Universiti Putra Malaysia Institute of Advanced Technology 43400, UPM, Serdang Selangor, Malaysia
biswajeet24@gmail.com
Biswajeet Pradhan graduated with a B.Sc. degree in Geology honours from Berhampur University, Orissa, and the M.Sc. in applied geology from Indian Institute of Technology (IIT), Bombay, and the M.Tech. in civil engineering from Indian Institute of Technology (IIT), Kanpur and Dresden University of Technology, Germany and PhD in GIS and Geomatics Engineering from University Putra Malaysia . He was an Alexander von Humboldt Research Fellow at Dresden University of Technology. He is a recipient of German Deutscher Akademischer Austausch Dienst (DAAD) and Saxony Scholarship holder from Germany. He has more than 12 years of teaching, research and industrial experience and has published over 100 research articles in referred technical journals and books. He specializes in Remote Sensing, GIS applications and soft computing techniques in natural hazard and environmental problems.
Abstract: A study was conducted to investigate the influence of Asian monsoon on chlorophyll-a (Chl-a) content in Sabah waters and to identify the related oceanographic conditions that caused phytoplankton blooms at the eastern and western coasts of Sabah, Malaysia. A series of remote sensing measurements including surface Chl-a, sea surface temperature, sea surface height anomaly, wind speed, wind stress curl, and Ekman pumping were analyzed to study the oceanographic conditions that lead to large-scale nutrients enrichment in the surface layer. The results showed that the Chl-a content increased at the northwest coast from December to April due to strong northeasterly wind and coastal upwelling in Kota Kinabalu water. The southwest coast (Labuan water) maintained high concentrations throughout the year due to the effect of Padas River discharge during the rainy season and the changing direction of Baram River plume during the northeast monsoon (NEM). However, with the continuous supply of nutrients from the upwelling area, the high Chl-a batches were maintained at the offshore water off Labuan for a longer time during NEM. On the other side, the northeast coast illustrated a high Chl-a in Sandakan water during NEM, whereas the northern tip off Kudat did not show a pronounced change throughout the year. The southeast coast (Tawau water) was highly influenced by the direction of the surface water transport between the Sulu and Sulawesi Seas and the prevailing surface currents. The study demonstrates the presence of seasonal phytoplankton blooms in Sabah waters which will aid in forecasting the possible biological response and could further assist in marine resource managements.
Abstract: In this paper, an attempt has been made to assess, prognosis and observe dynamism of soil erosion by universal soil loss equation (USLE) method at Penang Island, Malaysia. Multi-source (map-, space- and ground-based) datasets were used to obtain both static and dynamic factors of USLE, and an integrated analysis was carried out in raster format of GIS. A landslide location map was generated on the basis of image elements interpretation from aerial photos, satellite data and field observations and was used to validate soil erosion intensity in the study area. Further, a statistical-based frequency ratio analysis was carried out in the study area for correlation purposes. The results of the statistical correlation showed a satisfactory agreement between the prepared USLE-based soil erosion map and landslide events/locations, and are directly proportional to each other. Prognosis analysis on soil erosion helps the user agencies/decision makers to design proper conservation planning program to reduce soil erosion. Temporal statistics on soil erosion in these dynamic and rapid developments in Penang Island indicate the co-existence and balance of ecosystem.
Abstract: In this study, landslide risk assessment for Izmir city (west Turkey) was carried out, and the environmental effects of landslides on further urban development were evaluated using geographical information systems and remote sensing techniques. For this purpose, two different data groups, namely conditioning and triggering data, were produced. With the help of conditioning data such as lithology, slope gradient, slope aspect, distance from roads, distance from faults and distance from drainage lines, a landslide susceptibility model was constructed by using logistic regression modelling approach. The accuracy assessment of the susceptibility map was carried out by the area under curvature (AUC) approach, and a 0.810 AUC value was obtained. This value shows that the map obtained is successful. Due to the fact that the study area is located in an active seismic region, earthquake data were considered as primary triggering factor contributing to landslide occurrence. In addition to this, precipitation data were also taken into account as a secondary triggering factor. Considering the susceptibility data and triggering factors, a landslide hazard index was obtained. Furthermore, using the Aster data, a land-cover map was produced with an overall kappa value of 0.94. From this map, settlement areas were extracted, and these extracted data were assessed as elements at risk in the study area. Next, a vulnerability index was created by using these data. Finally, the hazard index and the vulnerability index were combined, and a landslide risk map for Izmir city was obtained. Based on this final risk map, it was observed that especially south and north parts of the Izmir Bay, where urbanization is dense, are threatened to future landsliding. This result can be used for preliminary land use planning by local governmental authorities.
Abstract: Geospatial data base creation for landslide-hazard mapping is often an almost inhibitive activity. This has been the reason that for quite some time landslide-hazard analysis was modeled on the basis of spatially related factors. This paper presents the use of fuzzy logic to landslide-hazard analysis in the Penang Island, Malaysia, using remote sensing data and a geographic information system (GIS). To achieve the goal, a data-derived model (frequency ratio) and a knowledge-derived model (fuzzy operator) were combined for landslide-hazard analysis. Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and field surveys. The nine factors that influence landslide occurrence were extracted from the database and the frequency ratio coefficient for each factor was computed. Using the factors and the identified landslide, the fuzzy membership values were calculated. Then fuzzy algebraic operators were applied to the fuzzy membership values for landslide-hazard mapping. Finally, the produced map was verified by comparing with existing landslide locations for calculating prediction accuracy. Among the fuzzy operators, in the case in which the gamma operator (λ = 0.8) showed the best accuracy (80%) while the case in which the fuzzy or operator was applied showed the worst accuracy (56%).
Abstract: Geomophological hazard assessment is an important component of natural hazard risk assessment. This paper presents GIS-based geomorphological hazard mapping in the Red Sea area between Safaga and Quseir, Egypt. This includes the integration of published geological, geomorphological, and other data into GIS, and generation of new map products, combining governmental concerns and legal restrictions. Detailed geomorphological hazard maps for flooding zones and earth movement potential, especially along the roads and railways, have been prepared. Further the paper illustrates the application of vulnerability maps dealing with the effect of hazard on urban areas, tourist villages, industrial facilities, quarries, and road networks. These maps can help to initiate appropriate measures to mitigate the probable hazards in the area.
Abstract: This paper deals with landslide hazard analysis using Geographic Information System (GIS) and remote sensing data for Cameron Highland, Malaysia. Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys. Topographical/geological data and satellite images were collected and processed using GIS and image processing tools. There are ten landslide inducing parameters which are considered for the landslide hazards. These parameters are topographic slope, aspect, curvature and distance from drainage, all derived from the topographic database; geology and distance from lineament, derived from the geologic database; landuse from Landsat satellite images; soil from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value from SPOT satellite images. Landslide hazard was analyzed using landslide-occurrence factors employing the logistic regression model. The results of the analysis were verified using the landslide location data and compared with logistic regression model. The accuracy of hazard map observed was 85.73%. The qualitative landslide hazard analysis was carried out using the logistic regression model by doing map overlay analysis in GIS environment. This information could be used to estimate the risk to population, property and existing infrastructure like transportation network.
Abstract: Recently, use of remote sensing data for determining the orientation of stress has been demonstrated. The present study deals with the estimation of stress pattern in the part of the Himalayan region which shows the ongoing neo-tectonic activities. The study area falls into a tectonically active zone of the Central-Himalaya, with a complex geotectonic set-up confined by a number of faults. Efforts have been made to evaluate the technique as a fast algorithm for quick and time limited analysis of linear feature from which the orientation of the lineaments are estimated by using remote sensing data. Further, the estimation of stress and the lineament analysis have been used in mapping of landslide prone areas. Terrain information such as land cover, geology, lineament, faults, mega faults, geomorphology and drainage has been derived from the satellite imageries, and the existing thematic information has been updated to enable the quantification of landslide causative parameters. Spatial and temporal multi-layered information have been used for landslides hazard susceptibility analysis. The qualitative hazard analysis has been carried out using the map overlying techniques in GIS environment along the central part of Himalayan region. It has been observed that the high potential zones have been found to have very high lineament density, moderate to low drainage density and high slope areas of the terrain. On the basis of the geological and morphological analysis, it is further suggested that the combined impacts of the crushed nature of bed rock (due to the neo-tectonic activities), heavy rainfall and lack of vegetation cover cause persistent recurrence of landslides along this region. The role of earthquake on induction of landslides will be presented.
Abstract: Gadarif region is one of the important mechanized rain-fed agricultural areas in Sudan and produces more than one-third of total national production of sorghum – the main food stuff in the country. Dryland farming throughout the region is practiced at various scales. The existing land use is characterized by complex vegetation covers and scattered distributed of small and large agricultural fields. Therefore it is difficult to delineate land cover features using only optical sensors. This study evaluates the potential of multi-sensor data for mapping of the cultivated area in a typical mechanized rain-fed agricultural environment in Ghadambaliya section of Gadarif region, Sudan. Multi-temporal images of Landsat (ETM+), ASTER, and TerraSAR-X data were used for the land use evaluation. For cultivated area classification, a pixel-based approach was applied to Landsat (ETM+) and ASTER data; while an object-based method was applied to TerraSAR-X data. Both supervised classification using Maximum Likelihood Classifier (MLC) and object-based image analysis were performed for land use analysis. The results show that, comprehensive information of land use provided by ASTER and Landsat (ETM+) images can be of great deal of help to identify the cultivated land areas. On the other hand a detailed land cover classes of the cultivated area was obtained from TerraSAR-X. The accuracy of the pixel-based and object-based classification methods was assessed using reference data sets derived from satellite data and ground truth field investigation data.
