Judul: Estimation of Peat Surface Moisture after Peatland Fires in Meranti Island Regency
Abstrak: Kabupaten Kepulauan Meranti didominasi oleh lahan gambut yang mencapai 80% area dengan sejarah kebakaran lahan gambut yang berulang. Hal tersebut dikonfirmasi oleh titik api (hotspots) yang terkonsentrasi pada lahan gambut. Kebakaran hutan dan lahan gambut terkait erat dengan kelembaban permukaan tanah. Penelitian ini bertujuan mengestimasi sebaran area kebakaran hutan dan lahan gambut dan mengestimasi kelembaban permukaan tanah pada lahan gambut sebelum dan sesudah kebakaran dengan studi kasus di Kabupaten Kepulauan Meranti. Pendekatan yang digunakan berdasarkan teknik penginderaan jauh dengan memanfaatkan Google Earth Engine untuk mengolah data citra satelit Sentinel. Areal kebakaran dideteksi dengan indeks Normalized Burn Ratio (NBR) yang diturunkan dari citra Sentinel-2, sedangkan nilai kebasahan permukaan tanah gambut diduga dengan indeks Normalized Difference Water Index (NDWI). Hasil penelitian menunjukkan bahwa kelembaban permukaan tanah gambut keluaran Sentinel-1 berkorelasi kuat dengan kelembaban tanah aktual (RMSE = 0,87, R2 = 97%). Hal ini menunjukkan bahwa hasil keluaran Sentinel-1 dapat digunakan untuk mengestimasi kelembaban permukaan tanah gambut ketika pengukuran langsung tidak tersedia. Hasil analisis menunjukkan bahwa kejadian kebakaran 2018-2020 terjadi secara berulang dan dapat dideteksi dengan NBR. Pasca kebakaran, kelembaban permukaan tanah gambut lebih kering berdasarkan deteksi indeks NDWI. Temuan penelitian ini menunjukkan kegunaan satelit sentinel untuk monitoring kelembaban gambut pada jangkauan yang luas dan area terpencil., Meranti Islands Regency is dominated by peatland, which covers approximately 80% of the area, and has experienced recurrent peat fires. The fires are confirmed by fire hotspots occurrences, which are concentrated on peatlands. Peat fires are closely related to the level of moisture at the peat surface. This study aims to estimate the distribution of burnt areas and to predict the moisture at peat surface with the condition of pre-fire and post-fire events. Meranti peatland was chosen as a study site to test the applicability of Google Earth Engine for assessing peat fires. The approach applied the Google Earth Engine to process Sentinel satellite imagery data from 2018-2021 based on Normalized Burn Ratio (NBR) and Normalized Difference Water Index (NDWI). NBR index was used to detect the burnt area from Sentinel-2 imagery, whereas NDWI was used to predict peat moisture. The results showed that the predicted peat moisture based on Sentinel-1 strongly correlated with actual soil moisture (RMSE = 0.87, R2 = 97%). This suggests that the Sentinel-1 output can be used to estimate peat soil surface moisture when there are no direct measurements at the fields. Also, the findings show that the 2018-2020 fire incidents occurred repeatedly and could be detected with NBR. After the fire, drying peat was prevalent, as detected by the NDWI index. Further, the findings demonstrate the usefulness of sentinel satellites for monitoring peat moisture over a wide range and remote areas.
Keyword: burn severity, hotspot, NBR, NDWI, spatial analysis

Judul: Analysis of Vegetation and Drought Conditions in Peatland following 2015’s Fires in Kepulauan Meranti
Abstrak: Lahan gambut di Indonesia banyak yang mengalami degradasi menjadi lahan tidak produktif. Kerusakan lahan gambut berdampak pada penurunan kualitas ekosistem gambut, penurunan keanekaragaman hayati, peningkatan risiko kebakaran, serta peningkatan emisi gas rumah kaca ke atmosfer. Tujuan dari penelitian ini untuk menganalisis kondisi vegetasi dan kekeringan pada lahan gambut pasca kebakaran hutan dan lahan tahun 2015. Penelitian mengambil kasus kebakaran di Pulau Padang, Kepulauan Meranti, Riau. Penelitian menggunakan data citra satelit Landsat-8 surface reflectance (SR) untuk menentukan indeks vegetasi dan kekeringan yaitu: Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), dan Normalized Multi-band Drought Index (NMDI). Hasil penelitian menunjukkan bahwa NBR merekam wilayah dengan tingkat kebakaran yang tinggi di tahun 2014, 2015, dan 2020. Hal tersebut didukung dengan sebaran vegetasi secara spasial yang ditunjukkan oleh citra NDVI. Nilai rata-rata NDVI yang rendah menunjukkan sebagian besar wilayah kajian merupakan lahan minim vegetasi . Sebagian besar area citra NMDI di lahan kosong menunjukkan kondisi kering dan sangat kering dengan nilai NMDI setiap tahun (2014-2020) yang tinggi. Tahun pre-fire 2019 memiliki cakupan area tertinggi untuk kondisi lahan sangat kering. Meski demikian, laju pertumbuhan vegetasi menunjukkan tren peningkatan setelah periode kebakaran., Most peatlands in Indonesia are degrading into unproductive land. Damage to peatlands decreases the quality of the peat ecosystem, decreasing biodiversity, increasing the risk of fire, and increasing greenhouse gas emissions into the atmosphere. This study aims to analyze the condition of vegetation and drought on peatlands after the 2015 fire in Padang Island, Meranti Islands, Riau. The method was processed by performing Landsat 8 surface reflectance (SR) image data to determine: Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), and Normalized Multi-band Drought Index (NMDI). The results of this study indicate that NBR recorded areas with high fire rates in 2014, 2015, and 2020. Validate by the spatial distribution of vegetation shown by NDVI images. The low average NDVI value indicates that most of the study area is land with minimal vegetation. Most of the NMDI image areas in vacant land show a dry and extreme dry condition with high NMDI values every year (2014-2020). The pre-fire year 2019 had the highest area coverage for extreme dry land conditions. However, the vegetation growth rate showed an increase after the fire period.
Keyword: burn severity, hotspot, plants water content, soil moisture, spatial index

Judul: Optimization of Alginate-Chitosan Microcapsules Formation for Leydig Cells Encapsulation
Abstrak: Hypogonadism is a clinical condition characterized by low concentrations of testosterone. It is caused by malfunction of Leydig cells in producing testosterone. Encapsulation method will protect the transplanted cells from the immune system rejection. The aims of this study was to optimize the formation of microcapsules for Leydig cells encapsulation. The microcapsules were made of alginate and chitosan as the first and the second coating agents, respectively. The result showed that the minimum concentration of alginate was 1.5% (w/v) with a viscosity of 33.8 cPs, resulted spherical microcapsules with diameters of 230-270 µm. The optimum concentration of chitosan as the second coating agent was 0.5% (w/v), resulted spherical microcapsule with mechanical stability in 4 hours. Leydig cells can be trapped inside the capsule with a density that proportional with concentration of cells used in the encapsulation.
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