Mangrove species mapping in Kuala Sepetang Mangrove Forest, Perak using high resolution airborne data

2015 ◽  
Author(s):  
B. C. Beh ◽  
M. Z. MatJafri ◽  
H. S. Lim
Keyword(s):  
High Resolution ◽  
Mangrove Forest ◽  
Mangrove Species ◽  
Species Mapping

An updated national-scale mangrove forest map in China Using Sentinel-1 and Sentinel-2 Time-Series Data with Google Earth Engine

2021 ◽  
Author(s):  
Luojia Hu ◽  
Wei Yao ◽  
Zhitong Yu ◽  
Yan Huang
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Mangrove Forest ◽  
Google Earth ◽  
Series Data ◽  
National Scale ◽  
Mangrove Area ◽  
Google Earth Engine ◽  
Forest Maps ◽  
Sentinel 2

<p>A high resolution mangrove map (e.g., 10-m), which can identify mangrove patches with small size (< 1 ha), is a central component to quantify ecosystem functions and help government take effective steps to protect mangroves, because the increasing small mangrove patches, due to artificial destruction and plantation of new mangrove trees, are vulnerable to climate change and sea level rise, and important for estimating mangrove habitat connectivity with adjacent coastal ecosystems as well as reducing the uncertainty of carbon storage estimation. However, latest national scale mangrove forest maps mainly derived from Landsat imagery with 30-m resolution are relatively coarse to accurately characterize the distribution of mangrove forests, especially those of small size (area < 1 ha). Sentinel imagery with 10-m resolution provide the opportunity for identifying these small mangrove patches and generating high-resolution mangrove forest maps. Here, we used spectral/backscatter-temporal variability metrics (quantiles) derived from Sentinel-1 SAR (Synthetic Aperture Radar) and sentinel-2 MSI (Multispectral Instrument) time-series imagery as input features for random forest to classify mangroves in China. We found that Sentinel-2 imagery is more effective than Sentinel-1 in mangrove extraction, and a combination of SAR and MSI imagery can get a better accuracy (F1-score of 0.94) than using them separately (F1-score of 0.88 using Sentinel-1 only and 0.895 using Sentinel-2 only). The 10-m mangrove map derived by combining SAR and MSI data identified 20,003 ha mangroves in China and the areas of small mangrove patches (< 1 ha) was 1741 ha, occupying 8.7% of the whole mangrove area. The largest area (819 ha) of small mangrove patches is located in Guangdong Province, and in Fujian the percentage of small mangrove patches in total mangrove area is the highest (11.4%). A comparison with existing 30-m mangrove products showed noticeable disagreement, indicating the necessity for generating mangrove extent product with 10-m resolution. This study demonstrates the significant potential of using Sentinel-1 and Sentinel-2 images to produce an accurate and high-resolution mangrove forest map with Google Earth Engine (GEE). The mangrove forest maps are expected to provide critical information to conservation managers, scientists, and other stakeholders in monitoring the dynamics of mangrove forest.</p>

scholarly journals KOMPOSISI JENIS MANGROVE DAN PENGETAHUAN MASYARAKAT TERHADAP KAWASAN MANGROVE DESA SAYOANG, HALMAHERA SELATAN, MALUKU UTARA Mangrove Species Compotition and Community Knowledge of Mangrove Area in Sayoang Village, Distric of South Halmahera

2017 ◽  
Vol 8 (1) ◽  
pp. 63-68
Author(s):  
Omo Rusdiana ◽  
Fajar Alif Sam Pangestu
Keyword(s):  
Protected Areas ◽  
Mangrove Forest ◽  
Fish Habitat ◽  
Mangrove Forests ◽  
Mangrove Species ◽  
Management Activity ◽  
Community Knowledge ◽  
Mangrove Area ◽  
Total Respondent ◽  
The Government

The area of mangrove forests in Indonesia is currently only spanning as much as 3.4 milion acres, so there is a need for the participation of the government and community to maintain its sustainability. South Halmahera is the district with the largest mangrove area in the North Maluku Province. One of the mangrove areas in the District of South Halmahera is located at Sayoang Village, East Bacan Subdistrict Up until its eleventh founding anniversary, this district have never conducted an inventorizing of its mangroves, both ecological and social studies in the field of public. This study aims to analyze the compotition of mangrove species in Sayoang Village, East Bacan Subdistrict, South Halmahera, and identify the knowledge of surrounding communities of mangrove areas as protected areas. Data were retrieved using sampling method with applications terraced paths, and analyzed by calculating its important value index (INP) and its index value diversity (IVD). The public social data were taken using in-depth interviews and questionnaires. Results obtained from this study show that the mangrove forest in Sayoang Village, East Bacan District, Halmahera, consists of major mangrove species with as many as eleven species belonging to families Rhizophoraceae, Sonneratiaceae, Avicenniaceae, Meliaceae and Myrtaceae, and as many as three species of minor mangrove belonging to families of Loranthaceae, Acanthaceae, and Pteridaceae. The mangrove's species diversity and richness is and low, but it has high evenness. The results showed that 60% of total respondents know the benefit of mangrove as fish habitat, while for mangrove area as conserving areas, 50% of total respondent don't know the status of the area. The cutting problems happened in mangrove areas, 90% of total respondent know the activity and 85% of total respondent think that the logging activities in mangrove area is still allowed. The management activity of mangrove area in Sayoang village hasn't been conducted, either by the community or by local Dinas Kehutanan, and 53% of total respondent still wishing the mangrove can give more benefit economically.Key words: Mangrove forest, mangrove protected areas, community knowledge

scholarly journals KEANEKARAGAMAN JENIS MANGROVE DI DESA MENDALOK KECAMATAN SUNGAI KUNYIT KABUPATEN MEMPAWAH

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Syahrul Muharamsyah ◽  
M Sofwan Anwari ◽  
Hafiz Ardian
Keyword(s):  
Mangrove Forest ◽  
Avicennia Marina ◽  
Raw Material ◽  
Mangrove Forests ◽  
Bruguiera Gymnorrhiza ◽  
Mangrove Species ◽  
Rhizophora Stylosa ◽  
Sonneratia Caseolaris ◽  
Rhizophora Apiculata ◽  
Bruguiera Cylindrica

Mangrove forests are unique ecosystems that have ecological, biological and socio-economic functions. The function of mangrove forests on the environment is very important especially in the coastal and oceanic regions. Mangrove forests providers of wood, leaves as raw material for medicines, and natural dye. This study aims to inventory the diversity of species of mangrove vegetation in Mendalok Village, Sungai Kunyit Subdistrict, Mempawah Regency. The benefits of this study are to provide the data on mangrove forest vegetation as basic data for local government and related agencies in efforts to protect and preserve mangrove forests in Mendalok Village, Sungai Kunyit Subdistrict, Mempawah Regency. Inventory the tree in mangrove forest used a line with measured 200 meters. There are 6 lines and the distance between the lines as far as 100 meters. The lines of observation are placed by purposive sampling. The results of research found 11 types of species and consisted of 6 genera. The genera are Avicennia, Bruguiera, Ceriops, Rhizophora, Soneratia and Xylocarpus. The species found were Avicennia alba, Avicennia marina, Bruguiera cylindrica, Bruguiera gymnorrhiza, Bruguiera parviflora, Ceriops decandra, Rhizophora apiculata, Rhizophora mucronata, Rhizophora stylosa, Sonneratia caseolaris, Xylocarpus mollucensis. Diversity of mangrove species in Mendalok Village, Sungai Kunyit Subdistrict, Mempawah Regency was high and should be maintained for conservation and ecotourism area. Keywords : conservation, ecotourism, mangrove, Mendalok Village

scholarly journals KONDISI WISATA MANGROVE DI DESA PASAR BANGGI, KABUPATEN REMBANG Mangrove Tourism Conditions in Pasar Banggi Village, Rembang Regency

2019 ◽  
Vol 8 (3) ◽  
pp. 221-225
Author(s):  
Danang Adi Saputro ◽  
Frida Purwanti ◽  
Siti Rudiyanti
Keyword(s):  
Species Composition ◽  
Mangrove Forest ◽  
Mangrove Ecosystem ◽  
Google Earth ◽  
Survey Method ◽  
Systematic Sampling ◽  
Sampling Techniques ◽  
Mangrove Species ◽  
Sampling Points ◽  
Exploratory Survey

ABSTRAK Mangrove merupakan tumbuhan yang hidup di daerah pasang surut sebagai ekosistem interface antara daratan dengan lautan. Ekosistem mangrove di desa Pasar Banggi Kabupaten Rembang merupakan perpaduan antara mangrove alami dan hasil rehabilitasi. Tujuan penelitian ini untuk mengetahui kondisi mangrove di Desa Pasar Banggi, Rembang dilihat dari  komposisi jenis, kerapatan dan ketebalan mangrove serta menganalisis tingkat kesesuaian wisata mangrove di Desa Pasar Banggi, Rembang. Metode yang digunakan adalah metode survey lapangan yang bersifat eksploratif, dimana  teknis pengumpulan data menggunakan sistematik sampling. Data yang diambil meliputi 5 variabel yaitu: jenis, kerapatan mangrove dan asosiasi biota (hasil pengamatan lapangan dan perbandingan dari penelitian terdahulu), ketebalan (citra Google Earth Oktober 2016), pasang surut (data BMKG Oktober 2016). Pengambilan sampel dilakukan pada 3 stasiun, dimana setiap stasiun terdapat 3 titik sampling. Komposisi jenis mangrove di desa Pasar Banggi terdapat 3 jenis mangrove yaitu Rhizopora stylosa, R. mucronata, dan R. Apiculata, dengan kerapatan mangrove tertinggi yaitu 62 ind/100m2 dan ketebalan mangrove tertinggi sepanjang 139 m. Kondisi hutan mangrove desa Pasar Banggi termasuk dalam kategori sesuai (S2) untuk kegiatan wisata berkelanjutan di Kabupaten Rembang. ABSTRACT Mangroves are plants that grow in a tidal areas an interface ecosystems between terrestrial and marine. Mangrove ecosystem in the Pasar Banggi Village,  Rembang Regency is a combination results of natural mangrove and rehabilitation. The purpose of this study were to determine condition of mangroves in the Pasar Banggi Village, Rembang, seen from the species composition, density and thickness of mangroves and to analyze the suitability level of mangrove tourism in the Pasar Banggi Village, Rembang. The method used in this study was an exploratory survey method, data collected using systematic sampling techniques. Mangrove tourism data collection was carried out of 5 variables, i.e.: type of mangrove, density of mangroves and associations of biota (from observations and comparisons of previous studies), thickness (Google Earth image October 2016), tides (data BMKG October 2016). Sampling was conducted at 3 stations, each station has 3 sampling points. The composition of mangrove species in Pasar Banggi village consists of 3 types of mangroves, namely Rhizopora stylosa, R. mucronata, and R. Apiculata, with the highest density of mangrove 62 ind / 100m2 and the highest thickness of mangrove along 139 m. The condition of mangrove forest in the Pasar Banggi village was included in the appropriate category (S2) for sustainable tourism activities in the Rembang Regency.

scholarly journals Characteristics and Spatial Influencing Factors of Natural Regeneration within Aquaculture ponds in a Mangrove Forest

2021 ◽  
Author(s):  
kun xin ◽  
Nong Sheng ◽  
Yanmei Xiong ◽  
Zhongmao Jiang ◽  
Yun Zhang ◽  
...  
Keyword(s):  
Natural Regeneration ◽  
Mangrove Forest ◽  
Diversity Index ◽  
Regeneration Process ◽  
Mangrove Species ◽  
Forest Protection ◽  
Spatial Factors ◽  
Regeneration Period ◽  
Aquaculture Ponds ◽  
Natural Dynamics

Abstract Regeneration is an important component of community succession and understanding regeneration dynamics is essential for forest protection and recovery management. Mangroves are distributed along coastlines and this unique habitat has resulted in very different regeneration process. This study took Dongzhaigang mangrove forest in Hainan, China as the study area, considered the 10 years regeneration process in 8 abandoned aquaculture ponds, and the spatial factors that influence the regeneration process are analyzed. The objectives were to: a) investigate the natural dynamics of the mangrove regeneration process in abandoned ponds, b) determine the main spatial factors affecting the natural regeneration process. The results showed that the number of species and individuals showed a tendency to initially rise and then decline, with the maximum occurring at 6–8 years. The results of a diversity index showed an initial rise, with stabilization then occurring over a 8 year period. Aegiceras corniculatum and Sonneratia apetala were typical pioneer mangrove species in the study area, while Bruguiera sexangula and Kandelia obovata were representative species of late regeneration period. Spatial factors, including pond area and shape, relative elevation, distance to a tidal creek and surrounding trees area played important roles in the regeneration of mangrove in ponds. Finally, the study considered the current situation regarding mangrove restoration in China and suggested that natural regeneration of mangroves is a good management option.

scholarly journals Advancing the Mapping of Mangrove Forests at National-Scale Using Sentinel-1 and Sentinel-2 Time-Series Data with Google Earth Engine: A Case Study in China

2020 ◽  
Vol 12 (19) ◽  
pp. 3120
Author(s):  
Luojia Hu ◽  
Nan Xu ◽  
Jian Liang ◽  
Zhichao Li ◽  
Luzhen Chen ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Mangrove Forest ◽  
Time Series Data ◽  
Landsat Imagery ◽  
Google Earth ◽  
Series Data ◽  
National Scale ◽  
Google Earth Engine ◽  
Sentinel 2

A high resolution mangrove map (e.g., 10-m), including mangrove patches with small size, is urgently needed for mangrove protection and ecosystem function estimation, because more small mangrove patches have disappeared with influence of human disturbance and sea-level rise. However, recent national-scale mangrove forest maps are mainly derived from 30-m Landsat imagery, and their spatial resolution is relatively coarse to accurately characterize the extent of mangroves, especially those with small size. Now, Sentinel imagery with 10-m resolution provides an opportunity for generating high-resolution mangrove maps containing these small mangrove patches. Here, we used spectral/backscatter-temporal variability metrics (quantiles) derived from Sentinel-1 SAR (Synthetic Aperture Radar) and/or Sentinel-2 MSI (Multispectral Instrument) time-series imagery as input features of random forest to classify mangroves in China. We found that Sentinel-2 (F1-Score of 0.895) is more effective than Sentinel-1 (F1-score of 0.88) in mangrove extraction, and a combination of SAR and MSI imagery can get the best accuracy (F1-score of 0.94). The 10-m mangrove map was derived by combining SAR and MSI data, which identified 20003 ha mangroves in China, and the area of small mangrove patches (<1 ha) is 1741 ha, occupying 8.7% of the whole mangrove area. At the province level, Guangdong has the largest area (819 ha) of small mangrove patches, and in Fujian, the percentage of small mangrove patches is the highest (11.4%). A comparison with existing 30-m mangrove products showed noticeable disagreement, indicating the necessity for generating mangrove extent product with 10-m resolution. This study demonstrates the significant potential of using Sentinel-1 and Sentinel-2 images to produce an accurate and high-resolution mangrove forest map with Google Earth Engine (GEE). The mangrove forest map is expected to provide critical information to conservation managers, scientists, and other stakeholders in monitoring the dynamics of the mangrove forest.

scholarly journals GF-5 Hyperspectral Data for Species Mapping of Mangrove in Mai Po, Hong Kong

2020 ◽  
Vol 12 (4) ◽  
pp. 656 ◽  
Author(s):  
Luoma Wan ◽  
Yinyi Lin ◽  
Hongsheng Zhang ◽  
Feng Wang ◽  
Mingfeng Liu ◽  
...  
Keyword(s):  
Hong Kong ◽  
Spectral Resolution ◽  
Hyperspectral Data ◽  
Support Vector ◽  
Species Discrimination ◽  
Infrared Range ◽  
Landsat 8 ◽  
Mangrove Species ◽  
Spectral Bands ◽  
Species Mapping

Hyperspectral data has been widely used in species discrimination of plants with rich spectral information in hundreds of spectral bands, while the availability of hyperspectral data has hindered its applications in many specific cases. The successful operation of the Chinese satellite, Gaofen-5 (GF-5), provides potentially promising new hyperspectral dataset with 330 spectral bands in visible and near infrared range. Therefore, there is much demand for assessing the effectiveness and superiority of GF-5 hyperspectral data in plants species mapping, particularly mangrove species mapping, to better support the efficient mangrove management. In this study, mangrove forest in Mai Po Nature Reserve (MPNR), Hong Kong was selected as the study area. Four dominant native mangrove species were investigated in this study according to the field surveys. Two machine learning methods, Random Forests and Support Vector Machines, were employed to classify mangrove species with Landsat 8, Simulated Hyperion and GF-5 data sets. The results showed that 97 more bands of GF-5 over Hyperion brought a higher over accuracy of 87.12%, in comparison with 86.82% from Hyperion and 73.89% from Landsat 8. The higher spectral resolution of 5 nm in GF-5 was identified as making the major contribution, especially for the mapping of Aegiceras corniculatum. Therefore, GF-5 is likely to improve the classification accuracy of mangrove species mapping via enhancing spectral resolution and thus has promising potential to improve mangrove monitoring at species level to support mangrove management.

scholarly journals ESTIMASI BIOMASSA PERMUKAAN DAN STOK KARBON PADA TEGAKAN POHON Avicennia marina DAN Rhizophora mucronata DI PERAIRAN PESISIR OEBELO KABUPATEN KUPANG

2016 ◽  
Vol 16 (2) ◽  
pp. 163 ◽  
Author(s):  
Glucklich Manafe ◽  
Michael Riwu Kaho ◽  
Fonny Risamasu
Keyword(s):  
Coastal Area ◽  
Forest Floor ◽  
Mangrove Forest ◽  
Co2 Sequestration ◽  
Avicennia Marina ◽  
Research Data ◽  
Nursery Ground ◽  
Above Ground Biomass ◽  
Mangrove Species ◽  
Ground Biomass

Mangrove forest has an important function for living thing especially in the ocean and coastal area. Besides as feeding and nursery ground, mangrove forest is also has a function as carbon sinker. The utilizing of mangrove forest as a corbon sinker is one of ways to reduce CO2 in atmosphere. Mangrove forest in Oebelo village has a capability to utilize as carbon sinker. The aim of this research was to estimate above ground biomass and carbon reserve from two mangrove species Avicennia marina and Rhizopora mucronata in coastal area of Oebelo Village. In this research data was collected from diameter breast high and litter from forest floor. Alometric was used to estimate the above ground biomass. After data collected, analysis would continue with t test to know the different between these two species.The result showed A. marina and R. mucronata were different, the highest biomass, carbon reserve and CO2 sequestration were in A.marina respectively 118.80 Mg.ha-1, 54.65 Mg.ha-1, 200.37 Mg.ha-1 and R. mucronata respectively 28.90 Mg.ha-1, 13.30 Mg.ha-1, 48.75 Mg.ha-1. The result for litter biomass and carbon reserve showed there was no different between these tow species.

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