IEEE Geoscience and Remote Sensing Magazine - June 2021 - 110

Lack of technical support and difficulty with data formats
were cited as moderate to major barriers by 44%
and 33% of participants, respectively. Other written comments
included issues related to lack of Internet connectivity,
computational resources, and/or software to download
and analyze the data; absence of satellite imagery due
to clouds; and English language.
CASE STUDY: SUCCESSFUL IMPLEMENTATION
IN BOLIVIA
Here, we describe a specific example of how ARSET learning
content has been incorporated in research and decision
making. Cristina Karen Ovando Crespo is an assistant professor
at the Mayor de San Simon University, Cochabamba,
Bolivia, who teaches undergraduate- and graduate-level
courses in remote sensing applications for natural resources
(water and soil), disaster, and climate change management.
She began attending ARSET trainings in 2013. The experience
has enabled her to incorporate remote sensing into university
courses and contributed to an increase in the number
of students and faculty using remote sensing in research
and/or undergraduate- and graduate-level theses.
Karen related that ARSET improves their knowledge of
available remote sensing data and offers the ability to access
open source software and high-resolution imagery they
were previously unaware of: " Better and updated lecture
material in Spanish for remote sensing classes from a reliable
source is really important, especially nowadays that you
can find plenty of resources but not as accurate or didactic. "
Language is currently a considerable barrier to learning in
Bolivia, where fewer than 5% of technical experts are fluent
in English and most students' English language skills are not
advanced enough to use English-only materials:
Most of them are from low-income rural communities,
where the native language is Quechua and Aymara.
They learned technical Spanish in the school
and university, so learning English is difficult and
sometimes inaccessible to them.
Karen also finds value in the segregation of courses according
to theme and level of difficulty:
One of the strengths of ARSET is the various levels of instruction.
Students come with different levels of knowledge,
and this levels the playing field. Undergraduate
students start with the basic Spanish webinars, while
many graduate students can begin with the advanced
webinars. After they leave the university, ARSET
courses inspire participants to continue the capacitybuilding
process as they take their knowledge to their
own institutions and organizations.
Together with her students, Karen has also applied the
newly acquired skills to support several organizations. They
work with stakeholders in Raqaypampa, the first autonomic
territory in Bolivia:
Applying ARSET and NASA tools and products at no
cost, we are obtaining maps and images that are useful to
the communities and the indigenous territory, so we are
going from the desk to the field with shared knowledge
solutions: local, indigenous, and scientific. We are
Spatial or vertical data resolution is insufficient.
Frequency and/or timing of satellite overpasses is insufficient.
Uncertainty in long-term data continuity or availability.
Lack of technical support to handle these data.
Finding the data I need among the many data archives
and web portals.
Lack of confidence in remote sensing data due to limited
ground truthing.
Remote sensing data are not accurate enough.
Data format is too difficult to use.
28.2%
44.2%
32.7%
37.2%
37.6%
33.7%
34.8%
37.3%
35.7%
40.1%
34.4%
36.9%
34.3%
33.3%
32.6%
26.8%
01020304050
(%)
5.7%
14% 13.6%
10.8% 16.3%
11% 17.4%
7% 18.6%
11.4%
10.5%
8.6%
20.6%
21.4%
21.5%
31.7%
60 70 80 90 100
Slight Barrier Moderate Barrier Major Barrier Not a Barrier for me
FIGURE 6. Participants' answers to the question, " Regarding barriers, how did the following affect your ability to use remote sensing data? "
110
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE JUNE 2021

IEEE Geoscience and Remote Sensing Magazine - June 2021

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