This PDF file contains the front matter associated with SPIE Proceedings Volume 7460, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

Wavelength beam combining was used to co-propagate beams from 28 elements in a linear array of distributedfeedback quantum cascade lasers (DFB-QCLs). The overlap of the beams in the far-field is improved using wavelength beam combining; the beam-quality product of the array, defined as the product of near-field spot size and far-field divergence for the entire array, was improved by a factor of 21. We measured the absorption spectrum of isopropanol at a distance of 6 m from the laser arrays, demonstrating the efficacy of wavelength beam combined DFB-QCL arrays for remote sensing.

A compact, widely tunable semiconductor based water vapor differential absorption lidar (DIAL) has been built and tested at Montana State University (MSU). The laser transmitter uses a tunable external cavity diode laser (ECDL) with a center wavelength of 830 nm to injection seed two cascaded tapered semiconductor optical amplifier (SOA), producing 1.5 micro joule pulses at a pulse repetition rate and pulse width duration of 20 kHz and 1000 ns respectively, allowing for water vapor number density retrievals up to approximately 4 km. Water vapor number density profiles collected with the MSU water vapor DIAL will be compared with co-located radiosonde measurements, demonstrating the instruments ability to measure daytime and nighttime water vapor profiles in the lower troposphere.

The Green-house gas Observation SATellite (GOSAT) was launched to determine the continental CO₂ inventories. Its sensor is based on a passive remote sensing technique developed to achieve less than 1% relative accuracy for atmospheric CO₂ measurements. Meanwhile, a laser remote sensor with the differential absorption spectrometry has been developed for a candidate of a future space-based mission to observe the atmospheric CO₂ or other trace gases. A prototype of the newly developed active remote sensor has been performed to demonstrate a properly validated performance for ground-based and airborne systems. This study shows the results of the in-house and field measurements. The in-house measurement demonstrated the linearity with the correlation coefficient of over 0.99 between the instrumental response and the known CO₂ density in the cell. The diurnal variation obtained from our system is consistent (correlation coefficient of 0.95) with that of multi-positioned in situ sensors, indicates the spatial responsibility of the atmospheric CO2 obtained from our remote sensor with two ~3-km observation paths.

New airborne LiDAR (Light Detection and Ranging) measurement systems, like the FLI-MAP 400 System, make it possible to obtain high density data containing far more information about single objects, like trees, than traditional airborne laser systems. Therefore, it becomes feasible to analyze geometric properties of trees on the individual object level. In this paper a new 3-step strategy is presented to calculate the stem diameter of individual natural trees at 1.3m height, the so-called breast height diameter, which is an important parameter for forest inventory and flooding simulations. Currently, breast height diameter estimates are not obtained from direct measurements, but are derived using species dependent allometric constraints. Our strategy involves three independent steps: 1. Delineation of the individual trees as represented by the LiDAR data, 2. Skeletonization of the single trees, and 3. Determination of the breast height diameter computing the distance of a suited subset of LiDAR points to the local skeleton. The use of a recently developed skeletonization algorithm based on graph-reduction is the key to the breast height measurement. A set of four relevant test cases is presented and validated against hand measurements. It is shown that the new 3-step approach automatically derives breast height diameters deviating only 10% from hand measurements in four test cases. The potential of the introduced method in practice is demonstrated on the fully automatic analysis of a LiDAR data set representing a patch of forest consisting of 49 individual trees.

The VisibleWind^TM initiative has sponsored the development and demonstration of a simple balloon tracking system for low altitude wind profile measurements using laser rangefinders, a surveying station, and small (0.25 m diameter) lightweight balloons. Experiments on balloon trajectories demonstrate that laser range detection (± 0.5 m) combined with azimuth and elevation measurements is a simple, accurate, and inexpensive alternative to other wind profiling methods. The maximum detection range has been increased to 2200 m using retroreflector tape on the balloons. Nighttime tracking is facilitated by low power LEDs. Small balloons with low ascent rates and Reynolds numbers are preferred to avoid the large trajectory fluctuations previously observed with large balloons. Under conditions of "light and variable winds", the wind profile features observed by VisibleWind^TM include the frequent onset of shear at altitudes 100 -200 m, 1-3 m/s velocity transitions across atmospheric layers only 10 -20 m thick, and rotation of wind direction exceeding 180 degrees in the altitude range 300 - 500 m. Wind speed and direction results are compared with simultaneous sodar measurements. The profiling resolution is greatly improved using a laser rangefinder, Impulse XL-200, with automatic coordinate and time recording; however, balloon tracking is still man-in-the-loop. Planned improvements include automation of the tracking system itself, so trajectory points are collected automatically at 1 Hz or faster. This ValidWind^TM system is a precise and adaptable means for characterizing highly variable wind fields for wind energy, micrometeorology, and air quality studies.

Compared to microwave radar systems, chaotic ladar has the potential for providing a range resolution well into the mm range. The purpose of this project is to determine the signal processing schemes required to extract range and Doppler information from a chaotic signal scattered by environmental targets. Specifically, a ladar would be driven into the coherence collapse through an external optical resonator, thus generating a chaotic electromagnetic field with a wide rms bandwidth of several GHz. The reflected field would be processed though optical correlation to extract range and Doppler information. Simulations show that the power spectral density properties of the field are dependent on the Lyapunov exponent of the chaotic field, which be exploited to obtain optimum range resolution. A complete statistical analysis of the wideband ambiguity function of the field reveals that the signal has better performance than noise-like signals generated via electro-optic amplitude modulation, thus allowing for high resolution imaging of terrains with pseudo random reflectivity variations.

The distributions of aerosol and planetary boundary layer (PBL) heights are presented from CALIOP/CALIPSO (Cloud- Aerosol Lidar with Orthogonal Polarization) and ground-based lidar measurements. We initially assess the approach of using the MODIS-retrieved aerosol optical depth over ocean to constrain lidar-ratio (extinction-to-backscatter ratio) and extinction profile at wavelength 532-nm. Statistical comparisons of cloud and aerosol layers are performed with the 20- day cases. We find in general excellent correlations exist between both cloud-base and top even for multiple deck cases that are not to close. In the clear skies, the CALIPSO-derived aerosol-layer-tops are consistent with ground-lidar derived PBL heights although the accuracy degrades if capped by cloud layers. In addition, PBL heights are derived from the CALIPSO level-1B profiles and mapped over the continental US. Finally, we perform a detailed comparison for a smoke plume event including aerosol classification, derivation of extinction profile and lidar ratio.

In this paper, the properties of Low-level clouds are explored with a Raman-elastic lidar. In particular, we examine two complementary methods to measure thin cloud optical depth (COD). The first is direct integration of Raman Derived extinction while the second method utilizes a regression technique. We show that if we correct for aerosol influences the regression method for low cloud optical depth can be dramatically improved. Furthermore, estimates of extinction to backscatter ratio can be made within the cloud. We find that when the lidar ratio in cloud is averaged over the vertical extent, an S ratio on the order of 20 sr is found which is consistent with conventional water phase cloud droplet models. Key words: Low cloud, optical depth, Raman lidar. Finally, correlations between aerosol loading below clouds and small droplets in cloud interior are studied illustrating possible connections between aerosols and small droplet seeding.

With the dramatically climate changing we are facing today atmospheric monitoring is of major importance. Several atmospheric monitoring instruments are used for measuring atmospheric composition, optical coefficients, PM2.5, aerosol optical depth, size distribution, PBL height and many other parameters. However an inexpensive method of determining these parameters is by use of models and one model that depicts the aerosol dynamics in the atmosphere is the Community Multi-scale Air Quality (CMAQ) model. Our paper is focused on converting CMAQ retrieval outputs into optical coefficients that can then be comparing the lidar, AERONET and TEOM measurements performed at City College of the City University of New York . Differences between the full approach and parameterized methods such as the MALM formula used in AIR-NOW are observed and comparisons with AERONET show the full modeling is in general superior to the MALM formula.