IEEE Geoscience and Remote Sensing Magazine - December 2020 - 103

Disaster Damage
Assessment

Environmental
Modeling

Urban Form and
Function

Earthquakes

Landslides

Change Detection

DTM

Agriculture, Forestry,
and Related Activities

FIGURE 4. Research areas using remote sensing and crowdsourcing integration.

30 28
25
20
15

OSMAnd

1
Globe

1
Geo-Wiki

1
MapSwipe

Bing Maps

2
OSM

2
Bing Aerial

Google Earth

Google Maps

Aerial

SAR

MSI

Lidar

GNSS

13
10

Sensors and Platforms
FIGURE 5. Sensors used for crowdsourcing. GNSS: global navigation satellite system.

WHICH SENSORS WERE USED IN THE STUDIES?
Figure 5 clearly demonstrates that MSIs are used in most
of the studies. Those are followed by OSM, SM, aerial
images, Google Earth, and other sensors and platforms.
The importance of OSM and Geo-Wiki platforms is that
they are created by crowds. As a data source, these platforms play an important role in meeting the need for
data in scientific studies. New sensors and sensing technologies, smartphones, GPS, web 2.0, and cloud computing make it easier to acquire and share geographic
data. In addition, digital information (from Wikipedia,
OSM, Geo-Wiki, Flickr photos, YouTube videos, Facebook, Twitter, and other sources) can be used to tag geographic data in specific areas. All these developments
show the importance of SM platforms in data production and sharing.
DECEMBER 2020

Flood Management

Data Quality

Land Cover

Number of Studies

16
14
12
10
8
6
4
2
0

Number of Studies

used together effectively for assessing damage from natural disasters.
Another application area in which
crowdsourcing and remote sensing
are used together is land cover classification, as can be seen from Figure 4.
LULC takes place continuously and
will continue without slowing down.
Changes to the Earth's surface are
both artificial (human intervention)
and natural (tsunamis, earthquakes,
melting of glaciers, landslides, and
so on). Artificial change is now much
faster, and the two most important
factors that trigger it are technological
development and the growing human population. This major change
also poses a significant environmental problem worldwide. Human-induced changes in LULC over the last
150 years have led to enormous emissions of carbon into the atmosphere
[48]. Although the use of fossil fuels
is the predominant source of carbon
emissions into the atmosphere, land
use still accounts for a significant
proportion (~20%) of anthropogenic
emissions, particularly in tropical
regions [49]. Knowledge of LULC is
required to manage natural resources
and monitor global environmental
changes and their consequences [50].
The most important source of this
information is remotely sensed data.
The further introduction of crowdsourcing for the purpose of examining, processing, and editing these
data can produce faster and more accurate results.

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

WHEN WAS THE STUDY CONDUCTED?
When the Geo-Wiki Project launched in 2009 to enhance
the accuracy of global land cover mapping, a significant increase in the use of crowdsourcing for remote sensing was
observed, and this trend has continued exponentially
since 2013. Because the data for this study were collected
before the end of 2019, it is not known what the total number of studies were that year, but clearly the total if all the
studies were counted would be many more than in 2018
(Figure 6). This shows us that the scientific literature on the
use of crowdsourcing in the field of remote sensing science
has grown and the number of publications in recent years
(2015-2019) has been increasing significantly.
FUTURE DIRECTIONS
How will the current trend of integrating crowdsourcing and
remote sensing evolve? Is crowdsourcing a useful method?
103

IEEE Geoscience and Remote Sensing Magazine - December 2020

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - December 2020