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Internal wave adalah gelombang laut yang terjadi di lapisan dalam di perairan laut dangkal dan dalam, di mana kemunculannya hanya dapat terjadi jika kolom air terstratifikasi akibat adanya perbedaan densitas massa air. Penelitian ini bertujuan untuk mendeteksi peristiwa internal wave, serta mengukur nilai hambur balik akustik dari internal wave yang terjadi di Selat Lombok. Data yang digunakan adalah hasil pengukuran instrumen broadband echosounder SIMRAD EK80 frekuensi 200 kHz tipe pulsa continuous wave (CW) dengan data pendukung elevasi muka air, suhu, salinitas, dan densitas dari Conductivity Temperature Depth (CTD) “Yoyo” selama 24 jam. Nilai hambur balik didapatkan dengan analisis menggunakan perangkat lunak Sonar5-Pro. Echogram menunjukkan adanya pembentukan nonlinear internal wave disertai dengan adanya turbulensi yang terjadi pada saat gelombang pasang membawa massa air dengan densitas berbeda melewati topografi kasar di Selat Lombok. Nilai backscatter hasil segmentasi berentang dari -75 dB sampai -59 dB.

Radar is one of remote sensing technology which utilizes active electromagnetic energy and are able to provide information about the characteristics of forest stand. This study utilized JERS-1 and ERS-1 radar images to analyze the relationship between the radar backscatter and forest stand characteristics such as Diameter Breast Height (DBH), basal area, and canopy cover. This research was conducted in Jambi Province, Bungo Tebo District, Sumatra, Indonesia. The research site covered the forest concession, Suku Anak Dalam, the area adjacent to Pelepat and Batang Tebo River, and Kuamang Kuning village. Gamma Map Filter with 7 x 7 window size was applied to reduce speckle noise of the SAR images (ERS-1 and JERS-1). This study found out the positive significant correlation between basal area and DBH with JERS-1 radar backscatter (i.e., r = 0.75 and r = 0.70), while ERS-1 radar backscatter has correlation (r = 0.64) with the canopy cover.

The accurate information derived from high accuracy of remote sensing imagery analyses coupled with field observation data are required to develop a sound forest management. The study is mainly emphasized on assessment of the capabilities of remote sensing imageries to identify ecosystem types within the transitional ecosystem. Since, the predominant transition ecosystems found within the study area were secondary forest, rubber jungle, rubber, oil palm plantation, and also other land cover such as mixed plantation and shrubs, therefore, the models developed were focused for those ecosystem types. Prior to any further analysis, this study was initiated to develop the biomass estimation model using 50 m resolution of ALOS PALSAR image in transition ecosystem, Jambi Province. Biomass models were developed by analyzing the relationship between backscatter magnitude and field biomass. Backscatter magnitude from 1 polarization images, namely HH, HV, and one additional band of ratio of HH/HV were analyzed simultaneously with field biomass. The best models established are AGB = 42,069 exp (0.510 HV) and AGB = 1,610 exp (-0.02 HV²) with R² of 52.3% and 50,8%, respectively. The models are then used to map out the biomass distribution within the transition ecosystem and to identify the factors affecting the magnitude of biomass content for all transition ecosystem types.