Abstract: Small cell backhaul solutions need to be cost-effective, scalable, and easy to install. This paper presents an overview of small cell backhaul technologies. Wireless solutions including TV white space, satellite, sub-6 GHz radio wave, microwave and mmWave with their backhaul characteristics are discussed. Recent research on issues like beamforming, backhaul architecture, precoding and large antenna arrays, and energy efficiency for dense small cell backhaul with mmWave communications is reviewed. Recent trials of 5G technologies are summarized.
Abstract: Human utilizes coastal resources as well as deteriorates them. Coastal tourism may degrade the environment if poorly managed. This research investigated the shoreline change at Koa Toa Island, one of the most famous tourist destinations. Aerial photographs and satellite images from three different periods were collected and analyzed. The results showed that the noticeable shoreline change before and after the tourism on the island had expanded. Between 1995 and 2002 when the tourism on Koh Toa Island was not intensive, sediment deposition occurred along most of the coastline. However, after the tourism had grown during 2002 to 2015, the coast evidently experienced less deposition and more erosion. The erosion resulted from less land-based sediment being provided to the littoral system. If the coastline of Koh Toa Island is not carefully sustained, the tourism will disappear along with the beautiful beach.
Abstract: The Metropolitan Region of Sao Paulo (MRSP) has suffered from serious water scarcity. Consequently, the most convenient solution has been building wells to extract groundwater from local aquifers. However, it requires constant vigilance to prevent over extraction and future events that can pose serious threat to the population, such as subsidence. Radar imaging techniques (InSAR) have allowed continuous investigation of such phenomena. The analysis of data in the present study consists of 23 SAR images dated from October 2007 to March 2011, obtained by the ALOS-1 spacecraft. Data processing was made with the software GMTSAR, by using the InSAR technique to create pairs of interferograms with ground displacement during different time spans. First results show a correlation between the location of 102 wells registered in 2009 and signals of ground displacement equal or lower than -90 millimeters (mm) in the region. The longest time span interferogram obtained dates from October 2007 to March 2010. As a result, from that interferogram, it was possible to detect the average velocity of displacement in millimeters per year (mm/y), and which areas strong signals have persisted in the MRSP. Four specific areas with signals of subsidence of 28 mm/y to 40 mm/y were chosen to investigate the phenomenon: Guarulhos (Sao Paulo International Airport), the Greater Sao Paulo, Itaquera and Sao Caetano do Sul. The coverage area of the signals was between 0.6 km and 1.65 km of length. All areas are located above a sedimentary type of aquifer. Itaquera and Sao Caetano do Sul showed signals varying from 28 mm/y to 32 mm/y. On the other hand, the places most likely to be suffering from stronger subsidence are the ones in the Greater Sao Paulo and Guarulhos, right beside the International Airport of Sao Paulo. The rate of displacement observed in both regions goes from 35 mm/y to 40 mm/y. Previous investigations of the water use at the International Airport highlight the risks of excessive water extraction that was being done through 9 deep wells. Therefore, it is affirmed that subsidence events are likely to occur and to cause serious damage in the area. This study could show a situation that has not been explored with proper importance in the city, given its social and economic consequences. Since the data were only available until 2011, the question that remains is if the situation still persists. It could be reaffirmed, however, a scenario of risk at the International Airport of Sao Paulo that needs further investigation.
Abstract: Advances in spatial and spectral resolution of satellite
images have led to tremendous growth in large image databases. The
data we acquire through satellites, radars, and sensors consists of
important geographical information that can be used for remote
sensing applications such as region planning, disaster management.
Spatial data classification and object recognition are important tasks
for many applications. However, classifying objects and identifying
them manually from images is a difficult task. Object recognition is
often considered as a classification problem, this task can be
performed using machine-learning techniques. Despite of many
machine-learning algorithms, the classification is done using
supervised classifiers such as Support Vector Machines (SVM) as the
area of interest is known. We proposed a classification method,
which considers neighboring pixels in a region for feature extraction
and it evaluates classifications precisely according to neighboring
classes for semantic interpretation of region of interest (ROI). A
dataset has been created for training and testing purpose; we
generated the attributes by considering pixel intensity values and
mean values of reflectance. We demonstrated the benefits of using
knowledge discovery and data-mining techniques, which can be on
image data for accurate information extraction and classification from
high spatial resolution remote sensing imagery.
Abstract: This paper presents the effect of the orbit inclination
on the pointing error of the satellite antenna and consequently on its
footprint on earth for a typical Ku- band payload system. The performance assessment is examined using both analytical
simulations and practical measurements, taking into account all the
additional sources of the pointing errors, such as East-West station
keeping, orbit eccentricity, and actual attitude control performance. An implementation and computation of the sinusoidal biases in
satellite roll and pitch used to compensate the pointing error of the
satellite antenna coverage is studied and evaluated before and after
the pointing corrections performed. A method for evaluation of the performance of the implemented
biases has been introduced through measuring satellite received level
from a mono-pulse tracking 11.1m transmitting antenna before and
after the implementation of the pointing corrections.
Abstract: The change in orbit evolution between collocated
satellites (X, Y) inside +/-0.09° E/W and +/- 0.07° N/S cluster, after
one of these satellites is placed in an inclined orbit (satellite X) and
the effect of this change in the collocation safety inside the cluster
window has been studied and evaluated. Several collocation scenarios had been studied in order to adjust
the location of both satellites inside their cluster to maximize the
separation between them and safe the mission.
Abstract: This paper focuses on the orbit avoidance strategy of
the optical remote sensing satellite. The optical remote sensing
satellite, moving along the Sun-synchronous orbit, is equipped with
laser warning equipment to alert CCD camera from laser attacks. This
paper explores the strategy of satellite avoidance to protect the CCD
camera and also the satellite. The satellite could evasive to several
target points in the orbital coordinates of virtual satellite. The so-called
virtual satellite is a passive vehicle which superposes the satellite at the
initial stage of avoidance. The target points share the consistent cycle
time and the same semi-major axis with the virtual satellite, which
ensures the properties of the satellite’s Sun-synchronous orbit remain
unchanged. Moreover, to further strengthen the avoidance capability
of satellite, it can perform multi-target-points avoid maneuvers. On
occasions of fulfilling the satellite orbit tasks, the orbit can be restored
back to virtual satellite through orbit maneuvers. There into, the avoid
maneuvers adopts pulse guidance. In addition, the fuel consumption is
optimized. The avoidance strategy discussed in this article is
applicable to optical remote sensing satellite when it is encountered
with hostile attack of space-based laser anti-satellite.
Abstract: The critical concern of satellite operations is to ensure
the health and safety of satellites. The worst case in this perspective
is probably the loss of a mission, but the more common interruption
of satellite functionality can result in compromised mission
objectives. All the data acquiring from the spacecraft are known as
Telemetry (TM), which contains the wealth information related to the
health of all its subsystems. Each single item of information is
contained in a telemetry parameter, which represents a time-variant
property (i.e. a status or a measurement) to be checked. As a
consequence, there is a continuous improvement of TM monitoring
systems to reduce the time required to respond to changes in a
satellite's state of health. A fast conception of the current state of the
satellite is thus very important to respond to occurring failures.
Statistical multivariate latent techniques are one of the vital learning
tools that are used to tackle the problem above coherently.
Information extraction from such rich data sources using advanced
statistical methodologies is a challenging task due to the massive
volume of data. To solve this problem, in this paper, we present a
proposed unsupervised learning algorithm based on Principle
Component Analysis (PCA) technique. The algorithm is particularly
applied on an actual remote sensing spacecraft. Data from the
Attitude Determination and Control System (ADCS) was acquired
under two operation conditions: normal and faulty states. The models
were built and tested under these conditions, and the results show that
the algorithm could successfully differentiate between these
operations conditions. Furthermore, the algorithm provides
competent information in prediction as well as adding more insight
and physical interpretation to the ADCS operation.
Abstract: Indonesia has experienced annual forest fires that have
rapidly destroyed and degraded its forests. Fires in the peat swamp
forests of Riau Province, have set the stage for problems to worsen,
this being the ecosystem most prone to fires (which are also the most
difficult, to extinguish). Despite various efforts to curb deforestation,
and forest degradation processes, severe forest fires are still
occurring. To find an effective solution, the basic causes of the
problems must be identified. It is therefore critical to have an indepth
understanding of the underlying causal factors that have
contributed to deforestation and forest degradation as a whole, in
order to attain reductions in their rates. An assessment of the drivers of deforestation and forest
degradation was carried out, in order to design and implement
measures that could slow these destructive processes. Research was
conducted in Giam Siak Kecil–Bukit Batu Biosphere Reserve
(GSKBB BR), in the Riau Province of Sumatera, Indonesia. A
biosphere reserve was selected as the study site because such reserves
aim to reconcile conservation with sustainable development. A
biosphere reserve should promote a range of local human activities,
together with development values that are in line spatially and
economically with the area conservation values, through use of a
zoning system. Moreover, GSKBB BR is an area with vast peatlands,
and is experiencing forest fires annually. Various factors were
analysed to assess the drivers of deforestation and forest degradation
in GSKBB BR; data were collected from focus group discussions
with stakeholders, key informant interviews with key stakeholders,
field observation and a literature review. Landsat satellite imagery was used to map forest-cover changes
for various periods. Analysis of landsat images, taken during the
period 2010-2014, revealed that within the non-protected area of core
zone, there was a trend towards decreasing peat swamp forest areas,
increasing land clearance, and increasing areas of community oilpalm
and rubber plantations. Fire was used for land clearing and most
of the forest fires occurred in the most populous area (the transition
area). The study found a relationship between the deforested/
degraded areas, and certain distance variables, i.e. distance from
roads, villages and the borders between the core area and the buffer
zone. The further the distance from the core area of the reserve, the
higher was the degree of deforestation and forest degradation. Research findings suggested that agricultural expansion may be
the direct cause of deforestation and forest degradation in the reserve,
whereas socio-economic factors were the underlying driver of forest
cover changes; such factors consisting of a combination of sociocultural,
infrastructural, technological, institutional (policy and governance), demographic (population pressure) and economic
(market demand) considerations. These findings indicated that local
factors/problems were the critical causes of deforestation and
degradation in GSKBB BR. This research therefore concluded that
reductions in deforestation and forest degradation in GSKBB BR
could be achieved through ‘local actor’-tailored approaches such as
community empowerment.
Abstract: Aurèsregion is one of the arid and semi-arid areas that
have suffered climate crises and overexploitation of natural resources
they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and
its spatiotemporal changes in the Aurès between 1987 and 2013, for
this work, we adopted a method of analysis based on the exploitation
of the images satellite Landsat TM 1987 and Landsat OLI 2013, from
the supervised classification likelihood coupled with field surveys of
the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover
maps from 1987 and 2013, one can extract a spatial map change of
different land cover units. The results show that between 1987 and
2013 vegetation has suffered negative changes are the significant
degradation of forests and steppe rangelands, and sandy soils and
bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013
allows us to understand the extensive or regressive orientation of
vegetation and soil, this map shows that dense forests give his place
to clear forests and steppe vegetation develops from a degraded forest
vegetation and bare, sandy soils earn big steppe surfaces that explain
its remarkable extension.
The analysis of remote sensing data highlights the profound
changes in our environment over time and quantitative monitoring of
the risk of desertification.
Abstract: Distributed applications deployed on LEO satellites
and ground stations require substantial communication between
different members in a constellation to overcome the earth
coverage barriers imposed by GEOs. Applications running on LEO
constellations suffer the earth line-of-sight blockage effect. They
need adequate lab testing before launching to space. We propose
a scalable cloud-based network simulation framework to simulate
problems created by the earth line-of-sight blockage. The framework
utilized cloud IaaS virtual machines to simulate LEO satellites
and ground stations distributed software. A factorial ANOVA
statistical analysis is conducted to measure simulator overhead on
overall communication performance. The results showed a very low
simulator communication overhead. Consequently, the simulation
framework is proposed as a candidate for testing LEO constellations
with distributed software in the lab before space launch.
Abstract: For this study, a town based soil database created in
Gümüsçay District of Biga Town, Çanakkale, Turkey. Crop and
livestock production are major activities in the district. Nutrient
management is mainly based on commercial fertilizer application
ignoring the livestock manure. Within the boundaries of district, 122
soil sampling points determined over the satellite image. Soil samples
collected from the determined points with the help of handheld
Global Positioning System. Labeled samples were sent to a
commercial laboratory to determine 11 soil parameters including
salinity, pH, lime, organic matter, nitrogen, phosphorus, potassium,
iron, manganese, copper and zinc. Based on the test results soil maps
for mentioned parameters were developed using remote sensing, GIS,
and geostatistical analysis. In this study we developed a GIS database
that will be used for soil nutrient management. Methods were
explained and soil maps and their interpretations were summarized in
the study.
Abstract: Durian is the flagship fruit of Mindanao and there is
an abundance of several cultivars with many confusing identities/
names.
The project was conducted to develop procedure for reliable and
rapid detection and sorting of durian planting materials. Moreover, it
is also aimed to establish specific genetic or DNA markers for routine
testing and authentication of durian cultivars in question.
The project developed molecular procedures for routine testing.
SSR primers were also screened and identified for their utility in
discriminating durian cultivars collected.
Results of the study showed the following accomplishments:
1. Twenty (29) SSR primers were selected and identified based on
their ability to discriminate durian cultivars,
2. Optimized and established standard procedure for identification
and authentication of Durian cultivars
3. Genetic profile of durian is now available at Biotech Unit
Our results demonstrate the relevance of using molecular
techniques in evaluating and identifying durian clones. The most
polymorphic primers tested in this study could be useful tools for
detecting variation even at the early stage of the plant especially for
commercial purposes. The process developed combines the efficiency
of the microsatellites development process with the optimization of
non-radioactive detection process resulting in a user-friendly protocol
that can be performed in two (2) weeks and easily incorporated into
laboratories about to start microsatellite development projects. This
can be of great importance to extend microsatellite analyses to other
crop species where minimal genetic information is currently
available. With this, the University can now be a service laboratory
for routine testing and authentication of durian clones.
Abstract: Edge is variation of brightness in an image. Edge
detection is useful in many application areas such as finding forests,
rivers from a satellite image, detecting broken bone in a medical
image etc. The paper discusses about finding edge of multiple aerial
images in parallel. The proposed work tested on 38 images 37
colored and one monochrome image. The time taken to process N
images in parallel is equivalent to time taken to process 1 image in
sequential. Message Passing Interface (MPI) and Open Computing
Language (OpenCL) is used to achieve task and pixel level
parallelism respectively.
Abstract: In this paper we propose a novel methodology for
extracting a road network and its nodes from satellite images of
Algeria country.
This developed technique is a progress of our previous research
works. It is founded on the information theory and the mathematical
morphology; the information theory and the mathematical
morphology are combined together to extract and link the road
segments to form a road network and its nodes.
We therefore have to define objects as sets of pixels and to study
the shape of these objects and the relations that exist between them.
In this approach, geometric and radiometric features of roads are
integrated by a cost function and a set of selected points of a crossing
road. Its performances were tested on satellite images of Algeria
country.
Abstract: Dengue outbreaks are affected by biological,
ecological, socio-economic and demographic factors that vary over
time and space. These factors have been examined separately and still
require systematic clarification. The present study aimed to investigate
the spatial-temporal clustering relationships between these factors and
dengue outbreaks in the northern region of Sri Lanka. Remote sensing
(RS) data gathered from a plurality of satellites were used to develop
an index comprising rainfall, humidity and temperature data. RS data
gathered by ALOS/AVNIR-2 were used to detect urbanization, and a
digital land cover map was used to extract land cover information.
Other data on relevant factors and dengue outbreaks were collected
through institutions and extant databases. The analyzed RS data and
databases were integrated into geographic information systems,
enabling temporal analysis, spatial statistical analysis and space-time
clustering analysis. Our present results showed that increases in the
number of the combination of ecological factor and socio-economic
and demographic factors with above the average or the presence
contribute to significantly high rates of space-time dengue clusters.
Abstract: Bir El Djir is an important coastal township in Oran
department, located at 450 Km far away from Algiers on northwest of
Algeria. In this coastal area, the urban sprawl is one of the main
problems that reduce the limited highly fertile land. So, using the
remote sensing and GIS technologies have shown their great
capabilities to solve many earth resources issues.
The aim of this study is to produce land use and cover map for the
studied area at varied periods to monitor possible changes that may
occurred, particularly in the urban areas and subsequently predict
likely changes. For this, two spatial images SPOT and Landsat
satellites from 1987 and 2014 respectively were used to assess the
changes of urban expansion and encroachment during this period
with photo-interpretation and GIS approach.
The results revealed that the town of Bir El Djir has shown a
highest growth rate in the period 1987-2014 which is 1201.5 hectares
in terms of area. These expansions largely concern the new real estate
constructions falling within the social and promotional housing
programs launched by the government.
The most urban expansion is characterized by the new
construction in the form of spontaneous or peripheral precarious
habitat, but also unstructured slums settled especially in the
southeastern part of town.
Abstract: In this paper, the problem of fault detection and
isolation in the attitude control subsystem of spacecraft formation
flying is considered. In order to design the fault detection method, an
extended Kalman filter is utilized which is a nonlinear stochastic state
estimation method. Three fault detection architectures, namely,
centralized, decentralized, and semi-decentralized are designed based
on the extended Kalman filters. Moreover, the residual generation
and threshold selection techniques are proposed for these
architectures.
Abstract: Much attention is paid to the development of space
branch in Kazakhstan at present. Two Earth remote sensing satellites
of Kazakhstan have been launched successfully. Many projects
related to the development of components for satellite are carried in
Kazakhstan, in particular the project related to the development of
star tracker experimental model. It is planned to use the results of this
project for development of star tracker prototype in the future. This
article describes the main stages of development of star tracker
experimental model.
Abstract: Remote sensing plays a vital role in mapping of
resources and monitoring of environments of the earth. In the present
research study, mapping and monitoring of clay siltations occurred in
the Alkhod Dam of Muscat, Sultanate of Oman are carried out using
low-cost multispectral Landsat and ASTER data. The dam is
constructed across the Wadi Samail catchment for ground water
recharge. The occurrence and spatial distribution of siltations in the
dam are studied with five years of interval from the year 1987 of
construction to 2014. The deposits are mainly due to the clay, sand
and silt occurrences derived from the weathering rocks of ophiolite
sequences occurred in the Wadi Samail catchment. The occurrences
of clays are confirmed by minerals identification using ASTER
VNIR-SWIR spectral bands and Spectral Angle Mapper supervised
image processing method. The presence of clays and their spatial
distribution are verified in the field. The study recommends the
technique and the low-cost satellite data to similar region of the
world.