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Lidar Remote Sensing for Ecosystem Studies

Michael A. Lefsky, +3 more
- 01 Jan 2002 - 
- Vol. 52, Iss: 1, pp 19-30
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TLDR
Lidar has been shown to accurately estimate aboveground biomass and leaf area index even in those high-biomass ecosystems where passive optical and active radar sensors typically fail to do so as discussed by the authors.
Abstract
Articles R emote sensing has facilitated extraordinary advances in the modeling, mapping, and understanding of ecosystems. Typical applications of remote sensing involve either images from passive optical systems, such as aerial photography and Landsat Thematic Mapper (Goward and Williams 1997), or to a lesser degree, active radar sensors such as RADARSAT (Waring et al. 1995). These types of sensors have proven to be satisfactory for many ecological applications , such as mapping land cover into broad classes and, in some biomes, estimating aboveground biomass and leaf area index (LAI). Moreover, they enable researchers to analyze the spatial pattern of these images. However, conventional sensors have significant limitations for ecological applications. The sensitivity and accuracy of these devices have repeatedly been shown to fall with increasing aboveground biomass and leaf area index (Waring et al. 1995, Carlson and Ripley 1997, Turner et al. 1999). They are also limited in their ability to represent spatial patterns: They produce only two-dimensional (x and y) images, which cannot fully represent the three-dimensional structure of, for instance, an old-growth forest canopy.Yet ecologists have long understood that the presence of specific organisms, and the overall richness of wildlife communities, can be highly dependent on the three-dimensional spatial pattern of vegetation (MacArthur and MacArthur 1961), especially in systems where biomass accumulation is significant (Hansen and Rotella 2000). Individual bird species, in particular, are often associated with specific three-dimensional features in forests (Carey et al. 1991). In addition, other functional aspects of forests, such as productivity, may be related to forest canopy structure. Laser altimetry, or lidar (light detection and ranging), is an alternative remote sensing technology that promises to both increase the accuracy of biophysical measurements and extend spatial analysis into the third (z) dimension. Lidar sensors directly measure the three-dimensional distribution of plant canopies as well as subcanopy topography, thus providing high-resolution topographic maps and highly accurate estimates of vegetation height, cover, and canopy structure. In addition , lidar has been shown to accurately estimate LAI and aboveground biomass even in those high-biomass ecosystems where passive optical and active radar sensors typically fail to do so. The basic measurement made by a lidar device is the distance between the sensor and a target surface, obtained by determining the elapsed time between the emission of a short-duration laser pulse and the arrival of the reflection of that pulse (the return signal) at the sensor's receiver. Multiplying this …

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Citations
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Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art

TL;DR: A general framework of DL for RS data is provided, and the state-of-the-art DL methods in RS are regarded as special cases of input-output data combined with various deep networks and tuning tricks.
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Remote sensing for biodiversity science and conservation

TL;DR: In this article, the authors proposed indirect approaches to derive meaningful environmental parameters from biophysical characteristics that can be used to identify species assemblages or even identifying species of individual trees.
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Field high-throughput phenotyping: the new crop breeding frontier

TL;DR: Recent advances in field HTPPs are reviewed, which should combine at an affordable cost, high capacity for data recording, scoring and processing, and non-invasive remote sensing methods, together with automated environmental data collection.
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The potential and challenge of remote sensing‐based biomass estimation

TL;DR: In this article, a review of previous research on remote sensing-based biomass estimation approaches and a discussion of existing issues influencing biomass estimation are valuable for further improving biomass estimation performance, especially in those study areas with complex forest stand structures and environmental conditions.
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Putting the "landscape" in landscape genetics.

TL;DR: A definition for the term ‘landscape genetics’ is offered, an overview of the landscape genetics literature is provided, guidelines for appropriate sampling design and useful analysis techniques are given, and future directions in the field are discussed.
References
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Journal ArticleDOI

On the relation between NDVI, fractional vegetation cover, and leaf area index

TL;DR: In this paper, a simple radiative transfer model with vegetation, soil, and atmospheric components is used to illustrate how the normalized difference vegetation index (NDVI), leaf area index (LAI), and fractional vegetation cover are dependent.
Journal ArticleDOI

Pattern and process in the plant community

Alex S. Watt
- 01 Dec 1947 - 
Book

Fire Ecology of Pacific Northwest Forests

James K. Agee
TL;DR: The Fire Ecology of Pacific Northwest Forests as discussed by the authors is a historical, analytical, and ecological approach to the effects and use of fire in Pacific Northwest wildlands, which provides an essential base of knowledge for all others interested in wildland management who wish to understand the ecological effects of fire.
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