The Role of Remote Sensing in Surveillance and Assessment of
Climate Change
Yizhou Yan
a
School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture,
Beijing, 102627, China
Keywords: Remote Sensing, Climate Change, Sea Level Rise, Glacial Retreat, Forest Fires.
Abstract: Climate change has currently evolved into a serious concern across the globe. Mainly focusing on climate
change and its effects on humanity in different aspects, this paper delves into the history and development of
Remote Sensing and analyzes the pivotal roles it plays in monitoring and assessing climate change by
scrutinizing previous studies and evaluating the effectiveness of the technology in three climatic phenomena
- sea level rise, glacial retreat and forest fires. The research results indicate that Remote Sensing can be
accurate and efficient in these climatic phenomena. However, the technology has limitations, such as limited
spectral range and coarse spatial resolution. To solve the problem, Remote Sensing can be coupled with other
technologies, such as Geographic Information System (GIS), to obtain remarkable efficiency and accuracy
when combating climate change. In the future, it can be leveraged across various sectors in efforts against
climate change. In addition, this paper emphasizes the necessity for ongoing enhancements in Remote Sensing
technologies, particularly in improving spectral range and spatial resolution. It also underlines the critical role
of international cooperation and data sharing in leveraging Remote Sensing for more comprehensive and
precise climate monitoring and mitigation efforts.
1 INTRODUCTION
With an increasing rate of industrialization and
urbanization, climate change has become a significant
concern to all. Climate change is defined as a chronic
alteration in weather patterns across the globe. While
numerous traditional methods, such as weather
stations, weather balloons, radars, ships and buoys,
have been undertaken across various sectors to
investigate its causes, track its progression, and
minimize its impacts, there is still a critical need for a
more comprehensive and effective tool in the effort.
In recent years, Remote Sensing has developed
rapidly and stood out as a convenient and powerful
tool for conducting geographical surveillance and
assessment due to the large area it can cover and its
capacity to provide insightful details on certain
geographical features. For example, it can help
satellites quickly identify infrared rays or ultraviolet
in a particular region, which human eyes cannot
identify. Calculating the NDVI (Normalized
Difference Vegetation Index) can also assist in
a
https://orcid.org/ 0009-0003-8379-3324
analyzing the status of vegetations in certain areas.
Nevertheless, there remains a noticeable lack of
studies and analyses on the effectiveness of Remote
Sensing technologies in climatic issues. This paper
intends to contribute to closing this gap by carrying
out insightful analyses of the role of Remote Sensing
in detecting the effects and potential threats
associated with various climatic phenomena in
aspects including sea level rise, glacial retreat, and
forest fires. It is expected that through harnessing
images and data collected through Remote Sensing,
as well as GIS (Geographical Information System)
and other geographic technologies, the paper will
help to gain a more comprehensive understanding and
more detailed information regarding the existing and
potential impacts of climate change from diverse
perspectives alongside showcasing how the
geographical technologies can be employed for the
betterment of the humanity. Furthermore, the paper
intends to contribute to the global bid to combat
climate change and mitigate related natural disasters.
Yan, Y.
The Role of Remote Sensing in Surveillance and Assessment of Climate Change.
DOI: 10.5220/0013024300004601
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 1st International Conference on Innovations in Applied Mathematics, Physics and Astronomy (IAMPA 2024), pages 195-200
ISBN: 978-989-758-722-1
Proceedings Copyright © 2024 by SCITEPRESS – Science and Technology Publications, Lda.
195

2 MAIN ASPECTS OF CLIMATE
CHANGE
In the last few decades, climate change has been
primarily characterized by a rise in global
temperature and an increase in natural disasters
worldwide.
The rise in global temperature, commonly known
as "global warming," is a key driver of climatic
changes, with a notable impact on oceans leading to
rising sea levels. This phenomenon thus serves as a
crucial indicator of the extent and pace of global
warming (Eniolorunda et al., 2014). In retrospect, the
retreat of glaciers in polar regions is a major
contributor to rising sea levels, underscoring the
undeniable signs of climate change. For this reason,
local authorities must monitor glacier losses and ice
thickness reduction to manage climate-related
challenges effectively (Peduzzi et al., 2010).
Among a series of natural disasters that have
occurred over the decades, forest fires stand out as a
prominent concern due to their increasing frequency
over the years. Flannigan et al. (2006) state in their
research that the link between fire and climate change
has essential implications for the management of
forests and the protection of communities. They also
claim that weather and climate conditions, influenced
by human-induced climate change, are vital in fueling
these devastating fires (Flannigan et al., 2014).
Understanding these dynamics is a major key to
efficient mitigation strategies and preparedness
measures.
In light of the considerations above, this paper
focuses on sea level rise, glacial retreat, and forest
fires as main aspects of climate change analysis,
aiming to provide a comprehensive and insightful
perspective about the threats of climate change posed
to mankind and the vital role played by Remote
Sensing in monitoring and assessing these
environmental shifts.
3 DEFINITION AND
DEVELOPMENT OF REMOTE
SENSING
Remote Sensing is the technology that scans the Earth
with the help of satellites or high-flying aircraft to
obtain related information. Unlike on-site
observations, it is essentially distinguished by
acquiring geographical images without direct contact
with the ground.
The evolution of Remote Sensing technology has
been intertwined with the advancement of flight.
Since the advent of photography, individuals have
affixed micro cameras to birds to capture panoramic
views of their surroundings. In 1858, a French
balloonist, G. Tournachon, captured an aerial photo
of Paris from his hot balloon, marking the formal
inception of modern Remote Sensing (Cracknell et
al., 2018). Advancements surged in the 20th century
as aerial photography from aircraft, created for armed
forces during World War I, shifted to civilian uses
after the war.
The term Remote Sensing started in the mid-20th
century, reflecting American geographer Evelyn
Pruitt's realization that traditional terms like "aerial
photography" were insufficient to describe the
emerging data streams fueled by technological
advancements. Remote Sensing is widely deployed
across multiple fields, with over 950 in-orbit satellites
traveling around Earth, providing detailed planetary
information.
Broadly stated, Remote Sensing can be
categorized into two main types based on their
principles - Passive Remote Sensing and Active
Remote Sensing. Passive sensors collect radiation
from their circumstances, with sunlight being a major
source. Infrared and film photography are common
instances of passive Remote Sensing. In contrast,
Active Remote Sensing emits energy to survey the
surrounding environment. A sensor then analyzes the
radiation reflected from the target area. LiDAR and
RADAR are examples of Active Remote Sensing
techniques.
Presently, Remote sensing enjoys a reputation as
a potent assistant in capturing data about the Earth
(Borre et al., 2011). Several noticeable advantages
have been recognized that contribute to its efficiency.
One invaluable merit is its capability to collect data
of impenetrable areas - from deep oceans to dense
forests and remote deserts. Remote Sensing enables
detailed data acquisition, making it a valuable tool for
research on climate and ecosystems. Moreover,
Remote Sensing offers a cost-effective and efficient
alternative to ground-based data collection processes,
considerably minimizing disturbances in areas under
analysis while ensuring swift processing and retrieval
of crucial information.
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196

4 APPLICATION OF REMOTE
SENSING IN SEA LEVEL RISE
Historically, people have set up weather stations
along coastlines and set off weather balloons over
oceans to monitor sea conditions. The trend of using
remote sensing technology for research is becoming
obvious in recent years.
Kavak et al. (2011) found a significant association
between sea surface temperature and levels of
chlorophyll (contributing to the variation of
watercolor) during the same period. They concluded
that Remote Sensing technology could considerably
promote studies on global ocean characteristics and
their potential impacts on the planet. This underscores
the vital role of Remote Sensing in monitoring and
handling sea level rise and its related effects (Peduzzi
et al., 2014).
On the other hand, Yang et al. (2013) have
pointed out that the global average sea level rise, as
measured by Remote Sensing since the 1990s,
exceeds the estimates derived from twentieth-century
tide-gauge data. This suggests that achieving absolute
precision in analyzing the extent of sea level rise
remains a considerable challenge. An extended
duration, therefore, is in demand to identify the year-
to-year and decade-to-decade changeability.
Fortunately, an effort that leverages multi-satellite
altimetry data to produce week-by-week sea level
data for part of the Earth (polar regions excluded) has
recently provided a valuable solution to the problem.
With the help of Remote Sensing technology, Yang
et al. (2013) accurately measured the variation in sea
levels between 1993 and 2012 (Figure 1), which not
only reveals significant changes over the years but
also demonstrates the differences between data
collected using differing methods (Yang et al., 2013).
It can be inferred that with the emergence of newly
developed Remote Sensing methods, the precision
and accuracy of Remote Sensing in analyzing sea
conditions has been continuously improving.
Figure 1: Sea-level changing trends from 2008 to 2012, measured by different Remote Sensing methods (Yang et al., 2013)
5 APPLICATION OF REMOTE
SENSING IN GLACIAL
RETREAT
Traditionally, scientists have set up surveillance
stations in polar regions to detect glacial activities.
While this method is cost-effective and
straightforward, it lacks efficiency in tracking overall
glacial changes in expansive areas.
At present, multiple Remote Sensing
technologies, the most representative including
Satellite Pour l’ Observation de la Terre (SPOT) and
Advanced Spaceborne Thermal Emission Reflection
Radiometer (ASTER), have been deployed to monitor
glacial retreat, characterized by extraordinary
accuracy, despite minor errors, in analyzing and
predicting glacial changes (Yang et al., 2013).
Peduzzi et al. (2010) leveraged Remote Sensing
in combination with DEM (Digital Elevation Model)
to analyze the changes in Nevado Coropuna, a glacier
located in Peru, over the years. Their research
The Role of Remote Sensing in Surveillance and Assessment of Climate Change
197

collected data on glacier areas from 1955 to 2008
(Table 1), supporting the evidence of significant
global glacier decline occurring at a relatively
consistent rate over the decades.
Table 1: Evolution of Ice Cover from Nevado Coropuna,
Peru from 1955 to 2008 (Peduzzi et al., 2010).
Date Surface
Area of
Glacier
(
km
2
)
Loss of Ice
Areas
(km
2
/year)
Ice Cover
Percentage
(1955 as
reference
)
1955 122.7 100%
November
6, 1980
80.14 1.7 65.3%
June 12,
1996
65.5 0.9 53.4%
May 7,
2003
57.3 1.2 46.7%
September
25, 2008
48.1 1.8 39.2%
Moreover, the research suggests that data
obtained through Remote Sensing technologies
exhibited exceptional reliability even before
corrections. Through further refinement of the data,
the study successfully mitigated errors from Remote
Sensing analysis (Table 2), lowering the standard
deviation to 14.4 meters (lower than that acquired in
a study by Racoviteanu et al., 2007). This underscores
the considerable capability of Remote Sensing in
determining the magnitude and pace of glacial retreat
across time.
Table 2: Comparison Between Pre-correction and Post-
correction Remote Sensing DEM Analysis (Peduzzi et al.,
2010)
Pre-
correction
Post-
correction 1
Post-
correction 2
Differe
nce
Standa
rd
Deviat
ion
Differe
nce
Standa
rd
Deviat
ion
Differe
nce
Standa
rd
Deviat
ion
DEM
97-55
-0.24m 18.6 -0.24m 16.1 0.00 18.6
DEM
00-55
0.04 18.2 0.00m 13.2 0.00 13.2
DEM
02-55
71.01
m
42.1 2.71m 27.9 3.28 14.4
6 APPLICATION OF REMOTE
SENSING IN FOREST FIRES
When addressing natural disasters such as forest fires,
traditional methods typically involve deploying
manpower into forested areas and installing fire
alarms in high-risk zones. However, these
conventional approaches put lives at stake and fall
short in facilitating rapid responses to sudden fire
outbreaks.
In light of these challenges, Remote Sensing
emerges as a highly effective alternative to traditional
methods. In a seasonal perspective, Ahmad et al.
(2018) leveraged Remote Sensing imagery provided
by the Forest Survey of India (FSI) and found that
most forest fires (approximately 79%) occurred
during April and May, with April recording the
highest frequency of fires. Their study illustrates the
fire occurrence patterns in a typical forest fire area in
India, shedding light on broader trends worldwide
(Table 3).
Table 3: Monthly Forest Fires in An Area in India (Ahmad
et al., 2018).
Month
Janua
ry
Februa
ry
Marc
h
April May June
Freque
ncies
14 80 553 3369 2545 956
Percent
age
0.19
%
1.06
%
7.3
6%
44.8
1%
33.8
6%
12.7
2%
In addition, Flannigan et al. (2006) opine that
coupling simulation models and classification models
with Remote Sensing can be instrumental to the
analysis of forest fires. In a recent investigation,
Sunar et al. (2001) combined Remote Sensing with
the Neural Network Supervised Classification Model
to analyze a forest fire in a region in Turkey. Their
study suggested that Remote Sensing gives rise to
decisions of greater objectivity, higher definitiveness,
and lower biasedness to be made from a
meteorological viewpoint. It also can analyze
vegetation quantity in finer detail compared to
ground-based measurements. As depicted in Figure 2,
the classifications visually represent areas with
distinct characteristics using varied colors. It can be
further inferred that there will be substantial potential
for future advancements if Remote Sensing
technologies are fully integrated with a diverse array
of models and algorithms.
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Figure 2: Classification Result of IRS-1C Image,
Supervised by Neural Network (Sunar et al., 2001).
7 DISCUSSION
In general, papers written over the decades not only
implicated the rapid development and high
effectiveness of Remote Sensing but also highlighted
the pivotal roles it plays in fighting against climate
change. Through comparison and analysis of these
papers, Remote Sensing, when appropriately utilized,
can be effective and accurate in monitoring climatic
phenomena. Likewise, GIS, ASTER, SPOT, GCM
and other technologies can also be exceptionally
useful for modeling the future trends of such
phenomena. Remote Sensing can be further enhanced
by these auxiliary technologies to acquire data
handling of higher efficiency, modeling with greater
accuracy, and estimates with increased precision
(Park et al., 1991). These findings underscore the
pivotal role that Remote Sensing can play in the
surveillance, evaluation, and mitigation of climate
change and its associated impacts. A more extensive
literature review reveals that climate change is
prominently implicated in the three analyzed aspects
- sea level rise, glacial retreat, and forest fires,
necessitating heightened awareness across all sectors
of society regarding its potential consequences.
Collaborative efforts are imperative to combat
climate change effectively.
However, despite the considerable advantages of
Remote Sensing technology, they also have certain
limitations. For example, Moran et al. (1997)
investigated "Precision Crop Management (PCM)"
utilizing Remote Sensing and highlighted challenges
related to such properties of sensors as restricted
range of spectrums, low resolution, extended
detection intervals, and inadequate coverage
repetition, which could impede its performance.
Thus, Remote Sensing technology alone may not
suffice in addressing climate-related challenges and
should be complemented by other technologies to
maximize its efficacy. Continuous enhancements are
required to refine the precision of Remote Sensing
techniques in the future.
While this paper specifically focuses on the roles
of Remote Sensing in three main aspects of climate
change, it acknowledges that other climate-related
phenomena demand investigation. Future studies
should explore topics such as flooding, vegetation
changes, greenhouse gas increases, marine life
variations, and the application of Remote Sensing in
these realms to gain a more comprehensive
understanding of climate change dynamics and the
potential of Remote Sensing.
8 CONCLUSION
Intended to address the insufficiency of papers
investigating the role of Remote Sensing in handling
threats posed by climate change, this paper has
undertaken a comprehensive evaluation of key
climate change aspects and traced the evolutionary
trajectory of this pivotal technology. Central to its
analysis is a detailed exploration of the functions and
utilitarian values of Remote Sensing, particularly
when integrated with diverse methodologies for
monitoring and assessing sea level rise, glacial
retreat, and forest fires - three critical aspects in
comprehending the impacts of climate change.
From multiple perspectives, previous papers have
utilized Remote Sensing and other technologies and
adopted various perspectives of analysis to assess the
effectiveness and accuracy of Remote Sensing. This
paper primarily makes a comprehensive comparison
and analysis and highlights two key points regarding
these studies conducted over the decades. For one
thing, Remote Sensing demonstrates significant
accuracy in analysis, further strengthened through
correction models and complementary technologies,
including supervised classification, GIS, AVHRR,
and ASTER. For another, the application of Remote
Sensing proves promising for aiding humanity in
The Role of Remote Sensing in Surveillance and Assessment of Climate Change
199

combatting climate change. It is therefore, evident
that Remote Sensing and relevant technologies have
a bright prospect. With future efforts, Remote
Sensing has the potential to achieve higher resolution,
increased precision, and enhanced accuracy in
information retrieval. Undeniably, it will play a
central role in helping humans navigate climatic
crises.
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