scholarly journals SPATIO-TEMPORAL MAPPING AND ANALYSIS OF MANGROVE EXTENTS AROUND MANILA BAY USING LANDSAT SATELLITE IMAGERY AND MANGROVE VEGETATION INDEX (MVI)

2021 ◽  
Vol XLVI-4/W6-2021 ◽  
pp. 103-108
Author(s):  
M. Conopio ◽  
A. B. Baloloy ◽  
J. Medina ◽  
A. C. Blanco
Keyword(s):  
Mangrove Forest ◽  
Vegetation Index ◽  
Land Reclamation ◽  
Detection Algorithm ◽  
The Philippines ◽  
Rapid Decline ◽  
Wide Range ◽  
Mangrove Vegetation ◽  
Manila Bay ◽  
Landsat Satellite

Abstract. Mangroves are considered one of the most undervalued ecosystems in the world. It provides shelter to a wide range of species and protection from natural hazards to coastal communities. The Philippines, being a country with long coastlines, benefits greatly from mangroves. Historically, it had 400,000–500,000 hectares of mangroves forest in 1920, which declined to 120,000 hectares in 1994 due to rapid industrialization, particularly the conversion of these forests into aquaculture such as fishponds Mangrove forest in the Philippines saw a rapid decline between 1920 and 1994 due to aquaculture conversion and land reclamation Mangrove Vegetation Index (MVI), an established mangrove detection algorithm, was applied on Landsat satellite images of Manila Bay to map the extent of the mangrove forest from 1990 to 2020. Thirteen time-series maps were produced. Area computation showed that the coastline of Bulacan had the most mangroves, while the coastline of Metro Manila had the least throughout the years.

scholarly journals UTILIZATION OF SENTINEL-2 IMAGERY IN THE ESTIMATION OF PLASTICS AMONG FLOATING DEBRIS ALONG THE COAST OF MANILA BAY

2021 ◽  
Vol XLVI-4/W6-2021 ◽  
pp. 177-184
Author(s):  
M. L. R. Gonzaga ◽  
M. T. S. Wong ◽  
A. C. Blanco ◽  
J. A. Principe
Keyword(s):  
Vegetation Index ◽  
The Philippines ◽  
Training Data ◽  
Economic Activities ◽  
Plastic Pollution ◽  
Different Types ◽  
Manila Bay ◽  
Supervised Classification Methods ◽  
Selection Of ◽  
Sentinel 2

Abstract. With the Philippines ranking as the third largest source of plastics that end up in the oceans, there is a need to further explore methodologies that will become an aid in plastic waste removal from the ocean. Manila Bay is a natural harbor in the Philippines that serves as the center of different economic activities. However, the bay is also threatened with plastic pollution due to increasing population and industrial activities. BASECO is one of the areas in Manila Bay where clean-up activities are focused as this is where trash accumulates. Sentinel-2 images are provided free of charge by the European Commission's Copernicus Programme. Satellite images from June 2019 to May 2020 were inspected, then cloud-free images were downloaded. After downloading and pre-processing, spectral data of different types of plastic such as shipping pouch, bubble wrap, styrofoam, PET bottle, sando bag and snack packaging that were measured by a spectrometer during a fieldwork by the Development of Integrated Mapping, Monitoring, and Analytical Network System for Manila Bay and Linked Environments (project MapABLE) were utilized in the selection of training data. Then, indices such as the Normalized Vegetation Index (NDVI), Floating Debris Index (FDI) and Plastic Index (PI) from previous studies were analyzed for further separation of classes used as training data. These training data served as an input to the two supervised classification methods, Naive Bayes and Mixture Tuned Matched Filtering (MTMF). Both methods were validated by reports and articles from Philippine agencies indicating the spots where trash frequently accumulates.

scholarly journals MANGROVE FOREST CHANGE IN NUSA PENIDA MARINE PROTECTED AREA, BALI - INDONESIA USING LANDSAT SATELLITE IMAGERY

2019 ◽  
Vol 15 (2) ◽  
pp. 141 ◽  
Author(s):  
August Daulat ◽  
Widodo Setiyo Pranowo ◽  
Syahrial Nur Amri
Keyword(s):  
Satellite Imagery ◽  
Vegetation Cover ◽  
Protected Area ◽  
Mangrove Forest ◽  
Vegetation Index ◽  
Marine Protected Area ◽  
Mangrove Forests ◽  
Forest Change ◽  
Landsat Satellite ◽  
The Impact

Nusa Penida, Bali was designated as a Marine Protected Area (MPA) by the Klungkung Local Government in 2010 with support from the Ministry of Marine Affairs and Fisheries, Republic of Indonesia. Mangrove forests located in Nusa Lembongan Island inside the Nusa Penida MPA jurisdiction have decreased in biomass quality and vegetation cover. It’s over the last decades due to influences from natural phenomena and human activities, which obstruct mangrove growth. Study the mangrove forest changes related to the marine protected areas implementation are important to explain the impact of the regulation and its influence on future conservation management in the region. Mangrove forest in Nusa Penida MPA can be monitored using remote sensing technology, specifically Normalized Difference Vegetation Index (NDVI) from Landsat satellite imagery combined with visual and statistical analysis. The NDVI helps in identifying the health of vegetation cover in the region across three different time frames 2003, 2010, and 2017. The results showed that the NDVI decreased slightly between 2003 and 2010. It’s also increased significantly by 2017, where a mostly positive change occurred landwards and adverse change happened in the middle of the mangrove forest towards the sea.

scholarly journals Development of a Rapid Mangrove Zonation Mapping Workflow Using Sentinel 2-Derived Indices and Biophysical Dataset

2021 ◽  
Vol 2 ◽  
Author(s):  
Alvin B. Baloloy ◽  
Ariel C. Blanco ◽  
Sahadev Sharma ◽  
Kazuo Nadaoka
Keyword(s):  
Mangrove Forest ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
The Philippines ◽  
Distribution Analysis ◽  
Rhizophora Stylosa ◽  
Area Index ◽  
Zonation Maps ◽  
Mangrove Zonation ◽  
Sentinel 2

Moderate to high resolution satellite imageries are commonly used in mapping mangrove cover from local to global scales. In addition to extent information, studies such as mangrove composition, ecology, and distribution analysis require further information on mangrove zonation. Mangrove zonation refers to unique sections within a mangrove forest being dominated by a similar family, genus, or species. This can be observed both in natural and planted mangrove forests. In this study, a mapping workflow was developed to detect zonation in test mangrove forest sites in Katunggan-It Ibajay (KII) Ecopark (Aklan), Bintuan (Coron), Bogtong, and Sagrada (Busuanga) in the Philippines and Fukido Mangrove Park (Ishigaki, Japan) using Sentinel-2 imagery. The methodology was then applied to generate a nationwide mangrove zonation map of the Philippines for year 2020. Combination of biophysical products, water, and vegetation indices were used as classification inputs including leaf area index (LAI), fractional vegetation cover (FVC), fraction of photosynthetically-active radiation (FAPAR), Canopy chlorophyll content (Cab), canopy water content (Cw), Normalized Difference Vegetation Index (NDVI), modified normalized difference water index (MNDWI), modified chlorophyll absorption in reflectance index (MCARI), and red-edge inflection point (REIP). Mangrove extents were first mapped using either the Maximum Likelihood Classification (MLC) algorithm or the Mangrove Vegetation Index (MVI)-based methodology. The biophysical and vegetation indices within these areas were stacked and transformed through Principal Component Analysis (PCA). Regions of Interest (ROIs) were selected on the PCA bands as training input to the MLC. Results show that mangrove zonation maps can highlight the major mangrove zones in the study sites, commonly limited up to genera level only except for genera with only one known species thriving in the area. Four zones were detected in KII Ecopark: Avicennia zone, Nypa zone, Avicennia mixed with Nypa zone, and mixed mangroves zones. For Coron and Busuanga, the mapped mangrove zones are mixed mangroves, Rhizophora zone and sparse/damaged zones. Three zones were detected in Fukido site: Rhizophora stylosa-dominant zone, Bruguiera gymnorrhiza-dominant zone, and mixed mangrove zones. The zonation maps were validated using field plot data and orthophotos generated from Unmanned Aerial System (UAS) surveys, with accuracies ranging from 75 to 100%.

scholarly journals ANALYSIS OF LAND COVER CHANGES IN MANGROVE VEGETATION USING LANDSAT IMAGE DATA IN COASTAL, SUNGAI APIT DISTRICT, SIAK REGENCY, RIAU PROVINCE

2021 ◽  
Vol 4 (2) ◽  
pp. 154-162
Author(s):  
Armanda Armanda ◽  
Mubarak Mubarak ◽  
Elizal Elizal
Keyword(s):  
Land Cover ◽  
Mangrove Forest ◽  
Vegetation Index ◽  
Image Data ◽  
Landsat Image ◽  
Survey Method ◽  
Land Cover Changes ◽  
Mangrove Forests ◽  
A Value ◽  
Mangrove Vegetation

This research was conducted in March-April 2021 in the Coastal District of Sungai Apit, Siak Regency, Riau Province. The purpose of this study was to analyze changes in the land cover area of ​​mangrove vegetation and mangrove vegetation index in Sungai Apit District, Siak Regency, Riau Province. The method used in this study is a survey method with the interpretation of Landsat image data recorded in 2000, 2005, 2010, 2015, 2020. The results of the study obtained that mangrove forests with the highest area were in 2000 with an area of ​​mangrove vegetation reaching 7990,586 ha and there was a decline with the lowest number in 2015 with a vegetation area of ​​486,43 ha and in 2020 the mangrove vegetation area of ​​497,511 ha. Overall as much as 79% of the mangrove forest area has been damaged and changed its function within a period of 20 years. The NDVI value in Sungai Apit District is moderate with a value of 0,3-0,5, the category of meeting with a value of 0,5-0,6, and the very dense category of 0,6-0,8

scholarly journals STUDI KERAPATAN MANGROVE DAN PERUBAHAN GARIS PANTAI TAHUN 1989-2018 DI PESISIR PROVINSI JAMBI

2020 ◽  
Vol 10 (2) ◽  
pp. 138-152
Author(s):  
Eva Achmad ◽  
Nursanti Nursanti ◽  
Marwoto ◽  
Fazriyas Fazriyas ◽  
Dwi Putri Jayanti
Keyword(s):  
Mangrove Forest ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Low Density ◽  
Shoreline Changes ◽  
Average Change ◽  
Coastal Province ◽  
Analysis System ◽  
Landsat Satellite

The density of mangrove cover is one of the factors that influence changes in shoreline both accretion and abrasion. This study aims to determine the effect of changes in density of mangrove cover on shoreline changes in 1989-2018 in the Coastal Province of Jambi. The method used is the interpretation of Landsat satellite images in 1989, 2000 and 2018 using NDVI (Normalized Difference Vegetation Index) and overlaying images to see shoreline changes and DSAS (Digital Shoreline Analysis System) to calculate the area of change. The results showed that there had been a change in shoreline both accretion and abrasion in several locations that had different mangrove densities in the period 1989-2018. The results showed that accretion occured in 6 locations with an average change of Kota Sebrang 771 m, Tungkal Ilir 240.65 m, Kuala Betara 153.73 m, Mendahara 167.78 m, Kuala Jambi 169.35 m and Nipah 57.3 m, while abrasion occurs at 2 locations with an average change in Sabak Timur -41.8 m and Sadu -36.55 m. Where in the 6 locations that had accretion, mangrove density dominantly was in a close-densed and moderate state and only a few are in a low-densed condition. Meanwhile, the 2 locations that had abrasion were in a moderate state and have a low density mangrove forest.

Spirobranchus bakau sp. nov. from Singapore: yet another species of S. kraussii-complex (Polychaeta: Serpulidae)

Zootaxa ◽  
2021 ◽  
Vol 5040 (1) ◽  
pp. 33-65
Author(s):  
GAYATHIRI D/O SIVANANTHAN ◽  
PAVARNE SHANTTI ◽  
ELENA K. KUPRIYANOVA ◽  
ZHENG BIN RANDOLPH QUEK ◽  
NICHOLAS WEI LIANG YAP ◽  
...  
Keyword(s):  
Embryonic Development ◽  
Sequence Data ◽  
Taxonomic Status ◽  
Molecular Data ◽  
The Philippines ◽  
Salinity Range ◽  
Dna Sequence Data ◽  
Wide Range ◽  
Manila Bay ◽  
Morphological And Molecular Data

The intertidal serpulid polychaete Spirobranchus kraussii was originally described from South Africa and has since been reported in numerous sub (tropical) localities around the world. Recently, however, S. kraussii was uncovered as a complex of morphologically similar and geographically restricted species, raising the need to revise S. cf. kraussii populations. We formally describe S. cf. kraussii from Singapore mangroves as Spirobranchus bakau sp. nov. based on morphological and molecular data. Despite their morphological similarities, Maximum Likelihood and Bayesian Inference analyses of 18S and Cyt b DNA sequence data confirm that S. bakau sp. nov. is genetically distinct from S. kraussii and other known species in the complex. Both analyses recovered S. bakau sp. nov. as part of a strongly supported clade (96% bootstrap, 1 posterior probability), comprising S. sinuspersicus, S. kraussii and S. cf. kraussii from Australia and Hawaii. Additionally, paratypes of S. kraussii var. manilensis, described from Manila Bay in the Philippines, were examined and elevated to the full species S. manilensis. Finally, we tested the hypothesis that fertilisation and embryonic development of S. bakau sp. nov. can occur under the wide range of salinities (19.6–30.9 psu) and temperatures (25–31°C) reported in the Johor Strait. Fertilisation success of ≥70% was achieved across a temperature range of 25–32°C and a salinity range of 20–32 psu. Embryonic development, however, had a narrower salinity tolerance range of 27–32 psu. Clarifying the taxonomic status of S. cf. kraussii populations reported from localities elsewhere in Singapore and Southeast Asia will be useful in establishing the geographical distribution of S. bakau sp. nov. and other members of the S. kraussii-complex.  

Read, Understand, Learn, & Excel: Development and Testing of an Automated Reading Strategy Detection Algorithm for Postsecondary Students

2019 ◽  
Vol 28 (3) ◽  
pp. 1257-1267 ◽  
Author(s):  
Priya Kucheria ◽  
McKay Moore Sohlberg ◽  
Jason Prideaux ◽  
Stephen Fickas
Keyword(s):  
Academic Success ◽  
Undergraduate Students ◽  
Expository Text ◽  
Reading Strategy ◽  
Detection Algorithm ◽  
Expository Texts ◽  
Human Observer ◽  
Behavioral Strategies ◽  
Periodic Review ◽  
Wide Range

PurposeAn important predictor of postsecondary academic success is an individual's reading comprehension skills. Postsecondary readers apply a wide range of behavioral strategies to process text for learning purposes. Currently, no tools exist to detect a reader's use of strategies. The primary aim of this study was to develop Read, Understand, Learn, & Excel, an automated tool designed to detect reading strategy use and explore its accuracy in detecting strategies when students read digital, expository text.MethodAn iterative design was used to develop the computer algorithm for detecting 9 reading strategies. Twelve undergraduate students read 2 expository texts that were equated for length and complexity. A human observer documented the strategies employed by each reader, whereas the computer used digital sequences to detect the same strategies. Data were then coded and analyzed to determine agreement between the 2 sources of strategy detection (i.e., the computer and the observer).ResultsAgreement between the computer- and human-coded strategies was 75% or higher for 6 out of the 9 strategies. Only 3 out of the 9 strategies–previewing content, evaluating amount of remaining text, and periodic review and/or iterative summarizing–had less than 60% agreement.ConclusionRead, Understand, Learn, & Excel provides proof of concept that a reader's approach to engaging with academic text can be objectively and automatically captured. Clinical implications and suggestions to improve the sensitivity of the code are discussed.Supplemental Materialhttps://doi.org/10.23641/asha.8204786

Brief history and ways of further development of the department of hydraulic engineering and hydraulics FSBI «VNIIGiM named after A.N. Kostyakov»

2020 ◽  
pp. 18-23
Author(s):  
Alexey Shcherbakov ◽  
Valentin Zhezmer
Keyword(s):  
Land Reclamation ◽  
Water Source ◽  
Water Sources ◽  
Hydraulic Engineering ◽  
Negative Effects ◽  
Extensive Experience ◽  
Safety Level ◽  
Theoretical Substantiation ◽  
Wide Range ◽  
Construction Operation

Department of hydraulic engineering and hydraulics FGBNU «VNIIGiM them. A.N. Kostyakova «has a long history. For many years, the department’s staff has been such scientists and water engineers with extensive experience as M.A. Volynov, V.S. Verbitsky, S.S. Medvedev, N.V. Lebedev, B.C. Panfilov, T.G. Voynich-Syanozhentsky, V.A. Golubkova, G.V. Lyapin and others. The department solved a wide range of tasks, the main areas of research were the following: – theoretical and applied hydrodynamics and hydraulics, with reference to the open channel flows that affect the state and level of safety of the hydraulic structures; – integrated use and protection of water bodies – water sources and water sources of water resources used in land reclamation; – development of measures and technical solutions for the protection of objects from the negative effects of water; – theoretical substantiation of works to improve the safety level of the GTS (declaration); – development and implementation of digitalization methods for solving design, construction, operation and control of landreclamation facilities. Currently, promising areas of research is the development of a decision-making algorithm in the designation of measures to rationalize the provision of resources to water amelioration. The algorithm is developed on the basis of a detailed study, systematization and processing of data both on safety and on the efficiency of systems and structures, ensuring the delivery of irrigation water of the required quality and in sufficient quantity from a water source to the field.

Analysis of Land Use Land Cover in Annapurna Conservation Area in Gandaki Province, Nepal using Vegetation Index and Land Use Land Cover Datasets

2019 ◽  
Vol 2 (2) ◽  
pp. 87-99
Author(s):  
Shiva Pokhrel ◽  
Chungla Sherpa
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
National Level ◽  
Climate Mitigation ◽  
Land Use Land Cover ◽  
Conservation Area ◽  
Barren Land ◽  
Wide Range ◽  
Annapurna Conservation Area

Conservation areas are originally well-known for protecting landscape features and wildlife. They are playing key role in conserving and providing a wide range of ecosystem services, social, economic and cultural benefits as well as vital places for climate mitigation and adaptation. We have analyzed decadal changes in land cover and status of vegetation cover in the conservation area using both national level available data on land use land cover (LULC) changes (1990-2010) and normalized difference vegetation index (NDVI) (2010-2018) in Annapurna conservation area. LULC showed the barren land as the most dominant land cover types in all three different time series 1990, 2000 and 2010 with followed by snow cover, grassland, forest, agriculture and water body. The highest NDVI values were observed at Southern, Southwestern and Southeastern part of conservation area consisting of forest area, shrub land and grassland while toward low to negative in the upper middle to the Northern part of the conservation area.

scholarly journals Mangrove Forest Landcover Changes in Coastal Vietnam: A Case Study from 1973 to 2020 in Thanh Hoa and Nghe An Provinces

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 637
Author(s):  
Huong Thi Thuy Nguyen ◽  
Giles E. S. Hardy ◽  
Tuat Van Le ◽  
Huy Quoc Nguyen ◽  
Hoang Huy Nguyen ◽  
...  
Keyword(s):  
Mangrove Forest ◽  
Monsoon Season ◽  
Coastal Development ◽  
Northern Coast ◽  
Mangrove Forests ◽  
Visual Interpretation ◽  
Mangrove Restoration ◽  
Coast Of Vietnam ◽  
Landsat Satellite

Mangrove forests can ameliorate the impacts of typhoons and storms, but their extent is threatened by coastal development. The northern coast of Vietnam is especially vulnerable as typhoons frequently hit it during the monsoon season. However, temporal change information in mangrove cover distribution in this region is incomplete. Therefore, this study was undertaken to detect change in the spatial distribution of mangroves in Thanh Hoa and Nghe An provinces and identify reasons for the cover change. Landsat satellite images from 1973 to 2020 were analyzed using the NDVI method combined with visual interpretation to detect mangrove area change. Six LULC classes were categorized: mangrove forest, other forests, aquaculture, other land use, mudflat, and water. The mangrove cover in Nghe An province was estimated to be 66.5 ha in 1973 and increased to 323.0 ha in 2020. Mangrove cover in Thanh Hoa province was 366.1 ha in 1973, decreased to 61.7 ha in 1995, and rose to 791.1 ha in 2020. Aquaculture was the main reason for the loss of mangroves in both provinces. Overall, the percentage of mangrove loss from aquaculture was 42.5% for Nghe An province and 60.1% for Thanh Hoa province. Mangrove restoration efforts have contributed significantly to mangrove cover, with more than 1300 ha being planted by 2020. This study reveals that improving mangrove restoration success remains a challenge for these provinces, and further refinement of engineering techniques is needed to improve restoration outcomes.

Sign in / Sign up

Export Citation Format

Share Document