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Titlebook: Learning Landscape Ecology; A Practical Guide to Sarah E. Gergel,Monica G. Turner Textbook 2017Latest edition Springer-Verlag New York 2017

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發(fā)表于 2025-3-21 19:41:13 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Learning Landscape Ecology
副標(biāo)題A Practical Guide to
編輯Sarah E. Gergel,Monica G. Turner
視頻videohttp://file.papertrans.cn/583/582757/582757.mp4
概述Utilizes examples, data and authors around the world to communicate to a more global audience.Provides a user-friendly translation of challenging quantitative techniques such as graph theory, spatial
圖書(shū)封面Titlebook: Learning Landscape Ecology; A Practical Guide to Sarah E. Gergel,Monica G. Turner Textbook 2017Latest edition Springer-Verlag New York 2017
描述This title meets a great demand for training in spatial analysis tools accessible to a wide audience. Landscape ecology continues to grow as an exciting discipline with much to offer for solving pressing and emerging problems in environmental science. Much of the strength of landscape ecology lies in its ability to address challenges over large areas, over spatial and temporal scales at which decision-making often occurs. As the world tackles issues related to sustainability and global change, the need for this broad perspective has only increased. Furthermore, spatial data and spatial analysis (core methods in landscape ecology) are critical for analyzing land-cover changes world-wide. While spatial dynamics have long been fundamental to terrestrial conservation strategies, land management and reserve design, mapping and spatial themes are increasingly recognized as important for ecosystem management in aquatic, coastal and marine systems.?.This second edition is purposefully more applied and international in its examples, approaches, perspectives and contributors. It includes new advances in quantifying landscape structure and connectivity (such as graph theory), as well as labs
出版日期Textbook 2017Latest edition
關(guān)鍵詞Landscape analysis; landscape change; sustainable landscapes; spatial modeling; spatial resilience; spati
版次2
doihttps://doi.org/10.1007/978-1-4939-6374-4
isbn_softcover978-1-4939-6372-0
isbn_ebook978-1-4939-6374-4
copyrightSpringer-Verlag New York 2017
The information of publication is updating

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Simulating Management Actions and Their Effects on Forest Landscape Pattern scales often are not feasible for political, economic, social and logistical reasons. Opportunistic studies of change (e.g., after a large fire) are often confounded by uncontrolled factors. For these reasons, changes in landscape pattern are often studied using simulation models. This lab will.
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nging quantitative techniques such as graph theory, spatial This title meets a great demand for training in spatial analysis tools accessible to a wide audience. Landscape ecology continues to grow as an exciting discipline with much to offer for solving pressing and emerging problems in environment
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Introduction to Markov Modelsainst which to assess alternative management scenarios or test hypotheses. There is a spectrum of ways to consider landscape change, ranging from simple and readily interpretable, to more realistic and less tractable. The goals of this lab are to.
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Regional and Continental-Scale Perspectives on Landscape Pattern relationships involves landscape comparisons among and within regions. Despite many advances in landscape pattern analysis, informed selection of landscapes for studying pattern–process relationships in real-world situations remains challenging. This lab explores these challenges with objectives designed to enable students to.
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Introduction to Remote Sensingderstanding these fundamental aspects of remote sensing will assist landscape ecologists in understanding and distinguishing the diversity and heterogeneity of land cover types in their study regions and better assess how landscapes might have changed over time. This chapter will enable students to.
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Characterizing Categorical Map Patterns Using Neutral Landscape Modelsndscape models have led to new understanding about habitat connectivity thresholds and the influence of landscape composition on spatial configuration (see Gardner and Urban, Landsc Ecol 22:15–29, 2007 for a review), and they offer a practical means of generating multiple landscape maps with similar statistical properties. This lab is designed to.
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