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  1. Book ; Online ; E-Book: COVID-19 pandemic trajectory in the developing world

    Mishra, Mukunda / Singh, R. B.

    exploring the changing environmental and economic milieus in India

    (Advances in Geographical and Environmental Sciences,)

    2021  

    Abstract: We are witnessing an unprecedented global outbreak of COVID-19, which has been devastating in its consequences. Beyond the acute health hazard, the pandemic has carried with it other threats for mankind associated with the human economy, society, culture, ...

    Author's details Mukunda Mishra, R.B. Singh, editors
    Series title Advances in Geographical and Environmental Sciences,
    Abstract We are witnessing an unprecedented global outbreak of COVID-19, which has been devastating in its consequences. Beyond the acute health hazard, the pandemic has carried with it other threats for mankind associated with the human economy, society, culture, psychology and politics. Amidst these multifarious dimensions of the pandemic, it is high time for global solidarity to save humankind. Human society, its ambient environment, the process of socio-economic development, and politics and power – all are drivers to establish the world order. All these parameters are intimately and integrally related. The interconnections of these three driving forces have a significant bearing on life, space and time. In parallel, the interrelationship between all these drivers is dynamic, and they are changed drastically with time and space. The statistics serve to align the thought, based on which social scientists need to understand the prevailing equation to project the unforeseen future. The trajectory of the future world helps in planning and policymaking with a scientific direction. The practitioners of all academic disciplines under the umbrella of the social sciences need a common platform to exchange ideas that may be effective in the sustainable management of the crisis and the way forward after it is mitigated. This book provides multidisciplinary contributions for expressing the solidarity of academic knowledge to fight against this global challenge. It is crucial that there should be an on-going discussion and exchange of ideas, not only from the perspective of the current times but keeping in view the preparedness for unforeseen post-COVID crises as well.
    Keywords COVID-19 Pandemic, 2020-/Economic aspects
    Subject code 362.1962414
    Language English
    Size 1 online resource (XXXII, 355 p. 98 illus., 93 illus. in color.)
    Edition 1st ed. 2021.
    Publisher Springer
    Publishing place Gateway East, Singapore
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 981-336-440-8 ; 981-336-439-4 ; 978-981-336-440-0 ; 978-981-336-439-4
    DOI 10.1007/978-981-33-6440-0
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article: A multistage hybrid model for landslide risk mapping: tested in and around Mussoorie in Uttarakhand state of India

    Mishra, Mukunda / Sarkar, Tanmoy

    Environmental earth sciences. 2020 Oct., v. 79, no. 19

    2020  

    Abstract: The study aims to develop a hybrid model approach for the assessment of the landslide (LS) risk qualitatively. It involves multiple consecutive stages of statistical prediction, machine learning, and mapping in the GIS environment. At the first stage, a ... ...

    Abstract The study aims to develop a hybrid model approach for the assessment of the landslide (LS) risk qualitatively. It involves multiple consecutive stages of statistical prediction, machine learning, and mapping in the GIS environment. At the first stage, a landslide susceptibility map has been developed using the analytic hierarchy process (AHP) algorithm, coupled with the binary logistic regression (BLR) technique. The AHP model incorporates 11 geo-hydrological and environmental variables as predictors sourced from remote-sensing datasets to generate the LS susceptibility as output. Twenty-three field-based validation locations validate the test result. Pearson's correlation coefficient (r) between the observed ([Formula: see text]) and predicted ([Formula: see text]) values of LS susceptibility is 0.928 at 0.01 level of significance. At the next stage, the LS risk is evaluated considering the ‘risk trio,’ i.e., the combination of the hazard, exposure, and vulnerability. This stage involves the transformation of a range of qualitative datasets to the virtual workspace of machine learning. The landslide risk output has been predicted with an initial fuzzy model, incorporating a set of 32 rules for membership functions (MF). This initial model uses randomly selected 20% datasets to tailor the fuzzy rules through the adaptive neuro-fuzzy interface (ANFIS). The training to ANFIS results in framing 120 fuzzy rules for the best possible prediction of the outcome. The final LS risk map from the ANFIS output shows that more than 70% area is under high-to-very high LS risk. The model is tested in a 5′ × 5′ grid around the famous hill station Mussoorie in the state of Uttarakhand, India. The model exhibits a satisfactory level of accuracy for the present-study area, which has made us confident to recommend it. The multistage model is worthy of being applied for landslide risk mapping for the similar kinds of study areas, and also for other areas of landslide with necessary customization as deemed necessary.
    Keywords algorithms ; data collection ; fuzzy logic ; landslides ; prediction ; regression analysis ; remote sensing ; risk ; risk assessment ; India
    Language English
    Dates of publication 2020-10
    Size p. 449.
    Publishing place Springer Berlin Heidelberg
    Document type Article
    Note NAL-AP-2-clean
    ZDB-ID 2493699-6
    ISSN 1866-6299 ; 1866-6280
    ISSN (online) 1866-6299
    ISSN 1866-6280
    DOI 10.1007/s12665-020-09180-3
    Database NAL-Catalogue (AGRICOLA)

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