scholarly journals PEMETAAN SUBSTRAT DASAR PERAIRAN DANGKAL DI KECAMATAN TAYANDO KOTA TUAL MENGGUNAKAN CITRA LANDSAT 8

2017 ◽  
Author(s):  
Fabian Souisa ◽  
Marvin Mario Makailipessy
Keyword(s):  
Coral Reefs ◽  
Classification Scheme ◽  
Shallow Waters ◽  
Landsat 8 ◽  
Dead Coral ◽  
Shallow Marine ◽  
Bottom Substrate ◽  
Habitat Classification ◽  
Basic Characteristics

This study aimed to determine mapped of the substrate (habitat) of the bottom shallow waters at Tayando District, Tual City with Landsat 8 imagery satellite. We used transformation blue and green bands with depth invariant index algorithm Y = ln Band 1 + (ki/kj) ln Band 2 on mapped the basic characteristics of the bottom shallow water. The classification of the imagery transformation by using shallow marine water habitat classification scheme based on color pallet and the result showed there were five classes on bottom substrate at Tayando District, those were sand, sand mixed coral, dead coral, coral reefs and seagrass.

TUTUPAN TERUMBU KARANG KABUPATEN KOTABARU PROVINSI KALIMANTAN SELATAN (STUDI KASUS PERAIRAN SEPAGAR)

2016 ◽  
Vol 3 (6) ◽  
pp. 90
Author(s):  
Deddy Dharmaji
Keyword(s):  
Coral Reefs ◽  
Coral Cover ◽  
Patch Reef ◽  
Shallow Waters ◽  
Living Coral ◽  
Dead Coral ◽  
Total Percentage ◽  
Coral Sand ◽  
The Village ◽  
Management And Conservation

This research aims to know the percentage of living coral cover in the village of Sepagar. The benefits of this research are as input for the parties involved in the efforts of the management and conservation of coral reefs in the waters of the village Sepagar. The results of the observation and calculation of the coral reefs is done using the method of Point Intercept Trancek (PIT) shows that the community of coral reefs in the waters of the Sepagar included in the types of coral reefs of the sandbar (patch reef). Generally burnt coral reefs grow and develop in the relatively shallow waters with depths ranging from 1-5 meters. The results showed on the three stations found 7 of the 10 components of the reef that is. Acropora (AC), Non-Acropora (NA), Dead Coral with Algae (DCA), Dead Coral (DC), Soft Coral Sand (SC) (S), and the Rubble (R). Component not found is Fleshy Seawed (FS), Rock (RK) and Silt (SL). At station 1, the total percentage of living coral closure (living cover) by 51.4%, In station 2 of 55,3 % , and in station 3 of 51.3 % .The percentage the coral lived in waters sepagar in good not far different the percentage the coral live in every station.

scholarly journals Classification of shallow water seabed profile based on Landsat 8 imagery and in-situ data. Case study in Gili Matra Island Lombok, Indonesia

2018 ◽  
Vol 47 ◽  
pp. 04002
Author(s):  
Ratih Ayustina ◽  
Zahra Aulia ◽  
Haji Mustakin ◽  
Fiyesti Alam ◽  
Amron Amron ◽  
...  
Keyword(s):  
Shallow Water ◽  
Image Classification ◽  
Field Survey ◽  
Landsat 8 ◽  
Dead Coral ◽  
In Situ Data ◽  
Remote Sensing Techniques

Shallow water seabed profile has considerable potential resources so the availability of information which very important for coastal resources. The use of remote sensing techniques is considered to provide coastal information effective and efficient. This research aimed to determine the shallow water seabed profile based on Landsat 8 Imagery and its accuracy related to the in situ data. Methods of this research are satellite mage pre-processing, image classification, field survey, image classification, and accuracy assesment . Therefore, 6 classification of shallow water seabed profile, there are rubble (R), seagrass mixed sand (MIX -SG/SD), coral reefs mixed rubble (MIX-C/RB), rubble mixed dead coral (MIX-RB/DC), sand mixed rubble (MIX-SD/RB), and sand mixed seagrass (MIX-SD/SG), respectevely. The result of this classification has an accuracy value 80%.

Raiders Activity on the Market for Corporate Control as a Product of Coercive Entrepreneurship Evolution

2007 ◽  
pp. 80-92
Author(s):  
A. Kireev
Keyword(s):  
Corporate Control ◽  
Role Of Government ◽  
Market For Corporate Control ◽  
Basic Characteristics

The paper studies the problem of raiders activity on the market for corporate control. This activity is considered as a product of coercive entrepreneurship evolution. Their similarities and sharp distinctions are shown. The article presents the classification of raiders activity, discribes its basic characteristics and tendencies, defines the role of government in the process of its transformation.

Pemetaan Pulau Kecil Gelasa Kabupaten Bangka Tengah

2019 ◽  
Vol 2 (1) ◽  
pp. 11-14
Author(s):  
Wahyu Adi
Keyword(s):  
Coral Reefs ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Image Interpretation ◽  
Vegetation Coverage ◽  
Small Island ◽  
Shallow Waters ◽  
Small Islands ◽  
Seagrass Beds ◽  
Cover Density

Pulau Kecil Gelasa merupakan daerah yang belum banyak diteliti. Pemetaan ekosistem di pulau kecil dilakukan dengan bantuan citra Advanced Land Observing Satellite (ALOS). Penelitian terdahulu diketahui bahwa ALOS memiliki kemampuan memetakan terumbu karang dan padang lamun di perairan dangkal serta mampu memetakan kerapatan penutupan vegetasi. Metode interpretasi citra menggunakan alogaritma indeks vegetasi pada citra ALOS yaitu NDVI (Normalized Difference Vegetation Index), serta pendekatan Lyzengga untuk mengkoreksi kolom perairan. Hasil penelitian didapatkan luasan Padang Lamun di perairan dangkal 41,99 Ha, luasan Terumbu Karang 125,57 Ha. Hasil NDVI di daratan/ pulau kecil Gelasa untuk Vegetasi Rapat seluas 47,62 Ha; luasan penutupan Vegetasi Sedang 105,86 Ha; dan penutupan Vegetasi Jarang adalah 34,24 Ha.   Small Island Gelasa rarely studied. Mapping ecosystems on small islands with the image of Advanced Land Observing Satellite (ALOS). Previous research has found that ALOS has the ability to map coral reefs and seagrass beds in shallow water, and is able to map vegetation cover density. The method of image interpretation uses the vegetation index algorithm in the ALOS image, NDVI (Normalized Difference Vegetation Index), and the Lyzengga approach to correct the water column. The results of the study were obtained in the area of Seagrass Padang in the shallow waters of 41.99 ha, the area of coral reefs was 125.57 ha. NDVI results on land / small islands Gelasa for dense vegetation of 47.62 ha; area of Medium Vegetation coverage 105.86 Ha; and the coverage of Rare Vegetation is 34.24 Ha.

scholarly journals Mapping Allochemical Limestone Formations in Hazara, Pakistan Using Google Cloud Architecture: Application of Machine-Learning Algorithms on Multispectral Data

2021 ◽  
Vol 10 (2) ◽  
pp. 58
Author(s):  
Muhammad Fawad Akbar Khan ◽  
Khan Muhammad ◽  
Shahid Bashir ◽  
Shahab Ud Din ◽  
Muhammad Hanif
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Learning Algorithms ◽  
Remote Sensing Data ◽  
Kappa Coefficient ◽  
Machine Learning Algorithms ◽  
Landsat 8 ◽  
Sensing Data ◽  
Fossiliferous Limestone

Low-resolution Geological Survey of Pakistan (GSP) maps surrounding the region of interest show oolitic and fossiliferous limestone occurrences correspondingly in Samanasuk, Lockhart, and Margalla hill formations in the Hazara division, Pakistan. Machine-learning algorithms (MLAs) have been rarely applied to multispectral remote sensing data for differentiating between limestone formations formed due to different depositional environments, such as oolitic or fossiliferous. Unlike the previous studies that mostly report lithological classification of rock types having different chemical compositions by the MLAs, this paper aimed to investigate MLAs’ potential for mapping subclasses within the same lithology, i.e., limestone. Additionally, selecting appropriate data labels, training algorithms, hyperparameters, and remote sensing data sources were also investigated while applying these MLAs. In this paper, first, oolitic (Samanasuk), fossiliferous (Lockhart and Margalla) limestone-bearing formations along with the adjoining Hazara formation were mapped using random forest (RF), support vector machine (SVM), classification and regression tree (CART), and naïve Bayes (NB) MLAs. The RF algorithm reported the best accuracy of 83.28% and a Kappa coefficient of 0.78. To further improve the targeted allochemical limestone formation map, annotation labels were generated by the fusion of maps obtained from principal component analysis (PCA), decorrelation stretching (DS), X-means clustering applied to ASTER-L1T, Landsat-8, and Sentinel-2 datasets. These labels were used to train and validate SVM, CART, NB, and RF MLAs to obtain a binary classification map of limestone occurrences in the Hazara division, Pakistan using the Google Earth Engine (GEE) platform. The classification of Landsat-8 data by CART reported 99.63% accuracy, with a Kappa coefficient of 0.99, and was in good agreement with the field validation. This binary limestone map was further classified into oolitic (Samanasuk) and fossiliferous (Lockhart and Margalla) formations by all the four MLAs; in this case, RF surpassed all the other algorithms with an improved accuracy of 96.36%. This improvement can be attributed to better annotation, resulting in a binary limestone classification map, which formed a mask for improved classification of oolitic and fossiliferous limestone in the area.

scholarly journals Retrieval of nearshore bathymetry from Landsat 8 images: A tool for coastal monitoring in shallow waters

2015 ◽  
Vol 159 ◽  
pp. 102-116 ◽  
Author(s):  
A. Pacheco ◽  
J. Horta ◽  
C. Loureiro ◽  
Ó. Ferreira
Keyword(s):  
Shallow Waters ◽  
Landsat 8 ◽  
Coastal Monitoring

Geometric Characteristics of the Center-Point Curve Based on the Kinematics of the Compatibility Linkage

1992 ◽  
Author(s):  
J. A. Schaaf ◽  
J. A. Lammers
Keyword(s):  
Complex Number ◽  
Change Point ◽  
Double Point ◽  
Classification Scheme ◽  
Center Point ◽  
Degenerate Form ◽  
Point Curve ◽  
Position Synthesis ◽  
Point Form

Abstract In this paper we develop a method of characterizing the center-point curves for planar four-position synthesis. We predict the five characteristic shapes of the center-point curve using the kinematic classification of the compatibility linkage obtained from a complex number formulation for planar four-position synthesis. This classification scheme is more extensive than the conventional Grashof and non-Grashof classifications in that the separate classes of change point compatibility linkages are also included. A non-Grashof compatibility linkage generates a unicursal form of the center-point curve; a Grashof compatibility linkage generates a bicursal form; a single change point compatibility linkage generates a double point form; and a double or triple change point compatibility linkage generates a circular-degenerate or a hyperbolic-degenerate form.

Atherosis of trophoblast type: A specific form of decidual vasculopathy distinct from atherosis of macrophage type

2021 ◽  
Author(s):  
Peilin Zhang
Keyword(s):  
Mixed Type ◽  
Classification Scheme ◽  
Late Pregnancy ◽  
Placental Weight ◽  
Placental Pathology ◽  
New Classification ◽  
Vascular Abnormalities ◽  
Medial Necrosis ◽  
Acute Atherosis

Background: There are three types of decidual vasculopathy, namely, acute atherosis, fibrinoid medial necrosis and mural arterial hyerptrophy. Persistence of vascular trophoblasts is also known to be related to maternal vascular malperfusion, but detailed study is lacking. Material and methods: A total 1017 placentas from 2021 were collected with clinical, neonatal and placental information, and routine placental pathology examination was performed. Decidual vasculopathy was classified based on the new classification scheme including atherosis of macrophage type atherosis of trophoblast type, fibrinoid medial necrosis, mural arterial hypertrophy and mixed type vasculopathy. The significance of these morphologic changes were examined based on the clinical, neonatal and placental pathology features. Results: Decidual vasculopathy is classified as classic type, mural hypertrophy and mixed type. Classic type vasculopathy is further separated as atherosis and fibrinoid medial necrosis. Atherosis is defined as atherosis of macrophage type and atherosis of trophoblast type. Each category of decidual vasculopathy was evaluated in association with maternal, neonatal and placental pathologic findings. Atherosis of macrophage type and mixed type vasculopathy showed statistically significant association with preeclampsia/pregnancy induced hypertension, low birth weight and low placental weight. Atherosis of trophoblast type was associated with lower placental weight but not with specific clinical features. There is no neonatal sex dimorphism in decidual vasculopathy. Conclusion: Atherosis of trophoblast type is a distinct pathologic feature in late pregnancy, and it is associated with lower placental weight. New classification of decidual vasculopathy helps with better stratification and categorization of placental maternal vascular abnormalities.

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