Polarized lidar reflectance measurements of vegetation at near-infrared and green wavelengths
25 Jul 2005-International Journal of Infrared and Millimeter Waves (Kluwer Academic Publishers-Plenum Publishers)-Vol. 26, Iss: 8, pp 1175-1194
TL;DR: In this article, the authors presented preliminary ground-based lidar reflectance measurements on a variety of deciduous and coniferous trees under fully foliated conditions with a view towards tree species discrimination.
Abstract: There is growing interest in the use of lidar for remote sensing of vegetation owing to the emergence of reliable and rugged lasers and highly sensitive detectors. Lidar remote sensing has a distinct advantage over conventional techniques in vegetation remote sensing due to its capability for three-dimensional characterization of vegetative targets. The Multiwavelength Airborne Polarimetric Lidar (MAPL) system was developed primarily for vegetation remote sensing applications from an airborne platform of up to 1,000 -m altitude. The lidar system has full waveform capture and polarimetric measurement capability at two wavelengths in the near-infrared (1064 nm) and the green (532 nm) spectral regions. This study presents preliminary ground-based lidar reflectance measurements on a variety of deciduous and coniferous trees under fully foliated conditions with a view towards tree species discrimination. Variations in the reflectance characteristics of selected deciduous trees under unfoliated and fully foliated conditions were also investigated. Our study reveals distinct differences in the reflectance characteristics of various trees.
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TL;DR: In this paper, the relationship between a laser-scanner-derived spectral index, using near infrared (1063 nm) and middle infrared (1545 nm) wavelengths, and the EWT of individual leaves was determined.
150 citations
TL;DR: A model-based analysis demonstrates that the LiDAR waveforms cannot only capture the tree height information but also picks up the seasonal and vertical variation of NDVI inside the tree canopy.
Abstract: The first demonstration of a multispectral light detection and ranging (LiDAR) optimized for detailed structure and physiology measurements in forest ecosystems is described. The basic principle is to utilize, in a single instrument, both the capacity of multispectral sensing to measure plant physiology [through normalized difference vegetation index (NDVI) and photochemical reflectance index (PRI)] with the ability of LiDAR to measure vertical structure information and generate “hot spot” (specular) reflectance data independent of solar illumination. A tunable laser operated at four wavelengths (531, 550, 660, and 780 nm) was used to measure profiles of the NDVI and the PRI. Laboratory-based measurements were conducted for live trees, demonstrating that realistic values of the indexes can be measured. A model-based analysis demonstrates that the LiDAR waveforms cannot only capture the tree height information but also picks up the seasonal and vertical variation of NDVI inside the tree canopy.
100 citations
Cites background from "Polarized lidar reflectance measure..."
...Digital Object Identifier 10.1109/LGRS.2011.2113312 provide unprecedented information, both as a detailed sampling tool and for calibration of passively acquired multispectral data....
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TL;DR: In this article, three radiometrically calibrated TLS systems with differing laser wavelengths were investigated using commercially available hardware and software, and the classification performance of the multispectral TLS intensity and calibrated reflectance datasets evaluated and compared to classification performed with passive visible wavelength imagery.
Abstract: Terrestrial laser scanning (TLS) is a valuable tool for creating virtual 3D models of geological outcrops to enable enhanced modeling and analysis of geologic strata. Application of TLS data is typically limited to the geometric point cloud that is used to create the 3D structure of the outcrop model. Digital photography can then be draped onto the 3D model, allowing visual identification and manual spatial delineation of different rock layers. Automation of the rock type identification and delineation is desirable, and recent work has investigated the use of terrestrial hyperspectral photography for this purpose. However, passive photography, whether visible or hyperspectral, presents several complexities, including accurate spatial registration with the TLS point cloud data, reliance on sunlight for illumination, and radiometric calibration to properly extract spectral signatures of the different rock types. As an active remote sensing method, a radiometrically calibrated TLS system offers the potential to directly provide spectral information for each recorded 3D point, independent of solar illumination. Therefore, the practical application of three radiometrically calibrated TLS systems with differing laser wavelengths, thereby achieving a multispectral dataset in conjunction with 3D point cloud data, is investigated using commercially available hardware and software. The radiometric calibration of the TLS intensity values is investigated and the classification performance of the multispectral TLS intensity and calibrated reflectance datasets evaluated and compared to classification performed with passive visible wavelength imagery. Results indicate that rock types can be successfully identified with radiometrically calibrated multispectral TLS data, with enhanced classification performance when fused with passive visible imagery.
67 citations
TL;DR: In this article, a tractor-mounted dual-wavelength laser system was used to evaluate the potential of an additional red reference wavelength to improve laser based estimates of foliar N by calculating laser spectral indices based on ratio combinations of green laser return intensity (GLRI) and red laser return intensities (RLRI).
Abstract: Advanced technologies for improved nitrogen (N) fertilizer management are paramount for sustainably meeting future food demands. Green laser systems that measure pulse return intensity can provide more reliable information about foliar N than can traditional passive remote sensing devices during the critical early crop growth stages (e.g., before canopy closure when vegetation and soil signals are spectrally mixed) when further decisions regarding N management can be made. However, current green laser systems are not designed for agricultural applications and only employ a single green laser wavelength, which may limit applications because many factors that require normalization techniques can affect pulse return intensity. Here, we describe the design of a tractor-mountable, green (532 nm)- and red (658 nm) dual wavelength laser system and evaluate the potential of an additional red reference wavelength to improve laser based estimates of foliar N by calculating laser spectral indices based on ratio combinations of green laser return intensity (GLRI) and red laser return intensity (RLRI). We hypothesized that such laser spectral indices aid in accounting for factors that confound laser based foliar N estimates including variations in leaf angle, measurement distance, soil returns, and mixed edge returns. Leaf level measurements in winter wheat ( Triticum aestivum ) revealed that the two laser spectral indices improved the relationship with foliar N ( r 2 > 0.71, RMSE r 2 = 0.47, RMSE = 0.38%). Laboratory measurements also showed that laser spectral indices reduced the effect of measurement distance on laser readings and allowed leaf returns to be better separated from edge returns and soil returns. However, laboratory measurements showed that laser spectral indices did not account for variations in leaf angle, possibly explaining the weak relationships ( r 2 r 2 = 0.65, RMSE = 0.37%) alone. Laboratory measurements suggest that the better performance of GLRI compared to ratio-based laser spectral indices may result from pronounced differences in the leaf-level bidirectional reflectance distribution factor (BRDF leaf ) between the green and red laser wavelengths, thus confounding leaf angle effects so that they are not cancelled when calculating laser spectral indices. This finding suggests that the small spot size of the laser pulses (⩽5 mm diameter) interacts with BRDF leaf at very fine scales, therefore causing differential, wavelength-specific scattering effects. Additional study of BRDF leaf at the mm scale is therefore warranted, and should be carefully considered in future development and use of multi-wavelength laser systems for remotely sensing foliar biochemistry.
47 citations
25 Jul 2010
TL;DR: ICESat-2 will employ several of the technologies advanced by SIMPL, including micropulse, single photon ranging in a multi-beam, push-broom configuration operating at 532 nm.
Abstract: The Slope Imaging Multi-polarization Photon-counting Lidar is an airborne instrument developed to demonstrate laser altimetry measurement methods that will enable more efficient observations of topography and surface properties from space. The instrument was developed through the NASA Earth Science Technology Office Instrument Incubator Program with a focus on cryosphere remote sensing. The SIMPL transmitter is an 11 KHz, 1064 nm, plane-polarized micropulse laser transmitter that is frequency doubled to 532 nm and split into four push-broom beams. The receiver employs single-photon, polarimetric ranging at 532 and 1064 nm using Single Photon Counting Modules in order to achieve simultaneous sampling of surface elevation, slope, roughness and depolarizing scattering properties, the latter used to differentiate surface types. Data acquired over ice-covered Lake Erie in February, 2009 are documenting SIMPL's measurement performance and capabilities, demonstrating differentiation of open water and several ice cover types. ICESat-2 will employ several of the technologies advanced by SIMPL, including micropulse, single photon ranging in a multi-beam, push-broom configuration operating at 532 nm.
35 citations
Cites methods from "Polarized lidar reflectance measure..."
...A subsequent modification to that instrument incorporating full waveform recording enabled polarimetric ranging at 532 and 1064 nm [7,8]....
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References
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TL;DR: 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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TL;DR: In this article, a large-footprint airborne scanning lidar was used to recover forest structural characteristics across a spectrum of land cover types from pasture to secondary and primary tropical forests.
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TL;DR: In this paper, a method of predicting two forest stand structure attributes, basal area and aboveground biomass, from measurements of forest vertical structure was developed and tested using field and remotely sensed canopy structure measurements.
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553 citations
TL;DR: In this paper, the classification of Scots pine versus Norway spruce on an individual tree level using features extracted from airborne laser scanning data was performed. And the results demonstrated the ability to discriminate between pine and spruce using laser data.
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