Geospatial technologies for detection and monitoring of Ganoderma basal stem rot infection in oil palm plantations: a review on sensors and techniques     

Maryam Khosrokhani  Biswajeet Pradhan 《国际地球制图》2018,33(3):260-276

Basal stem rot (BSR) is a type of disease that induces oil palm death within a short span of the appearance of symptoms. BSR early detection would facilitate to curb this by adopting appropriate strategies. In this paper, a systematic review was undertaken to demonstrate the need for authentic health condition monitoring of oil palm plantations. The currently used remotely sensed (RS) techniques for BSR detection and classification were reviewed. Several kinds of RS techniques were exerted for BSR detection and its severity classification up to four levels. It was identified that applied geospatial technologies, including multispectral and hyperspectral remote sensing, terrestrial laser scanning, spatial maps, tomography images, intelligent e-nose and Microfocus X-ray fluorescence, were capable of distinguishing infected oil palms from the non-infected ones. Furthermore, some of them are able to categorize BSR severity level up to four levels as well as of its early detection.  相似文献   

Energy:Preface     

Biswajeet Pradhan 《地学前缘(英文版)》2021,12(6):354-355

Energy is a vital commodity that sustains human lives,as well as eco-nomic processes.The challenges towards energy generation,demand and supply are plenty owing to the use of fossil fuels leading to climate change and environmental problems like water and air pollution.With the increasing awareness over climate change,post Paris Agreement,the role of energy plays a key role towards achieving the proposed tar-get.The contributions in this Special Issue of Geoscience Frontiers on En-ergy includes 8 papers from esteemed research groups worldwide which explores,highlights and provide new insights towards the vari-ous aspects of energy.  相似文献   

Improving the accuracy of landslide susceptibility model using a novel region-partitioning approach     

Haoyuan Hong  Biswajeet Pradhan  Maher Ibrahim Sameen  Bahareh Kalantar  Axing Zhu  Wei Chen 《Landslides》2018,15(4):753-772

Landslide is a natural disaster that threatens human lives and properties worldwide. Numerous have been conducted on landslide susceptibility mapping (LSM), in which each has attempted to improve the accuracy of final outputs. This study presents a novel region-partitioning approach for LSM to understand the effects of partitioning a focused region into smaller areas on the prediction accuracy of common regression models. Results showed that the partitioning of the study area into two regions using the proposed method improved the prediction rate from 0.77 to 0.85 when support vector machine was used, and from 0.87 to 0.88 when logistic regression model was utilized. The spatial agreements of the models were also improved after partitioning the area into two regions based on Shannon entropy equations. Our comparative study indicated that the proposed method outperformed the geographically weighted regression model that considered the spatial variations in landslide samples. Overall, the main advantages of the proposed method are improved accuracy and the reduction of the effects of spatial variations exhibited in landslide-conditioning factors.  相似文献   

Hyperspectral satellite data analysis for pure pixels extraction and evaluation of advanced classifier algorithms for LULC classification   总被引：1，自引：0，他引：1  

Gopal Krishna  Rabi N. Sahoo  Sanatan Pradhan  Tauqueer Ahmad  Prachi M. Sahoo 《Earth Science Informatics》2018,11(2):159-170

The study was carried out for Indian capital city Delhi using Hyperion sensor onboard EO-1 satellite of NASA. After MODTRAN-4 based atmospheric correction, MNF, PPI and n-D visualizer were applied and endmembers of 11 LCLU classes were derived which were employed in classification of LULC. To incur better classification accuracy, a comparative study was also carried out to evaluate the potential of three classifier algorithms namely Random Forest (RF), Support Vector Machines (SVM) and Spectral Angle Mapper (SAM). The results of this study reemphasize the utility of satellite borne hyperspectral data to extract endmembers and also to delineate the potential of random forest as expert classifier to assess land cover with higher classification accuracy that outperformed the SVM by 19% and SAM by 27% in overall accuracy. This research work contributes positively to the issue of land cover classification through exploration of hyperspectral endmembers. The comparison of classification algorithms’ performance is valuable for decision makers to choose better classifier for more accurate information extraction.  相似文献   

Landslide Susceptibility Mapping along Bhalubang–Shiwapur Area of Mid-Western Nepal Using Frequency Ratio and Conditional Probability Models   总被引：3，自引：3，他引：0  

Amar Deep Regmi  Kohki Yoshida  Hamid Reza Pourghasemi  Megh Raj DhitaL  Biswajeet Pradhan 《山地科学学报》2014,11(5):1266-1285

Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang–Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping(LSM) of this region was carried out using frequency ratio(FR) and weights-of-evidence(W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226(70%) were randomly selected for model training and the remaining 106(30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified andcompared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region(W of E model(success rate = 83.39%, prediction rate = 79.59%); FR model(success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area.  相似文献   

Effect of Random Inclusion of Polypropylene Fibers on Strength Characteristics of Cohesive Soil   总被引：2，自引：1，他引：1  

Pradip Kumar Pradhan  Rabindra Kumar Kar  Ashutosh Naik 《Geotechnical and Geological Engineering》2012,30(1):15-25

This paper presents the effect of random inclusion of polypropylene fibers on strength characteristics of soil. Locally available cohesive soil (CL) is used as medium and polypropylene fibers with three aspect ratios (l/d = 75, 100 and 125) are used as reinforcement. Soil is compacted with standard Proctor’s maximum density with low percentage of reinforcement (0–1% by weight of oven-dried soil). Direct shear tests, unconfined compression tests and CBR tests were conducted on un-reinforced as well as reinforced soil to investigate the strength characteristics of fiber-reinforced soil. The test results reveal that the inclusion of randomly distributed polypropylene fibers in soil increases peak and residual shear strength, unconfined compressive strength and CBR value of soil. It is noticed that the optimum fiber content for achieving maximum strength is 0.4–0.8% of the weight of oven-dried soil for fiber aspect ratio of 100.  相似文献   

Geochemistry and petrogenesis of pyrophyllite deposit of Madrangjodi,Keonjhar district,Orissa     

M. Das  S. M. Monalisa  A. K. Paul  R. K. Mishra  J. K. Mohanty  A. A. Pradhan  S. Goswami 《Journal of the Geological Society of India》2012,79(5):460-466

Pyrophyllite deposit at Madrangjodi is a large lensoidal massif overlain unconformably by Dhanjori quartzite and underlain by the parent Singhbhum granite (Phase — II). Pyrophyllite and quartz are the major minerals with minor to trace amounts of muscovite, chloritoid opaques and tourmaline. It is broadly divisible into lamellar, granular and schistose varieties. SiO₂ (66.90–74.36%) and Al₂O₃ (20.80–27.54%) are the major oxides. The major elements data indicate its derivation from Singhbhum granite with depletion of SiO₂ and increment of Al₂O₃. Trace and REE data are discussed to corroborate its genesis.  相似文献   

GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost,Bagging, and MultiBoost ensemble frameworks     

Dieu Tien Bui  Tien-Chung Ho  Biswajeet Pradhan  Binh-Thai Pham  Viet-Ha Nhu  Inge Revhaug 《Environmental Earth Sciences》2016,75(14):1101

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Weathering and mineralogical variation in gneissic rocks and their effect in Sangrumba Landslide,East Nepal     

Amar Deep Regmi  Kohki Yoshida  Megh Raj Dhital  Biswajeet Pradhan 《Environmental Earth Sciences》2014,71(6):2711-2727

Sangrumba landslide is one of the largest and the most active landslides in Nepal Himalaya. Geologically the landslide belongs to the Higher Himalaya and consists of Pre-Cambrian biotite–garnet and sillimanite gneiss with some quartzite. The present paper aims at describing various degrees of rock weathering and their effect in Sangrumba landslide. Field study followed by mineralogical, geochemical and geotechnical analyses of the collected rock and soil samples from the landslide zone were used in characterizing weathering degree. The gneisses are intensely weathered while quartzite is unweathered. Petrographical and X-ray diffraction analyses showed that the rocks in the landslide zone had undergone weathering process with the formation of different types of clay minerals as kaolinite, vermiculite, smectite and chlorite. This was further confirmed by the Scan Electron Microscope and Energy Dispersive X-ray analyses. These clay minerals drastically reduced the rock strength facilitating the extensive failure of the Sangrumba landslide. The major and trace element composition of the rock and soil samples was calculated from the XRF analyses. The geochemical analyses and weathering indexes of rocks showed that they are significantly weathered and had a major influence in the formation of the Sangrumba landslide. In addition, mechanical strength measurement of rock/soil showed that the strength drastically decreases as the weathering intensity increases. Rainfall followed by the rock type are the most dominant parameters influencing the weathering process which leads to the formation of large landslide as the present one. These findings can be used in other areas with similar geological and topographical conditions.  相似文献   

Assessment of fractal dimension and geometrical characteristics of the landslides identified in North of Tehran,Iran     

H. R. Pourghasemi  H. R. Moradi  S. M. Fatemi Aghda  E. A. Sezer  A. Goli Jirandeh  B. Pradhan 《Environmental Earth Sciences》2014,71(8):3617-3626

The aim of the presented study is to assess the fractal dimension (D) and the geometrical characteristics (length and width) of the landslides identified in North of Tehran, Iran. At first, the landslide locations (528 landslides) were identified by interpretation of aerial photographs, satellite images and field surveys, and then to calculate the fractal dimension (D), we used the computer programming named as FRACEK. In the next step, geometrical characteristics of each landslide such as length (L) and width (W) were calculated by ArcGIS software. The landslide polygons were digitized from the mentioned landslide inventory map and rotated based on movement direction. The fractal dimension for all landslides varied between 1.665 and 1.968. Subsequently, the relationship between the length/width ratios and theirs fractal D values for 528 landslides was calculated. The results showed that correlation coefficients (R), which are different regression models such as exponential, linear, logarithmic, polynomial, and power, between D and L/W ratio are relatively high, respectively (0.75, 0.75, 0.76, 0.78, and 0.75). It can be concluded that the fractal dimension values and geometry characteristics of landslides would be useful indices for the management of hazardous areas, susceptible slopes, land use planning, and landslide hazard mitigation.  相似文献