Detecting changes and health status of mangrove forest in Achara estuary, Maraharashtra using remote sensing and GIS

Mangrove forests protect the Western coast of Maharashtra from natural disasters striking from seaward and riverside. The quantity and quality of mangroves were influenced by the morphological and hydraulic characteristics of estuaries. The study aims to identify the Spatio-temporal changes that took place in the mangrove forest of Achara estuary in the last four decades since 1989. It also highlights the zonal horizontal distribution of mangrove land from its mouths to the head of the estuary. Most of the mangroves concentrate in the zone that comprises the area of 1-3 km from the mouth. A gain of 39.17% of the mangrove area shows the growth of mangroves in the study area during this period. NDVI value, which ranges from 0.123 to 0.560, acknowledged the dense and healthy status of mangroves in Achara estuary

Modeling the Change of Mangrove Forests in Irrawaddy Delta, South Myanmar

Mangrove forests distributed along the coastal areas and river deltas in tropical and subtropical regions provide fundamental ecological services and habitats for a variety of wildlife species. Because of the conversion of mangrove forests to agricultural lands, the dramatic decline of mangrove forests in Irrawaddy Delta, South Myanmar during the past 30 years has been noticed and caused environment impacts, including habitat loss, reduction of biodiversity, and the increase of coastal erosion. This study firstly aims to investigate the changes of mangrove forests over the region of Irrawaddy Delta, using Landsat imageries during the periods of 1989 to 2014. Second, a land cover modeling tool, Probabilistic Landscape Simulation (ProLAMS), is developed and applied for modeling and predicting the change of mangrove forests. Specifically, ProLAMS adopts logistic regression analysis and cellular automata to assess the likelihood of future mangrove forest distribution. Two major findings are: (1) from 1989 to 2014, about 26.7% decline of mangrove forest has been detected; (2) ProLAMS predicts 16.8% decline of mangrove area from 2014 to 2030. In sum, this study suggests that satellite imagery and the proposed model can provide the prediction of future scenarios for mangrove forests. We expect this approach can be useful and applicable for other regions to assist ecosystem conservation activity

Changes Detection of Mangrove Ecosystembased on Obia Method in Liong River, Bengkalis Riau Province

Status of mangrove ecosystem on Liong River, Bengkalis Island, Riau Province, is currently in a condition that tends to get a stressed doe to 60% of indigenous people living around mangroves are loggers. Series Landsat is used as recording data to map the mangrove and to see the changes in the region. This study aims to map changes in mangrove ecosystems from 1990 - 2017 using the OBIA method. The field observation was done using Unmanned Aerial Vehicle (UAV). The results showed that mangrove area has decreased every year. It was caused by anthropogenic and natural factors. Approximately 4.2% of mangrove decrease from 1990 to 2017 and mangrove highest exploitation occurred in 2007 with a decline of 31.5%

PEMBERDAYAAN MASYARAKAT DUSUN PEJEM BANGKA DALAM MENGATASI LIMBAH TAMBAK UDANG MELALUI REHABILITASI LINGKUNGAN KAWASAN WISATA PESISIR BERBASIS ECO-DIGITOURISM

Pemberdayaan masyarakat Dusun Pejem melalui rehabilitasi lingkungan kawasan wisata wilayah pesisir Kabupaten Bangka berbasis eco-digitourism bertujuan untuk mengatasi permasalahan tingginya pencemaran bahan organik yang merusak ekosistem pesisir akibat aktivitas tambak udang Vaname (Litopenaeus vannamei). PkM ini memfasilitasi masyarakat untuk mendapatkan pengetahuan dan keterampilan dalam mengatasi dan mengantisipasi permasalahan yang terjadi di lingkungan Dusun Pejem akibat dari tambak udang. Metode PkM menggunakan mixed method (observasi, diskusi dan praktik). Kegiatan dilaksanakan pada bulan Juni - Agustus 2022 dengan jumlah peserta sebanyak 50 orang terdiri atas masyarakat, karang taruna dan pokdarwis Dusun Pejem. Berdasarkan hasil akhir nilai evaluasi dari kegiatan PkM diketahui masyarakat mengalami peningkatan aspek pengetahuan, sikap dan keterampilan dengan rerata keseluruhan nilai 86,1 yang berada pada kategori amat baik (2%), cukup baik (4%) dan baik (94%). Hasil tersebut menunjukkan bahwa masyarakat Dusun Pejem sudah mampu untuk mengatasi berbagai permasalahan yang dihadapi seperti upaya rehabilitasi alih fungsi lahan melalui cara penanaman mangrove, jambu mete dan cemara laut di wilayah pesisir (tepat di belakang area aktivitas tambak udang). Selain itu, masyarakat dapat membuat obat nyamuk berbahan serai yang banyak ditemukan di pemukiman masyarakat sekitar sebagai upaya untuk mencegah malaria dan demam berdarah akibat aktivitas tambak udang. Pokdarwis dan karang taruna dapat mengoperasikan website dan aplikasi Eco-Digitourism sebagai media untuk mengenalkan wisata, hasil olah laut dari masyarakat wilayah pesisir dan potensi SDA seperti pantai dan hamparan batu metamorf secara nasional bahkan global

PEMBERDAYAAN MASYARAKAT WILAYAH PESISIR DALAM MENGATASI LIMBAH TAMBAK UDANG MELALUI REHABILITASI LINGKUNGAN

Abstrak: Maraknya aktivitas tambak udang Vaname (Litopenaeus vannamei) di wilayah pesisir lokasi mitra berdampak secara langsung bagi masyarakat sekitar. Dampak yang dirasakan nelayan adalah berkurangnya hasil tangkap laut dan hasil olah laut yang biasanya untuk konsumsi dan dijual serta banyak masyarakat terpapar malaria dan demam berdarah. Tujuan pengabdian dilakukan untuk meningkatkan pengetahuan dan kemampuan masyarakat dalam menjaga keseimbangan ekosistem di lingkungan wilayah pesisir yang terdampak dari aktivitas tambak udang. Jumlah peserta yang terlibat sebanyak 50 orang dari masyarakat desa Gunung Pelawan, masyarakat dusun Pejem, pokdarwis, kumpulan PKK dan karang taruna. Pelaksanaan dari bulan Mei-September 2022. Metode yang digunakan adalah sosialisasi cara memanfaatkan mangrove dan untuk meniminalisir terpaparnya malaria dan demam berdarah serta menerapkan metode praktik cara hitung jarak tanam dan penanaman mangrove, jambu mete dan cemara laut. Hasil kegiatan menunjukkan peningkatan pada aspek pengetahuan, sikap dan keterampilan dengan rerata 86 yang berada pada kategori amat baik 2%, cukup 4% dan baik 94% serta masyarakat menilai kepuasan terhadap PkM sebesar 90%.Abstract: The Litopenaeus vannamei ponds' rife activity in the coastal regions of partner locations has a direct influence on the community and fishermen. The impact is decrease in marine catches and product for consumption and sale, dengue disease and malaria are spread widely. The service's goal is to maintain the ecological balance of the coastal region to optimizing recover aquatic species with economic worth. There were 50 participants, including members of the women's, youth, and pokdarwis organizations and local people. Service implementation from May to September 2022. The strategy is to spread knowledge on how to utilize mangroves while reducing risk of contracting dengue and malaria. Furthermore, there are useful techniques for mangrove, cashew, and sea pine planting as well as plant spacing calculations. The activities produced an average score of 86, of which 2% fell into the excellent category, 4% into the moderate category, 94% into the good category and assessment of service satisfaction by 90%

Klasifikasi Mangrove Berbasis Objek dan Piksel Menggunakan Citra Sentinel-2b di Sungai Liong, Bengkalis, Provinsi Riau

Penelitian pemetaan mangrove di Sungai Liong, Bengkalis Provinsi Riau sangat terbatas, sehingga ketersediaan data spasial di wilayah ini masih sangat terbatas. Pemanfaatan citra satelit dapat dijadikan alternatif dalam menyediakan data spasial secara efektif dan efesien. Penelitian ini bertujuan untuk memetakan mangrove sampai tingkat komunitas menggunakan citra sentinel 2B dengan metode klasifikasi berbasis objek/OBIA dan membandingkannya dengan teknik klasifikasi berbasis piksel. Algoritma yang digunakan pada penelitian ini adalah support vector machine (SVM). Pengembangan skema klasifikasi mangrove pada penelitian ini di bagi menjadi 2 level, yaitu kelas penutup lahan di sekitar mangrove dan kelas komunitas mangrove. Data yang digunakan untuk klasifikasi kelas penutup lahan adalah data foto udara yang diperoleh dengan menggunakan pesawat tanpa awak (unmanned aerial vehicle/UAV) dan untuk klasifikasi komunitas menggunakan data transek tahun 2013. Akurasi keseluruhan (OA) yang diperoleh untuk klafikasi penutup lahan mangrove dengan kedua teknik klasifikasi berbasis objek dan piksel berturut-turut adalah 78,7% dan 70,9%. Sedangkan akurasi keseluruhan (OA) untuk klasifikasi komunitas mangrove berbasis objek dan piksel berutru-turut yaitu 76,6% dan 75,0%. Sekitar 7,8% peningkatan akurasi pemetaan penutup lahan dan sekitar 1,6% peningkatan akurasi pemetaan komunitas mangrove yang diperoleh dengan metode klasifikasi berbasis objek

KLASIFIKASI MANGROVE BERBASIS OBJEK DAN PIKSEL MENGGUNAKAN CITRA SENTINEL-2B DI SUNGAI LIONG, BENGKALIS, PROVINSI RIAU

ABSTRAK Penelitian pemetaan mangrove di Sungai Liong, Bengkalis Provinsi Riau sangat terbatas, sehingga ketersediaan data spasial di wilayah ini masih sangat terbatas. Pemanfaatan citra satelit dapat dijadikan alternatif dalam menyediakan data spasial secara efektif dan efesien. Penelitian ini bertujuan untuk memetakan mangrove sampai tingkat komunitas menggunakan citra sentinel 2B dengan metode klasifikasi berbasis objek/OBIA dan membandingkannya dengan teknik klasifikasi berbasis piksel. Algoritma yang digunakan pada penelitian ini adalah support vector machine (SVM). Pengembangan skema klasifikasi mangrove pada penelitian ini di bagi menjadi 2 level, yaitu kelas penutup lahan di sekitar mangrove dan kelas komunitas mangrove. Data yang digunakan untuk klasifikasi kelas penutup lahan adalah data foto udara yang diperoleh dengan menggunakan pesawat tanpa awak (unmanned aerial vehicle/UAV) dan untuk klasifikasi komunitas menggunakan data transek tahun 2013. Akurasi keseluruhan  (OA) yang diperoleh untuk klafikasi penutup lahan mangrove dengan kedua teknik klasifikasi berbasis objek dan piksel berturut-turut adalah 78,7% dan 70,9%. Sedangkan akurasi keseluruhan (OA) untuk klasifikasi komunitas mangrove berbasis objek dan piksel berutru-turut yaitu 76,6% dan 75,0%. Sekitar 7,8% peningkatan akurasi pemetaan penutup lahan dan sekitar 1,6% peningkatan akurasi pemetaan komunitas mangrove yang diperoleh dengan metode klasifikasi berbasis objek. ABSTRACTResearch on mangrove mapping at the Liong River Bengkalis Riau Province was very limited, therefore the spatial data availability of mangrove in Liong River is also very limited. The use of satellite remote sensing to map mangrove has become widespread as it can provide accurate, effecient, and repeatable assessments. The purposed of this study was to map mangrove at the community level using sentinel 2B imagery based on object-based classification method (OBIA) and it compared pixel-based classification at Liong River, Bengkalis, Riau Provinc. This study was used support vector machine (SVM) algorithm. The scheme classification use is that land cover and mangrove community. The classification data of land cover was collected using unmanned aerial vehicle (UAV) and community mangrove was using transect data of 2013. The result of land cover classification and community mangrove indicated that object-based classification technique was better than pixel-based classification. The highest an overall accuracy of land cover is 78.7% versus 70.9%, whereas mangrove community is 76.6 versus 75.0%. Approximately 7.8% increase in accuracy can be achieved by object-based method of classification for land cover and 1.6% for mangrove community

Effects of nesting waterbirds on nutrient levels in mangroves, Gulf de Fonseca, Honduras

Mangroves provide numerous ecosystem services, including biodiversity values such as nesting sites for piscivorous waterbirds. High concentrations of pisicivoirous birds are hypothesized to affect ecosystem dynamics, yet few studies have examined their effects in mangroves. We examined the effects of nutrient enrichment by colonial waterbirds at a mangrove rookery in the Gulf of Fonseca, Honduras. We compared macronutrient levels in the vegetation and soils between two sites — a small island that hosted large numbers of roosting waterbirds and a nearby control site with little evidence of waterbird activity. Nest density at the rookery was 1721 ± 469 nests ha⁻¹. Mangrove community structure and ecosystem carbon stocks were quantified by measuring above and belowground biomass, downed wood, and soil carbon. The nutrient input via bird guano deposition was quantified at each site. Rookery birds deposited 7.2 ± 3.4 g m⁻² day⁻¹ guano dry weight. This large nutrient influx contributed to substantially higher concentrations of biologically important nutrients in the soil and mangrove leaves. These results suggest that colonial waterbirds may significantly impact mangrove ecology and productivity at local scales. Further research is needed to understand the effects of avian delivered nutrients on mangrove growth rates, nutrient export to adjacent waters, invertebrate communities, and mangrove associated fisheries

Projecting Climate and Land Use Change Impacts on Actual Evapotranspiration for the Narmada River Basin in Central India in the Future

Assessment of actual evapotranspiration (ET) is essential as it controls the exchange of water and heat energy between the atmosphere and land surface. ET also influences the available water resources and assists in the crop water assessment in agricultural areas. This study involves the assessment of spatial distribution of seasonal and annual ET using Surface Energy Balance Algorithm for Land (SEBAL) and provides an estimation of future changes in ET due to land use and climate change for a portion of the Narmada river basin in Central India. Climate change effects on future ET are assessed using the ACCESS1-0 model of CMIP5. A Markov Chain model estimated future land use based on the probability of changes in the past. The ET analysis is carried out for the years 2009-2011. The results indicate variation in the seasonal ET with the changed land use. High ET is observed over forest areas and crop lands, but ET decreases over crop lands after harvest. The overall annual ET is high over water bodies and forest areas. ET is high in the premonsoon season over the water bodies and decreases in the winter. Future ET in the 2020s, 2030s, 2040s, and 2050s is shown with respect to land use and climate changes that project a gradual decrease due to the constant removal of the forest areas. The lowest ET is projected in 2050. Individual impact of land use change projects decreases in ET from 1990 to 2050, while climate change effect projects increases in ET in the future due to rises in temperature. However, the combined impacts of land use and climate changes indicate a decrease in ET in the future