scholarly journals Natural Phenomena, Geoactive Zones and Their Use in Landscape Design

2021 ◽  
Vol 7 (12) ◽  
Author(s):  
M. Rogozin
Keyword(s):  
Satellite Images ◽  
Nature Reserve ◽  
Landscape Design ◽  
Natural Phenomena ◽  
Space Images ◽  
Different Types ◽  
Perm Krai ◽  
Trees And Shrubs

The research was carried out in the Vishersky Nature Reserve and in the adjacent territories (Perm Krai). We used methods of phyto- and bioindication and decoding of satellite images with the allocation of 8 types of geoactive zones with diameters 1, 3, 8, 16, 32, 55, 76 and 110 m. Such zones are favorable for biota and are studied by the biolocation method, the data of which have been confirmed by contact photography since 2009. It is shown that the studied 25 natural phenomena were formed on a combination of 2-3 “junior” zones with dimensions of 1–8 m when they were placed inside 2–3 “senior” zones with a size of 16–110 m. A hypothesis is put forward explaining the appearance of natural phenomena by the action of the Earth’s energies and their synergetic when radiating through geoactive zones. Distances from the centers of zones forming comfortable belts in the form of rings for biota are recommended for use in landscape design. For the most numerous zones of 1 and 3 m in size, this belt is located between radii of 0.31–0.48 m. For a zone of 8 m in size, the comfort ring is located between radii of 0.91–3.20 m; for a zone of 16 m — within a radius of 1.45 m and further to the zone border; for a zone of 32 m — from 1.75 m and to its border. For large zones 55, 76 and 110 m, they are determined from single observations and start from about a distance of 5.3 m; at the same time, there are additional belts identified in space images. The use of comfort rings of geoactive zones will help to create compositions of trees and shrubs directly on the rocks, as well as to grow different types of plants in dense biogroups.

Simulating Self-Regeneration and Self-Replication Processes Using Movable Cellular Automata with a Mutual Equilibrium Neighborhood

2020 ◽  
Vol 29 (4) ◽  
pp. 741-757
Author(s):  
Kateryna Hazdiuk ◽  
◽  
Volodymyr Zhikharevich ◽  
Serhiy Ostapov ◽  
◽  
...  
Keyword(s):  
Cellular Automata ◽  
Cellular Automaton ◽  
Three Dimensional ◽  
Computer Models ◽  
The Self ◽  
Model Construction ◽  
Natural Phenomena ◽  
Different Types ◽  
Movable Cellular Automata ◽  
Self Replication

This paper deals with the issue of model construction of the self-regeneration and self-replication processes using movable cellular automata (MCAs). The rules of cellular automaton (CA) interactions are found according to the concept of equilibrium neighborhood. The method is implemented by establishing these rules between different types of cellular automata (CAs). Several models for two- and three-dimensional cases are described, which depict both stable and unstable structures. As a result, computer models imitating such natural phenomena as self-replication and self-regeneration are obtained and graphically presented.

Podarcis siculus (Reptilia: Sauria: Lacertidae), a new alien species for Russian fauna

2020 ◽  
Vol 324 (3) ◽  
pp. 364-370
Author(s):  
B.S. Tuniyev ◽  
L.M. Shagarov ◽  
O.J. Arribas
Keyword(s):  
Alien Species ◽  
Urban Area ◽  
First Record ◽  
Survey Method ◽  
The Black Sea ◽  
Species Introduction ◽  
Space Images ◽  
The Caucasus ◽  
Podarcis Siculus ◽  
Trees And Shrubs

Podarcis siculus (Rafinesque-Schmaltz, 1810) or Italian wall lizard is one of the most invasive reptile-species. Recently, this lacertid lizard has been introduced to Mediterranean areas of southern Europe, South-West Asia (Turkey) and North America (USA). An abundant population of P. siculus was discovered on one of the sites of the Natural Ornithological Park in the Imeretinskaya Lowland, on an area of over 0.22 km2 (Sochi, Russia). The data were collected in the May of 2020 in a strip survey method in the Imeretinskaya Lowland. To identify the colonization area of the invader, we examined all 8 sections of the Natural Ornithological Park in the Imeretinskaya Lowland and adjacent urbanized areas. More than 150 animals were observed. These Italian wall lizards, undoubtedly, belong to the northern-central Italian morphotype (presumably P. s. campestris). This is the first record of this species in the former USSR area and, also, this is the species’ north-easternmost locality. The population inhabits secondary natural biotopes and urban area. Among them are the banks of artificial water bodies, areas with cultivated trees and shrubs, as well as parks, and house lawns in the urban area. Population density was estimated from eight to 40 specimens per 100 m of the transect. A moderate proportion of young specimens (more than a 40%) would indicate a healthy and continued growth of the emerging population. To determine the possible period of the species introduction, space images of the Imeretinskaya Lowland were analyzed beginning from the transformation of its landscape for the Winter Olympic Games of Sochi 2014 until the May of 2020. The introduction of the species presumably occurred with the delivery of large-sized ornamental trees and shrubs from Italy in 2012–2013. Podarcis siculus should be included in the list of herpetofauna of Russia and particularly of the Caucasus. This is an alien species with a proven ability to become an invasive species, what will lead to a greater undesirable and unavoidable contact with native small lizards of the genus Darevskia Arribas, 1997. On the other hand, as it is often observed with new invaders, a sudden rise in population abundance could be followed by a sharp decline. A continuous monitoring of the area in question and of the number of local Italian wall lizards is necessary to confirm or refute the assumed scenarios of further invasion of P. siculus on the Black Sea Coast of the Caucasus. Further action plans for this population should be developed depending on supposed future trends.

A dual U-Net algorithm for automating feature extraction from satellite imagery

2021 ◽  
pp. 154851292098354
Author(s):  
Samuel Humphries ◽  
Trevor Parker ◽  
Bryan Jonas ◽  
Bryan Adams ◽  
Nicholas J Clark
Keyword(s):  
Neural Networks ◽  
Object Detection ◽  
Satellite Images ◽  
Detection Algorithm ◽  
Military Operations ◽  
Detection Algorithms ◽  
Us Military ◽  
Standard Product ◽  
Different Types ◽  
Road Intersections

Quick identification of building and roads is critical for execution of tactical US military operations in an urban environment. To this end, a gridded, referenced, satellite images of an objective, often referred to as a gridded reference graphic or GRG, has become a standard product developed during intelligence preparation of the environment. At present, operational units identify key infrastructure by hand through the work of individual intelligence officers. Recent advances in Convolutional Neural Networks, however, allows for this process to be streamlined through the use of object detection algorithms. In this paper, we describe an object detection algorithm designed to quickly identify and label both buildings and road intersections present in an image. Our work leverages both the U-Net architecture as well the SpaceNet data corpus to produce an algorithm that accurately identifies a large breadth of buildings and different types of roads. In addition to predicting buildings and roads, our model numerically labels each building by means of a contour finding algorithm. Most importantly, the dual U-Net model is capable of predicting buildings and roads on a diverse set of test images and using these predictions to produce clean GRGs.

scholarly journals Impact of forest fire on the vegetable cover of radioactively contaminated areas

2021 ◽  
pp. 68-80
Author(s):  
V. Landin ◽  
O. Tishchenko ◽  
V. Gurelia ◽  
T. Kuchma ◽  
V. Feshchenko
Keyword(s):  
Remote Sensing ◽  
Spectral Data ◽  
Nature Reserve ◽  
Dry Forest ◽  
Exclusion Zone ◽  
Space Images ◽  
The Earth ◽  
Drainage Canals ◽  
The Impact ◽  
Artificial Reservoirs

This article presents the results of assessing the impact of fires on the vegetation of the Chernobyl Exclusion Zone and the zone of unconditional (mandatory) resettlement, Drevlyansky Nature Reserve using means of remote sensing of the Earth for the period from 1986 to 2020. The methods and criteria for assessing vegetation damage using spectral data obtained from space satellites of the Earth and using methods of geoinformation technologies are proposed. This methodology provides mapping vegetation through remote sensing imagery. Comparing space images of the territory of the exclusion zone and the zone of unconditional mandatory resettlement for 1986, 1999, 2013, 2017, 2018, 2019, 2020, for the period of 34 years after the accident, identified significant changes in the condition of lands belonging to forest and agricultural lands. In the result of the study revealed the changes observed in the boundaries of water bodies because drying of artificial reservoirs, changes in the direction of riverbeds, waterlogging of drainage canals and adjacent forest areas. The identified effect from fires in forests where dry forest materials have accumulated and from consequences of forest management. It is also noted, that according to the spectral data of space images, areas of forest damaged by insects are well defined. The study reveals

scholarly journals Pemetaan Klasifikasi Dan Analisa Perubahan Ekosistem Mangrove Menggunakan Citra Satelit Multi Temporal Di Karimunjawa, Jepara, Indonesia

2018 ◽  
Vol 21 (2) ◽  
pp. 97
Author(s):  
Nurul Latifah ◽  
Sigit Febrianto ◽  
Hadi Endrawati ◽  
Muhammad Zainuri
Keyword(s):  
Supervised Classification ◽  
Satellite Images ◽  
Mangrove Ecosystem ◽  
Nursery Ground ◽  
Fish Ponds ◽  
Natural Phenomena ◽  
Key Factors ◽  
Marine Life ◽  
Fisheries Resources ◽  
Multi Temporal

Mapping of Classification and Analysis of Changes in Mangrove Ecosystem Using Multi-Temporal Satellite Images in Karimunjawa, Jepara, Indonesia  Mangrove ecosystem is one of the three ecosystem in the coastal area which has important ecological role in supporting marine life and fisheries resources. These important roles include spawning ground and nursery ground for various marine organisms. However, in the last decades, mangrove ecosystem has been undergoing significant degradation. The aim of this research is to quantify the changes of mangrove coverage and density in Karimunjawa as well as key-factors leading to the changes. Supervised classification method (83% accuracy and Kappa coefficient 0.73%) was applied to satellite images to identify the temporal changes in mangrove coverage. Mangrove density was quantified using NDVI algorithm and NIR-RED wavelength. The result shows that during three periods of observed data, changes in mangrove coverage were significant: 126.81 ha increase (1992 – 2003); 82.37 ha decrease (1992 – 2017); and 209.18 ha decrease (2003 – 2017). Mangrove density in most part of Karimunjawa belongs to the category of ‘low’ (NDVI value: -1 – 0.33). Key factors contributing to the decrease mangrove coverage are deforestation, natural phenomena, land conversion into fish ponds and hotels. The only increase in the year 1992 – 2003 was caused by high sedimentation level that allows more mangroves to grow. Overall, the methods in this research could be used as an approach to describe to effectively monitor the changes of mangrove coverage in an area as basic data for sustainable environmental management. Ekosistem mangrove merupakan salah satu dari tiga ekosistem pesisir yang memiliki peranan ekologis penting dalam mendukung kehidupan dan keberlangsungan dari sumberdaya perikanan.  Hal tersebut dikarenakan fungsi mangrove sebagai tempat memijah dan asuhan bagi banyak biota air. Beberapa dekade terakhir keberadaan dari ekosisitem mangrove mengalami degradasi yang sangat signifikan. Tujuan dari penelitian ini adalah untuk mengetahui perubahan luasan dan kerapatan mangrove dan mengidentifikasi faktor penyebabnya.  Metode analisa perubahan luasan mangrove menggunakan citra satelit multi temporal dengan dilakukan pembuatan klasifikasi menggunakan metode supervised classification dengan nilai akurasi total 83% dengan Kappa koefisien 0,73%.  Setelah terseleksi antara mangrove dan non mangrove maka dilakukan perhitungan kerapatan tajuk menggunakan algoritma NDVI dengan memanfaatkan panjang gelombang NIR dan RED.  Hasil analisa spasial dengan rentang 3 tahun berbeda didapatkan perubahan penurunan dan penambahan luasan mangrove terjadi secara signifikan: tahun 1992 – 2003 telah terjadi penambahan luasan sebesar 126,81 ha; tahun 1992–2017 terjadi perubahan luasan sebesar 82,37 ha;  tahun 2003–2017 terjadi perubahan luasan sebesar 209,18 ha.  Kerapatan mangrove di Karimunjawa sebagian besar tergolong kategori kerapatan jarang dengan nilai NDVI antara -1 – 0,33. Faktor utama penyebab penurunan luasan mangrove antara lain penebangan liar, faktor alam, perubahan fungsi lahan menjadi pertambakan dan perhotelan.  Penambahan luasan mangrove terjadi pada antara tahun1992 sampai 2003 hal tersebut disebabkan sedimentasi yang menumpuk di pantai dan sudah ditumbuhi oleh mangrove.  Secara keseluruhan metode ini dapat menggambarkan perubahan secara efektif serta hasilnya dapat dipergunakan untuk pemantauan dan perencanaan ekosistem mangrove di suatu wilayah. 

scholarly journals Historical timber as a sustainable material, Studies about Islamic architecture in Egypt

2018 ◽  
Vol 5 (1) ◽  
pp. 27
Author(s):  
Dalia Shebl Said
Keyword(s):  
Timber Structures ◽  
Natural Phenomena ◽  
Historical Buildings ◽  
Islamic Architecture ◽  
Modern Material ◽  
Sustainable Building ◽  
Wide Range ◽  
Different Types ◽  
Material Studies

<p>Wood is an old – modern material, It was and still used in a wide range in a various purposes as construction, decoration and remains the most popular material all over the world, The research provides an overview of the role of  timber as an important heritage element which forms the main characters and distinguishes features of many historical buildings in Islamic architecture and used widely in many applications, it had been played a great role in construction and structure of buildings, besides that it had been used in a beautiful purpose in different places whether indoors or outdoors use<strong> </strong>. The research presents the case studies of historical timber in different types of building in Islamic architecture which constructed from more than 1400 years ago, although the historical timber in old buildings exposed to many disasters and faced quite numbers of problems as a result of natural phenomena, man-made, humidity, and termites but it still stands proudly as a great sustain materials. The research shows how he use of timber in historical buildings as sources of inspiration and living evidence of ways of sustainable building practices the types of deterioration which appeared clearly an effect on the statue of historical timber, for that the research introduces some recommendations in the light of ICOMOS international charter “ <a href="http://www.icomos.org/en/home/179-articles-en-francais/ressources/charters-and-standards/163-principles-for-the-preservation-of-historic-timber-structures">Principles for the Preservation of Historic Timber Structures</a> 1999” that Emphasizes the necessity of taking a serious steps and clear strategy to save our heritage elements</p>

scholarly journals Estimation of land-use changes on Kitulo Plateau, Tanzania, using satellite imagery

Oryx ◽  
1994 ◽  
Vol 28 (3) ◽  
pp. 173-182
Author(s):  
Jon C. Lovett ◽  
Erik Prins
Keyword(s):  
Land Use ◽  
Satellite Imagery ◽  
Vascular Plants ◽  
Satellite Images ◽  
Nature Reserve ◽  
Land Use Changes ◽  
Bare Soil ◽  
Digital Analysis ◽  
Threatened Plants ◽  
Strong Case

The Kitulo Plateau of southern Tanzania is a lava plateau covering 273 sq km at an altitude of over 2500 m. The vegetation is predominately grassland with more than 350 taxa of vascular plants, of which nearly 5 per cent are of restricted distribution. Although the plateau is extensive, much of it is now cultivated. Digital analysis of satellite images showed that at least 24 per cent of the plateau was bare soil, modified grassland or cultivation between 1973 and 1989. The botanical importance of the plateau and increase in cultivation make a strong case for the establishment of a nature reserve to protect its rare and threatened plants.

scholarly journals An Improved Boosting Learning Saliency Method for Built-Up Areas Extraction in Sentinel-2 Images

2018 ◽  
Vol 10 (12) ◽  
pp. 1863 ◽  
Author(s):  
Zhenhui Sun ◽  
Qingyan Meng ◽  
Weifeng Zhai
Keyword(s):  
Satellite Images ◽  
Good Accuracy ◽  
Particle Swarm Optimization Algorithm ◽  
Saliency Map ◽  
Band Combination ◽  
Saliency Maps ◽  
Training Samples ◽  
Different Types ◽  
Optical Satellite Images ◽  
Sentinel 2

Built-up areas extraction from satellite images is an important aspect of urban planning and land use; however, this remains a challenging task when using optical satellite images. Existing methods may be limited because of the complex background. In this paper, an improved boosting learning saliency method for built-up area extraction from Sentinel-2 images is proposed. First, the optimal band combination for extracting such areas from Sentinel-2 data is determined; then, a coarse saliency map is generated, based on multiple cues and the geodesic weighted Bayesian (GWB) model, that provides training samples for a strong model; a refined saliency map is subsequently obtained using the strong model. Furthermore, cuboid cellular automata (CCA) is used to integrate multiscale saliency maps for improving the refined saliency map. Then, coarse and refined saliency maps are synthesized to create a final saliency map. Finally, the fractional-order Darwinian particle swarm optimization algorithm (FODPSO) is employed to extract the built-up areas from the final saliency result. Cities in five different types of ecosystems in China (desert, coastal, riverside, valley, and plain) are used to evaluate the proposed method. Analyses of results and comparative analyses with other methods suggest that the proposed method is robust, with good accuracy.

Vegetation mapping of Svalbard utilising Landsat TM/ETM+ data

Polar Record ◽  
2011 ◽  
Vol 48 (1) ◽  
pp. 47-63 ◽  
Author(s):  
Bernt E. Johansen ◽  
Stein Rune Karlsen ◽  
Hans Tømmervik
Keyword(s):  
Satellite Images ◽  
Satellite Image ◽  
Landsat Tm ◽  
Inland Waters ◽  
Vegetation Density ◽  
Ancillary Data ◽  
Vegetation Map ◽  
Digital Format ◽  
Different Types ◽  
Classified Image

ABSTRACTThe overall objective of this paper is to present and discuss the most recently developed vegetation map for Svalbard, Arctic Norway. The map is based on satellite images in which several Landsat TM/ETM+ images were processed through six operational stages involving: (1) automatic image classification, (2) spectral similarity analysis, (3) generation of classified image mosaics, (4) ancillary data analysis, (5) contextual correction, and (6) standardisation of the final map products. The developed map is differentiated into 18 map units interpreted from 37 spectral classes. Among the 18 units separated, six of the units comprise rivers, lakes and inland waters, glaciers, as well as non- to sparsely vegetated areas. The map unit 7 is a result of shadow effects and different types of distortions in the satellite image. The vegetation of the remaining eleven units varies from dense marshes and moss tundra communities to sparsely vegetated polar deserts and moist gravel snowbeds. The accuracy of the map is evaluated in areas were access to traditional maps have been available. The vegetation density and fertility is reflected in computed NDVI values. The map product is in digital format, which gives the opportunity to produce maps in different scales. A map sheet portraying the entire archipelago is one of the main products from this study, produced at a scale of 1:500,000.

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