scholarly journals Observation of Fish Dissemination Pattern on Madura Coastal Using Segmentation of Satellite Images

2019 ◽  
Vol 7 (1) ◽  
pp. 343-365
Author(s):  
Citra Nurina Prabiantissa ◽  
Achmad Basuki ◽  
Wahjoe Tjatur Sesulihatien
Keyword(s):  
Research Area ◽  
Physical Parameters ◽  
Landsat 8 ◽  
Fish Production ◽  
Colored Dissolved Organic Matter ◽  
Validation Data ◽  
Good Pattern ◽  
Manual Methods ◽  
June July ◽  
July August September

Almost traditional fishermen still use manual methods to catch fish that rely on experience in fishing and information among fellow fishermen. This method is not effective for maximizing fish production. A good pattern or strategy is needed to increase fish production. In determining dissemination pattern of fish, it can be predicted from physical parameters such as temperature, salinity, chlorophyll, turbidity, total suspended solids, and colored dissolved organic matter using the Landsat 8 images.  This research area is on the Island of Madura Coast. The pattern is determined by using Lagrange Interpolation and clustering using K-Means. The results of the study of the pattern of fish dissemination were then validated with data from the Dinas Kelautan dan Perikanan Jawa Timur. The results between fish patterns and validation data in 2015 showed similarities in January, February, March, May, June, July, August, September. In 2016, results between fish patterns and validation data showed that similarities in July, August, September, and December. In 2017, results between fish patterns and validation data showed similarities in November. 2015 has the most similarities between the patterns and validation data and the least similarity are 2017.

scholarly journals ESTIMASI PRODUKSI PADI DENGAN ANALISIS CITRA SATELIT LANDSAT 8 DI KABUPATEN KLUNGKUNG PROVINSI BALI

2018 ◽  
Vol 12 (1) ◽  
pp. 93
Author(s):  
Made Arya Bhaskara Putra ◽  
I Wayan Nuarsa ◽  
I Wayan Sandi Adnyana
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Image Data ◽  
Research Area ◽  
Rice Production ◽  
Landsat 8 ◽  
Estimation Model ◽  
Accuracy Test ◽  
Accuracy Level

Rice crop is one of the important commodities that must always be available, so estimation of rice production becomes very important to do before harvesting time to know the food availability. The technology that can be used is remote sensing technology using Landsat 8 Satellite. The aims of this study were (1) to obtain the model of estimation of rice production with Landsat 8 image analysis, and (2) to know the accuracy of the model that obtained by Landsat 8. The research area is located in three sub-districts in Klungkung regency. Analysis in this research was conducted by single band analysis and analysis of vegetation index of satellite image of Landsat 8. Estimation model of rice production was developed by finding the relationship between satellite image data and rice production data. The final stage is the accuracy test of the rice production estimation model, with t test and regression analysis. The results showed: (1) estimation of rice production can be calculated between 67 to 77 days after planting; (2) there was a positive correlation between NDVI (Normalized Difference Vegetation Index) vegetation index value with rice yield; (3) the model of rice production estimation is y = 2.0442e1.8787x (x is NDVI value of Landsat 8 and y is rice production); (4) The results of the model accuracy test showed that the obtained model is suitable to predict rice production with accuracy level is 89.29% and standard error of production estimation is + 0.443 ton/ha. Based on research results, it can be concluded that Landsat 8 Satellite image can be used to estimate rice production and the accuracy level is 89.29%. The results are expected to be a reference in estimating rice production in Klungkung Regency.

scholarly journals Atmospheric correction of multispectral satellite imagery

2020 ◽  
pp. 4-11
Author(s):  
Leonid Katkovsky
Keyword(s):  
Land Surface ◽  
Satellite Image ◽  
Atmospheric Correction ◽  
Remote Sensing Data ◽  
Sensor Data ◽  
Physical Parameters ◽  
Landsat 8 ◽  
Optical Parameters ◽  
Outgoing Radiation ◽  
Correction Technique

Atmospheric correction is a necessary step in the processing of remote sensing data acquired in the visible and NIR spectral bands.The paper describes the developed atmospheric correction technique for multispectral satellite data with a small number of relatively broad spectral bands (not hyperspectral). The technique is based on the proposed analytical formulae that expressed the spectrum of outgoing radiation at the top of a cloudless atmosphere with rather high accuracy. The technique uses a model of the atmosphere and its optical and physical parameters that are significant from the point of view of radiation transfer, the atmosphere is considered homogeneous within a satellite image. To solve the system of equations containing the measured radiance of the outgoing radiation in the bands of the satellite sensor, the number of which is less than the number of unknowns of the model, it is proposed to use various additional relations, including regression relations between the optical parameters of the atmosphere. For a particular image pixel selected in a special way, unknown atmospheric parameters are found, which are then used to calculate the reflectance for all other pixels.Testing the proposed technique on OLI sensor data of Landsat 8 satellite showed higher accuracy in comparison with the FLAASH and QUAC methods implemented in the well-known ENVI image processing software. The technique is fast and there is using no additional information about the atmosphere or land surface except images under correction.

scholarly journals Analysis Comparison of Algorithms for Determination Concentration of Chlorophyll-a in Traditional and Intensive Milkfish Ponds Using LANDSAT 8 Images

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Nurhadi Bashit ◽  
Abdi Sukmono ◽  
Baskoro Agum Gumelar
Keyword(s):  
Remote Sensing ◽  
Chlorophyll A ◽  
Coastal Area ◽  
Average Concentration ◽  
The Body ◽  
Landsat 8 ◽  
Northern Coast ◽  
Fish Production ◽  
Remote Sensing Technology ◽  
Sensing Technology

Indonesia is an Archipelago Country because the Country of Indonesia consists of many islands stretching from Sabang in the west to the island of Merauke on the east. The Archipelago Country also comes from the old name of the Indonesian Country called Nusantara, because Nusantara is a country that consists of many islands. Indonesia is an Archipelago Country which means it has potential resources in the coastal areas, one of which is found on the northern coast of Java. The coastal area is an important area to be reviewed, one of which is the use of coastal resources by paying attention to the condition of the ecosystem that remains stable. Opportunities for coastal area utilization in the field of fisheries are in the form of fishing activities or fish farming, especially pond cultivation activities. Based on data from the Department of Marine and Fisheries of the Province of Central Java in 2010, pond cultivation is one of the potential resources on the coast. This potential is supported by the government to increase fish production in order to increase the consumption of fish in the community. Therefore, it is necessary to choose the most effective method of pond cultivation between traditional methods and intensive methods to optimize fish production. One indicator of effectiveness between the two methods can be seen from the phytoplankton distribution. Phytoplankton contains chlorophyll-a in the body and is a natural food from fish. Phytoplankton provides important ecological functions for the aquatic life cycle by serving as the basis of food webs in water. Phytoplankton also functions as the main food item in freshwater fish culture and seawater fish cultivation. Therefore, it is necessary to know the chlorophyll-a concentration in the ponds of traditional and intensive methods to determine the concentration chlorophyll-a of the two pond methods. One method used to determine the concentration of chlorophyll-a using remote sensing technology. Remote sensing technology can be used to determine the concentration of chlorophyll-a using the Wouthuyzen, Wibowo, Pentury, Much Jisin Arief and Lestari Laksmi algorithms. The results showed that the Pentury algorithm was relatively better to determine the concentration of chlorophyll-a in shallow waters (ponds). The lowest concentration of chlorophyll-a in traditional ponds is 0.47068 mg/m3, the highest concentration is 1.95017 mg/m3 and the average concentration is 1.12893 mg/m3, while in intensive ponds the lowest concentration is 0.36713 mg/m3, the concentration the highest is 3.17063 mg/m3 and the average concentration is 1.53556 mg/m3.

scholarly journals SPATIAL-TEMPORAL DISTRIBUTION OF CHLOROPHYLL-A IN SOUTHERN PART OF THE MAKASSAR STRAIT

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Wasir Samad Daming ◽  
Muhammad Anshar Amran ◽  
Amir Hamzah Muhiddin ◽  
Rahmadi Tambaru
Keyword(s):  
Chlorophyll A ◽  
Satellite Data ◽  
Chlorophyll Concentration ◽  
Temporal Distribution ◽  
Fishing Ground ◽  
Landsat 8 ◽  
Trade Winds ◽  
Chl A ◽  
June July ◽  
Potential Area

Surface chlorophyll-a (Chl-a) distribution have been analyzed with seasonal variation during southeast monsoon in southern part of Makassar Strait and Flores Sea. Satellite data of Landsat-8 is applied to this study to formulate the distribution of chlorophyll concentration during monsoonal wind period. The distribution of chlorophyll concentration was normally peaked condition in August during southeast monsoon. Satellite data showed that a slowdown in the rise of the distribution of chlorophyll in September with a lower concentration than normal is likely due to a weakening the strength of southeast trade winds during June – July – August 2016. Further analysis shows that the southern part of the Makassar strait is likely occurrence of upwelling characterized by increase in surface chlorophyll concentrations were identified as the potential area of fishing ground.

scholarly journals The dynamics change of fishpond land into settlement the east coast of Surabaya 2004-2017

2018 ◽  
Vol 73 ◽  
pp. 13001
Author(s):  
Chahya Chairani ◽  
Ratna Saraswati ◽  
Iqbal Putut Ash Shidiq
Keyword(s):  
East Coast ◽  
Dynamic Change ◽  
Research Area ◽  
Landsat Image ◽  
Landsat 8 ◽  
Area 17 ◽  
Landsat 8 Oli ◽  
Settlement Area ◽  
East Region ◽  
Overlay Method

Surabaya rapidly developed to the east region which grew the formal/non-formal settlement in Pamurbaya. This area is dominated by fishpond that is converted into settlement area. This research aims to observe the dynamic change of fishpond which is already converted into settlement area in the east coast of Surabaya, during 2004-2017. This research applies landsat image 7 ETM+ and landsat 8 OLI with overlay method which is analyzed descriptively. During 2004-2017, the settlement area had been developing for 218,296 Ha or 88% and during the same years, the fishpond had been reducing for 531,639 Ha or 24%, this reduction can change into mangrove or settlement area. During 13 years, the change of fishpond into settlement area is 15%. The research area which experienced the change is the fishpond of Kejawan Putih (24%), Medokan Ayu area (17%), and Keputih area (16%).

INVESTIGATION AND EVALUATION OF NOISE LEVEL IN THE NORTHERN PART OF KLAIPEDA CITY/TRIUKŠMO LYGIO ŠIAURINĖJE KLAIPĖDOS MIESTO DALYJE TYRIMAI IR ĮVERTINIMAS/ИССЛЕДОВАНИЕ И АНАЛИЗ ШУМОВОГО УРОВНЯ В СЕВЕРНОЙ ЧАСТИ ГОРОДА КЛАЙПЕДЫ

2008 ◽  
Vol 16 (2) ◽  
pp. 89-96 ◽  
Author(s):  
Vaidotas Vaišis ◽  
Tomas Januševičius
Keyword(s):  
Noise Level ◽  
Heavy Traffic ◽  
Motor Vehicles ◽  
Noise Levels ◽  
June July August ◽  
The World ◽  
Noise Measurements ◽  
June July ◽  
July August September

The problem of noise is topical not only in Lithuania but the world over as well. The northern part of Klaipeda city is distinct for its industry and heavy traffic in the streets. Noise research was carried out in 17 selected measurement locations in the northern part of Klaipeda city. Noise measurements were taken in May, June, July, August, September, October and November. The measurements were made three times during the day: in the day time from 6 a.m. till 6 p.m., in the evening from 6 p.m. till 10 p.m. and at night from 10 p.m. till 6 a.m. The locations of the measurements are marked on the map. In order to distinguish the source of bigger noise between industry and transport, the northern part was divided into two belts. Industry is prevalent in the first belt, whereas the main troublemakers in the second belt are motor vehicles. The measured noise level is compared with permissible standards in measurement locations, where noise level is usually exceeded, and the analysis of noise levels is presented. In order to show the spread of noise in Klaipeda at all three times of the day more vividly, maps of isolines were compiled. Santrauka Triukšmas - ne tik Lietuvoje, bet ir visame pasaulyje aktuali problema. Klaipedos miesto šiaurine dalis yra išskirtine savo pramone ir intensyviu eismu gatvese. Triukšmo tyrimai atlikti šiaurineje Klaipedos miesto dalyje, 17‐oje pasirinktu matavimo vietu. Triukšmas matuotas gegužes, birželio, liepos, rugpjūčio, rugsejo, spalio ir lapkričio menesiais. Matavimai atlikti trimis paros laikais: diena nuo 6–18 valandos, vakare nuo 18–22 valandos ir nakti nuo 22–6 valandos. Matavimo vietos pateiktos žemelapyje. Siekiant nustatyti, kas kelia didesni triukšma ‐ pramone ar transportas, šiaurine miesto dalis suskirstyta i dvi zonas. Pirmojoje zonoje vyrauja pramone, o antrojoje zonoje pagrindinis triukšmo šaltinis automobiliai. Išmatuotas triukšmo lygis palygintas su leistinosiomis normomis. Pateikta matavimo vietu, kuriose dažniausiai viršijamas triukšmo lygis, triukšmo lygiu analize. Siekiant aiškiau parodyti, kaip triukšmas pasiskirsto Klaipedos mieste visais trimis paros laikais, sudaryti izoliniju žemelapiai. Резюме Шум является актуальной проблемой не только в Литве, но и во всем мире. Северная часть города Клайпеды является промышленным районом с интенсивным транспортным движением. Для исследования шума в этой части города было выбрано 17 мест замера. Шум измерялся с мая по ноябрь. Измерения проводились 3 раза в разное время суток: днем в 6–18 ч, вечером в 18–22 ч и ночью в 22–6 ч. Места замеров показаны на карте. С целью установить, что является бóльшим источником шума – промышленные предприятия или транспортные средства, северная часть города была поделена на две зоны. В первой зоне преобладали промышленные предприятия, а во второй – транспорт. Измеренный уровень шума сравнивался с разрешенным нормами. Для мест замеров, в которых чаще всего уровень шума превышал норму, предлагался анализ уровня шума. Для лучшего представления о распределении шума в городе Клайпеде в разное время суток были созданы карты изолиний.

The Role of Visible Data in Improving Satellite Rain-Rate Estimates

1995 ◽  
Vol 34 (7) ◽  
pp. 1608-1621 ◽  
Author(s):  
Patrick W. S. King ◽  
William D. Hogg ◽  
Philip A. Arkin
Keyword(s):  
Rain Rate ◽  
Apparent Brightness ◽  
Satellite Measurements ◽  
Validation Data ◽  
Southern Ontario ◽  
Gauge Data ◽  
Intercomparison Project ◽  
Validation Set ◽  
June July

Abstract Data from the first Algorithm Intercomparison Project(AIP/1) collected over Japan and surrounding waters in June, July, and August 1989 are used in this study to assess the importance of visible data in satellite rain estimation techniques. The purpose of the project was to compare different methods for estimating rainfall using satellite measurements. Radar and surface gauge data provided the validation set. RAINSAT, an estimation technique using both visible (VIS) and infrared (IR) data, achieved the highest correlation with the validation data. In this paper rainfall estimates from RAINSAT (VIS+IR) am compared with two IR-only techniques to deduce the effectiveness of VIS data. Some estimates are also made using a VIS-only technique. Comparisons am made on both a spatial and diurnal basis. Cloud climatologies for a subset of the AIP/1 data and the southern Ontario data on which RAINSAT was trained showed a marked similarity. It is found that the total volume of rain as a function of albedo is very similar for both Japanese and Ontario data. The VIS data generally produced higher correlations with the validation data than did the IR data. This was especially the case when rain fell from warm, orogaphically induced rainfall. When rain fell from cold bright clouds. especially over the ocean, the correlations of the two types of data with the validation data were similar. It is also shown that normalization of VIS data by the cosine of solar zenith data was inadequate to remove diurnal variations in apparent brightness.

scholarly journals Influence of Inoculation Date on the Colonization of Xylella fastidiosa and the Persistence of Almond Leaf Scorch Disease Among Almond Cultivars

Plant Disease ◽  
2011 ◽  
Vol 95 (2) ◽  
pp. 158-165 ◽  
Author(s):  
Tiesen Cao ◽  
Joseph H. Connell ◽  
Margot Wilhelm ◽  
Bruce C. Kirkpatrick
Keyword(s):  
Xylella Fastidiosa ◽  
Prunus Dulcis ◽  
Current Season ◽  
Leaf Scorch ◽  
Growing Seasons ◽  
Almond Trees ◽  
Cultivar Susceptibility ◽  
June July ◽  
July August September ◽  
Almond Leaf Scorch

Field grown 2-year-old almond trees (Prunus dulcis cvs. Butte, Carmel, Mission, Ne Plus Ultra, Padre, Peerless, Price, Solano, Sonora, and Thompson) were mechanically inoculated with Xylella fastidiosa in the growing seasons of 2002 and 2003 to study the effect of inoculation date on the movement and colonization of X. fastidiosa and the overwintering persistence of almond leaf scorch disease (ALS) in these cultivars. X. fastidiosa was inoculated into the base of current-season growing shoots in April, May, June, July, August, September, and October. Almond trees inoculated in spring months developed more ALS-symptomatic leaves and more extensive within-plant spread of X. fastidiosa by the end of the current growing season compared with trees inoculated in July, August, September, and October. Trees inoculated in June developed the most severe ALS symptoms during the season in which they were inoculated. Trees inoculated in June and July 2002 had significantly higher disease ratings in 2003 than inoculations made in August and October 2002. Based on disease ratings observed in 2003, 1 year after inoculation, Sonora and Solano were the most ALS susceptible, Mission and Price intermediate, and Carmel, Padre, Ne Plus Ultra, Butte, Peerless, and Thompson were the least susceptible cultivars for allowing X. fastidiosa to overwinter and cause disease the following year. Assessment of all trees in August 2004 indicated that trees inoculated in June and July 2002 had a significantly higher amount of ALS-infected branches than trees inoculated in other months. Butte, Carmel, Padre, and Thompson cultivars had no symptomatic branches, while X. fastidiosa infections persisted or colonized new branches in Sonora, Solano, Peerless, Price, Mission, and Ne Plus Ultra. Based on the 2004 assessment, Sonora was the most susceptible cultivar. Surveys of a diseased orchard in Chico, CA showed large differences in ALS incidence in four almond cultivars. Nonpareil and Peerless had significantly greater incidence of disease than Butte and Carmel over the 2 years surveyed. These data suggest that cultivar susceptibility and the time of X. fastidiosa infection are important factors in determining the persistence of ALS in almond trees.

scholarly journals Flexible 6-in-1 Microsensor for Real-Time Microscopic Monitoring of Proton Battery

Membranes ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 615
Author(s):  
Chi-Yuan Lee ◽  
Chia-Hung Chen ◽  
Chin-Yuan Yang ◽  
John-Shong Cheong ◽  
Yun-Hsiu Chien ◽  
...  
Keyword(s):  
Proton Exchange Membrane ◽  
Water Electrolysis ◽  
Research Area ◽  
Carbon Layer ◽  
Proton Exchange ◽  
Physical Parameters ◽  
Proton Battery ◽  
Practical Applications ◽  
Mems Technology ◽  
Physical Quantities

According to the comparison between a proton battery and a proton exchange membrane fuel cell (PEMFC), the PEMFC requires oxygen and hydrogen for generating electricity, so a hydrogen tank is required, leading to larger volume of PEMFC. The proton battery can store hydrogen in the carbon layer, combined with the oxygen in the air to form water to generate electricity; thus, the battery cost and the space for a hydrogen tank can be reduced a lot, and it is used more extensively. As the proton battery is a new research area, multiple important physical quantities inside the proton battery should be further understood and monitored so as to enhance the performance of battery. The proton battery has the potential for practical applications, as well as water electrolysis, proton storage and discharge functions, and it can be produced without expensive metals. Therefore, in this study, we use micro-electro-mechanical systems (MEMS) technology to develop a diagnostic tool for the proton battery based on the developed microhydrogen sensor, integrated with the voltage, current, temperature, humidity and flow microsensors developed by this laboratory to complete a flexible integrated 6-in-1 microsensor, which is embedded in the proton battery to measure internal important physical parameters simultaneously so that the reaction condition in the proton battery can be mastered more accurately. In addition, the interaction of physical quantities of the proton battery are discussed so as to enhance the proton battery’s performance.

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