ALBERT

Description: An accurate assessment of evapotranspiration (ET) is crucially needed at the basin scale for studying the hydrological processes and water balance especially from upstream to downstream. In the mountains, this term is poorly understood because of various challenges, including the vegetation complexity, plant diversity, lack of available data and because the in situ direct measurement of ET is difficult in complex terrain. The main objective of this work was to investigate the potential of a Two-Source-Energy-Balance model (TSEB) driven by the Landsat and MODIS data for estimating ET over a complex mountain region. The complexity is associated with the type of the vegetation canopy as well as the changes in topography. For validating purposes, a large-aperture scintillometer (LAS) was set up over a heterogeneous transect of about 1.4 km to measure sensible (H) and latent heat (LE) fluxes. Additionally, two towers of eddy covariance (EC) systems were installed along the LAS transect. First, the model was tested at the local scale against the EC measurements using multi-scale remote sensing (MODIS and Landsat) inputs at the satellite overpasses. The obtained averaged values of the root mean square error (RMSE) and correlation coefficient (R) were about 72.4 Wm−2 and 0.79 and 82.0 Wm−2 and 0.52 for Landsat and MODIS data, respectively. Secondly, the potential of the TSEB model for evaluating the latent heat fluxes at large scale was investigated by aggregating the derived parameters from both satellites based on the LAS footprint. As for the local scale, the comparison of the latent heat fluxes simulated by TSEB driven by Landsat data performed well against those measured by the LAS (R = 0.69, RMSE = 68.0 Wm−2), while slightly more scattering was observed when MODIS products were used (R = 0.38, RMSE = 99.8 Wm−2). Based on the obtained results, it can be concluded that (1) the TSEB model can be fairly used to estimate the evapotranspiration over the mountain regions; and (2) medium- to high-resolution inputs are a better option than coarse-resolution products for describing this kind of complex terrain.

Description: Public transportation serves people with mobility and accessibility to workplaces, health facilities, community resources, and recreational areas across the country. Development in the application of Geographical Information Systems (GIS) to transportation problems represents one of the most important areas of GIS-technology today. To show the importance of GIS network analysis, this paper highlights the determination of the optimal path between two or more destinations based on multi-mode concepts. The abstract connector is introduced in this research as an approach to integrate urban public transportation in Kuala Lumpur, Malaysia including facilities such as Light Rapid Transit (LRT), Keretapi Tanah Melayu (KTM) Komuter, Express Rail Link (ERL), KL Monorail, road driving as well as pedestrian modes into a single intelligent data model. To assist such analysis, ArcGIS's Network Analyst functions are used whereby the final output includes the total distance, total travelled tim...

Description: The wide-ranging evolution of remote sensing technology has offered a promising application to the hydrographic surveying, the Satellite-Derived Bathymetry (SDB). SDB is a contemporary acquisition technique which derives bathymetric data from multispectral satellite imagery for various hydrographic purposes. The introduction and availability of the chargeless Sentinel-2A multispectral satellite data in the region, has inspired the National Hydrographic Centre (NHC) and Universiti Teknologi Malaysia (UTM) to collaborate in assessing the level of accuracy provided by Sentinel-2A imageries as a data sources for shallow water hydrographic mapping. The assessment is concentrating on both empirical algorithm methods, Lyzenga and Stumpf models in two different seabed topology conditions. Both Lyzenga and Stumpf model produced almost identical results for the area with normal gradient seabed. Conversely, for the rough and irregular seabed surface, results from Lyzenga model was much bet...

Description: Some of the factors that causing abuse of alcohol by adolescents are the descendants, families influences, friends influence, ethnicities, and personal issues. Today’s teenage problems are complex and worrying. This is indicated by the low knowledge of adolescents about the dangers of alcohol for health. The importance of knowledge about the danger of alcohol for health is needed. Therefore, adolescents need to get enough information to know how dangerous alcohol. Peer group is a method of delivering information through peers that effective to use in adolescents. The study aims to determine the effect of health education with peer group approach toward adolescents’ knowledge about the dangers of alcohol for health in the village of Wungkolo, District of South Wawonii, Konawe Islands. The study did not use the Pre-Experiment with the control group. The sampling technique is purposive sampling , with 17 people as the samples. The results of statistical test pair t-test obtai...

Description: Spatio-temporal measurement and prediction of urban growth patterns are the main challenges that face researchers, planners, decision makers, and local authorities when building a realistic sustainable urban planning model. This study aims to apply spatio-temporal data, methods, and models to generate a realistic measurement and prediction of the urban growth issue. Three Landsat TM5 and OLI images of 1997, 2007, and 2017 were used to create urban growth maps. Land-use maps were used to measure change in urban area during the periods 1997 to 2017. A CA-Markov model was used to predict the urban growth trends of 2027 and 2037. The results of the study confirm that urban area increased and continued to cover most of the city area of Putrajaya. The urban development process has greatly affected the Putrajaya green lands between 1997 and 2017. This impact is expected to increase in the future based on the prediction results, which in turn will lead to an increased need for new polic...

Description: Many geophysical methods at various scales have been applied to understand the internal structure beneath Merapi volcano and its magmatic process. As part of the DOMERAPI project, a seismic experiment was conducted from October 2013 to mid April 2015 in order to determine the deep magma source beneath the volcano through seismic travel-time tomography. The earthquake events were identified and picked manually and carefully to determine the hypocenters. They were then relocated to get precise hypocenter locations before running the seismic tomographic imaging. The data from the BMKG network from the same period of time as mentioned above were also incorporated to minimize azimuthal gap, because the majority of events occurred outside the DOMERAPI network. The checkerboard resolution test result depicts that the area around the network can be well resolved. Compared to previous studies, our result shows a higher resolution at shallow depths, i.e., less than 35 km and a low velocit...

Description: At present, literature data on density of nanofluids are still scarce and controversial. In this paper, density data for nanofluids formed by water, as a base fluid, and solid nanoparticles of two different materials are presented. Density was measured by using a Density Meter DA-130N from Kyoto Electronics. The obtain result is compared with previous models and found incompatible for temperature variations.

Description: It is well-documented in the visible and near-infrared reflectance spectroscopy (VNIRS) studies that soil moisture content (SMC) negatively affects the prediction accuracy of soil attributes. This work was undertaken to remove the negative effect of SMC on the on-line prediction of soil organic carbon (SOC). A mobile VNIR spectrophotometer with a spectral range of 305–1700 nm and spectral resolution of 1 nm (CompactSpec, Tec5 Technology, Germany) was used for the spectral measurements at four farms in Flanders, Belgium. A total of 381 fresh soil samples were collected and divided into a calibration set (264) and a validation set (117). The validation samples were processed (air-dried and grind) and scanned with the same spectrophotometer in the laboratory. Three SMC correction methods, namely, external parameter orthogonalization (EPO), piecewise direct standardization (PDS), and orthogonal signal correction (OSC) were used to correct the on-line fresh spectra based-on its corresponding laboratory spectra. Then, the Cubist machine learning method was used to develop calibration models of SOC using the on-line spectra (after correction) of the calibration set. Results indicated that the EPO-Cubist outperformed the PDS-Cubist and the OSC-Cubist, with considerable improvements in the prediction results of SOC (coefficient of determination (R2) = 0.76, ratio of performance to deviation (RPD) = 2.08, and root mean square error of prediction (RMSEP) = 0.12%), compared with the corresponding uncorrected on-line spectra (R2 = 0.55, RPD = 1.24, and RMSEP = 0.20%). It can be concluded that SOC can be accurately predicted on-line using the Cubist machine learning method, after removing the negative effect of SMC with the EPO method.

Description: This paper proposes a novel method to estimate the lateral displacement of high-rise structures under wind loads. The coefficient β(x) is firstly derived, reflecting the relation between the structural lateral dynamic displacement and the inclination angle at the height x of a structure. If the angle is small, it is the ratio between the structural fundamental mode shape and its first-order derivative without influence of external loads. Several dynamic experiments of structures are performed based on a laser remote sensing vibrometer and an inclinometer, which shows that the fundamental mode is dominated in the structural displacement response under different types of excitations. Once the coefficient β(x) is curve-fitted by measuring both the structural lateral dynamic displacement and the inclination angle synchronously, the real-time structural lateral displacement under operational conditions is estimated by multiplying the coefficient β(x) with the inclination angle. The advantage of the proposed method is that the coefficient β(x) can be identified by lateral dynamic displacement measured in high resolution by the remote sensing vibrometer, which is useful to reconstruct the displacement accurately by the inclination angle under operational conditions.

Description: Thermal and hyperspectral proximal disease sensing are valuable tools towards increasing pesticide use efficiency. However, some practical aspects of the implementation of these sensors remain poorly understood. We studied an optimal measurement setup combining both sensors for disease detection in leek and potato. This was achieved by optimising the signal-to-noise ratio (SNR) based on the height of measurement above the crop canopy, off-zenith camera angle and exposure time (ET) of the sensor. Our results indicated a clear increase in SNR with increasing ET for potato. Taking into account practical constraints, the suggested setup for a hyperspectral sensor in our experiment involves (for both leek and potato) an off-zenith angle of 17°, height of 30 cm above crop canopy and ET of 1 ms, which differs from the optimal setup of the same sensor for wheat. Artificial light proved important to counteract the effect of cloud cover on hyperspectral measurements. The interference of these lamps with thermal measurements was minimal for a young leek crop but increased in older leek and after long exposure. These results indicate the importance of optimising the setup before measurements, for each type of crop.