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Titlebook: Environmental Change in South Asia; Essays in Honor of M Anup Saikia,Pankaj Thapa Book 2022 The Editor(s) (if applicable) and The Author(s)

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發(fā)表于 2025-3-21 18:54:52 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Environmental Change in South Asia
副標(biāo)題Essays in Honor of M
編輯Anup Saikia,Pankaj Thapa
視頻videohttp://file.papertrans.cn/313/312560/312560.mp4
概述Adds to the limited literature available on countries like Nepal, Bhutan, and Myanmar.Uses remote sensing datasets and geographic information systems to analyze current environmental issues.Includes a
圖書封面Titlebook: Environmental Change in South Asia; Essays in Honor of M Anup Saikia,Pankaj Thapa Book 2022 The Editor(s) (if applicable) and The Author(s)
描述.Studies on South Asia are an emerging interdisciplinary field, this volume expands on the currently limited literature available on South Asia and focuses on the regions environmental, climatic and natural resource base by looking at case studies from Nepal, India and Bangladesh. The book contains twelve chapters which deal with various environmental challenges, such as the impacts of climate change on floods and droughts, population structure and regeneration dynamics of dominant? treeline species, environmental changes and rural livelihoods, and change analysis and impacts of hard coastal structures. .Apart from the various thematic areas and diversity of geographical coverage, most of the studies also demonstrate the application of geospatial techniques for the collection of environmental data, and the use of GIS for spatial analysis of the data. The specific application of geospatial techniques and methods includes NDVI, NDWI, NDBI, SMI, SPOT-VGT NDVI, environmental flow, distribution and trend estimation of tropospheric formaldehyde, vegetation sensitivity to climate change, variability of tropospheric? ozone, and geo-environmental problems...The contributors are seasoned res
出版日期Book 2022
關(guān)鍵詞South Asian studies; Remote Sensing; natural resources; climate change case studies; GIS; Environmental d
版次1
doihttps://doi.org/10.1007/978-3-030-47660-1
isbn_softcover978-3-030-47662-5
isbn_ebook978-3-030-47660-1
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Assessment of Climate Change Impacts on Floods and Low Flows of the Brahmaputra River,ncrease in all three rivers. The frequency of occurrence of flood flows is likely to increase and that of low flows are likely to decrease, especially near the end of this century. The projections presented in this article can be useful in adaptation planning as well as in supporting discussions on
地板
發(fā)表于 2025-3-22 05:10:22 | 只看該作者
Population Structure and Regeneration Dynamics of Three Dominant Treeline Species from Treeline Ecoogical techniques to obtain age information. The population age structure was analyzed using a static life table and survivorship curves. All three species showed the reverse J-shaped age distribution indicative of undisturbed forests with sustainable regeneration. Young individuals mostly dominated
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,Long-Term Shoreline Change Analysis and Impact of Hard Coastal Structures on Shorelines—A Case Studh between land and water boundaries clearly. The shorelines were demarcated and digitized using various sources including LANDSAT, LISS and Google Earth Imageries. The datasets were saved based on the standard format of (DD/MM/YYYY) for analysis. The erosion and accretion rates have been calculated
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Reassessing the Karakoram Through Historical Archives,ure to present the evolution of the geographical term ‘the Karakoram’ and its spatial extent based on historical archives. We also provide a digital outline of the Karakoram region using GIS tools based on descriptive enumerations of the Royal Geographical Society (RGS) and the Survey of India (SoI)
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發(fā)表于 2025-3-23 08:05:42 | 只看該作者
Vegetation Sensitivity to Changing Climate in Bangladesh Using SPOT-VGT NDVI Time Series Data,lly distributed random points in Bangladesh for the same period. A Pearson’s correlation coefficient was used to define the relationship of monthly growing season NDVI with monthly rainfall and temperature derived from CRU TS 3.2 datasets. And analysis of 30- and 60-day lag rainfall was also figured
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