Recently, a citizen science project
that enables citizens around the globe to be involved in forest
monitoring tasks has been proposed, called ForestWatchers
(www.forestwatchers.net). Its main goal is to allow volunteers
(many of them with no scientific training) around the globe, with
their own smartphones, tablets and notebooks, review satellite
images of forested regions and confirm whether automatic
assignments of forested and deforested regions are correct.
Inspected images are then sent to a central database where the
results are integrated to generate up-to-date deforestation maps.
This approach offers a low-cost way to both strengthen the
scientific infrastructure and engage members of the public in
science. Here, we describe the methods developed within the scope
of the ForestWatchers project to assess the volunteers
performance. These tools have been evaluated with data of two of
the projects preliminary tasks. The first, called BestTile, asks
volunteers to select which of several images of the same area has
the least cloud cover, while in the second, called Deforestation,
volunteers draw polygons on satellite images delimiting areas they
believe have been deforested. The results from more than 500
volunteers show that using simple statistical tests, it is
possible to achieve a triple goal: to increase the overall
efficiency of the data collecting tasks by reducing the required
number of volunteers per task, to identify malicious behavior and
outliers, and to motivate volunteers to continue their
contributions.",
doi = "10.1016/j.future.2015.07.005",
url = "http://dx.doi.org/10.1016/j.future.2015.07.005",
issn = "0167-739X",
language = "en",
targetfile = "arcanjo_methods.pdf",
urlaccessdate = "11 maio 2024"
}