scholarly journals Effect of artificial structures on shoreline profile of Selingan Island, Sandakan, Sabah, Malaysia

2018 ◽  
Vol 2 ◽  
pp. 9-15
Author(s):  
Ejria Saleh ◽  
Chen Nuo Geng ◽  
Yap Tzuen Kiat ◽  
Irwan Isnain
Keyword(s):  
Field Observation ◽  
Satellite Images ◽  
High Volume ◽  
Google Earth ◽  
Beach Erosion ◽  
Coral Triangle ◽  
Shoreline Changes ◽  
Shoreline Protection ◽  
Beach Profiling ◽  
Shape And Size

Selingan Island off Sandakan, Sabah is a famous turtle nesting ground and gazette as Turtle Island Park (TIP) within Malaysian Coral Triangle areas. However, beach erosion contribute to loss of turtle nesting area on the island. To counter this, Sabah Parks had deployed stone revetments in 2005, followed by the reef balls deployment at the southern part of the Selingan Island in 2007. Therefore, objectives of this study are to determine the shoreline changes and reef balls’ effectiveness as shoreline protection. Shoreline changes were determined from satellite images, beach profiling and field observation. Two years interval of satellite images from 2010 to 2016 were obtained from Google Earth Pro, analyzed and overlaid to determine changes of shape and size of the island with QGIS software. Beach profiling was performed on 29th December 2017 at three sites and compared with 2011. The findings indicated that the shape of the island was squeezed towards the east where the reef balls were located. The size of the island does not change much within 9 years after the deployment of the reef balls, but a high volume of sediments accumulated at the south due to the presence of shoreline protection. Generally, the man-made structures in Selingan Island are effective trapping sediment and provide more nesting area for turtles. It is recommended that the dynamic of the island should be monitored by analyzing more satellite images or photos to reflect the changes of the island for better understanding on the changes of the island.

Regional-scale analysis of dune-beach systems using Google Earth Engine

2021 ◽  
Author(s):  
Melissa Latella ◽  
Arjen Luijendijk ◽  
Carlo Camporeale
Keyword(s):  
Ecosystem Services ◽  
Satellite Images ◽  
Regional Scale ◽  
Google Earth ◽  
Classification Algorithm ◽  
Mitigation Strategies ◽  
Training Data ◽  
Machine Learning Techniques ◽  
Beach Width ◽  
Google Earth Engine

<p>Coastal sand dunes provide a large variety of ecosystem services, among which the inland protection from marine floods. Nowadays, this protection is fundamental, and its importance will further increase in the future due to the rise of the sea level and storm violence induced by climate change. Despite the crucial role of coastal dunes and their potential application in mitigation strategies, the phenomenon of the coastal squeeze, which is mainly caused by the urban sprawl, is progressively reducing the extents of the areas where dune can freely undergo their dynamics, thus dramatically impairing their capability of providing ecosystem services.</p><p>Aiming to embed the use of satellite images in the study of coastal foredune and beach dynamics, we developed a classification algorithm that uses the satellite images and server-side functions of Google Earth Engine (GEE). The algorithm runs on the GEE Python API and allows the user to retrieve all the available images for the study site and the chosen time period from the selected sensor collection. The algorithm also filters the cloudy and saturated pixels and creates a percentile-composite image over which it applies a random forest classification algorithm. The classification is finally refined by defining a mask for land pixels only. </p><p>According to the provided training data and sensor selection, the algorithm can give different outcomes, ranging from sand and vegetation maps, beach width measurements, and shoreline time evolution visualization. This very versatile tool that can be used in a great variety of applications within the monitoring and understanding of the dune-beach systems and associated coastal ecosystem services. For instance, we show how this algorithm, combined with machine learning techniques and the assimilation of real data, can support the calibration of a coastal model that gives the natural extent of the beach width and that can be, therefore, used to plan restoration activities. </p>

scholarly journals Correction of Very High-Resolution Satellite Images using Control Points Captured by Web Map Service (WMS) server: Google Earth

2020 ◽  
Vol 9 (8) ◽  
pp. 188-194
Keyword(s):  
Large Scale ◽  
Satellite Images ◽  
Google Earth ◽  
Ground Control ◽  
Control Points ◽  
Web Map ◽  
Ground Control Points ◽  
High Resolution Satellite Images ◽  
Map Scale ◽  
Map Service

The recent progress for spatial resolution of remote sensing imagery led to generate many types of Very HighResolution (VHR) satellite images, consequently, general speaking, it is possible to prepare accurate base map larger than 1:10,000 scale. One of these VHR satellite image is WorldView-3 sensor that launched in August 2014. The resolution of 0.31m makes WorldView-3 the highest resolution commercial satellite in the world. In the current research, a pan-sharpen image from that type, covering an area at Giza Governorate in Egypt, used to determine the suitable large-scale map that could be produced from that image. To reach this objective, two different sources for acquiring Ground Control Points (GCPs). Firstly, very accurate field measurements using GPS and secondly, Web Map Service (WMS) server (in the current research is Google Earth) which is considered a good alternative when GCPs are not available, are used. Accordingly, three scenarios are tested, using the same set of both 16 Ground Control Points (GCPs) as well as 14 Check Points (CHKs), used for evaluation the accuracy of geometric correction of that type of images. First approach using both GCPs and CHKs coordinates acquired by GPS. Second approach using GCPs coordinates acquired by Google Earth and CHKs acquired by GPS. Third approach using GCPs and CHKs coordinates by Google Earth. Results showed that, first approach gives Root Mean Square Error (RMSE) planimeteric discrepancy for GCPs of 0.45m and RMSE planimeteric discrepancy for CHKs of 0.69m. Second approach gives RMSE for GCPs of 1.10m and RMSE for CHKs of 1.75m. Third approach gives RMSE for GCPs of 1.10m and RMSE for CHKs of 1.40m. Taking map accuracy specification of 0.5mm of map scale, the worst values for CHKs points (1.75m&1,4m) resulted from using Google Earth as a source, gives the possibility of producing 1:5000 large-scale map compared with the best value of (0.69m) (map scale 1:2500). This means, for the given parameters of the current research, large scale maps could be produced using Google Earth, in case of GCPs are not available accurately from the field surveying, which is very useful for many users.

scholarly journals JAMAICA BAY HURRICANE BARRIER

1970 ◽  
Vol 1 (12) ◽  
pp. 125
Author(s):  
Frank L. Panuzio
Keyword(s):  
New York ◽  
Mathematical Models ◽  
High Volume ◽  
Beach Erosion ◽  
High Peak ◽  
Flood Protection ◽  
Rainfall Runoff ◽  
Design Storm ◽  
Jamaica Bay ◽  
Ecological Objectives

A 12 4 mile beach erosion control and hurricane flood protection project includes Jamaica Bay and the Rockaway Inlet in the southwest corner of Long Island, New York«i The project would provide 6 1 miles of beach fill and floodwalls along the Atlantic Ocean shore and 6 3 miles of inland structures to tie back to high ground, including a 0 9 mile barrier across the inlet The barrier, with a 300 foot gated opening and a 300 foot ungated opening, would permit suppression of the design hurricane surge so as to eliminate the need of flood protection works within the bay Linear mathematical models were used to determine these openings Because of the limitation of these models to produce adequate data m the bay pertinent to environmental and ecological considerations, three hydraulic models were utilized General conclusions drawn from the hydraulic model test data are that the results of the mathematical models were upheld, a design storm with high peak is critical for determining the height of protection, a design storm with high volume rather than high peak plus rainfall runoff is critical in determining ungated openings and suppression of bay levels, and there is a combination of gated and ungated openings that would meet the flood protection, navigation, environmental and ecological objectives.

BEACH PROCESSES AND SHORE PROTECTION ALONG THE NORTHERN COLOMBIA COAST

2020 ◽  
Vol 1 (2) ◽  
pp. 60-85
Author(s):  
PING WANG
Keyword(s):  
Beach Erosion ◽  
Trade Wind ◽  
Sand Transport ◽  
Shore Protection ◽  
Tropical Zone ◽  
Longshore Sediment Transport ◽  
Longshore Transport ◽  
Shoreline Protection ◽  
Beach Processes ◽  
Northeast Trade Wind

The shoreline of northern Colombia is located in the tropical zone along the south coast of Caribbean Sea. Its coastal processes are strongly influenced by the northeast trade wind, which results in the dominating northeasterly approaching wave occurring over 95% of the time. This drives a persistent southwestward longshore sand transport. The state of the beach along the generally northeast-southwest trending northern Colombia coast is strongly influenced by this constant unidirectional longshore sediment transport. At locations where this westward longshore sand transport is interrupted, naturally or  anthropogenically, beach accretion occurs along the updrift shoreline coupled with erosion at the downdrift side. Natural interruption of longshore transport can be caused by tidal inlets, protruding headland, shoreline orientation change, and nearshore bathymetry variations. Anthropogenic interruption of the longshore transport along the northern Colombia coast is mainly caused by the construction of groins, as well as harbors at some locations. Numerous groins were constructed due to their local success in creating beach accretion at the drift side. However, severe beach erosion occurs along the downdrift shoreline. Shoreline protection along the northern Colombia coast, and coasts in the tropical area in general, should carefully consider the persistent unidirectional longshore sand transport and should not be misguided by the local updrift accumulation as being a successful project.

Identification of Tectonic Activity and Fault Mechanism From Morphological Signatures

2019 ◽  
pp. 99-123
Author(s):  
Arunima Nandy
Keyword(s):  
Active Zone ◽  
Satellite Images ◽  
Google Earth ◽  
Tectonic Activity ◽  
Landsat 8 ◽  
North East India ◽  
North East ◽  
Gis And Rs ◽  
Fault Mechanism ◽  
Tectonic Activities

Agartala, the capital of Tripura, is one of the most important and populated cities of North-East India. From the aspect of geomorphology, the whole area is characterized by highlands (tilla) and lowlands (lunga). Tectonically, Tripura falls under very active zone (Zone V). Assessment of tectonic activities of this region is very significant. For identification of tectonic activity, morphological or geomorphic signatures play very important role. The chapter identifies the presence of tectonic activity from morphological signatures in and around Agartala city. Landsat 8 OLI, maps from Geological Survey of India, Google Earth imageries have been used in this study. The presence of some lineaments and sag ponds has been identified on the basis of which fault mechanism of Agartala and Baramura hills has been delineated. This study contains a brief note on the conceptual demonstration of application of GIS and RS technologies and how morphological signatures and satellite images can help us to recognize tectonic activities over a region.

scholarly journals Detection of Archaeological Looting from Space: Methods, Achievements and Challenges

2019 ◽  
Vol 11 (20) ◽  
pp. 2389 ◽  
Author(s):  
Deodato Tapete ◽  
Francesca Cigna
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
High Resolution ◽  
Satellite Data ◽  
Satellite Images ◽  
Google Earth ◽  
Optical Data ◽  
Mena Region ◽  
Processing Methods ◽  
Optical Imagery

Illegal excavations in archaeological heritage sites (namely “looting”) are a global phenomenon. Satellite images are nowadays massively used by archaeologists to systematically document sites affected by looting. In parallel, remote sensing scientists are increasingly developing processing methods with a certain degree of automation to quantify looting using satellite imagery. To capture the state-of-the-art of this growing field of remote sensing, in this work 47 peer-reviewed research publications and grey literature are reviewed, accounting for: (i) the type of satellite data used, i.e., optical and synthetic aperture radar (SAR); (ii) properties of looting features utilized as proxies for damage assessment (e.g., shape, morphology, spectral signature); (iii) image processing workflows; and (iv) rationale for validation. Several scholars studied looting even prior to the conflicts recently affecting the Middle East and North Africa (MENA) region. Regardless of the method used for looting feature identification (either visual/manual, or with the aid of image processing), they preferred very high resolution (VHR) optical imagery, mainly black-and-white panchromatic, or pansharpened multispectral, whereas SAR is being used more recently by specialist image analysts only. Yet the full potential of VHR and high resolution (HR) multispectral information in optical imagery is to be exploited, with limited research studies testing spectral indices. To fill this gap, a range of looted sites across the MENA region are presented in this work, i.e., Lisht, Dashur, and Abusir el Malik (Egypt), and Tell Qarqur, Tell Jifar, Sergiopolis, Apamea, Dura Europos, and Tell Hizareen (Syria). The aim is to highlight: (i) the complementarity of HR multispectral data and VHR SAR with VHR optical imagery, (ii) usefulness of spectral profiles in the visible and near-infrared bands, and (iii) applicability of methods for multi-temporal change detection. Satellite data used for the demonstration include: HR multispectral imagery from the Copernicus Sentinel-2 constellation, VHR X-band SAR data from the COSMO-SkyMed mission, VHR panchromatic and multispectral WorldView-2 imagery, and further VHR optical data acquired by GeoEye-1, IKONOS-2, QuickBird-2, and WorldView-3, available through Google Earth. Commonalities between the different image processing methods are examined, alongside a critical discussion about automation in looting assessment, current lack of common practices in image processing, achievements in managing the uncertainty in looting feature interpretation, and current needs for more dissemination and user uptake. Directions toward sharing and harmonization of methodologies are outlined, and some proposals are made with regard to the aspects that the community working with satellite images should consider, in order to define best practices of satellite-based looting assessment.

scholarly journals New discoveries on astronomical orientation of Inca site in Ollantaytambo, Peru

2015 ◽  
Vol 14 (2) ◽  
pp. 37-46
Author(s):  
Karolína Hanzalová ◽  
Jaroslav Klokočník ◽  
Jan Kostelecký
Keyword(s):  
Digital Elevation Model ◽  
Satellite Images ◽  
Observation Point ◽  
Google Earth ◽  
The Sun ◽  
Winter Solstice ◽  
Machu Picchu ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Temple

<p>This paper deals with astronomical orientation of Incas objects in Ollantaytambo, which is located about 35 km southeast from Machu Picchu, about 40 km northwest from Cusco, and lies in the Urubamba valley. Everybody writing about Ollantaytambo, shoud read Protzen. (1)  He devoted his monograph to description and interpretation of that locality. Book of Salazar and Salazar (2) deals, among others, with the orientation of objects in Ollantaytambo with respect to the cardinal direction. Zawaski and Malville (3) documented astronomical context of major monuments of nine sites in Peru, including Ollantaytambo. We tested astronomical orientation in these places and confirm or disprove hypothesis about purpose of Incas objects. For assessment orientation of objects we used our measurements and also satellite images on Google Earth and digital elevation model from ASTER. The satellite images were used to estimate the astronomical-solar-solstice orientation, together with terrestrial images from Salazar and Salazar (2). The digital elevation model is useful in the mountains, where we need the actual horizon for a calculation of sunset and sunrise on specific days (solstices), which were for Incas people very important. We tested which astronomical phenomenon is connected with objects in Ollantaytambo. First, we focused on Temple of the Sun, also known the Wall of six monoliths.  We tested winter solstice sunrise and the rides of the Pleiades for the epochs 2000, 1500 and 1000 A.D. According with our results the Temple isn´t connected neither with winter solstice sunrise nor with the Pleiades. Then we tested also winter solstice sunset. We tried to use the line from an observation point near ruins of the Temple of Sun, to west-north, in direction to sunset. The astronomical azimuth from this point was about 5° less then we need. From this results we found, that is possible to find another observation point. By Salazar and Salazar (2) we found observation point at the corner (east rectangle) of the pyramid by <em>Pacaritanpu,</em> down by the riverside. There is a line connecting the east rectangular “platform” at the river, going along the Inca road up to vicinity of the Temple of the Sun and then in the direction to the Inca face. Using a digital elevation model we found the astronomical azimuth, which is needed for confirm astronomical orientation of the Temple. So, finally we are able to demonstrate a possibility of the solar-solstice orientation in Ollantaytambo.</p>

The Northern Bald Ibis Geronticus eremita in Morocco since 1900: Analysis of ecological requirements

2019 ◽  
Vol 30 (1) ◽  
pp. 117-138 ◽  
Author(s):  
ANDRE SCHENKER ◽  
FABIAN CAHENZLI ◽  
KARL G. GUTBROD ◽  
MICHEL THEVENOT ◽  
ANDREAS ERHARDT
Keyword(s):  
National Park ◽  
Satellite Images ◽  
Atlantic Coast ◽  
Bird Species ◽  
Earth Satellite ◽  
Google Earth ◽  
Mean Annual Precipitation ◽  
Breeding Sites ◽  
Ecological Requirements ◽  
Geronticus Eremita

SummaryThe Northern Bald Ibis (NBI) Geronticus eremita, is an ‘Endangered’ bird species of which only very few wild breeding colonies have survived along the Atlantic coast of south-west Morocco. This paper analyses ecological conditions of the 72 breeding sites of the NBI that have been known since 1900 in Morocco. Characterisation of breeding sites is based on physical criteria (elevation above sea level, geomorphology, mean annual precipitation and types of landscape) as well as land use, vegetation cover, infrastructure and types of settlement within three perimeters (0–1 km, > 1–5 km and > 5–10(20) km) using Google Earth satellite images. Statistical analyses of the number of breeding pairs, fledglings and rainfall during different quarters of the year from 1994 to 2016 in the two remaining breeding sites in Souss-Massa National Park and Tamri showed expected patterns as well as unexpected differences between the two localities. Based on our findings and indications in the literature, we suggest general and specific recommendations for potential future translocation projects of the NBI. Based on the analysis of the 28 breeding colonies existing after 1977, two elements emerge as the most important prerequisites: a low level of disturbances at the breeding sites and adequate feeding areas at a reasonable distance of 5–15 km.

scholarly journals Integration of Machine Learning and Open Access Geospatial Data for Land Cover Mapping

2019 ◽  
Vol 11 (16) ◽  
pp. 1907 ◽  
Author(s):  
Mohammad Mardani ◽  
Hossein Mardani ◽  
Lorenzo De Simone ◽  
Samuel Varas ◽  
Naoki Kita ◽  
...  
Keyword(s):  
Machine Learning ◽  
Developing Countries ◽  
Open Access ◽  
Land Cover ◽  
Satellite Images ◽  
National Level ◽  
Google Earth ◽  
Support Vector ◽  
Land Cover Mapping ◽  
Sustainable Food

In-time and accurate monitoring of land cover and land use are essential tools for countries to achieve sustainable food production. However, many developing countries are struggling to efficiently monitor land resources due to the lack of financial support and limited access to adequate technology. This study aims at offering a solution to fill in such a gap in developing countries, by developing a land cover solution that is free of costs. A fully automated framework for land cover mapping was developed using 10-m resolution open access satellite images and machine learning (ML) techniques for the African country of Lesotho. Sentinel-2 satellite images were accessed through Google Earth Engine (GEE) for initial processing and feature extraction at a national level. Also, Food and Agriculture Organization’s land cover of Lesotho (FAO LCL) data were used to train a support vector machine (SVM) and bagged trees (BT) classifiers. SVM successfully classified urban and agricultural lands with 62 and 67% accuracy, respectively. Also, BT could classify the two categories with 81 and 65% accuracy, correspondingly. The trained models could provide precise LC maps in minutes or hours. they can also be utilized as a viable solution for developing countries as an alternative to traditional geographic information system (GIS) methods, which are often labor intensive, require acquisition of very high-resolution commercial satellite imagery, time consuming and call for high budgets.

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