Spatial Thinking in Environmental Contexts Maps, Archives, and Timelines
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- Taschenbuch ausgewählt
- eBook
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Sprache:Englisch
Fr. 89.90
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
31.05.2023
Abbildungen
schwarz-weiss Illustrationen, Tabellen, schwarz-weiss
Herausgeber
Arlinghaus Sandra Lach + weitereVerlag
Taylor & FrancisSeitenzahl
248
Maße (L/B)
23.4/15.6 cm
Gewicht
421 g
Sprache
Englisch
ISBN
978-1-138-74731-9
Spatial Thinking in Environmental Contexts: Maps, Archives, and Timelines cultivates the spatial thinking "habit of mind" as a critical geographical view of how the world works, including how environmental systems function, and how we can approach and solve environmental problems using maps, archives, and timelines. The work explains why spatial thinking matters as it helps readers to integrate a variety of methods to describe and analyze spatial/temporal events and phenomena in disparate environmental contexts. It weaves together maps, GIS, timelines, and storytelling as important strategies in examining concepts and procedures in analyzing real-world data and relationships. The work thus adds significant value to qualitative and quantitative research in environmental (and related) sciences.
Features
- Written by internationally renowned experts known for taking complex ideas and finding accessible ways to more broadly understand and communicate them.
- Includes real-world studies explaining the merging of disparate data in a sensible manner, understandable across several disciplines.
- Unique approach to spatial thinking involving animated maps, 3D maps, GEOMATs, and story maps to integrate maps, archives, and timelines-first across a single environmental example and then through varied examples.
- Merges spatial and temporal views on a broad range of environmental issues from traditional environmental topics to more unusual ones involving urban studies, medicine, municipal/governmental application, and citizen-scientist topics.
- Provides easy to follow step-by-step instructions to complete tasks; no prior experience in data processing is needed.
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