Landsat 8 Observation of the Internal Solitary Waves in the Lombok Strait

Landsat  8,  Landsat  Data  Continuity  Mission  (LDCM)  satellite,  was  launched  on  11 February 2013 with Operation Land Imager (OLI) sensors. Tis sensor has better radiometric performance than the previous mission, which is quantized in the 12-bit dynamic range due to an increase in the signal-to-noise (SNR) ratio. In this analysis, the spatio-temporal distribution of the propagation of the internal solitary wave (ISW) in the Lombok Strait was extracted from the Landsat 8 images described for the first time.  Tere were 14 ISW events studied for period 2014  -  2015  using  Landsat  8.  Te  manifestations  of  ISW  recorded  on  Landsat  8  images  were then extracted using digitization method to investigate and measure several parameters and ISW distribution in the Lombok Strait. Te estimation results of the average ISW phase velocity in this study are 2.05 ms-1 with the direction of propagation heading north at an average angle of 19.08°. Tis study has shown that Landsat 8 can be used to monitor and analyze several internal wave parameters in the ocean

ESTIMATION OF TIDAL ENERGY DISSIPATION AND DIAPYCNAL DIFFUSIVITY IN THE INDONESIAN SEAS

The Indonesian Seas separating the Indian Ocean from the West Pacific Oceanare representative regions of strong tidal mixing in the world oceans. In the present study,we first carry out numerical simulation of the barotropic tidal elevation field in theIndonesian Seas using horizontally two-dimensional primitive equation model. It is foundthat, to reproduce realistic tidal elevations in the Indonesian Seas, the energy lost by theincoming barotropic tides to internal waves within the Indonesian seas should be taken intoaccount. The numerical experiments show that the model predicted tidal elevations in theIndonesian Seas best fit the observed data when we take into account the baroclinic energyconversion in the Indonesian Seas ~86.1 GW for the M2 tidal constituent and ~134.6 GWfor the major four tidal constituents (M2, S2, K1, O1). For this baroclinic energy conversion,the value of Kñ averaged within the eastern area (Halmahera, Seram, Banda and MalukuSeas), the western area (Makassar and Flores Seas), and the southern area (Lombok Straitand Timor Passage) are estimated to be ~23 × 10-4 m2s-1, ~5 × 10-4 m2s-1, and ~10× 10-4m2s-1, respectively. This value is about 1 order of magnitude more than assumed for theIndonesian Seas in previous ocean general circulation models. We offer this study as awarning against using diapycnal diffusivity just as a tuning parameter to reproduce largescalephenomena

RELATIONSHIP AMONG MANGROVE STAND STRUCTURE PARAMETERS IN ESTIMATING THE COMMUNITY SCALE OF ABOVEGROUND CARBON STOCK

Mangrove merupakan ekosistem pesisir yang memiliki kemampuan sangat baik dalam menyerap dan menyimpan karbon. Struktur tegakan mangrove memberikan kontribusi signifikan terhadap estimasi simpanan karbon yang umumnya tergambarkan pada persamaan alometrik dalam skala individu. Penelitian simpanan karbon atas permukaan tanah (abovegroundada komunitas mangrove telah dilakukan di mangrove Teluk Benoa. Penelitian ini bertujuan untuk membangun model dalam mengestimasi simpanan karbon aboveground dari beberapa parameter struktur tegakan mangrove. Metode stratified purposive sampling digunakan dalam penentuan sebaran titik penelitian. Sebanyak tiga zona (1–3) diidentifikasi berdasarkan interpretasi analisis mRE-SR (modified red edge-simple ratio) dan jenis mangrove yang mendominasi. Estimasi simpanan karbon aboveground diperoleh dengan metode non-destructive menggunakan persamaan common allometric. Hasil penelitian menunjukkan struktur tegakan mangrove zona 1 cenderung berbeda signifikan dengan zona lainnya. Secara keseluruhan, rata-rata simpanan karbon aboveground sebesar 193,45±34,88 ton C/ha. Simpanan karbon aboveground tertinggi ditemukan pada zona 1 yang didominasi jenis Sonneratia alba. Analisis regresi linear dan Akaike’s Information Criterion (AIC) menunjukkan bahwa kombinasi dari tutupan kanopi, kerapatan pohon, kerapatan pancang dan diameter pohon menjadi model terbaik dalam mengestimasi simpanan karbon pada skala komunitas. Model kombinasi ini memiliki nilai koefisien regresi tertinggi dan nilai root mean squared error (RMSE) terendah dibandingkan dengan model lainnya. Hasil penelitian diharapkan dapat digunakan dalam mengestimasi simpanan karbon secara lebih efisien dan akurat dalam skala komunitas.Mangrove is one of coastal ecosystem which has a major role to sequastrate and store carbon. Mangrove stand structure delivers a significant contribution for estimating biomass carbon stock through individual scale allometric equations. On the other hand, the aboveground carbon research on the community scale was conducted in Teluk Benoa. The study aimed to establish a model for estimating mangrove aboveground carbon stock from the multiple variables of mangrove stand structure. A stratified purposive sampling method was applied for distributing quadratic samples. Three mangrove zones (1–3) were identified using mRE-SR (modified red edge-simple ratio) interpretation based on mangrove species domination. A common allometric equation was applied for estimating aboveground carbon stock. The result showed that mangrove stand structure in zone 1 was significantly different to other zones. Aboveground carbon stock was 193.45±34.88 tons C/ha on entire sites. It was found highest in zone 1 which was dominated by Sonneratia alba. The linear regression and Akaike’s Information Criterion (AIC) analysis showed that the combination of canopy cover, tree density, sapling density and tree diameter became the best model in estimating carbon stock at the community scale. The multiple model had the highest regression coefficient and the lowest root mean square error (RMSE) value. We expect that the multiple variable model could be more efficient and accurate to estimate aboveground carbon stock on community scale

Investigating El Nino Southern Oscillation as the main driver of forest fire in Kalimantan

Strong El Nino events have been identified as major factors contributing to the forest fire in Indonesia. This is due to El Nino Southern Oscillation (ENSO) variability has a distinct connection with tropical precipitation, mainly in Indonesia. El Nino years are typically drier, while La Nina events generally increase precipitation in Indonesia. Although very strong El Nino events have been connected with massive forest fires, fire continue to occur during the other phases of ENSO: La Nina and normal. Here, the research reports a time series of monthly counted fires in Kalimantan between the period 2001-2020 from MODIS fire hotspot and MODIS Burned Area products. The region is divided into three categories, Primary Intact Forest, Primary Degraded Forest and Outside Forest/ Deforested area. This categorization validates the location of the fire. Our results show that in general wildfires in Kalimantan follow a similar temporal pattern with Oceanic Nino Index (ONI), with several anomalies. If ONI is high, wildfires are more intense and vice versa. The wildfire appears almost every month and increases drastically in June-October of El Nino years. However, the proportion of wildfires in Primary Intact Forest are tiny and insignificant. The primary intact forest fire only appears in July-October and have a different pattern with wildfires in general. In conclusion, wildfires are highly correlated with El Nino but limited in primary intact forests. The fires dominantly appear in the deforested area, about 80%. The rest 20% are in degraded forest and only less than 1% in primary intact forest