Performance of SARAL/AltiKa satellite altimetry mission over the Strait of Malacca and the South China Sea

Satellite altimetry faces challenges when attempting to monitor sea surface heights (SSHs) in coastal zones due to the rapid changes in sea state and land contamination within altimeter footprints. This leads to the lack of high resolution and data quality observations, thus creating a significant gap in the data availability over the coast. A new generation of SARAL/AltiKa satellite altimetry mission with Ka-band promises a significant refinement of coastal altimetry data and provides unprecedented level of ocean SSH data as close as 10 km from the coastline. In this paper, selective passes of SARAL/AltiKa over the Strait of Malacca and the South China Sea were chosen to examine the performance of SSH data quality over the coast, and relatively compared with Jason-2 satellite altimetry mission

Validation and Quality Assessment of Sea Levels from SARAL/ AltiKa Satellite Altimetry over the Marginal Seas at the Southeast Asia

In this study, high resolution (40 Hz) sea levels derived from the advanced SARAL/AltiKa satellite altimetry are validated over the Southeast Asia coastal regions. The parameter of sea level is derived based on three standard retracking algorithms of MLE-4, Ice-1, and Ice-2. The assessments of quantity and quality of the retracked sea levels are conducted to identify the optimum retracker over the study regions, which are the Andaman Sea, the Strait of Malacca, the South China Sea, the Gulf of Thailand, and the Sulu Sea. The quantitative analysis involves the computation of percentage of data availability and the minimum distance of sea level anomaly (SLA) to the coastline. The qualitative analysis involves the absolute validation with tide gauge. In general, AltiKa measurement can get as close as ˜1 km to the coastline with ≥85% data availability. The Ice-1 retracker has shown an excellent performance with percentage of data availability ≥90% and minimum distance as close as 0.9 km to the coastline. In term of quality of the data, 3 out of 6 validation site show that Ice-1 retracker is superior than the other retracker with temporal correlation up to 0.89 and RMS error up to 8 cm

Along-track high resolution sea levels from SARAL/AltiKa satellite altimetry data over the maritime continent

A new generation of satellite altimetry with a high spatial resolution is a very useful tool for providing information about ocean characteristics including the study of sea levels. This paper is concerned on the comparison of sea levels from the newly launched SARAL/AltiKa satellite altimetry data with the data model from the Coriolis Data Centre. The paper focuses over the regions of the Maritime Continent, which includes the Straits of Malacca, the South China Sea, and the Sulu Sea. The statistical analysis is performed over these three seas because they have different coastal characteristics and ocean variabilities, therefore, the quality of the derived sea levels may be varies. The results show that the sea levels from SARAL/Altika generally well-agree to those of Coriolis Data Centre. However, significant differences are observed at certain regions especially at the Strait of Malacca and Banda Sea. The highest correlation is found over the South China Sea while the lowest value is found over the Sulu Sea. The lowest RMSE is observed at Strait of Malacca while the highest value is over the Sulu Sea

Coastal land-use mapping along Johore Straits using Sentinel 1-SAR data with maximizing parameterization of machine learning classification

In tropical regions, cloud cover accounts for a major obstacle to detect the coastal land-use while adopting remote sensing technology. The advent of the latest Sentinel-1 C-band synthetic aperture radar (SAR) satellite provides advantages to collect data in all-weathered conditions. In this study, Sentinel-1 images are processed using Lee filter and GLCM-Mean texture analysis in order to enhance the classification results. Several sets of parameters have been tested and these resulted in the optimum overall accuracy by Neural Network with 79.00% in 2015 and 68.29% in 2019. In contrast, Support Vector Machine classifiers obtained overall accuracies of 77.44% and 71.26% in 2015 and 2019 respectively. The results were accessed and it is found that Support Vector Machine outperforms the Neural Network classifier in discriminating data with high heterogeneity properties. Besides, Support Vector Machine has more consistent results in parameter testing compared to Neural Network

Shallow-water benthic habitat mapping using drone with object based image analyses

Spatial information on benthic habitats in Wangiwangi island waters, Wakatobi District, Indonesia was very limited in recent years. However, this area is one of the marine tourism destinations and one of the Indonesia’s triangle coral reef regions with a very complex coral reef ecosystem. The drone technology that has rapidly developed in this decade, can be used to map benthic habitats in this area. This study aimed to map shallow-water benthic habitats using drone technology in the region of Wangiwangi island waters, Wakatobi District, Indonesia. The field data were collected using a 50 × 50 cm squared transect of 434 observation points in March–April 2017. The DJI Phantom 3 Pro drone with a spatial resolution of 5.2 × 5.2 cm was used to acquire aerial photographs. Image classifications were processed using object-based image analysis (OBIA) method with contextual editing classification at level 1 (reef level) with 200 segmentation scale and several segmentation scales at level 2 (benthic habitat). For level 2 classification, we found that the best algorithm to map benthic habitat was the support vector machine (SVM) algorithm with a segmentation scale of 50. Based on field observations, we produced 12 and 9 benthic habitat classes. Using the OBIA method with a segmentation value of 50 and the SVM algorithm, we obtained the overall accuracy of 77.4% and 81.1% for 12 and 9 object classes, respectively. This result improved overall accuracy up to 17% in mapping benthic habitats using Sentinel-2 satellite data within the similar region, similar classes, and similar method of classification analyses

May Luxury Hotel / Ahmad Nazimi Sani…[et al.]

May Luxury Hotel adalah mempakan satu cadangan Rancangan Perniagaan yang disediakan bagi mereka yang ingin menceburi bidang perniagaan perhotelan khususnya bagi perniagaan perhotelan kategori Tiga Bintang. Di dalam Rancangan Perniagaan ini terkandung cadangan bagaimana untuk mentadbir, mengoperasi, memasar dan menguruskan kewangan perniagaan jenis ini. Perkhidmatan perhotelan yang dicadangkan di Ayer Keroh ini dijangkakan akan dapat menampung kekurangan penginapan yang akan dihadapi bagi pelancong - pelancong yang akan datang ke negara Malaysia khususnya ke negeri Melaka. Pertambahan pelancong yang akan datang ke negeri Melaka dijangkakan akan meningkat secara mendadak oleh kerana Malaysia akan menjadi tuan rumah bagi Sukan Komenwel 1998 dan Malaysia mempunyai pusat tarikan pelancongan yang terkenal di seluruh dunia

Textural measures for estimating oil palm age

In oil palm management, age is one of the yield determinant factors. The conventional field investigations are often exhaustive and costly methods when implemented on a large scale. Despite much attention to classify individual oil palm ages by using various remote sensing images, none of the studies depicted satisfying overall accuracies. The overall aim of this study was to optimize window size and number of texture measurements for oil palm ages classification. The study was conducted in a commercial oil palm plantation comprised of palms of multiple ages planted from 1991 to 2008. Three Satellite Pour l’Observation de la Terre (SPOT)-5 multispectral images, acquired on 12 April 2012, 4 April 2013, and 14 April 2014, were evaluated. The individual ages were successfully classified with accuracy ranging from 59% to 97%, with an average overall accuracy of 84%. The results illustrated that the largest window size related to the smallest oil palm planting block in the study area, 390 m × 390 m on-the-ground window size, and seven combination of texture measurements, resulted in the highest classification overall accuracy. The utilization of texture measurements produced synergistic effects able to discriminate the oil palm age, with mean, entropy, homogeneity, and angular second moment as among the significant textures

Evaluation of quickbird data for topographic detail mapping

The latest technology of high resolution satellite imagery has provided its metric potential for mapping. Quickbird imaging systems offer ortho-image products which comply with the specification of map accuracy for scales as large as 1:10,000. This study is to determine the ability of Quickbird satellite imagery to be used for topographic detail mapping. In this study, the systematic procedure and the suitable technique to extract ground features from Quickbird data were carried out. The procedure includes the Digital Elevation Model (DEM) extraction to remove the relief displacement of the Quickbird image. The DEM was extracted using scanned aerial photograph and processed by stereo correlation technique. Visual interpretation technique was used to extract the point features, while the Edge Detector filters to extract the linear features. In order to extract polygon features, Canny Filter and Region Growing Segmentation were used. The accuracy of the results comprises of Root Mean Square Error (RMSE). In this study, the accuracy of the topographic detail plan derived from Quickbird image is 3.1068 meters, which fulfill requirement mapping of 1:1,000 scales. This leads to conclusion that Quickbird image can be used as a data source for topographic detail mapping

Modelling of sea surface current and cirulation from satellite altimetry and ancillary data

Altimeter data from Jason-1 satellite are very useful in providing general and continuous information about the ocean, including sea surface currents. The main objective of study is to identify the most appropriate mathematical equation for determining sea surface current in the South China Sea. The seasonal changes of surface current during different monsoon periods in 2004 and 2005 were also identified. The equations used to derive sea surface current are geostrophic current equations, wind-driven current equations and tidal current equations. The methodology of this study involves the use of sea level height and sea surface wind speed data from Jason-1 satellite altimeter to derive geostrophic current and wind-driven current. Tidal amplitudes from co-tidal charts were used to derive tidal current. The derived surface currents were used to produce combined geostrophic and wind-driven current. Combined geostrophic and tidal current as well as total surface current which is the combination of geostrophic current, wind-driven current and tidal current were also derived. Maps of total surface current circulation pattern were produced during four monsoon periods in 2004 and 2005. Regression analysis and comparison of mean and standard deviation values with sea truth data were carried out to identify the most appropriate equation of surface current for the South China Sea. Results of the analysis indicate that total surface current speed and direction have good correlation with the sea truth data, that is 0.68 and 0.70 respectively. The analysis by comparing the mean values indicate that there are no significant difference between the means of total surface current and the means of sea truth data. The standard deviations of total surface current are smaller compared to the sea truth data values. In conclusion, altimeter data from Jason-1 satellite combined with tidal data to derive the total surface current is appropriate to determine sea surface current circulation pattern in the South China Sea