ThompsonMark_CapstoneResearch

Running head: Advancing Geospatial Technology Applied to Sustainable Development Theory
California State University, Monterey Bay, Seaside, California
Undergraduate Capstone Research Analysis
Advancing Geospatial Technology
Applied to Sustainable
Development Theory
Application of unmanned aerial vehicles and remote sensing applied to
environmental land management and precision agriculture
Mark S. Thompson
Dr. Yong Lao
May 5, 2016

Advancing Geospatial Technology Applied to Sustainable Development Theory 2
Abstract
Present day technology has become an innovating aspect in geospatial assistance when observing
the earth’s environment. Goals for environmental sustainable development have led to the global
monitoring of population, human footprint, and environmental impact. This capstone applies
theory to research and makes correlations between advancing geospatial technology and how
such can be a contribution in achieving sustainable goals. This was done in part by the
observation of environmental land management and precision agriculture through the use of
unmanned aerial vehicles, remote sensing satellite imagery, and geographic information systems
(GIS). The results indicate that both satellite imagery and unmanned aerial vehicles were found
to be beneficial in analyzing the current state of the Fort Ord National Monument and a 12.5 acre
almond orchard in Ripon, California due to their ease in accessibility and data processing.
Further research findings, as well as analytical difficulties and future procedures and changes,
are discussed more in depth within the report.
Introduction
Global goals for environmental sustainable development are at the forefront of innovation
and creativity. As an ever-evolving global society, it is the responsibility for present day humans
to view the current state of the earth’s environment and make preparation for future generations
here on earth. The vast impact of the human footprint is evident in the earth’s environment when
considering endangered species, oceanic dead zones, glacier melts, and an overall rise in
atmospheric temperature. As global population continues to grow, increased international
industries, innovations, and expanding infrastructures contribute to overall pollution and e-waste.
To best meet the needs of the present day population without compromising the accessibility for
future generations, it is vital that humans utilize resources correlated and accessible when
researching sustainable development.
In order to best assess the situation of human footprint and environmental impact,
humans must set forth sustainable goals, ones that are within generational reach and ones that
provide a foundation for future generations to build upon. Utilizing state of the art technology
(unmanned aerial vehicles and satellite imagery) to assess and carry out these environmental

goals offers researchers and politicians a visual of the current global status. Such advances in
technology can also provide insight into spatial and temporal changes over multiple decades and
even centuries. Applying the skill sets of Geographic Information Systems (GIS) that I have
obtained thought my coursework, while expanding on the concepts of social theory; I chose to
research how the advancements of geospatial technology, unmanned aerial vehicle (UAV)
drones and remote sensing satellite imagery, can aid in the theory of environmental sustainable
development. Highlighting two specific advancements in geospatial technology, I will
demonstrate how remote sensing imagery and calculations, along with the use of unmanned
aerial vehicle drones carry out observations of both large scale and small scale sustainable
monitoring. Sustainable development is vast in ways in which it can be studied and dissected;
therefore I have chosen to focus my efforts on sustainable land management and precision
agriculture (PA).
This topic holds great interest with me due to my current status as an undergraduate
student studying social and behavioral sciences with a concentration in geographic information
systems. The premise of my capstone and overall hypothesis is to demonstrate how geospatial
technology, UAV drones, remote sensing imagery and GIS software can be applied to real world
social issues and concerns. Viewing this topic in-depth, I aimed to examine two categories that
dwell within the concept of environmental sustainable development. The first subject I will focus
on involves the concept of sustainable land management. Land management is a broad term that
addresses the integrating management of land, water, and overall biodiversity. Constructing long
term sustainability for multiple ecosystems can be a heavy task. In part, I will focus more
directly on the idea of urban and regional planning, as well as environmental land protection that
occurs on the Fort Ord National Monument.

As the demographic growth of Marina, CSU Monterey Bay, and surrounding areas
continues to expand, it is vital to view the current state of the former Fort Ord, address any issues
that may be a result to this potential growth and make predictions for future assessment of the
land. Within Fort Ord National Monuments (55,000 acres), remote sensing imagery and
calculations will hopefully provide aid when addressing my research questions: How can remote
sensing imagery and normalized difference vegetation index (NDVI) calculations assist in
displaying the current vegetation state of Coastal Live Oak trees (quercus agrifolia) within Fort
Ord National Monument? How will current and future growth of urban development on Fort Ord
directly harm the present ecosystems within the Fort Ord National Monument?
The second subject I will focus on within the concept of environmental sustainable
development is that of precision agriculture. Precision agriculture, also known as satellite
farming, is the observation, measuring and response to field variability in crops, depending on
the crop at hand, weather variables and global positioning. When observing precision agriculture,
both spatial and temporal components are comprised in taking pre and post-crop imagery.
Precision agriculture aims to optimize crop returns in comparison to initial input, all awhile
preserving resources vital to agricultural farming, such as the use of water and soil fertility. For
the second part of my capstone, I will demonstrate how the use of unmanned aerial vehicles
(UAV drones) can be utilized in precision agriculture for the ability to capture low altitude, high
resolution images for use of crop watch. Images were taken over a 12.5acre almond orchard
located in the San Joaquin County of California. As this land is owned by my family, this
granted me access to take pre and post-crop imagery, analyze annual financial input to output
variables and mosaic all UAV images using GIS software for final mapping purposes. Such data
and accessible technology led me in the following research questions: What benefits can UAV

Figure 1: Study areas for use in two separate case studies. Box A displays the Fort Ord National
Monument used to demonstrate the use of remote sensing imagery in the monitoring of
environmental land management. Box B displays a 14acre parcel of land located in Ripon,
California. The 12.5 acre Almond orchard located on the property was utilized in the demonstration
of unmanned aerial vehicles for use in precision agriculture.
drone imagery offer in the observation of precision agriculture? How does the use of UAV
imagery better improve precision agriculture when looking to reduce the environmental risks and
ecological footprint of farming?
Literature Review
Advancements in geospatial technology are fast-pace and growing within the industry.
This technology continues to branch out in multiple fields, including environmental protection,
urban planning, disaster relief, public health, natural resource extraction, precision agriculture,
journalism and military surveillance. With the growth of such technology, changes and additions
to theories, methods, tools and applications continue to evolve (van Manen, et al. 2009).

Geospatial technology is held at a global scale and it is vital to assess these advancements with
caution. Remote sensing and unmanned aerial vehicles have introduced a new realm of
observation and data retrieval. UAV’s offer real-time data with the allowance of instant
networking and such technology can offer aid in continuous global sustainability (Anderson,
Gaston 2013).
History of Unmanned Aerial Vehicles
Obtaining imagery from an aerial perspective has been an ongoing process that continues
to evolve. Historically, UAV’s have been directly affiliated with military surveillance and strike
missions since the beginning of the First World War. A decreased interest in automated and
remote piloted unmanned aerial vehicles took place directly after the war but heading into World
War II, Nazi Germany used this silent killer to their advantage. The United States military
observed the accessibility of UAV’s and put them to direct use when the U.S. went to war with
Vietnam, using UAV’s for stealth surveillance (Sullivan, 2005). Through the 1970’s, 1980’s and
into the 1990’s, UAV’s continued to expand in capacity and capability at a global rate. The 21st
century has offered the accessibility of UAV drones to branch out far beyond their initial
purpose. UAV’s play a pertinent roll in today’s military war missions, from the U.S. and Europe
to Asia and the Middle East; however, currently they are beginning to offer peaceful roles, such
as monitoring our earth's environment.
Advancements in Geospatial Technology:
New advancements in geospatial technology have made a lasting impact on ways in
which global monitoring is done; however, these advancements also come with downfalls and
regulations. UAV drones have fallen under strict regulations from the Federal Aviation
Administration and this leads to complications when utilizing UAV imagery and data for study

purposes. The accessibility from drones to survey and collect data in record time and at minimal
cost is almost unparalleled. The use and applications of drone technology are being expanded to
make the devices active tools in humanitarian and environmental protection work (Anderson,
Gaston 2013). These advancements have been full-fledged since NASA first released Explorer 1
in 1958, sent to obtain radiation levels in the earth’s orbit. In recent years, geospatial
advancements have allowed UAV’s to demonstrate a wide range of capabilities like never
before. Megan Lang (2009) also enlightens on this subject, stating “recent advances in the
quality and availability of remotely sensed data, as well as the introduction of new processing
and modeling methods, hold great potential for the further advancement of regional, national and
global mapping and monitoring efforts” (Lang, Awi, Wilen et al. 2009). Such advancements
provided by satellite and aerial imagery can offer aid in land management and precision
agriculture when addressing goals that are globally sustainable.
Unmanned Aerial Drones for use of Remote Sensing and Aerial Imagery
Advancements in geospatial technology can also be applied to a wide range of fields
within GIS remote sensing and aerial imagery. Victor Klemas narrows down the specifics of
time, cost and accuracy when using UAV in the comparison of satellite imagery. His research is
very similar to that of Robert Breckenridge’s work which views the comparison of Unmanned
Aerial Vehicle Platforms for assessing vegetation cover in sagebrush steppe ecosystems. Remote
sensing imagery can observe and survey a larger span of landscape; however time and cost can
hinder such capabilities. Images taken over large landscapes require the mosaicking of each
georeferenced point to produce small scale images. This has been analyzed by Gomez and a team
of researchers who assess the accuracy of mosaics from unmanned aerial vehicle imagery for
precision agriculture purposes in wheat fields (Gomez-Cando, De Castro, Lopez-Granados

2013). In doing so, accuracy of the mosaicked image determines the feasibility of using UAV’s
in such operations. Hardin dives deeper into such imagery obtained from UAV platforms as he
demonstrates his findings in the article An Unmanned Aerial Vehicle for Rangeland
Photography, published by the Society for Rangeland Management. Hardin examines multiple
sensor platforms to assess their use in multiple settings of aerial imagery (Hardin, Jackson 2005).
Matese and his team of researchers follow the same guidelines as Klemas and Breckenridge,
where Matese observes the intercomparison of UAV, aircraft and satellite remote sensing
platforms for precision viticulture. Here, three separate remote sensing platforms are employed
to produce and map normalized difference vegetation index (NDVI) images implemented within
precision viticulture (Matese, Toscano, Di Gennaro et al. 2015). Together, these articles
demonstrate the ability of unmanned aerial vehicles to be utilized within remote sensing
techniques and for obtaining large scale aerial imagery.
Application in Land Management and Precision Agriculture
Within the concept of sustainable development lies a collection of applications in which
focus directly on the issues of land, population growth and urban sprawl. Here, we can view how
two categories within sustainable development, precision agriculture and urban land
management, have been making vast changes over recent years. Precision agriculture (PA) views
how farmers are engaged in adaptive management in a highly variable and unpredictable
environment and therefore no farm (or farmer) is equally alike. Decision making and strategies
for site-specific crop management will be best achieved through experiments performed
economically on the farm, by farmers, using advanced tools for precision agriculture (McBratney
et.al. 2005). These advanced tools include two specific techniques that will be used within my
capstone; the use of UAV imagery and remote sensing techniques and calculations. Site-specific

management of agricultural fields has the potential to increase crop yields and profitability, while
minimizing environmental contamination. Farmers will be better able to implement site specific
management practices when they understand the causes of spatial and temporal variability of
their field. Using geographic information systems (GIS), yield monitors, aerial imagery, and soil
analysis can aid in examining the relationships between crop yield and terrain and soil properties
across multiple production fields (Kaspar et.al., 2003).
Land management, better focused towards urban development and habitat conservation,
can be addressed within the concept of environmental sustainable development as well.
Sustainable land management looks to meet the needs of an ever-growing global population and
monitor forestry and agriculture industries with respect to demographic growth and increasing
pressure on land use. As urban populations in developing countries continue to increase, food
and fiber supply is reduced, creating greater strain on agricultural land use and resources that
supply against these rising demands (The World Bank, 2006). As urban sprawl surrounds land
utilized for habitat conservation and that of preexisting habitats, it is vital to produce
environmental impact assessments (EIA) in order to fully delegate land use and potential effects.
Land degradation is a long-term loss of terrestrial ecosystem goods and services. Land
degradation and improved land management approaches involve evaluating the costs of land
loss, including short-term and long-term, direct and indirect, and both on-site and off-site
benefits of sustainable land management. Such evaluations are used in comparison to the overall
corresponding cost of total land degradation. This now leads to an estimated 40% of the earth’s
land in seriously degraded condition (Mirzabaev, et.al. 2015).

Theory
The theory of sustainable development can be directly correlated to the surrounding
environmental changes that are happening on a global scale. John Overton, in his book entitled
Strategies for Sustainable Development, states “Sustainable development has lead to the
exploration of diverse theoretical avenues, it has encompassed a wide range of disciplinary
approaches and it has fostered changes in development practice world-wide” (pg.1). Such
theoretical avenues branch off into categories much like the two in which I have chosen for my
capstone research, environmental land management and precision agriculture. However, what
does it mean to focus on sustainable development when viewing social and global issues?
Hartmet Bossel (1999), author of Indicators of Sustainable Development: Theory, Method,
Applications defines sustainable development as “economic development that meets the needs of
the present generation without compromising the ability of future generations to meet their own
needs” (pg.2). Bossel clearly lays out the foundation for practical sustainability; however, when
trying to balance environmental sustainability, it is important to view its history. Mebratu
touches on this topic as his review analyzes the environmental parallels in human history, the
historical perspective of the evolution of the concept of sustainable development, and the current
definitions and interpretations of sustainable development. Gaining comprehension of geospatial
advancements includes applications and methods that are utilized when applied to sustainable
development (Mebratu, 1998). Much of what today’s global society defines sustainable
development as is drawn from the 1987 book published by the WCED (United Nations World
Commission on Environment and Development) entitled Our Common Future. In this book,
three main goals are brought to light, 1) to examine environmental and developing global issues
and construct proposed actions on resolution, 2) to construct international cooperation of global

sustainable goals and 3) to raise the awareness of global societies to issues that concern today’s
global environment.
Many of the common topics the United Nations now aim to gain control and equalize are
focused around population growth, food security, climate change adaptation, renewable energy
sources and watershed science and distribution. The United Nations has also constructed a 2030
Future Goals Report which highlights 17 SDG’s (sustainable development goals) that address
issues worldwide. For example, goal 1 seeks to end poverty in all forms globally, goal 5 looks to
achieve gender equality for all, goal 2 hopes to promote sustainable agriculture, goal 13 aims to
take urgent action in the combat for climate change and goal 15 seeks the protection and
promotion of sustainable ecosystems and an increase in overall biodiversity (United
Nations.com, 2016). Many of these sustainable goals overlap one another and this leads to
complications when striving to gain global participation. One example compares population
growth to biodiversity. It is difficult to develop strong sustainable agricultural goals for an ever-
growing global population while simultaneously applying the same efforts focusing on the
preservation of a diminishing biodiversity, both flora and fauna. Many of these issues arise from
the continuously expanding population. Sustainable development is achievable in locations
where the population remains below or level to the productivity and renewability of the
surrounding ecosystem (WCED, 1983). Environmental monitoring and observation of these
densely populated countries is important to the sustainability and longevity of their surrounding
ecosystems. The monitoring of environment can greatly benefit from these geospatial
technological advancements which I have addressed within my capstone research. Focusing on
sustainable land management and precision agriculture, I am able to demonstrate the

accessibility of remote sensing and unmanned aerial vehicle imagery in monitoring of
sustainable development.
Methodology
The methodology used within this analysis sought out to demonstrate what advancements
in geospatial technology are currently available. With this, methods for analyzing this technology
in current categories of environmental sustainable development (land management and precision
agriculture) meant deciphering how each form of technology could benefit which category. Two
parcels of land were chosen to map and analyze; the Fort Ord National Monument located in
Seaside, California and a 12.5acre almond orchard located in Ripon, California. Focus was set
towards that of 1) remote sensing imagery and calculations through GIS software and 2)
unmanned aerial vehicle drones and their imagery. After thorough individual and class-oriented
research, it became evident that the use of remote sensing would best analyze and display
sustainable land management within the former Fort Ord, which left the use of UAV drone
imagery to aid in precision agriculture (PA) in Ripon, California.
Land Management and Remote Sensing
The former Fort Ord is a retired United States Army post located in Monterey County,
California. Fort Ord was in operation from 1917 to 1994. The land is currently managed by the
U.S. Bureau of Land Management and the For Ord Reuse Authority and houses numerous urban
developments and diverse habitats, including California State University, Monterey Bay,
Veterans Transition Center, and the Fort Ord Dunes State Park and National Monument. The
former Fort Ord runs along the coastal waters of Monterey Bay and lies north of Seaside, west of
Salinas and south of Marina. Offering 14,658 acres of public use, Fort Ord has largely diverse

flora and fauna that include streamside corridors, grasslands, maritime chaparral, oak woodlands
and seasonal pools (U.S. BLM, 2014).
Choosing to monitor land management while viewing the current status of living and
dead oak cover on the former Fort Ord, I utilized NASA’s Landsat 8 satellite imagery from the
fall season of 2013 and 2015 and predicted a decrease in living vegetation. Landsat 8 imagery is
an observation satellite that orbits over the Monterey Bay every sixteen days. The imagery from
Landsat 8 offers 30m pixel resolution with downloading capabilities in less than forty eight
hours. Using the most recent image with low cloud cover, I downloaded the Landsat 8 OLI
images from the USGS Global Visualization Viewer. The image downloaded was from the
twenty eighth of August, 2015, path44, row35 with latitude 36.0/longitude -122.6. Landsat 8
imagery comes in nine spectral bands ranging from near infrared, panchromatic thermal infrared
and cirrus. In order to show vegetation indices, converting the spectral bands into a raster tiff file
was required. Running the composite band tool in ArcMap10.2 offers the ability to symbolize the
NDVI output raster image. Normalized Difference Vegetation Index is a remote sensing
measurement that offers the assessment and observation of living vegetation. NDVI is displayed
by calculating visual and near-infrared light (0.40-0.70um) that is reflected by vegetation using
the formula: NDVI= (NIR – RED) / (NIR + RED)
(Bradley and Mustard, 2006). Calculating imagery from fall 2013 and fall 2015 reveled the
change in NDVI (dNDVI) and allowed for the prediction of increasing oak dieback over the two
year span.
A visual display of oak cover within the study area was needed in order to classify the
pixels that made up the composite tiff file. The end result was to create a masking layer to
display oak versus non oak. I ran a supervised image classification in ArcMap10.2 that allowed

me to create multiple classes for the existing Fort Ord landscape. Thirty-seven classes in total
were created and then classified using the Maximum Likelihood Classification (MLC) tool. Such
classification was necessary in order to convert the GSG file into a TIFF file. The MLC tool
allowed for the narrowing of thirty-seven classes into a more defined classification of ten classes:
Oak Woodland, Chaparral Dense, Chaparral Light, Urban, Beach Sand, Grassland, Dirt, Farm
Land, Deep Ocean and Shallow Waters. The oak mask layer was created by reclassifying the
new Tiff file into oak versus non oak and displaying the oak mask overtop the NDVI output
image.
Change in NDVI, commonly referred to as dNDVI, is the difference between two
different NDVI values. Using the Landsat 8 imagery from fall 2013 and fall 2015, I was able to
calculate dNDVI beginning with the most recent year. dNDVI was calculated in ArcMap10.2
using the raster calculator tool. I had to first compute two separate NDVI calculations from
Landsat 8 bands four and five. With the NDVI values for 2015 and 2013, I ran another raster
calculation using the formula:
dNDVI = (NDVI2015 – NDVI2013)
(Chen, 2015). This computation created a raster Tiff file for which I could manipulate and
symbolize into eleven classes that display NDVI change and range from < -0.05 to +0.05.
Field validation was needed to back up predictions that were made when analyzing the
NDVI images. Field work took place on the 19th
and 21st
of October, 2015. Viewing the overall
landscape of Fort Ord using Google Earth, study sample trails that ran along pre existing trials
within the oak woodland areas were selected and KML files were downloaded for each trail. All
trials were selected within the rightful boundaries of public use within the Fort Ord National
Monument. I was then able to export the pixels that ran though each trial using the Data

Management, Raster Dataset tool in ArcMap10.2 and create a master shapefile that would
display the entirety of the study area. In order to take proper field validation of estimated living
and dead oak cover, a Garmin 62sc was utilized and offered the capability of uploading the two
KMZ files, one for each trial. Converting the KML file to a GPX file was done using
www.gpsvisualizer.com and each file was then uploaded to the Garmin GPS in order to show
waypoints along the trail. Once in the field, study samples were taken by percentage of estimated
live versus dead oak trees, non oak cover and chaparral, all contained in each 30m pixel polygon,
that ran along the site selected trail. I was able to utilize the GPS to display the pixel boundaries
and trail line, a rangefinder to show depth and proximity of the 30m pixel polygon and a
compass to determine direction and horizontal slope. Using handwritten forms to tally all data
and findings, I followed the trial of pixels for both days, determining the percent coverage of
living oak, dead oak and remaining percent of area not relative to oak dieback. All data collected
in the field was converted to a master excel file holding the input data and findings. This data
offered the ability to display scatter plots of NDVI versus estimated living oak and dNDVI
versus dead oak.
Precision Agriculture and Unmanned Aerial Vehicles
Ripon, California is located in the San Joaquin County of California and is a mecca for
agricultural landscape. Mostly dominated by orchards harvesting fruit and nuts, almond trees are
the largest producing crop for the city of Ripon. In the northwestern region of the city sits my
grandparents’ property, a 14 acre plot of land that houses 12.5 acres of almond trees. Now
managed by my father and brother, this orchard has been in production since my grandfather
harvested his first crop in 1972. Since their takeover in 2013, my father and brother have begun
to see deminished crop output on an annual basis. This would be the platform for which I will

demonstrate the use of unmanned aerial vehicles in the monitoring of precision agriculture.
Utilizing aerial imagery of the orchard before, during, and after the almonds trees’ February
blossom season, all while calculating crop input to total output, I sought to analyze the overall
living condition of the almond trees and to hypothesize the cause if loss in crop output.
Understanding the needs of the orchard was my first priority and therefore the
establishment of overall budgeting was needed to visualize and keep recorded data of all
expenses being put forth into the field. Using Microsoft Excel, spreadsheets were created for
each calendar harvest and were followed by the input of all total billing and expenditures.
Records collected demonstrate a large necessity in the field for 1) electricity used to power the
water pump 2) water supplied by the county water district 3) orchard fertilizers 4) final shaking
and sweeping of the harvest. Added costs were put forth for miscellaneous items such as gopher
removal, tree pruning and the cost of purchased farm equipment, such as a backhoe, mower and
ATV for transportation within the orchard. Although the cost for farm equipment is not an
annual expense, it does offset the seasonal output for specific crop years. Such budgeting offered
insight into what expenses are necessary for the field and what expenses are considered
supplementary amongst the farm. Excel spreadsheets were created and passed along to help with
budget monitoring for the 2016 harvest and for future years.
I now wanted to utilize the accessibility of an unmanned aerial vehicle drone and capture
imagery of the field as the orchard moved closer to its February blossom season. From the
second week to the fourth week in the month of February, almond trees produce white blossoms
which offer the pollination of trees for the upcoming harvest year. Blossoms are a good indicator
of a tree’s nut-bearing potential for that year’s calendar harvest. I began by collecting images of
the orchard utilizing the quadcopter UAV drone produced by DJI called the Phantom 3

Advanced. The Phantom 3 Advanced offers GPS assisted flight linked up to 36 orbiting
satellites, vision positioning sensors and automated flight logging integrated into its intelligent
flight battery. The Phantom 3 Advanced also comes equipped with a 3-axis gimbal utilized for
ultimate stability. The camera offers 2.7K video and 12 megapixel images producing two inch
pixel resolution on images captured at an altitude of 400 feet. Federal Aviation Administration
limits all UAV drones to fly at or below an altitude of 400 feet. With such regulations, all images
taken for precision agriculture research purposes were captured at a flight altitude of 397 feet and
were taken over a three month period.
Images of the 12.5acre almond orchard were captured over the course of two months, all
benefiting the 2016 harvest year. The first collection consists of 9 images that were taken on
January 27th
, 2016 and the second consist of 10 images taken on February 26th
, 2016. All images
were captured at a flight altitude of 397 feet and cross overlay each other for final ease in image
mosaicking. All images were then processed thought two separate software systems,
ArcMap10.2 and MapsMadeEasy. ArcMap10.2 is geographic information software that allows
for the manipulation and analysis of geographic information. With this, I was able to use the
georeferencing tool to manually establish control points in each overlapping image, resulting in a
final mosaicked image of the entire 12.5acre parcel. The same images were also run through web
based software called MapsMadeEasy, which has built-in georeferencing tools that view the
metadata for each image and utilize its X, Y and Z (latitude, longitude, altitude) points to
construct final mosaicked images. Final mosaicked images were then added back to ArcMap10.2
for additional base mapping, roadway overlays and finalized mapping production for use in
research analysis.

Social Perception of Unmanned Aerial Vehicles
The subject of unmanned aerial vehicles has been a hot topic of debate in recent years.
Drone technology has expanded and evolved faster than the industry can keep up and constant
changes are being made to ways in which the public gains access to air space, the FAA’s
monitoring of individuals who own and fly hobby drones, and the regulation of those seeking to
profit from drones multiple capabilities. I wanted to gain a better understanding of how
knowledgeable the student body of CSU, Monterey Bay are on the topic of drones, as well as
their personal perspective on the idea of drones for use in both the public and military settings. I
had constructed a survey titled Student Perception of UAV Drones. Using Google Forms to
formulate and design the survey offered ease when distributing it among the student body. A
total of 180 responses were collected from an initial 1000 surveys administered. Students were
selected randomly with no consideration to age, major, or current college status. A total of 19
questions were asked with 5 focusing on individual demographics. Questions were designed to
ascertain student perception and knowledge of UAV drone use in the general public, within the
military and police force, as well as students’ trust level or wariness towards drones. Microsoft
excel was utilized in the process of data coding and tab analysis when computing final results.
Results
Analyzing Oak Tree Dieback Using Remote Sensing Imagery and Calculations
Assessment of oak cover on the Fort Ord National Monument highlighted the large
quantities of living oak within Fort Ord, yet traces of dieback are being present. Observations
made over the designated trail is shown in Figure 2 and is broken into three panels that display
the study area, NDVI values and the percent cover of living and dead oak. Panel B offers a visual
of the 30m pixels and the values of NDVI that was collected from Landsat 8 fall 2015 imagery.

Figure 2: Selected site trail displaying raw NAIP imagery, 2015
NDVI calculations and pixel polygons with percent rating of oak
coverage
Figure 3: Display of 2015 NDVI calculations using scatter plot and
increasing trend line to display positive calculations of living vegetation
within the former Fort Ord.
Panel C represents percent
cover. Pixel polygons are
displayed and percent of
live oak area is illustrated
using a graduated
representation. In Figure 3,
a direct correlation
between the percent of
living oak and the range of
positive NDVI values
shows that the prediction
and calculation of NDVI
are correct and correlate to the overall hypothesis. An increasing regression line demonstrates the
calculations.
The values calculated
for dNDVI were taken
from two separate
years, fall 2015 and
fall 2013.
Representation of
dNDVI or change in
NDVI from the
following years

Figure 4: dNDVI values display the change in NDVI or living
vegetation over the two year span.
displays a negative
change in living oak and
therefore, a growth in
dying oak. Viewing
Figure 4 shows positive
and negative NDVI
values that have changed
over the two year span,
with a greater percentage
of dead oak cover. The dNDVI scatter plot demonstrates the growth of dead oak cover and
therefore supports the hypothesis of increased dying oak woodlands. It is important to note the
large amount of scatter that has taken place due to the range of percent classification when
working in the field and the laminations to where the trail bypasses the image pixel. These NDVI
values were utilized in the final computation of dNDVI reduction that took place within the
designated study area of former Fort Ord.
The mapping of oak dieback is shown as estimates of the 2015 NDVI and the overall
dNDVI reduction. NDVI calculations are shown in Figure 5 and spatial patterns are displayed in
Figure 6 and show reduction of the NDVI with comparison to the dNDVI values from 2015 and
2013. Spatial patterns of the study area show trends of uniformity with a slight reduction south of
Inter-Garrison road, north of Gigling Road and east of the CSU, Monterey Bay main campus.
Results indicate reduction due to close proximity to urban pathways and the College campus.
Additional reduction occurs in the southern boundaries of the Fort Ord study area. Predictions of
this change could take place due to highs and lows of terrain when considering water shortages.

Figure 5: 2015 NDVI computed on the Fort Ord National Monument. Focus towards Live Oak
woodlands
Figure 6: Display of dNDVI reduction over the 2015 – 2013 span. Spatial patterns congregating
south of Inter-Garrison road

California drought has lead to critically low water levels. When water is present, natural flows
from high to low will place water at the troughs of such terrain. It is vital to clearly understand
the map, as it only displays given estimates, and that there is substantial variation from pixel to
pixel that is not shown within the final map.
Final analysis and predictions of total oak dieback were successfully achieved using the
remote sensing imagery and calculations. The assessment and analysis of Landsat 8 imagery
allowed for manipulation of those data to be entered into ArcGIS10.2 and to visualize the NDVI
and dNDVI of all Coast Live Oak trees on the former Fort Ord. Total oak dieback can be
mapped using such tools and techniques but it is pertinent to understand the variation that occurs
in plotting and mapping dNDVI when focusing on large parcels of land. Final estimated spatial
pattern of total oak dieback amongst the selected study area does not appear to be substantial, yet
levels of dNDVI reduction reach limits of up to 50% in selected areas (Fig.6). The remote
sensing techniques of calculating NDVI and change in NDVI (dNDVI) are shown to be effective
in estimating and mapping the dieback of coastal live oak on the Fort Ord National Monument.
Such observations make contributions to the monitoring and management of large parcels of
land, offering aid in the longevity and sustainability of such oak groves. The estimated spatial
patterns of oak dieback display unity throughout the study area. Slight dNDVI reduction
occurred (averaging 30%) with the majority retaining south of Inter-Garrison road and scatter
along the north side of Eucalyptus Road and east of CSU, Monterey Bay. Continuous urban
crawl of both the East Garrison housing development and the expansion of CSUMB, along with
seasonal water shortages, led to hypothesized contributions of both spatial and temporal dieback
of coastal live oak tree groves within the Fort Ord National Monument.

Figure 7: visual of top three largest expenses on the farm, as well as
total crop output in currency values
Monitoring Almond Trees using Unmanned Aerial Vehicle Imagery
Analyzing the current state of Almond trees using UAV imagery and crop calculations
show a decrease in total crop output between two calendar harvests (2014-2015). The output
from each harvest is shown in Figure 7 and offers insight to major expenses that are needed on
the farm. Here, we
can view the three
largest expenses on
the farm and total
crop output for each
calendar harvest.
Essentially, farming
the 12.5 acres of
almonds is creating a
zero balance of profit
back into the farm.
We can also see that
some of the largest
cost during harvest dwells within fertilizer purchases from Wilber Ellis, Pacific Gas and Electric
Company to help power the water pump and Cali Valley in harvest assistance. The observation
of crop loss through the decrease of total pound output shows regression over the two year span
from 32,060 pounds in 2014 to 30,980 in 2015.
Mapping of the almond orchard offered visual perspective of the spatial formation when
viewing potential reasons for annual crop loss. The use of unmanned aerial vehicles proved

Figure 8: 12.5acre almond orchard displayed with field boundaries. Image A was taken on
January 27, 2016, two weeks before blossom season began. Image B was taken on February 26,
2016 during the blossoming weeks. Both images were taken using UAV aerial imagery and
processed in MapsMadeEasy.com. Both panels display an incomplete image of the field due to
insufficient amount of images during geoprocessing.
beneficial in the observation and mapping of the land parcel when looking to provide
contributions in sustainable precision agriculture. In spite of time limitations when capturing
images during the almond blossom season, the UAV drone offered accessibility to capture
images at any particular date with little consideration to weather conditions and cloud cover.
Both dated images are displayed within Figure 8 and Figure 9 and offer insight to optional
georeferencing and finalized mapping. Two separate options were explored when creating final
mosaics of the UAV imagery, ESRI’s ArcMap10.2 and MapsMadeEasy.com. Figure 8 shows
the mapping that was produced by MapsMadeEasy.com and came with its pros and cons.
Benefits to using such software were that it is cloud based, so access to the map is universal.
The online software also provided built-in georeferencing and a final image production time of
less than 24 hours. Cons are shown within both maps as final images did not produce full size

Figure 9: 12.5 almond orchard displayed with field boundaries. Image A was taken on January 27,
2016, two weeks before blossom season begins. Image B was taken on February 26, 2016 during the
blossoming weeks. Both images were taken using UAV aerial imagery and processed in ArcGIS10.2.
Both panels display a full orchard image yet slight off placement due to manual geoprocessing
within the GIS software.
maps of the orchard, as here we can see the extent of the field boundaries. This was done in part
due to the limited images taken to provide overlaps of the georeferenced points (fig. 8).
Constructing the final mosaicked image using ArcMap10.2 also came with its pros and cons
during final mapping. The benefit of using ArcMap was that a full sized image can be produced
and no edges were cut off in limits to the field boundaries. Negatives to using ArcMap were that
each image has to be georeferenced individually; this leads to images not aligning 100% and
creating some overlaps within images. Another downside to this software is the processing time
it takes to georeferenced each image to the airborne NAIP imagery (fig. 9).
Finalized mapping of the 12.5acre almond orchard using unmanned aerial vehicle
imagery proved beneficial and a contribution when observing land for sustainable precision
agriculture. Utilizing UAV’s for research purposes offered me the ability to capture images at
any time of the day, regardless of weather conditions. This allowed me the ability to capture

images at the time of my choosing and have instant access in observation. In comparison, the use
of satellite imagery is limited to satellites that fly over the field every 16 days and can take 24 to
48 hours for downloads, yet still may be limited by weather and cloud cover. Unmanned aerial
vehicle imagery also offered an extensively higher pixel resolution per image in comparison to
satellite imagery. UAV’s can offer up to 2 inch resolution and Landsat8 offers 1 meter
resolution. Such UAV imagery also offered the capabilities on multiple software all focusing on
GIS mapping and analysis.
Viewing Students Perception of UAV Drones
I chose to take a quantitative approach when observing student perceptions. Final results
for survey analysis when viewing CSUMB student perception of UAV drones concluded that
95% of students possess average to little knowledge of drones. A total of 98% of students do not
own their own drone and 38% of students are interested in purchasing a drone but have never put
forth the funds. To date, 37% of students have heard of accidents involving UAV drones that
make them skeptical about to their availability to the public. A staggering 77% agree that UAV
drones should be used in military war missions and 34% of students strongly agree that UAV
drones are more effective than sending in active soldiers. When it comes to the hot topic of UAV
drones, 51% of students are agree that drones are an invasion of their privacy and 18% agree that
they find it hard to trust someone who flies UAV drones for recreational purposes. Although a
majority of students find it hard to trust UAV drones, the technology is rapidly growing and
changing, and this is one aspect that students have been able to catch on to. A total of 51% of
students agree that drones are not just a trend that will die off soon. Aside from recreational
purposes, 19% of students are aware that UAV drones are now being used in a multitude of
industries.

Conclusion
The study of observing and testing advancing geospatial technology, remote sensing and
unmanned aerial vehicles, were found beneficial and successful for the implementation and
contribution to the theory of environmental sustainable development. Major evaluation and
reconstruction of global monitoring is vital in sustaining the longevity of human existence on
earth. New technologies are rapid in expansion and such advancements are now easily accessible
and crucial in ways we now observe and monitor the earth’s environment. Improvements for
future analysis in the observation of oak dieback on the former Fort Ord would require more time
for field validation and processing, implementing a larger time span to show lapses of change
and establishing a defined scale of oak verification when in the field. Improvements for future
analysis in the observation of almond trees in Ripon, California would include a longer elapsed
time to capture images during blossom season, perhaps over a five year span, capturing images
during weekly watering periods to view dispersion, as well as calculating NDVI for the almond
orchard to display change in living vegetation over several years to add predictions in the
diminishing crop yields.
Results and findings have provided contribution to a possible change in ways we address
sustainable goals. Active monitoring and recording is essential in knowing if the goals
established and changes being made are actively working. In theory, we address the global issues
we have at hand and make efforts to provide longevity to human life on earth. We begin to clean
up the ocean waters, construct sustainable energy, expand biodiversity, and monitor growing
populations. However, this is in fact a theory, one that builds off of environmental research and
global monitoring. As we meet the needs of our present day generation, can we be certain that
future generations will be as fortunate as their predecessors?

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accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision
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Photography. Rangeland Ecology & Management, Vol. 58(4), 439-442pp. (5p.)
http://www.jstor.org/stable/3899995
Hollister Field Office. (Dec. 15, 2014) Fort Ord History: Fort Ord National Monument.
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Appendix I
How does my research project work reciprocally with my community and provide
contribution to community capacities?
My research project was focused on the direct benefits that can come about from the use
of recent technology. Such technology is easily accessible to the general public and can be
obtained and applied directly to issues that are present in my surrounding communities. My first
case study deals directly with the current oak tree dieback that is occurring on the Fort Ord
National Monument. Offering 55,000 plus acres of land accessible to the public, the former Fort
Ord houses hiking trails, residential living communities and a California State University
campus. Viewing the current state of oak trees and observing the dieback offer aid in the
implementation and regulations of expansion and growth that can occur on Fort Ord in years to
come. Bringing light to the spatial and temporal changes of these oak trees can provide
community councils the insight needed when addressing Fort Ord’s current vegetation state. This
can also be useful when implementing growth and expansion on the Fort Ord National
Monument.
My second case study dealt with the observation of almond trees and decreased crop
output on a 12.5acre farm in Ripon, California. This deals directly with my community as this is
the hometown in which I grow up and the almond orchard is owned by my grandfather and
managed by my father and brother. Looking at returns after almond harvest, a negative profit
was being made for each calendar year. This project offered the implementation of organized
management and a way to visualize the current state of almond trees within the field. Offering
such information allowed my family to analyze what procedures they are currently carrying out
and make predictions into what is vital and what is secondary for the 2016 harvest. In doing so, I
hope to provide a larger crop output for 2016, 2017 and beyond.
Implementing advancing geospatial technology into my service learning seminar allowed
me the opportunity to work directly with the Monterey Bay Aquarium. It is here that I have been
given the chance to apply the GIS skills I have gained through course work taken at CSU,
Monterey Bay. Working directly with the Seafood Watch Program, myself alongside two other
GIS students, are preparing API maps for both the Seafood Watch website and their mobile
applications. Seafood Watch works with communities worldwide to inform business partners,
collaborators and seafood suppliers about ways in which they can manage their business on a
global sustainable level. My community service learning experience provided me with the
knowledge and skills to work in a professional environment towards sustainable goals. This has
also allowed me to pass along my knowledge of analyzing imagery for research purposes and
how it can be applied directly to the earth’s ocean.

Appendix II
Student Survey
UAV = Unmanned Aerial Vehicle
1) How knowledgeable are you on UAV drones?
a. Very knowledgeable
b. Average knowledge
c. Little to no knowledge
2) I personally own a UAV drone.
a. Yes If yes, What Kind__________________________.  Homemade.
b. No
3) I personally know someone who owns a UAV drone.
a. Sibling
b. Parent
c. Spouse
d. Cousin, Aunt or Uncle
e. Friend
f. Co-worker
g. Neighbor
h. I know No one with a drone
4) I have flown a UAV drone before.
a. Yes
b. No
5) I am interested in UAV drones but have never put forth the funds to purchase or build one.
a. Agree
b. Disagree
6) I have personally encountered or have heard of accidents involving UAV drones that make me sceptic of
their use and access to the public.
a. Agree
b. Disagree
7) Do you think UAV drones should be allowed for use in military war missions?
a. Yes
b. No
8) I believe that using UAV drones in military war missions is more effective than sending in active soldiers.
1 2 3 4 5
Strongly Agree / Somewhat Agree / Neutral / Somewhat Disagree / Strongly Disagree
9) Do you think UAV drones should be allowed for recreational and research purposes?
a. Yes
b. No
10) How do you feel on the concept of city police officials using UAV drones to surveillance neighborhoods?
1 2 3 4 5

11) I feel as if UAV drones are an invasion of my privacy.
1 2 3 4 5
12) I find it hard to trust anyone who flies UAV drones for recreational purposes.
1 2 3 4 5
13) I feel as if UAV drones are just a trend and will die off soon.
1 2 3 4 5
14) I am aware that UAV drones are used in a multitude of industries, including search and rescue missions,
environmental monitoring, real-estate marketing, cinematography etc…
a. Very knowledgeable
b. Average knowledge
c. Little to no knowledge
15) My age is…
a. 18-21
b. 22-25
c. 26-30
d. 31-40
e. 41-50
f. 51+
16) I identify as…
a. Male c. Transgender
b. Female d. Other
17) I identify as…
a. Latino/a
b. American Indian / Alaska Native
c. Asian
d. Black / African American
e. Native Hawaiian / Pacific Islander
f. White
g. Other ________________________
18) My college standing is… (Unit Based)
a. Freshmen
b. Sophomore
c. Junior
d. Senior
19) My current major in school is _______________________________________________.
What are your personal thoughts on UAV drones?
___________________________________________________________________________________

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