Extraction of soil moisture from RADARSAT-1 and its role in the formation of the 6 December 2008 landslide at Bukit Antarabangsa,Kuala Lumpur

Active microwave has a huge potential in the estimation of soil moisture especially over large areas where the meteorological observations are seldom. The large contrast in dielectric constant between different types of soil is considered as the main factor for measuring the moisture content. This study is aimed at the extraction of soil moisture over the areas of Bukit Antarabangsa, Malaysia using active microwave remote sensing technique in order to examine the impact of moisture content dynamically on landslides occurrence, which have been a basic challenge that threaten Bukit Antarabangsa area, particularly in falling of monsoon seasons. This study addressed a specific event that took place in 6 December 2008 due to a very high level of precipitation that resulted in a raise in ground water table causing the occurrence of landslide. One Radarsat-1 image acquired in July 2008 before the landslide was used for generating the moisture content map. The resultant moisture content map showed a reasonable distribution of the moisture concentrated over the forest areas which has previous records landslides. Moreover, it was found that the previous landslide events were within the high moisture zone indicating the presence of high moisture content. Subsequently, three moisture maps were extracted from Landsat-7 ETM+, which were then used for validation process. A statistically based validation technique was used by calculating area under the curve that correlates the high moisture values of three images. In order to validate the Landsat-7 ETM+ moisture content, monthly rainfall data was plotted against the high moisture values derived from three Landsat-7 images. The validation result indicated an acceptable compatibility. The spatial relation between high moisture areas in Landsat-7 ETM+ images along the year resulted in a good fitting in the high–low moisture distribution areas with sensitivity ranged of 60–70 %. Finally, the moisture content map generated by Radarsat-1 was validated using a landslide inventory map. The resultant validation produced an area under curve of 0.704 (70 %).     

An Integrated GIS Based Statistical Model to Compute Groundwater Vulnerability Index for Decision Maker in Agricultural Area

The conservation areas in a plain are affected by the groundwater contamination from intense application of the fertilizers. The vulnerability of groundwater can be tested by using the DRASTIC model for the pollutants. The groundwater susceptibility to pollution in the various areas is mapped through DRASTIC model. However, the effects of pollution types and its characteristics are not considered, as this model is used without any modifications. This technique must be standardized for usage in the various aquifers and specific pollution types. The rates of DRASTIC parameters are corrected to obtain the potential for a more accurate analysis of the vulnerability pollution. The relationships between the parameters are identified with respect to the nitrate concentration in the groundwater by calculating the new rates. The methodology was applied to the selected area situated in the south eastern region of Iran at Kerman plain. Twenty-seven different locations were selected to test and analyse the nitrate concentration in the water from underground wells. The pollution in the aquifer was associated and correlated with the DRASTIC index by using the measured nitrate concentrations. The relationship between the index and the measured pollution in the Kerman plain was determined by applying the Wilcoxon rank-sum nonparametric statistical tests and the rates were calculated. It was found specifically in the agricultural areas that the modified DRASTIC model performed more efficiently than the traditional method for nonpoint source pollution, as indicated by the results. After modifications, the regression coefficients revealed that the relationship between the vulnerability index and the nitrate concentration was 77 %, while it was 37 % before the modifications were used. These statistics show that the modified DRASTIC performed far more efficiently than the original version.     

Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models

This paper presents landslide hazard analysis at Cameron area, Malaysia, using a geographic information system (GIS) and remote sensing data. Landslide locations were identified from interpretation of aerial photographs and field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence are topographic slope, topographic aspect, topographic curvature, and distance to rivers, all from the topographic database; lithology and distance to faults were taken from the geologic database; land cover from TM satellite image; the vegetation index value was taken from Landsat images; and precipitation distribution from meteorological data. Landslide hazard area was analyzed and mapped using the landslide occurrence factors by frequency ratio and bivariate logistic regression models. The results of the analysis were verified using the landslide location data and compared with the probabilistic models. The validation results showed that the frequency ratio model (accuracy is 89.25%) is better in prediction of landslide than bivariate logistic regression (accuracy is 85.73%) model.     

Remote sensing-based studies coupled with field data reveal urgent solutions to avert the risk of flash floods in the Wadi Qus (east of Jeddah) Kingdom of Saudi Arabia

Natural Hazards - On November 25, 2009, heavy amount of rainfall precipitated in the city of Jeddah that led to floods causing unexpected loss of life (113 person died), and damaged public and...     

Tilted Bianchi type I cosmological models filled with disordered radiation in general relativity revisitedD

Tilted Bianchi type I cosmological models filled with disordered radiation in presence of a bulk viscous fluid and heat flow are investigated. The coefficient of bulk viscosity is assumed to be a power function of mass density. Some physical and geometric properties of the models are also discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Trend analysis of evapotranspiration over India: Observed from long-term satellite measurements

Owing to the lack of consistent spatial time series data on actual evapotranspiration (ET), very few studies have been conducted on the long-term trend and variability in ET at a national scale over the Indian subcontinent. The present study uses biome specific ET data derived from NOAA satellite’s advanced very high resolution radiometer to investigate the trends and variability in ET over India from 1983 to 2006. Trend analysis using the non-parametric Mann–Kendall test showed that the domain average ET decreased during the period at a rate of \(0.22\,\hbox {mm year}^{-1}\). A strong decreasing trend (\(m = -1.75\, \hbox {mm year}^{-1}\), \(F = 17.41\), \(P\) 0.01) was observed in forest regions. Seasonal analyses indicated a decreasing trend during southwest summer monsoon (\(m= -0.320\, \hbox {mm season}^{-1}\,\hbox {year}^{-1})\) and post-monsoon period (\(m= -0.188\, \hbox {mm season}^{-1 }\,\hbox {year}^{-1})\). In contrast, an increasing trend was observed during northeast winter monsoon (\(m = 0.156 \,\hbox {mm season}^{-1 }\,\hbox {year}^{-1})\) and pre-monsoon (\(m = 0.068\, \hbox {mm season}^{-1 }\,\hbox {year}^{-1})\) periods. Despite an overall net decline in the country, a considerable increase ( \(4 \,\hbox {mm year}^{-1}\)) was observed over arid and semi-arid regions. Grid level correlation with various climatic parameters exhibited a strong positive correlation (\(r \!>\!0.5\)) of ET with soil moisture and precipitation over semi-arid and arid regions, whereas a negative correlation (\(r\) \(-0.5\)) occurred with temperature and insolation in dry regions of western India. The results of this analysis are useful for understanding regional ET dynamics and its relationship with various climatic parameters over India. Future studies on the effects of ET changes on the hydrological cycle, carbon cycle, and energy partitioning are needed to account for the feedbacks to the climate.     

Spatio-Temporal Assessment of Groundwater Potential Zone in the Drought-Prone Area of Bangladesh Using GIS-Based Bivariate Models

Natural Resources Research - Groundwater is one of the most dynamic and renewable natural resources found in the earth’s crust. A spatio-temporal assessment of groundwater potential zone...     

Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms

Landslide susceptibility and hazard assessments are the most important steps in landslide risk mapping. The main objective of this study was to investigate and compare the results of two artificial neural network (ANN) algorithms, i.e., multilayer perceptron (MLP) and radial basic function (RBF) for spatial prediction of landslide susceptibility in Vaz Watershed, Iran. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 136 landside locations were constructed from various sources. Then the landslide inventory map was randomly split into a training dataset 70 % (95 landslide locations) for training the ANN model and the remaining 30 % (41 landslides locations) was used for validation purpose. Nine landslide conditioning factors such as slope, slope aspect, altitude, land use, lithology, distance from rivers, distance from roads, distance from faults, and rainfall were constructed in geographical information system. In this study, both MLP and RBF algorithms were used in artificial neural network model. The results showed that MLP with Broyden–Fletcher–Goldfarb–Shanno learning algorithm is more efficient than RBF in landslide susceptibility mapping for the study area. Finally the landslide susceptibility maps were validated using the validation data (i.e., 30 % landslide location data that was not used during the model construction) using area under the curve (AUC) method. The success rate curve showed that the area under the curve for RBF and MLP was 0.9085 (90.85 %) and 0.9193 (91.93 %) accuracy, respectively. Similarly, the validation result showed that the area under the curve for MLP and RBF models were 0.881 (88.1 %) and 0.8724 (87.24 %), respectively. The results of this study showed that landslide susceptibility mapping in the Vaz Watershed of Iran using the ANN approach is viable and can be used for land use planning.     

Geochemistry and petrogenesis of anorogenic(?) granitoids of west Garo Hills,Meghalaya

The granite in Samingiri — Dilsekgiri area occurs as discordant, isolated pluton within the migmatitic terrain of West Garo Hills district, Meghalaya. The pluton is exposed over 140 sq km (18 km × 8 km). It exhibits structures of solid state and piecemeal stoping effect proximal to the contact and enveloped by a contact metamorphic aureole of albite-epidote-hornfels facies. Modally, it is biotite-monzogranite and biotite-syenogranite with minor biotite, chlorite, epidote and sericite and accessories like zircon, apatite, allanite, pyrite, magnetite and sphene. Geochemically, it is marked by restricted composition (69–76 wt% SiO₂), high alkalies, low Ca, metaluminous to strongly peraluminous (Molar Al₂O₃/CaO+Na₂O+K₂O = 0.95 ? 1.54), high FeO/MgO, high Ga/Al, high contents of Rb, Sr, Ba, Y, Zr and Ce and depleted in Ti and P. The field observation, mineralogical and geochemical aspects indicate the post-tectonic nature of West Garo pluton more like as A-type granite formed by partial melting of lower crustal blocks followed by low to moderate degree of fractional differentiation. Low Ca, alkaline nature and peraluminous character point to A-type nature of West Garo granite significantly different from other granites of Meghalaya Plateau. Rb-Sr age (616±86 Ma) of granite, however, corresponds to widespread Middle to Upper Pan African activity, a thermal event prevailed during Late Proterozoic — Early Palaeozoic (500–800 Ma) period, manifested in the form of several granitic intrusions in the basement gneissic complex and the overlying Proterozoic metasediments of the Shillong Group in Meghalaya Plateau.