کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6538328 1421026 2018 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An observational and theoretical framework for interpreting the landscape palimpsest through airborne LiDAR
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک جنگلداری
پیش نمایش صفحه اول مقاله
An observational and theoretical framework for interpreting the landscape palimpsest through airborne LiDAR
چکیده انگلیسی
High resolution airborne Light Detection and Ranging (LiDAR) has become a commonly used resource on a global scale to study landscapes and associated cultural features, especially in areas covered by dense forest. While LiDAR allows for unprecedented views of the terrain beneath the forest canopy, and of landscapes at broad scales generally, few studies have provided an examination of features within theoretical frameworks used to describe landscapes, or have acknowledged LiDAR data as a palimpsest. Any derivative imagery from LiDAR data depicts a moment in time of a contemporary landscape with topographic traces of cultural and physical elements from a range of time periods within and beyond human history. In order to effectively interpret the landscape as represented through LiDAR, it is critical to supplement this data with multiple contextual sources and a more robust theoretical geographic framework. While the concept of landscape as a palimpsest is well known, for the first time in hyper-realistic form we can see and physically interpret that palimpsest, along with the traces of data processing and visualization that we ourselves add to the digital landscape palimpsest in an effort to interpret it. This study provides a critical examination of the LiDAR landscape as a palimpsest, summarizes studies that have used a combination of LiDAR and supplementary resources, and provides observational examples from the northeastern United States, thus providing a practice-based observational and theoretical framework from which other landscapes and associated cultural features can be studied using LiDAR.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Geography - Volume 91, February 2018, Pages 32-44
نویسندگان
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