  Rainforests play an important role in the global ecosystem. However,
significant regions of them are facing deforestation and degradation due to
several reasons. Diverse government and private initiatives were created to
monitor and alert for deforestation increases from remote sensing images, using
different ways to deal with the notable amount of generated data. Citizen
Science projects can also be used to reach the same goal. Citizen Science
consists of scientific research involving nonprofessional volunteers for
analyzing, collecting data, and using their computational resources to outcome
advancements in science and to increase the public's understanding of problems
in specific knowledge areas such as astronomy, chemistry, mathematics, and
physics. In this sense, this work presents a Citizen Science project called
ForestEyes, which uses volunteer's answers through the analysis and
classification of remote sensing images to monitor deforestation regions in
rainforests. To evaluate the quality of those answers, different
campaigns/workflows were launched using remote sensing images from Brazilian
Legal Amazon and their results were compared to an official groundtruth from
the Amazon Deforestation Monitoring Project PRODES. In this work, the first two
workflows that enclose the State of Rond\^onia in the years 2013 and 2016
received more than $35,000$ answers from $383$ volunteers in the $2,050$
created tasks in only two and a half weeks after their launch. For the other
four workflows, even enclosing the same area (Rond\^onia) and different setups
(e.g., image segmentation method, image resolution, and detection target), they
received $51,035$ volunteers' answers gathered from $281$ volunteers in $3,358$
tasks. In the performed experiments...
