scholarly journals Shallow Water Seabed Profile Changes in 2016 - 2018 Based on Landsat 8 Satellite Imagery (Case Study: Semak Daun Island, Karya Island and Gosong Balik Layar)

Omni-Akuatika ◽  
2020 ◽  
Vol 16 (3) ◽  
pp. 26
Author(s):  
Zahra Safira Aulia ◽  
Triguardi Tharik Ahmad ◽  
Ratih Rachma Ayustina ◽  
Fauzi Tri Hastono ◽  
Rizqi Rizaldi Hidayat ◽  
...  
Keyword(s):  
Shallow Water ◽  
Satellite Imagery ◽  
Accuracy Assessment ◽  
Satellite Image ◽  
Benthic Habitat ◽  
Landsat 8 ◽  
Marine Tourism ◽  
Profile Changes ◽  
High Level

Seribu Islands is one of the marine tourism destinations in  Jakarta. The high level of tourism in the Seribu Islands can be a threat to shallow water seabed profile habitat. Therefore, monitoring of changes in shallow water seabed profile habitat is needed so the sustainability can be monitored. This study aimed to determine changes in the shallow water seabed profile on Karya Island, Semak Daun Island, and Gosong Balik Layar in 2016 and 2018 based on Landsat 8 Satellite Imagery. Methods of this research used satellite image pre-processing, image classification, field survey, image reclassification, and accuracy assessment.  The results showed that the coral area had decrease trend, while the area of Seagrass mix Seaweed had increased. The result of this classification had an accuracy value of 71.52%. Keywords: remote sensing, multispectral imagery, Lyzenga, benthic habitat, Seribu Island

scholarly journals MAPPING OF THE SEAGRASS COVER ALONG THE MEDITERRANEAN COAST OF TURKEY USING LANDSAT 8 OLI IMAGES

2016 ◽  
Vol XLI-B8 ◽  
pp. 1103-1105 ◽  
Author(s):  
T. Bakirman ◽  
M. U. Gumusay ◽  
I. Tuney
Keyword(s):  
Accuracy Assessment ◽  
Mediterranean Coast ◽  
Environmental Data ◽  
Benthic Habitat ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Carbon Dioxide Absorption ◽  
Landsat Images ◽  
Marine Animals ◽  
Seagrass Cover

Benthic habitat is defined as ecological environment where marine animals, plants and other organisms live in. Benthic habitat mapping is defined as plotting the distribution and extent of habitats to create a map with complete coverage of the seabed showing distinct boundaries separating adjacent habitats or the use of spatially continuous environmental data sets to represent and predict biological patterns on the seafloor. Seagrass is an essential endemic marine species that prevents coast erosion and regulates carbon dioxide absorption in both undersea and atmosphere. Fishing, mining, pollution and other human activities cause serious damage to seabed ecosystems and reduce benthic biodiversity. According to the latest studies, only 5–10% of the seafloor is mapped, therefore it is not possible to manage resources effectively, protect ecologically important areas. In this study, it is aimed to map seagrass cover using Landsat 8 OLI images in the northern part of Mediterranean coast of Turkey. After pre-processing (e.g. radiometric, atmospheric, water depth correction) of Landsat images, coverage maps are produced with supervised classification using in-situ data which are underwater photos and videos. Result maps and accuracy assessment are presented and discussed.

scholarly journals Analysis of Changes in Area and Density of Mangroves through Landsat 8 Satellite Image Processing

2019 ◽  
Vol 9 (2) ◽  
pp. 16-22
Author(s):  
Nadya Fiqi Nurcahyani
Keyword(s):  
Image Processing ◽  
Satellite Imagery ◽  
Good Accuracy ◽  
Social Values ◽  
Satellite Image ◽  
Landsat 8 ◽  
Mangrove Forests ◽  
Android Application ◽  
Mangrove Area ◽  
Satellite Image Processing

Mangrove forests have high ecological, economic and social values ??which function to maintain shoreline stability, protect beaches and riverbanks, filter and remediate waste, and to withstand floods and waves. The facts show that mangrove damage is everywhere, even the intensity of damage and its area tends to increase significantly. Many roles of mangroves require proper management to maintain the existence of mangroves. One way to determine the area of ??mangroves is by processing Landsat 8 satellite imagery. The stages of mangrove identification are carried out by using 564 RGB band merger, then separating the mangrove and non-mangrove objects. Next step is to analyze the density of mangroves using NDVI formula. To maximize monitoring of mangrove area, an android application was created that provides information on the area and density of mangroves at several locations, namely Clungup, Bangsong Teluk Asmara and Cengkrong from 2015 to 2018.The results showed that Landsat 8 satellite imagery can be used to identify changes in the area of ??mangrove forests with good accuracy, namely in the Clungup area of ??90% and Cengkrong of 86.67%. From processing results, the mangrove area in the Clungup area has also decreased from 2015 to 2017 but has increased in 2018 so that the application provides recommendations for embroidering mangroves in 2016 to 2017 and mangrove recommendations are maintained in 2018. As for Bangsong Teluk area Asmara and Cengkrong have increased the area of ??mangroves every year so that the application provides recommendations to be maintained from 2016 to 2018.

scholarly journals NDVI Based Assessment of Land Cover Changes Using Remote Sensing and GIS (A case study of Srinagar district, Kashmir)

2020 ◽  
Author(s):  
Perminder Singh ◽  
Ovais Javeed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Spectral Signature ◽  
Landsat 8 ◽  
Thematic Mapping

Normalized Difference Vegetation Index (NDVI) is an index of greenness or photosynthetic activity in a plant. It is a technique of obtaining  various features based upon their spectral signature  such as vegetation index, land cover classification, urban areas and remaining areas presented in the image. The NDVI differencing method using Landsat thematic mapping images and Landsat oli  was implemented to assess the chane in vegetation cover from 2001to 2017. In the present study, Landsat TM images of 2001 and landsat 8 of 2017 were used to extract NDVI values. The NDVI values calculated from the satellite image of the year 2001 ranges from 0.62 to -0.41 and that of the year 2017 shows a significant change across the whole region and its value ranges from 0.53 to -0.10 based upon their spectral signature .This technique is also  used for the mapping of changes in land use  and land cover.  NDVI method is applied according to its characteristic like vegetation at different NDVI threshold values such as -0.1, -0.09, 0.14, 0.06, 0.28, 0.35, and 0.5. The NDVI values were initially computed using the Natural Breaks (Jenks) method to classify NDVI map. Results confirmed that the area without vegetation, such as water bodies, as well as built up areas and barren lands, increased from 35 % in 2001 to 39.67 % in 2017.Key words: Normalized Difference Vegetation Index,land use/landcover, spectral signature 

scholarly journals Preliminary Study of Total Suspended Solid Distribution in Coastal Ujung Pangkah Gresik Based Reflectance Value of Landsat Satellite Imagery

2019 ◽  
Vol 51 (1) ◽  
pp. 42
Author(s):  
Hendrata Wibisana ◽  
Bangun Muljo Soekotjo ◽  
Umboro Lasminto
Keyword(s):  
Satellite Image ◽  
Image Data ◽  
Total Suspended Solid ◽  
Suspended Solid ◽  
Landsat 8 ◽  
Time Period ◽  
Satellite Image Data ◽  
Landsat Satellite ◽  
Solid Distribution

Total suspended solid (TSS) is one of the parameters that uses for detecting health in aquatic environments. The distribution of the TSS value in the water body will affect the aquatic ecosystem. In this research will be analyzed the distribution value of TSS during 5 year period by utilizing Landsat 8 satellite image data, where the developed method is extraction of reflectance value from Landsat 8 satellite image for 5 years using SEADASS and then compiled the TSS algorithm with reflectance value that already obtained on the existing conditions, the algorithm obtained is estimated over 5 years back to get a picture of change and distribution of TSS value. As a case study , the coast of Ujung Pangkah Gresik was taken which has the mouth of the river Bengawan Solo. The results obtained from this study illustrate the decrease of TSS value during that time period, so that with this decrease can be concluded that at the point of field coordinate, TSS value was decreasing and causing the erosion in the environment.

scholarly journals Research Bathymetry Mapping of Shallow Water Areas around Islands in the Truong Sa Archipelago by Deep - Remote sensing technology

2017 ◽  
Vol 33 (4) ◽  
Author(s):  
Phan Quoc Yen ◽  
Dao Khanh Hoai ◽  
Dinh Thi Bao Hoa
Keyword(s):  
Remote Sensing ◽  
Shallow Water ◽  
Satellite Image ◽  
Image Data ◽  
Landsat 8 ◽  
Military Operations ◽  
Sensing Technology ◽  
Remote Sensing Techniques ◽  
Map Data ◽  
The Military

Satellite image data is being researched and applied effectively in the survey and establishment of bathymetry mapping in shallow water areas in both time and human terms. Remote sensing techniques contribute to rapid updating of topography, timely assurance of civil and military operations such as maritime safety, environmental security and rescue, Warfare in the military, especially the ability to remotely monitor disputed areas. The article experiment with the Stumpf et al algorithm to estimate the shallow water depths on the Spratly Island by Landsat 8 image. The correlation coefficient of the model R2 is 0.924; RMSE is 0.99m. In addition, the results are compared with the map data of C-map and use 12 actual test points scores to evaluate the accuracy of the model.

scholarly journals Spatial analysis of coral reefs and its degradation patterns in Bunaken National Park

2019 ◽  
Vol 76 ◽  
pp. 01001
Author(s):  
Nafil Rabbani Attamimi ◽  
Ratna Saraswati
Keyword(s):  
Coral Reefs ◽  
Spatial Pattern ◽  
Shallow Water ◽  
National Park ◽  
Sea Water ◽  
Satellite Image ◽  
Landsat 8 ◽  
Marine Habitats ◽  
Observation Process ◽  
Healthy Coral

This article will analyze the spatial pattern as well as the degradation pattern of the coral reefs in the Bunaken National Park. Bunaken National Park is a marine national park located in the Province of North Sulawesi; the park was built as means of conservation as well as providing a region for tourism. The national park contains a different type of marine and land ecosystem, one of the many types of the ecosystem that are in the national park is coral reefs. Coral reefs in Bunaken National Park provides different kinds of function and benefits whether for the marine habitats that live around the ecosystem, as well as for the local people who live in the islands of the national park. Remote sensing could be used as a tool to identify the spatial pattern and the type of ecosystem that habits inside shallow sea water. The main issue with this method is that the research cannot be conduct directly to identify which type of ecosystem specifically (such as coral reefs, seagrass, etc.), as well as its condition. Therefore, data collecting is necessary to observe and identify the ecosystem and its condition specifically. This study uses satellite image from Landsat 8 OLI as the main secondary data to be processed. The satellite image will be processed by using an algorithm of shallow water analysis that was introduced by Lyzenga in 1981. Since data verification and data observation is needed for this study, the research observes the pattern of the different type of ecosystem and its condition that spreads around Bunaken National Park. The verification and observation process was done by GPS, there were 250 different samples from the data that were collected around the Bunaken National Park. The sample that was collected in the study area will be used to classify the satellite image that has been processed by shallow water algorithm, on which could identify: seagrass, bleached coral reefs, deceased coral reefs, and healthy coral reefs around the national park. The results of this study show the spatial pattern of the coral reefs is located usually around the islands in the Bunaken National Park. The results show that the coral reefs are mostly located around the islands in the National Park. The map results show that the healthy coral reefs are usually located in the outermost layer around the shallow water ecosystem. The bleached reefs are usually located in the middle section of the shallow water, between the healthy coral and the islands itself. Most of the reefs that died and bleached are in the southwest of Bunaken Island, and the northwest of Nain Island.

Sign in / Sign up

Export Citation Format

Share Document