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 Monitoring the Land Cover Changes in Mangrove Areas and Urbanization using Normalized Difference Vegetation Index and Normalized Difference Built-up Index in Krabi Estuary Wetland, Krabi Province, Thailand

2021 ◽  
pp. 1-16
Author(s):  
Katawut Waiyasusri
Keyword(s):  
Land Cover ◽  
Mangrove Forest ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Accuracy Assessment ◽  
Forest Degradation ◽  
Tourism Industry ◽  
Land Cover Changes ◽  
Band Ratio ◽  
The Impact

Krabi Estuary Wetland (KEW) is an outstanding wetland with an estuary environment. At present, the tourism industry has rapidly grown, resulting in the impact of land cover changes. This research aims to assess the changes that have occurred in the KEW from 1999 to 2020 using NDVI and NDBI for monitoring changes in mangrove areas and urbanization in Krabi Province, Thailand. Landsat satellite images in years 1999, 2009 and 2020 were classified by using a band ratio to create land cover maps. The results show that NDVI between 0.41–1.00 clearly shows the mangrove forest area, while NDBI between 0.01–0.40 shows urban and built-up land, and 0.41–1.00 appears as bare land. The NDVI overall accuracy assessment is 82.88%, 97.46% and 88.25% with Kappa values of 0.64, 0.92, and 0.85 for year 1999, 2009 and 2020, respectively. The NDBI overall accuracy assessment is 92.81%, 77.11% and 64% with Kappa values of 0.93, 0.77, and 0.63 for year 1999, 2009 and 2020, respectively. In addition, areas that are sensitive to land-cover change appear around the Chi rat River, Pak Nam Krabi River, and Yuan River, which are tourist areas close to the Krabi and Ao Nang communities. Therefore, it is necessary to speed up the problem solving and find measures to prevent mangrove forest degradation in these 3 mangrove forest areas so that the mangrove forest areas will not decrease rapidly in the future. This research can be valuable for land-cover management in the KEW by policy and decision makers.

scholarly journals PERUBAHAN LUAS DAN KERAPATAN HUTAN MANGROVE PULAU PANIKIANG KABUPATEN BARRU

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
A. Ibnu Rahmatullah Qamal
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Satellite Imagery ◽  
Mangrove Forest ◽  
Forest Area ◽  
Vegetation Changes ◽  
Mangrove Forests ◽  
Remote Sensing Images ◽  
Mangrove Vegetation ◽  
Landsat 5 Tm

ABSTRACT                This study aims to find out how changes in mangrove forest area and how the density of mangrove forests in Panikiang Island changes from 1998 to 2018. Analysis of changes used is the analysis of remote sensing images. The image used is satellite imagery LANDSAT 5 TM acquisition 1998 and LANDSAT OIL imagery acquisition in 2018. The guided classification method with the maximum like-lihood method is used to determine changes in mangrove forest area, while for non-guided classification using NDVI formula.                The results obtained in 1998 mangrove vegetation covering an area of 6.93 hectares experienced changes in land cover to non-vegetative mangrove and elsewhere on the island became 3.24 hectares of mangrove vegetation. Changes in the area of mangrove forests from 1998-2018 were 3.92 hectares.The density of the Pannikiang Island mangrove forest in 1998 with the class of meetings decreased by 34.56 hectares, the density class increased by 23.67 hectares and the density rarely increased by 7.2 hectares.

scholarly journals Detection of Land Cover Changes using Landsat ETM Images at Mendanau North Coastal and Batu Dinding Island in Selat Nasik District, Belitung Regency

2018 ◽  
Vol 12 (1) ◽  
pp. 83-87
Author(s):  
Irma Akhrianti ◽  
Franto Franto ◽  
Eddy Nurtjahya ◽  
Indra Ambalika Syari
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Images ◽  
Image Data ◽  
Mining Area ◽  
Land Cover Changes ◽  
Residential Areas ◽  
Mangrove Vegetation ◽  
Open Land ◽  
High Level

Land cover changes is a physical impact which caused by the the existence of human activity that is quite high in parts of the lithosphere of the earth. The change in landscape certainly has a positive correlation with the dynamics of land use in an area, so that regular monitoring needs to be done, because often land use occurs out of control and not even in accordance with its designation. The main problems that occur in Mendanau Isalnd and Batu Dinding Island are the high level of utilization of mangrove ecosystems, the conversion of mangrove land into ecotourism areas, ports area, residental area and mining area (bauxite). This study aims to monitor changes in land cover in the northern coastal areas of Mendanau Island and Batu Dinding Island in Belitung Regency for 6 years (2000, 2002, and 2006) using a remote sensing technology approach, where image data processing refers to a guided classification method combined with check the field. The satellite images used are still classified as low resolution, namely Multitemporal ETM satellite images with ± 10% cloud cover rate. The results showed that, found 6 land cover classes, namely settlement, open land, mangrove vegetation, non-mangrove vegetation, marine waters, and clouds, which can be detected there has been a change in the increase in the area of non-mangrove vegetation by 365.47 ha, while residential areas experienced fluctuating conditions, namely an increase in cover area in 2000-2002 around 111.94 ha, then declined again in 2006 amounting to 61.28 ha. Unlike the case with the area of open land cover and cover of mangrove vegetation which tends to decrease. The area of open land cover in 2000-2002 decreased by 16.96 ha, then declined again in 2006 by 32.32 ha. The cover area of mangrove vegetation in 2000-2002 decreased by 69.5 ha, then decreased again in 2016 amounting to 208.82 ha.  

scholarly journals PEMANFAATAN VEGETASI MANGROVE DI PULAU PADANG TIKAR KECAMATAN BATU AMPAR KABUPATEN KUBU RAYA

2018 ◽  
Vol 7 (2) ◽  
Author(s):  
. Ratnasari ◽  
M Dirhamsyah
Keyword(s):  
Natural Resources ◽  
Mangrove Forest ◽  
Herbal Medicines ◽  
Survey Method ◽  
Mangrove Forests ◽  
Excoecaria Agallocha ◽  
Nypa Fruticans ◽  
Sonneratia Caseolaris ◽  
Mangrove Vegetation ◽  
Bruguiera Cylindrica

Utilization of natural resources by the community sometimes does not pay attention to the limits of ability or environmental carrying capacity in the regeneration process for sustainable life cycle, both biologically, physically, ecologically and economically. Optimal and environmentally sound utilization and management of natural resources is required to support the sustainability of natural resources including mangrove forests. Mangrove forest is one type of tropical rainforest located along the coastline of tropical waters. This forest is a transition of terrestrial and marine environment habitat. One of the mangrove forest in West Kalimantan is located on Pulau Padang Tikar Batu Ampar Sub-district of Kubu Raya Regency with mangrove forest area of approximately 58,953 Ha which consists of 11 villages inside the forest. The purpose of this research is to know the types of mangrove vegetation and the utilization of mangrove vegetation by the community in 11 villages of Pulau Padang Tikar. This research uses survey method with interview technique. Numbers of respondents were 10 people from each village (total number 110 respondents) in Pulau Padang Tikar. Results of the research found 20 mangrove vegetation species found in the community and 9 types of mangrove vegetation are used for firewood, building material, charcoal, honey bee cultivation and herbal medicines. The species found were Acanthus ilicifolius, Acrostichum aureum, Avicennia sp. Amyema anisomeres, Bruguiera parviflora, Excoecaria agallocha, Heritiera globosa, Kandelia candel, Lumnitzera littorea, Nypa fruticans, Rhizophora sp., Sonneratia alba, Sonneratia caseolaris, Xylocarpus granatum, Oncosperma tigilarium, Hibiscus tiliaceus, Ipomea pescaprae, Sonneratia sp, Bruguiera cylindrica and Sonneratia ovata back.Keywords:  Batu Ampar, Kubu Raya Regency, mangrove, Pulau Padang Tikar, Utilization 

scholarly journals Short Communication: Species composition and density of mangrove forest in Kedawang Village, Pasuruan, East Java, Indonesia

2019 ◽  
Vol 20 (6) ◽  
Author(s):  
WAHYU ISRONI ◽  
R ADHARYAN ISLAMY ◽  
MOHAMAD MUSA ◽  
PUTUT WIJANARKO
Keyword(s):  
Species Composition ◽  
Mangrove Forest ◽  
Short Communication ◽  
Avicennia Marina ◽  
Tree Level ◽  
Survey Method ◽  
Sampling Point ◽  
Rhizophora Apiculata ◽  
Mangrove Vegetation ◽  
Avicennia Alba

Abstract. Isroni W, Islamy RA, Musa M, Wijanarko P. 2019. Short Communication: Species composition and density of mangrove forest in Kedawang Village, Pasuruan, East Java. Biodiversitas 20: 1688-1692. Mangrove is one of ecosystems located in estuary and shallow coastal waters and its existence has a significant role for life. The aim of this study was to identify species composition and density of mangrove forest in Kedawang village, Nguling Sub-district, Pasuruan District, East Java, Indonesia. Survey method using belt transects was carried at three sampling points. Results of this study showed that mangrove vegetation in Kedawang includes five species from three families, namely Avicenniaceae (Avicennia alba and Avicennia marina), Rhizophoraceae (Rhizophora apiculata and Rhizophora mucronata), and Sonneratiace (Sonneratia alba). At sampling point 1, A. alba dominated with a density of 37 individuals/ha at tree level, 380 individuals/ha at pole level and 3100 individuals/ha at stake level. At sampling point 2, the tree level was dominated by A. alba with 142 individuals/ha, while R. mucronata dominated the pole and stake level with 1300 and 1467individuals/ha, respectively. At sampling point 3, the pole and stake level was dominated by A. alba with 167 and 933 individuals/ha respectively, while A. marina dominated the sapling level with 800 individuals/ha. At all stations, the density at stake level is greater than that tree level. Therefore, it is necessary to carry out conservation efforts in the form of protection combined with restoration by enrichment planting at all study locations to increase the diversity and density of mangrove vegetation.

scholarly journals PENGARUH PERUBAHAN LUAS HUTAN MANGROVE TERHADAP KONSENTRASI TOTAL SUSPENDED MATTER (TSM) DI MUARA PERANCAK, JEMBRANA – BALI

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Komang Iwan Suniada
Keyword(s):  
Suspended Matter ◽  
Mangrove Forest ◽  
Satellite Image ◽  
River Mouth ◽  
Remote Sensing Data ◽  
Image Data ◽  
Mangrove Ecosystem ◽  
Total Suspended Matter ◽  
Forest Area ◽  
Mangrove Forests

Study of the function of mangrove forests as a sediment trap has been largely undertaken using field measurement methods, but only a few researches that fully utilize remote sensing data to find out the influence of mangrove forest’s area changes against the Total Suspended Matter (TSM) making this study very interesting and important to do.  This research was conducted in Perancak estuary area which is one of mangrove ecosystem area in Bali besides West Bali National Park, Benoa Forest Park and Nusa Lembongan. The data used to generate TSM information and change of mangrove forest area in this research is medium resolution satellite image data, Landsat.  Tidal data and rainfall data were used as a supporting data. The information of TSM concentration obtained by using Budhiman (2004) algorithm, shows that along with the increasing of mangrove forest area has caused the decreasing of TSM concentration at mouth Perancak river. The decline was caused by sediments trapped and settled around trees or mangrove roots, especially the Rhizophora mangroves. In addition to the increasing of mangrove forest area, the tidal oceanography factor also greatly influences the TSM fluctuation around Perancak river mouth. 

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 MANGROVE FOREST EFFECT ON THE COASTLINE IN RANGSANG ISLAND RIAU PROVINCE

2020 ◽  
Vol 3 (1) ◽  
pp. 29-37
Author(s):  
Paulinus ◽  
Mubarak Mubarak ◽  
Efriyeldi Efriyeldi
Keyword(s):  
Image Data ◽  
Landsat Image ◽  
Sampling Location ◽  
Landsat 8 ◽  
Mangrove Forests ◽  
Bruguiera Gymnorrhiza ◽  
Mangrove Species ◽  
Rhizophora Apiculata ◽  
Xylocarpus Granatum ◽  
Avicennia Alba

The study was conducted in May-June 2019 on Rangsang Island. This study aims to determine the effect of mangrove forests on coastline found on the island of Rangsang in Riau Province. The sampling location was determined by purposive sampling, namely 3 station points, namely Segomeng Village, Tanjung Kedabu Village, and Sungai Gayung Kiri Village. Landsat image data analyzed at the Oceanographic Physics Laboratory of the Department of Marine Sciences, Faculty of Fisheries and Maritime Affairs, University of Riau. To find out the area of ​​mangroves using Landsad 5 TM satellite imagery and Landsat 8 OLI Tirs imagery and analyzed using Er Mapper Software, Envi 4.5 and Arcgis 10.3. Calculation of the structure of the mangrove community is carried out using the line plot plot method. The results of the analysis of the vast landsat image of mangroves in the coastal areas of Rangsang Island in 1997, 2002, 2007, 2013, 2019 were respectively 11,093 ha, 10,807 ha, 10,393 ha, 10,121 ha and 9,971 ha. Changes in the coastline indicate the occurrence of abrasion and accretion, where the highest abrasion occurs at station three with an average of -7.6 m/year and accretion occurs at station one with an average of 2.68 m / year. Mangrove density at station one is 2266.7 ind / ha and at station two that is 1466.7 ind / ha. Mangrove species found were Rhizophora apiculata, Rhizophora mucronata, Avicennia alba, Sonneratia ovata, Bruguiera gymnorrhiza, and Xylocarpus granatum.

scholarly journals LIMITATION ASSESSMENT AND WORKFLOW REFINEMENT OF THE MANGROVE VEGETATION INDEX (MVI)-BASED MAPPING METHODOLOGY USING SENTINEL-2 IMAGERY

2021 ◽  
Vol XLVI-4/W6-2021 ◽  
pp. 235-242
Author(s):  
M. P. Neri ◽  
A. B. Baloloy ◽  
A. C. Blanco
Keyword(s):  
Land Cover ◽  
Vegetation Index ◽  
Climatic Conditions ◽  
Complex Environments ◽  
Spectral Signatures ◽  
Palm Trees ◽  
Otsu Method ◽  
Mangrove Vegetation ◽  
Threshold Setting ◽  
Sentinel 2

Abstract. The Mangrove Vegetation Index (MVI) was developed to map mangroves extent from remotely-sensed imageries accurately and quickly. MVI measures the probability of a pixel to be a ‘mangrove’ by extracting the greenness and moisture information from the green, NIR, and SWIR bands. The range of MVI values may vary depending on factors such as land cover classes, climatic conditions, or tidal conditions. Mapping the scope of mangrove sites involves setting a maximum and minimum MVI threshold to separate them from other land cover classes and vegetation. Although the MVI has a high index accuracy, its mapping performance is limited by some biophysical and environmental factors. Misclassification occurs in aquacultural areas, irrigated croplands, and sites with palm trees where mangrove and surrounding vegetation pixels have highly similar spectral signatures. There are scenes with complex environments, such as in aquaculture areas and along a network of rivers and streams, where an optimal threshold varies across the site, and setting a single MVI threshold may not yield excellent results. An automated threshold setting using the Otsu method was explored; however, the results were inaccurate due to a low intensity contrast between mangroves and other vegetation in the MVI raster layer. This study also looked into possible adjustments to improve the manual threshold setting workflow for a successful mapping of mangrove extent using MVI on Sentinel-2 imagery.

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