Mazlan Hashim

Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment

This research presents the results of the GIS-based statistical models for generation of landslide susceptibility mapping using geographic information system (GIS) and remote-sensing data for Cameron Highlands area in Malaysia. Ten factors including slope, aspect, soil, lithology, NDVI, land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from SAR data, SPOT 5 and WorldView-1 images. The relationships between the detected landslide locations and these ten related factors were identified by using GIS-based statistical models including analytical hierarchy process (AHP), weighted linear combination (WLC) and spatial multi-criteria evaluation (SMCE) models. The landslide inventory map which has a total of 92 landslide locations was created based on numerous resources such as digital aerial photographs, AIRSAR data, WorldView-1 images, and field surveys. Then, 80% of the landslide inventory was used for training the statistical models and the remaining 20% was used for validation purpose. The validation results using the Relative landslide density index (R-index) and Receiver operating characteristic (ROC) demonstrated that the SMCE model (accuracy is 96%) is better in prediction than AHP (accuracy is 91%) and WLC (accuracy is 89%) models. These landslide susceptibility maps would be useful for hazard mitigation purpose and regional planning.

The application of remote sensing to seagrass ecosystems: an overview and future research prospects

This review evaluates various methods employed to produce seagrass habitat maps using optical and acoustic remote-sensing (RS) techniques coupled with in situ sampling to highlight recent advances and to define areas where potential future research should be focused in the application of RS technologies. A critical review of 195 studies revealed that, in the past four decades, advances in the application of RS methods, notably using Landsat imagery, are identified for seagrass detection, assessment of areal coverage, distribution and abundance mapping, and the detection of extent and biomass changes, as illustrated in peer-reviewed literature. Rapid technological and methodological advances have occurred in the acquisition and interpretation of optical and acoustic data for the mapping of seagrass habitats. The methods have been tested to segment, classify, and combine RS data with biological field or ground truth sample data. There is no single technology or approach that is suitable for and capable of measuring all seagrass parameters (presence/absence, cover, species, and biomass) and assessing change. Integration of field, imagery, and mapping approaches is therefore required. Further research is required for continued improvements in understanding of theoretical and methodological aspects of seagrass RS.

Integrating PALSAR and ASTER data for mineral deposits exploration in tropical environments: a case study from Central Belt, Peninsular Malaysia

Remote sensing investigation for mineral deposits exploration in tropical environments is not completely implemented due to obstacles imposed by tropical climate. Recent challenge is to use the most suitable recent generation of remote sensing data and image processing approaches for the detection of lithological units and structural features associated with epithermal and polymetallic vein-type mineralisation, which are concealed by tropical rainforest. This research investigates the integration of the Phased Array type L-band Synthetic Aperture Radar (PALSAR) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data for geological mapping applications in tropical environments. The eastern part of the Central Belt of Peninsular Malaysia with high potential for gold prospecting has been investigated as a case study to identify structural features and mineral assemblages using PALSAR and ASTER data. Adaptive local sigma and directional filters were applied to PALSAR data for detecting geological structure elements in the study area. Vegetation, mineralogic and lithologic indices for ASTER bands were tested in tropical climate. Lineaments (fault and fractures) and curvilinear (anticline or syncline) were detected using PALSAR image map of directional filters (N–S, NE–SW and NW–SE).Vegetation index image map show vegetation cover using ASTER visible and near-infrared radiation (VNIR) bands. High concentration of clay minerals zone was detected using image map derived from ASTER shortwave infrared (SWIR) bands. ASTER thermal infrared (TIR) bands produced image map of the lithological units. Results indicate that data integration from PALSAR and ASTER sources enhanced information extraction for geological mapping in tropical environments. The study presented here encourages further applications of satellite remote sensing data integration for mapping structural elements, hydrothermal alteration minerals and lithological units associated with epithermal and polymetallic vein-type mineralisation in tropical environments.

Exploration of gold mineralization in a tropical region using Earth Observing-1 (EO1) and JERS-1 SAR data: a case study from Bau gold field, Sarawak, Malaysia

Bau gold mining district, located near Kuching, Sarawak, Malaysia, is a Carlin style gold deposits. Geological analyses coupled with remote sensing data were used to detect hydrothermal alteration rocks and structure elements associated with this type of gold mineralization. Image processing techniques, including principal components analysis, linear spectral unmixing, and Laplacian algorithms, were employed to carry out spectrolithological–structural mapping of mineralized zones, using Advanced Land Imager, Hyperion, and JERS-1 synthetic aperture radar scenes covering the study area and surrounding terrain. Hydrothermally alteration mineral zones were detected along the SSW to NNE structural trend of the Tai Parit fault that corresponds to the areas of occurrence of the gold mineralization in the Bau limestone. The results show that potentially interesting areas are observable by the methods used, despite limited bedrock exposure in this region and the constraints imposed by the tropical environment.

Modification of fractal algorithm for oil spill detection from RADARSAT-1 SAR data

This paper introduces a modified formula for the fractal box counting dimension. The method is based on utilization of the probability distribution formula in the fractal box count. The purpose of this method is to use it for the discrimination of oil spill areas from the surrounding features, e.g., sea surface and look-alikes in RADARSAT-1 SAR Wide beam mode (W1) and Standard beam mode (S2) data have been collected under different wind speeds. The results show that the new formula of the fractal box counting dimension is able to discriminate between oil spills, look-alike areas and pixels of the size of a single ship. The W1 mode data illustrate an error standard deviation of 0.05, thus performing a better discrimination of oil spills as compared to S2 mode data. We conclude that automatic detection and discrimination of oil spill and other sea surface features can be opertionalized by using the new formula for fractal box counting.

Fusing ASTER, ALI and Hyperion data for enhanced mineral mapping

This investigation fused Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI) and Hyperion data for detecting hydrothermal alteration minerals associated with porphyry copper mineralisation and related host-rock lithology. The distribution of iron oxide/hydroxide minerals, vegetation and clay minerals was identified based on principal component analysis, using the distinctive bands of ASTER and ALI at a regional scale. The analysis also showed that by fusing these different data sources, the discrimination of quartz-rich igneous rocks from the magmatic bedrock and the boundary between igneous and sedimentary rocks using ASTER thermal infrared bands could be made. An image map of spectrally predominant mineral assemblages in the hydrothermal alteration zones could be produced using the shortwave infrared bands of Hyperion data at a district scale. Phyllic, advanced argillic and propylitic alteration zones associated with porphyry copper mineralisation were discriminated based on the identified alteration minerals such as sericite, kaolinite, illite, alunite, chlorite, epidote and calcite. Results have proven to be effective, and in accordance with the results of field investigations. It is concluded that the methods of image and data fusion of spectral information derived from ASTER, ALI and Hyperion data can produce comprehensive and accurate information for copper resource investigations.

3-D visualizations of coastal bathymetry by utilization of airborne TOPSAR polarized data

Abstract Multi-frequency C and L bands in the TOPSAR data have been utilized to reconstruct three-dimensional (3-D) bathymetry pattern. The main objective of this study is to utilize fuzzy arithmetic to reduce the errors arising from speckle in synthetic aperture radar (SAR) data when constructing ocean bathymetry from polarized SAR data. In doing so, two 3-D surface models, the Volterra algorithm and a fuzzy B-spline (FBS) algorithm, which construct a global topological structure between the data points, were used to support an approximation to the real surface. Volterra algorithm was used to express the non-linearity of TOPSAR data intensity gradient based on the action balance equation (ABC). In this context, a first-order kernel of Volterra algorithm was used to express ABC equation. The inverse of Volterra algorithm then performed to simulate 2-D current velocities from CVV and LHH band. Furthermore, the 2-D continuity equation then used to estimate the water depth. In order to reconstruct 3-D bathymetry pattern, the FBS has been performed to water depth information which was estimated from 2-D continuity equation. The best reconstruction of coastal bathymetry of the test site in Kuala Terengganu, Malaysia, was obtained with polarized L and C bands SAR acquired with HH and VV polarizations, respectively. With 10 m spatial resolution of TOPSAR data, bias of –0.004 m, the standard error mean of 0.023 m, r 2 value of 0.95, and 90% confidence intervals in depth determination was obtained with LHH band.

The earth observing-1 (eo-1) satellite data for geological mapping, southeastern segment of the central Iranian volcanic belt, Iran

This investigation used Earth Observing-1 (EO-1) ALI (advanced land imager) and hyperion data to extract the geological and mineralogical information for identifying hydrothermal alteration zones associated with porphyry copper deposits in southeastern segment of the Central Iranian Volcanic Belt, SE Iran. A band ratio derived from image spectra (4/2, 8/9, 3 in RGB) has been developed to identify lithological units and hydrothermally altered rocks using ALI data in a regional scale. Analytical imaging and geophysics (AIG)-Developed Hyperspectral Analysis processing methods were tested on the shortwave infrared bands of hyperion for mapping mineral assemblages in hydrothermal alteration zones associated with two known copper ore deposits, namely Sar Cheshmeh and Meiduk. The methods produced image map of spectrally predominant minerals in alteration zones using hyperion data. Therefore, phyllic, argillic, and propylitic alteration zones were significantly discriminated from surrounding country rock. The spatial distribution of identified hydrothermal alteration zones has been confirmed by spectral reflectance measurements, XRD analysis and in-situ inspection. The research presented here indicated that lithological units, hydrothermally altered rocks, and hydrothermal alteration zones associated with porphyry copper mineralization can be accurately mapped by ALI and hyperion data at both regional and district scales.

Logging History and Its Impact on Forest Structure and Species Composition in the Pasoh Forest Reserve — Implications for the Sustainable Management of Natural Resources and Landscapes

Abstract: A part of the Pasoh Forest Reserve (Pasoh FR) was once logged under a logging regime called the Malayan Uniform System (MUS) in the 1950s. The core area of the reserve is a residual unlogged (primary) forest that shows the typical structure and species composition of lowland dipterocarp forest; the logged area of the reserve is also a relict area of regenerating lowland forest. In this chapter, we review and summarize previous studies of logging impacts on the forest structure and total aboveground biomass by comparing the primary and regenerating forests of this reserve. We also studied landscape changes in the Pasoh Forest Region in order to discuss the relationship between logging history in this region and its impacts on the forest. From a chronological analysis of the changes in land use in this region, we found that ca. 50% of the forested area had been converted to either oil palm or rubber plantations from 1971 to 1996. Almost all of the lowland dipterocarp forest that had developed in the flat and alluvial topography had vanished from this region, except in the Pasoh FR. Thus, very little area was left to be managed by the MUS approach, which was originally designed for extracting timber with a longer logging cycle (>70 years) in this type of forest. By examining the canopy and stand structure and the species composition of these forests, we found a greater density of semi-medium (6-10 cm in diameter) and medium trees (10–30 cm), a higher density of canopy-forming trees with relatively smaller crowns, and a higher density of non-commercial canopy-forming trees in the regenerating forest. These findings suggest that the MUS was incompletely implemented, since this system originally aimed to encourage the development of a uniform forest structure with a large number of sound commercial timber trees by removing noncommercial trees. Owing to the high density of canopy-forming trees, which probably resulted from incomplete post-logging thinning and vegetation-control operations, structural development was delayed in the regenerating forest. In addition, the species composition and the distribution of wildlife in the regenerating forest differed from those in the primary forest. We also found that the total aboveground biomass in the regenerating forest had not fully recovered to the level in the primary forest even 40 years after logging. We suggest that “follow-up operations” should be undertaken, with a special concern for encouraging the structural development of the stand, which we consider to be crucial for ecologically sustainable management.

Comparison between radarsat-1 SAR different data modes for oil spill detection by a fractal box counting algorithm

Abstract This work presents a modified formula for the fractal box counting dimension. The method is based on the utilisation of the probability distribution formula in the fractal box count. The purpose of this method is to use it for the discrimination of oil spill areas from the surrounding features, e.g. sea surface and look-alikes, using RADARSAT-1 SAR Wide beam mode (W1), Standard beam mode (S2) and Standard beam mode (S1) data acquisition under different wind speeds. The results show that the new formula is able to discriminate between oil spills and look-alike areas. The results also illustrate that the new fractal formula identifies well the deficiency of oil spills in pairs of S2 data. Further, there are no significant differences between fractal values of look-alikes, low wind zone, and current shear features in different beam modes for acquisition of RADARSAT-1 SAR data. The W1 mode data, however, show an error standard deviation of 0.002, thus performing a better discrimination of oil spills than the S1 and S2 mode data.