Seulawah Agam, a stratovolcano located in the Aceh province, Indonesia, has not erupted for a long decade after the last eruption in 1839. Thermal infrared remote sensing has been used to determine the land surface temperature (LST) of the volcano area. However, the application of remotely sensed thermal imagery in identifying the LST of the Seulawah Agam volcano, as a precursor of geothermal energy and eruption hazard, has not been completely monitored. The volcano locates relatively close to residential areas, which is a challenging approach to apply thermal bands in determining geothermal identities. In this research, we assess the LST and vegetation index for the detection of the thermal activity of the mountain. These characteristics were retrieved from Landsat 7 ETM+ and Landsat 8 TIRS/OLI imageries, acquired on 23 April 2004 and 16 March 2015 over the Seulawah Agam area, respectively. The normalized difference vegetation index (NDVI) threshold method for emissivity retrieval and split-window algorithm for land surface temperature (LST) were utilized. The results show that the vegetation index changes moderately over the geothermal area, especially at the residential area and western side of the volcano which is in line with a fault structure of the Seulimeum segment. We calculated the LST from the thermal bands of Landsat images 2004 and 2015 with approximate results are 28 – 35 °C. The spatial distribution of surface temperatures at the mountain derived from the classified image 2015 varies considerably compared with the classified image 2004. The surface temperature and vegetation index changes indicate a thermal activity at the Seulawah Agam volcano. It can be concluded that the Landsat 7 ETM+ and Landsat 8 TIRS/OLI imageries are potentially used to study the thermal status of the Seulawah Agam geothermal area.

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The use of the notorious synthetic dye, rhodamine B, in food and beverage products has been widely reported. This application urges the need to develop an analytical method that can provide reliable rhodamine B data with an easy operational technique. Therefore, this research is aimed to develop an Arduino Uno-based TCS3200 color sensor and study its application to determine rhodamine B levels in syrup. The design of the analytical instrument included TCS3200, an Arduino Uno microcomputer, an Integrated Development Environment (IDE) software, a black box container, and a 24 × 2 matrix display screen, where samples were prepared via absorption using wool thread. With a linear range of 1–20 mg/L, our proposed colorimetric sensor had recoveries of 96.25–110.3%, which was better compared to that was obtained from the UV-vis (81.8–100.6%) method. The detection and quantification limits of the sensor were 2.766 and 8.383 mg/L, respectively. The syrup samples used in this study were purchased from the local stores in Banda Aceh. Based on the proposed TCS3200 color sensor, the highest rhodamine B concentration from the syrup sample was 16.74 mg/L. The t-test analysis in this study revealed that the Rhodamine B levels quantified using the newly developed TCS3200 color sensor were not statistically or significantly different from the UV-Vis spectrophotometer method.

Danau Aneuk Laut berasal dari bekas kepundan gunungapi yang telah mati dan secara bertahap terisi air. Sejak 15 tahun belakangan ini danau mengalami penurunan muka air, hal ini diduga akibat Gempa dan tsunami pada 26 Desembar 2004. Pemantauan penyusutan air danau dilakukan dengan metode penginderaan jauh menggunakan data DEM SRTM dan citra satelit Landsat. DEM SRTM digunakan untuk analisis struktur sesar dan rekahan melalui peta Fault Fracture Density (FFD). Citra satelit landsat digunakan untuk identifikasi sebaran vegetasi menggunakan transformasi Normalized Difference Vegetation Index (NDVI) dan klasifikasi tutupan lahan menggunakan metode Maximum likelhood dari tahun 2001-2017. Berdasarkan peta FFD ditemukan kelurusan tertinggi yaitu danau Aneuk Laot yang memiliki zona permeabel dari struktur geologi sehingga semakin kecil kerapatan struktur maka semakin besar permeabilitasnya. Peta penyusutan air danau dengan menghitung luas permukaan air danau dari periode 2001 -2017 telah mengalami penurunan sebesar 102.600 m². Untuk tahun 2001-2003 mengalami kenaikan sebesar 68700 m² dan pada tahun 2003-2004 mengalami penurunan sebesar -42300 m². Peta sebaran vegetasi di pulau Weh memiliki index vegetasi NDVI maksimum 0,863554 yang artinya memiliki sebaran vegetasi sangat rapat berwarna hijau pekat dan Index vegetasi minimum NDVI sebesar -0,375631 menunjukkan tidak adanya rapat vegetasi berwarna coklat. Aneuk Laot Lake comes from the former crater of a volcano that has died and gradually filled with water. For about 15 years lakes have decreased Lake water level, allegedly caused by earthquake and tsunami on 26 desembar 2004. Monitoring of lake water depreciation is done by remote sensing method using DEM SRTM data and Landsat satellite image. DEM SRTM is used for analysis of fault and fracture structures through the Fault Fracture Density (FFD) map. Landsat satellite imagery was used to identify vegetation distribution using Normalized Difference Vegetation Index (NDVI) transformation and land cover classification using Maximum likelihary method from 2001-2017. Based on the FFD map found the highest alignment of the Aneuk Laot lake that has a permeable zone of geological structure so that the smaller the density of the structure the greater the permeability. Map of the lake's water depreciation by calculating the lake surface area from 2001 -2017 has decreased by 102,600 m². For 2001-2003 increased by 68700 m² and in 2003-2004 decreased by -42300 m². The vegetation distribution map on Weh island has a maximum NDVI vegetation index of 0.863554 having very dense green vegetation density and a minimum vegetation index of NDVI-0.375631 indicating the absence of a brown vegetation meeting. Keywords: AneukLaot lake, DEM SRTM, Landsat, FFD

Remote sensing makes it possible to map potential geothermal site for a large area effectively using thermal infrared. The purpose of the present research is to overlay ground temperature, resistivity and satellite retrieved temperature in identifying geothermal potential site in Jaboi, Sabang-Indonesia. The data of acquisition of the DEM imagery was January 3rd, 2009 and the Landsat 8 imagery is July 18th, 2017. The satellite data were applied to extract the land surface temperature and land classification across. Two supporting data in situ were used to validate the results from remote sensing. First dataset was ground temperature measurements with total 114 points and second dataset was vertical electrical sounding (VES) with total of 51 points. Satellite, VES and ground temperature data were processed and analysed using the Envi 5.3, PCI Geomatica 2016 and ArcMap 10.4. The results from each data were integrated to produce a map shows geothermal potential. Its integration produced four areas which were considered to have high geothermal potential. However, these areas vary in term of the clustering of the features of interest, for example lineament and drainage density of the area, high temperature in the surface area, fault existence and low resistivity subsurface. All the features must take into consideration to rank potential area which has higher potential. Finally, a map of geothermal potential across were successfully created as an insight for future reference. ©2020. CBIORE-IJRED. All rights reserved