scholarly journals Spectral Reflectance-Based Mangrove Species Mapping from WorldView-2 Imagery of Karimunjawa and Kemujan Island, Central Java Province, Indonesia

2022 ◽  
Vol 14 (1) ◽  
pp. 183
Author(s):  
Arie Dwika Rahmandhana ◽  
Muhammad Kamal ◽  
Pramaditya Wicaksono
Keyword(s):  
Spectral Reflectance ◽  
Spectral Feature ◽  
Individual Species ◽  
Mangrove Forests ◽  
Mangrove Species ◽  
Spectral Angle Mapper ◽  
Central Java ◽  
Feature Fitting ◽  
Species Mapping ◽  
Central Java Province

Mangrove mapping at the species level enables the creation of a detailed inventory of mangrove forest biodiversity and supports coastal ecosystem management. The Karimunjawa National Park in Central Java Province is one of Indonesia’s mangrove habitats with high biodiversity, namely, 44 species representing 25 true mangroves and 19 mangrove associates. This study aims to (1) classify and group mangrove species by their spectral reflectance characteristics, (2) map mangrove species by applying their spectral reflectance to WorldView-2 satellite imagery with the spectral angle mapper (SAM), spectral information divergence (SID), and spectral feature fitting (SFF) algorithms, and (3) assess the accuracy of the produced mangrove species mapping of the Karimunjawa and Kemujan Islands. The collected field data included (1) mangrove species identification, (2) coordinate locations of targeted mangrove species, and (3) the spectral reflectance of mangrove species measured with a field spectrometer. Dendrogram analysis was conducted with the Ward linkage method to classify mangrove species based on the distance between the closest clusters of spectral reflectance patterns. The dendrogram showed that the 24 mangrove species found in the field could be grouped into four levels. They consisted of two, four, and five species groups for Levels 1 to 3, respectively, and individual species for Level 4. The mapping results indicated that the SID algorithm had the highest overall accuracy (OA) at 49.72%, 22.60%, and 15.20% for Levels 1 to 3, respectively, while SFF produced the most accurate results for individual species mapping (Level 4) with an OA of 5.08%. The results suggest that the greater the number of classes to be mapped, the lower the mapping accuracy. The results can be used to model the spatial distribution of mangrove species or the composition of mangrove forests and update databases related to coastal management.

scholarly journals Distribusi Scylla spp. di perairan estuari Sungai Donan Segara Anakan Bagian Timur, Cilacap

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Sulistiono Sulistiono ◽  
Nurul Musyariafah Yahya ◽  
Etty Riani
Keyword(s):  
Economic Value ◽  
Scylla Serrata ◽  
Mangrove Forests ◽  
Mud Crab ◽  
Mangrove Species ◽  
Central Java ◽  
Rhizophora Apiculata ◽  
Mangrove Ecosystems ◽  
Avicennia Alba ◽  
Mangrove Crabs

Mangrove forests are ecosystems that make up coastal areas and river estuaries. The examples of mangrove ecosystems found in Indonesia are in Segara Anakan, Central Java. One of the aquatic biota with the economic value found in the mangrove forest ecosystem is the mud crab (Scylla spp.). The purpose of this study was to assess the distribution of mangrove crabs (Scylla spp.) to the presence of mangrove species in the mouth of the Donan River, Segara Anakan. A sampling of crabs and observations of mangrove vegetation were carried out at five stations spread from the river to the sea. The results showed that there were three types of mangrove crabs caught in the vicinity of the study, namely Scylla tranquebarica, S. olivacea, and S. serrata. The types of mangroves found include Rhizophora apiculata, R. mucronata, Avicennia rumphiana, A. alba, A. officinalis, and Nypa. Regression analysis showed that mangrove density correlated with the abundance of Scylla tranquebarica and Scylla olivacea, but contradicts the abundance of Scylla serrate. PCA analysis showed that the Crab species Scylla tranquebarica and Scylla olivacea were associated with mangroves of Avicennia alba, Avicennia rumphiana, and Rhizophora apiculata. Meanwhile, Scylla serrata crabs are associated with Avicennia officinalis.

scholarly journals Asbestos—Cement Roofing Identification Using Remote Sensing and Convolutional Neural Networks (CNNs)

2020 ◽  
Vol 12 (3) ◽  
pp. 408
Author(s):  
Małgorzata Krówczyńska ◽  
Edwin Raczko ◽  
Natalia Staniszewska ◽  
Ewa Wilk
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Spectral Feature ◽  
Hyperspectral Data ◽  
Aerial Photographs ◽  
Support Vector ◽  
Spectral Angle Mapper ◽  
Asbestos Cement ◽  
Feature Fitting

Due to the pathogenic nature of asbestos, a statutory ban on asbestos-containing products has been in place in Poland since 1997. In order to protect human health and the environment, it is crucial to estimate the quantity of asbestos–cement products in use. It has been evaluated that about 90% of them are roof coverings. Different methods are used to estimate the amount of asbestos–cement products, such as the use of indicators, field inventory, remote sensing data, and multi- and hyperspectral images; the latter are used for relatively small areas. Other methods are sought for the reliable estimation of the quantity of asbestos-containing products, as well as their spatial distribution. The objective of this paper is to present the use of convolutional neural networks for the identification of asbestos–cement roofing on aerial photographs in natural color (RGB) and color infrared (CIR) compositions. The study was conducted for the Chęciny commune. Aerial photographs, each with the spatial resolution of 25 cm in RGB and CIR compositions, were used, and field studies were conducted to verify data and to develop a database for Convolutional Neural Networks (CNNs) training. Network training was carried out using the TensorFlow and R-Keras libraries in the R programming environment. The classification was carried out using a convolutional neural network consisting of two convolutional blocks, a spatial dropout layer, and two blocks of fully connected perceptrons. Asbestos–cement roofing products were classified with the producer’s accuracy of 89% and overall accuracy of 87% and 89%, depending on the image composition used. Attempts have been made at the identification of asbestos–cement roofing. They focus primarily on the use of hyperspectral data and multispectral imagery. The following classification algorithms were usually employed: Spectral Angle Mapper, Support Vector Machine, object classification, Spectral Feature Fitting, and decision trees. Previous studies undertaken by other researchers showed that low spectral resolution only allowed for a rough classification of roofing materials. The use of one coherent method would allow data comparison between regions. Determining the amount of asbestos–cement products in use is important for assessing environmental exposure to asbestos fibres, determining patterns of disease, and ultimately modelling potential solutions to counteract threats.

scholarly journals Incorporating the Plant Phenological Trajectory into Mangrove Species Mapping with Dense Time Series Sentinel-2 Imagery and the Google Earth Engine Platform

2019 ◽  
Vol 11 (21) ◽  
pp. 2479 ◽  
Author(s):  
Huiying Li ◽  
Mingming Jia ◽  
Rong Zhang ◽  
Yongxing Ren ◽  
Xin Wen
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Google Earth ◽  
Late Winter ◽  
Mangrove Forests ◽  
Mangrove Species ◽  
Ndvi Time Series ◽  
Google Earth Engine ◽  
Species Mapping ◽  
Sentinel 2

Information on mangrove species composition and distribution is key to studying functions of mangrove ecosystems and securing sustainable mangrove conservation. Even though remote sensing technology is developing rapidly currently, mapping mangrove forests at the species level based on freely accessible images is still a great challenge. This study built a Sentinel-2 normalized difference vegetation index (NDVI) time series (from 2017-01-01 to 2018-12-31) to represent phenological trajectories of mangrove species and then demonstrated the feasibility of phenology-based mangrove species classification using the random forest algorithm in the Google Earth Engine platform. It was found that (i) in Zhangjiang estuary, the phenological trajectories (NDVI time series) of different mangrove species have great differences; (ii) the overall accuracy and Kappa confidence of the classification map is 84% and 0.84, respectively; and (iii) Months in late winter and early spring play critical roles in mangrove species mapping. This is the first study to use phonological signatures in discriminating mangrove species. The methodology presented can be used as a practical guideline for the mapping of mangrove or other vegetation species in other regions. However, future work should pay attention to various phenological trajectories of mangrove species in different locations.

scholarly journals Using geochemical imaging data to map nickel sulfide deposits in Daxinganling, China

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Xiaoyan Chen ◽  
Jiang Chen ◽  
Jun Pan
Keyword(s):  
Nickel Sulfide ◽  
Spectral Feature ◽  
Geochemical Data ◽  
Ultramafic Rocks ◽  
Imaging Data ◽  
Spectral Angle Mapper ◽  
Sulfide Deposits ◽  
Feature Fitting ◽  
Prospectivity Mapping ◽  
Spectral Angle

AbstractNickel sulfide deposits occur in ultramafic rocks in the Daxinganling area, China; however, the prospectivity of these deposits has received little attention. This study transformed rasterized regional 1:200,000 geochemical data into spectral-like data and then used hyperspectral tools of the spectral angle mapper (SAM) to classify possible ultramafic lithologies and the multirange spectral feature fitting (MRSFF) method to classify prospective areas that are similar to a typical Gaxian Ni deposit. The prospective area map generated by the MRSFF implies the possible occurrence of ultramafic rocks classified by the SAM method. These results confirm the suitability of this innovative approach for prospectivity mapping of Ni sulfide deposits.

scholarly journals Jeffries Matusita-Spectral Angle Mapper (JM-SAM) spectral matching for species level mapping at Bhitarkanika, Muthupet and Pichavaram mangroves

2014 ◽  
Vol XL-8 ◽  
pp. 1403-1411 ◽  
Author(s):  
S. Padma ◽  
S. Sanjeevi
Keyword(s):  
Tamil Nadu ◽  
Distance Measure ◽  
Mangrove Forests ◽  
Average Difference ◽  
Mangrove Species ◽  
Spectral Angle Mapper ◽  
Matching Algorithm ◽  
Hyperion Image ◽  
Combined Algorithm ◽  
Spectral Angle

This paper proposes a novel hyperspectral matching algorithm by integrating the stochastic Jeffries-Matusita measure (JM) and the deterministic Spectral Angle Mapper (SAM), to accurately map the species and the associated landcover types of the mangroves of east coast of India using hyperspectral satellite images. The JM-SAM algorithm signifies the combination of a qualitative distance measure (JM) and a quantitative angle measure (SAM). The spectral capabilities of both the measures are orthogonally projected using the tangent and sine functions to result in the combined algorithm. The developed JM-SAM algorithm is implemented to discriminate the mangrove species and the landcover classes of Pichavaram (Tamil Nadu), Muthupet (Tamil Nadu) and Bhitarkanika (Odisha) mangrove forests along the Eastern Indian coast using the Hyperion image dat asets that contain 242 bands. The developed algorithm is extended in a supervised framework for accurate classification of the Hyperion image. The pixel-level matching performance of the developed algorithm is assessed by the Relative Spectral Discriminatory Probability (RSDPB) and Relative Spectral Discriminatory Entropy (RSDE) measures. From the values of RSDPB and RSDE, it is inferred that hybrid JM-SAM matching measure results in improved discriminability of the mangrove species and the associated landcover types than the individual SAM and JM algorithms. This performance is reflected in the classification accuracies of species and landcover map of Pichavaram mangrove ecosystem. Thus, the JM-SAM (TAN) matching algorithm yielded an accuracy better than SAM and JM measures at an average difference of 13.49 %, 7.21 % respectively, followed by JM-SAM (SIN) at 12.06%, 5.78% respectively. Similarly, in the case of Muthupet, JM-SAM (TAN) yielded an increased accuracy than SAM and JM measures at an average difference of 12.5 %, 9.72 % respectively, followed by JM-SAM (SIN) at 8.34 %, 5.55% respectively. For Bhitarkanika, the combined JM-SAM (TAN) and (SIN) measures improved the performance of individual SAM by (16.1 %, 15%) and of JM by (10.3%, 9.2%) respectively.

scholarly journals Improved Spectral Angle Mapper applications for mangrove classification using SPOT5 imagery

2019 ◽  
Author(s):  
Xiu Su ◽  
Xiang Wang ◽  
Jianhua Zhao ◽  
Ke Cao ◽  
Jianchao Fan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Classification Accuracy ◽  
Spectral Feature ◽  
Mangrove Ecosystem ◽  
Training Sample ◽  
Mangrove Species ◽  
Spectral Angle Mapper ◽  
Structure Information ◽  
Mangrove Ecosystems ◽  
Spectral Angle

Abstract. The traditional Spectral Angle Mapper (SAM) is an image classification method that uses image endmember spectra. Image spatial structure information may be neglected, especially in mangrove classification research where there is greater spectral similarity between species. This study combined object-oriented classification to improve the accuracy of the method in mangrove ecosystems. A mangrove area in Guangxi's coastal zone was chosen as the study site, and spectral feature analysis and ground investigations were carried out, combining pixel purification, training sample set optimization, and watershed image segmentation algorithm to improve the SAM. The improved SAM was used to classify SPOT5 remote sensing image data for a mangrove ecosystem and then classification accuracy was assessed. The results showed that the improved SAM had better classification accuracy for SPOT5 imagery. Accuracy for each mangrove species was greater than 80 % and overall accuracy was greater than 90 %, which showed that SAM was applicable for mangrove remote sensing. This application potential for classification and information extraction lays the foundation for commercialized remote sensing monitoring of mangrove ecosystems.

scholarly journals Mangrove Plants Use As Medicine In Gedangan Village, Purwodadi District, Purworejo Regency, Central Java Province

2020 ◽  
Vol 5 (2) ◽  
pp. 76-84
Author(s):  
Slamet Mardiyanto Rahayu ◽  
Sunarto
Keyword(s):  
Mangrove Forest ◽  
Medicinal Products ◽  
Mangrove Species ◽  
Mangrove Area ◽  
Mangrove Plants ◽  
Central Java ◽  
Nypa Fruticans ◽  
Acanthus Ilicifolius ◽  
Sonneratia Alba ◽  
Central Java Province

Coastal ecosystems have high plant levels, for example mangroves and seagrasses. Mangrove forest is a type of forest located in tidal areas, especially on protected beaches, lagoons, river estuaries that are inundated and free from inundation at low tide, whose plant communities tolerate salt. Gedangan Village is one of the villages in Purwodadi District, which has mangrove areas in Purworejo Regency. This study aims to determine the types of mangrove plants that are useful the Gedangan Village, Purwodadi District, Purworejo Regency, Central Java as medicinal products. The study was conducted using roaming method in the form of observations or field observations in the mangrove area of Gedangan Village, Purwodadi District, Purworejo Regency, Central Java. Based on the research, there were eight (8) types of mangrove plants that were found as medicinal plants in Gedangan Village, namely Rhizophora mucronata, Sonneratia alba, Calotropis gigantea, Nypa fruticans, Acanthus ilicifolius, Hibiscus tiliaceus, Ipomoea pescaprae, and Wedelia biflora. Traditionally, these mangrove species can be used as a medicine items for beri-beri, hepatitis, ulcers, wounds, diarrhea, fever, antibacterial, anti-inflammatory, dizziness, asthma, bronchitis, dyspepsia, leprosy, tumors, diabetes, stomach ache, toothache, thrush, tuberculosis, muscle aches, and eczema.

ECOLOGY AND SUSTAINABLE DEVELOPMENT IN LOCAL BUSINESS:SIMULATION OF LOW IMPACT DEVELOPMENT IN SURAKARTA REGENCY

2018 ◽  
Vol 4 (1) ◽  
pp. 32-38
Author(s):  
Bhimo Rizky Samudro ◽  
Yogi Pasca Pratama
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
River Flow ◽  
Low Impact Development ◽  
Development Model ◽  
Business Activity ◽  
Resources Management ◽  
Central Java ◽  
Specific Culture ◽  
Central Java Province

This paper will describe the function of water resources to support business activities in Surakarta regency, Central Java province. Surakarta is a business city in Central Java province with small business enterprises and specific culture. This city has a famous river with the name is Bengawan Solo. Bengawan Solo is a River Flow Regional (RFR) to support business activities in Surakarta regency. Concious with the function, societies and local government in Surakarta must to manage the sustainability of River Flow Regional (RFR) Bengawan Solo. It is important to manage the sustainability of business activity in Surakarta regency.   According to the condition in Surakarta regency, this paper will explain how the simulation of Low Impact Development Model in Surakarta regency. Low Impact Development is a model that can manage and evaluate sustainability of water resources in River Flow Regional (RFR). Low Impact Development can analys goals, structures, and process water resources management. The system can also evaluate results and impacts of water resources management. From this study, we hope that Low Impact Development can manage water resources in River Flow Regional (RFR) Bengawan Solo.  

Management Dakwah Mosque in Eradicate Use Drugs Problem in Adolescent

2016 ◽  
Vol 1 ◽  
pp. 224-231
Author(s):  
Abdul Aziz
Keyword(s):  
Drug Abuse ◽  
Social Action ◽  
Field Research ◽  
Drug Problem ◽  
Religious Activities ◽  
Central Java ◽  
Youth Activities ◽  
Younger Generation ◽  
Education And Development ◽  
Central Java Province

The mosque is a building or an environment surrounded by a fence, especially built for the worship of God Almighty and most commendable. The mosque will function and will be very meaningful if there is proper management and good. Mainly using management science, and one of them is religious propaganda management. It is one of the Islamization of education all because it is a kenyatan that education and development as a process of intensive, to make someone to be able to optimize the physical and non physical aspects. Purpose writing  this is to describe the management of the mosque and its application to ensure that drug abuse does not occur in the younger generation. Today, this problem becomes a reality in cities and villages almost become a culture, as we all know that genersi youth as part of the religion, country and product of the nation if it was not in physical condition is good and fit will take them on social action, crime such as theft, drug abuse. One solution is the mosque's activities. Based on these problems, the authors really want to know the role of propaganda bagimana done to address the drug problem in the younger generation. Writing is supported by literature and field research. And the authors get the data through observation, interviews and documentation. Then analyze the data from a reduction, to see the data and conclusions. While the subject of research is the mosque of Abu Bakr As-Sidiqdesa Grujugan Kemranjen districts Banyumas in Central Java province of Indonesia. Based on the results there are: (1) Masjid Abu Bakar As-Sidiq using good management on the physical plane and function. (2) Management of religious proselytizing by DKM and Ikrima to ensure to prevent drug abuse in rural districts Grujugan Kemranjen Banyumas regency, Central Java Province using religious activities such as youth activities in the field of sports, the call of young people or youth build character.

Soy milk and avocado juice: what is the best to reduce cholesterol among obesity children?

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Rizki Agustin Purwaningtyas ◽  
Kustiningsih Kustiningsih
Keyword(s):  
Physical Activity ◽  
Cholesterol Level ◽  
Male Student ◽  
Control Group ◽  
P Value ◽  
Soy Milk ◽  
High Cholesterol ◽  
Central Java ◽  
Equivalent Control ◽  
Central Java Province

Children with obesity have high risk to have abnormal cholesterol rate. Obesity and high cholesterol rate can cause cardiovascular disease at a later time. Children have normal rate of cholesterol if the cholesterol rate in the blood is <170 mg/dL, the threshold category between 170-199 mg/dL, and high category is >200 mg/dL. Soy Milk and avocado juice are the ways of non pharmacological care that can be applied to reduce cholesterol rate. This study aims to compare Soy Milk and avocado juice giving toward cholesterol rate in children with obesity in State Elementary School 1 and 2 of Katerban, Central Java Province, Indonesia. The study used quasi experiment design with non-equivalent control group framework. Samples of the study were 30 children taken by use purposive sampling. Soy Milk and avocado juice effective to reduce cholesterol level in obesity children (p value=0,000, p<0,05), but neither soy milk and avocado juice there’re no one that more effective to decrease cholesterol level (p value=0,902, p>0,05). 60% of respondent were male student age 11 years (36,7%). Father education were high. Soya milk and avocado juice are able to reduce cholesterol rate. Parents must give attention to children’s dietary intake to reduce cholesterol and obesity, also motivate them to do physical activity.

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