Browsing by Subject "lidar"
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Item Application of Remote Sensing Technology and Ecological Modeling of Forest Carbon Stocks in Mt. Apo Natural Park, Philippines(2015-01-23) Leal, Ligaya RubasThis dissertation work explored the application of remote sensing technology for the assessment of forest carbon storage in Mt. Apo Natural Park. Biomass estimation is traditionally conducted using destructive sampling with high levels of uncertainty. A more accurate and non-destructive method for assessment of biomass level is imperative to characterize remaining forest cover. This research study aimed to: 1) examine the vegetation profile and estimate species-specific biomass of Mt. Apo Natural Park, 2) develop an algorithm to assess biomass in plot-level using a terrestrial lidar system (TLS), and 3) generate landscape-level biomass estimates using interferometric synthetic aperture radar (IFSAR). This research endeavors to provide answers to these questions: 1) how the 3 tropical allometries compare in estimating field collected species-level biomass and carbon stocks in three management zones?, 2) what are the significant terrestrial laser scanning-derived metrics to assess plot-level biomass?, and 3) to what degree of uncertainty can IFSAR estimate biomass at the landscape level? Field data was gathered from 1382 trees, covering 52 local species during fieldwork in July and August 2013. Twenty-six plots (30 m x 30 m) were sampled on three management zones: multiple use, strict protection and restoration. Local insurgency problems restricted the research team from sampling additional plots. Destructive sampling was not permitted inside the protected area, thus requiring biomass to be estimated via the use of referenced biomass from 3 allometric equations by relating tree height, diameter-at-breast height, and wood specificity volume. A vegetation profile across the park was generated using a canopy height map (CHM). Results showed that resampled IFSAR products can be used to characterize biomass and carbon storage at the landscape level. This research has demonstrated the adoption of IPCC?s Tier 2, a combination of field and remote sensing data in the assessment of available biomass levels in a tropical forest. The maps created can assist in providing information for biomass and carbon level in MANP for monitoring, reporting and verification in compliance with REDD requirements. Furthermore, this study can provide helpful information regarding policy implications for reforestation and afforestation activities. Results showed that resampled IFSAR products can be used to characterize biomass and carbon storage at the landscape level. This research has demonstrated the adoption of IPCC?s Tier 2, a combination of field and remote sensing data in the assessment of available biomass levels in a tropical forest. The maps created can assist in providing information for biomass and carbon level in MANP for monitoring, reporting and verification in compliance with REDD requirements. Furthermore, this study can provide helpful information regarding policy implications for reforestation and afforestation activities.Item Assessing Available Woody Plant Biomass on Rangelands with Lidar and Multispectral Remote Sensing(2012-07-16) Ku, Nian-WeiThe majority of biofuels are produced from corn and grain. The drawback to these sources of biofuels is the vast amount of cultivated land needed to produce substantial amounts of biofuel, potentially increasing the price of food and livestock products. Mesquite trees, a type of woody plant, are a proven source of bioenergy feedstock found on semi-arid lands. The overall objectives of this study were to develop algorithms for determining woody plant biomass on rangelands in Texas at plot-level using terrestrial lidar and at the local scale by integrating reference biomass and multispectral imagery. Terrestrial lidar offers a more efficient method for estimating biomass than traditional field measurements. Variables from the terrestrial lidar point cloud were compared to ground measurements of biomass to find a best fitting regression model. Two processing methods were investigated for analyzing the lidar point cloud data, namely: 1) percentile height statistics and 2) a height bin approach. Regression models were developed for variables obtained through each processing technique for estimating woody plant, above-ground biomass. Regression models were able to explain 81 percent and 77 percent of the variance associated with the aboveground biomass using percentile height statistics and height bins, respectively. The aboveground biomass map was generated by using the cokriging interpolation method with NDVI and ground biomass data. According to cross-validation, ordinary cokriging estimated biomass accurately (R^2 = 0.99). The results of this study revealed that terrestrial lidar can be used to accurately and efficiently estimate the aboveground biomass of mesquite trees in a semi-arid environment at plot level. Moreover, spatial interpolation techniques proved useful in scaling up biomass estimates to local scale.Item Deriving a Framework for Estimating Individual Tree Measurements with Lidar for Use in the TAMBEETLE Southern Pine Beetle Infestation Growth Model(2011-02-22) Stukey, Jared D.The overall goal of this study was to develop a framework for using airborne lidar to derive inputs for the SPB infestation growth model TAMBEETLE. The specific objectives were (1) to estimate individual tree characteristics of XY location, individual bole height (IBH), diameter at breast height (DBH), length of crown (CrHT), and age for use in TAMBEETLE; (2) to estimate individual tree age using lidar-estimated height and site index provided by the United States Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) Soil Survey Geographic Database (SSURGO); and (3) to compare TAMBEETLE simulation results using field measurements and lidarderived measurements as inputs. Diameter at breast height, individual bole height, and crown length were estimated using lidar with an error for mean measurements at plot level of 0.16cm, 0.19m, and 1.07m, respectively. These errors were within root mean square error (RMSE) for other studies at the study site. Age was estimated using the site index provided by SSURGO and the site index curves created for the study area with an RMSE of 4.8 years for mean plot age. Underestimation of tree height by lidar and error in the site index curve explained 91% of the error in mean plot age. TAMBEETLE was used to compare spot growth between a lidar-derived forest map and a forest map generated by TAMBEETLE, based on sample plot characteristics. The lidar-derived forest performed comparably to the TAMBEETLE generated forest. Using lidar to map forests can provide the large spatial extents of the TAMBEETLE generated forest while maintaining the spatially explicit forest characteristics, which were previously only available through field measurements.Item Forms and Distributions of Hurricane Ike Backflow and Scour Features: Bolivar Peninsula, Texas(2011-08-08) Potts, Michael KillgoreThe storm surge from Hurricane Ike inundated Bolivar Peninsula as well as pooled up (~4 meters above sea level) in the Galveston Bay System behind Bolivar. After the hurricane passed, this water flowed back over the peninsula for about 19 hours, causing a great deal of coastal destruction. Analysis of post-Hurricane Ike aerial photography and Lidar data revealed the development of dramatically different scour and backflow features in the beach and dune environments along Bolivar Peninsula, Texas. Using Ward's cluster analysis, the 454 identified features were grouped according to shape and size characteristics generated by an object-oriented shape analysis program. Five distinct groups of features emerged from the cluster analysis. Group 1 features were small and compact, distributed mostly in the west; Group 2 features were large and dendritic in nature, distributed where the peninsula was narrow. Group 3 features had a longshore orientation with many of them resembling piano keys, distributed in the east. Group 4 features were oriented longshore and ornate in shape. Many of them were similar in shape to Group 2 or 3 features though statistically different enough to be grouped alone; they were distributed mostly in the eastern half of the study area. Group 5 features tended to be elongated, oriented cross-shore, nonbranching, and distributed mostly in the east. At least four flow environments caused characteristic forms. The first flow environment is typified by seaward flowing water encountering a road parallel with the coastline. The water flowing over the road scours deeply on the leeward side (seaward side), denuding beach sediments down to the resistant mud layer (Groups 3 and 4). The second flow environment was caused by a geotube, which breached during the storm and channelized flow through the breaches (Groups 2 and 5). The third flow environment had a comparatively high elevation, high development, and shore-perpendicular roads (Group 2). The fourth flow environment was typified by wide beaches backed by dunes (lost in the storm) as well as flat vegetated areas. Water flowing seaward over the vegetation scoured deeply into troughs after it came off the vegetation (Groups 1, 3, and 4).Item Interactive Holographic Cinema(2012-07-16) Portales, ChristopherIn mainstream media and entertainment, holography is often misrepresented as single perspective non-stereoscopic imagery suggesting three-dimensionality. Traditional holographic artists, however, utilize a laser setup to record and reconstruct wavefronts to describe a scene in multi-perspective natural parallax vision ("auto-stereoscopic"). Although these approaches are mutually exclusive in practice, they share a similar goal of staging three-dimensional (3D) imagery for a window-like viewing experience. This thesis presents a non-waveform digital computer approach for recording, reconstructing, and experiencing holographic visualizations in a cinematic context. By recording 3D information from a scene using the structured light method, a custom computer program performs stereoscopic reconstruction in real-time during presentation. Artists and computer users could then use a hardware device, such as the Microsoft Kinect, to explore the holographic cinematic form interactively.Item Quantification of Salt Marsh Carbon Stocks: Integration of Remote Sensing Data and Techniques with Field Measurements(2013-12-02) Kulawardhana, Ranjani WRecent climatic change projections have increased scientific and public attention on the issues relating to carbon cycling patterns, its controls, and the importance of ecosystems in the cycling and sequestration process. Global carbon studies, however, primarily have focused on dry land ecosystems that extend over large areas and have not accounted for the relatively small and scattered, though highly carbon rich, ecosystems such as mangrove swamps and salt marshes. Using data from a Spartina alterniflora dominated salt marsh in Galveston, Texas this study integrates remote sensing data (multispectral and Light Detection and Ranging - lidar) with field measurements for the quantification of carbon pools in salt marsh ecosystems. Findings in this study show the capability of remote sensing data for the characterization of salt marsh terrain and vegetation heights and the estimation of above-ground biomass quantities. The best biomass prediction models using lidar heights reported considerably low errors, i.e. the percent root square errors (% RSEs) are close to 20%, which is the recommended error threshold for remote sensing based forest biomass prediction models. Our findings also demonstrate that lidar as compared to spectral data can provide better estimates of above-ground biomass and carbon, even in the herbaceous and low-relief context of a salt marsh. A clear zonation of terrain, vegetation characteristics and the distribution of biomass quantities within the marsh extent was also observed. Distribution of biomass quantities revealed linkages with the elevation. Variations in soil properties (i.e. carbon and bulk density) in the soil profile were linked to the temporal changes in soil carbon accumulations on the marsh surface, relative sea level history and resulting vegetation transitions as corroborated by historical aerial images. In general, the amounts of soil carbon stored in recently established Spartina alterniflora intertidal marshes were significantly lower than those that have remained in situ for a longer period of time. These findings indicate that, even though salt marshes can respond to relative sea level rise by migrating landward, their status as a carbon sink varies as a function of both space and time. Thus, in order to predict carbon in a wetland, researchers need to know not only the elevation, the relative sea level rise rate, and the accretion rate ? but also the history of land cover change and vegetation transition. Findings of this study contribute to carbon quantification efforts in these vulnerable ecosystems. Further, these findings will also contribute to the increased understanding of the capabilities of remote sensing datasets and techniques for the quantification of these important carbon stocks.Item Simulation of Lidar Return Signals Associated with Water Clouds(2010-01-14) Lu, JianxuWe revisited an empirical relationship between the integrated volume depolar- ization ratio, oacc, and the effective multiple scattering factor, -n, on the basis of Monte Carlo simulations of spaceborne lidar backscatter associated with homogeneous wa- ter clouds. The relationship is found to be sensitive to the extinction coefficient and to the particle size. The layer integrated attenuated backscatter is also obtained. Comparisons made between the simulations and statistics derived relationships of the layer integrated depolarization ratio, oacc, and the layer integrated attenuated backscatter, -n, based on the measurement by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite show that a cloud with a large effective size or a large extinction coefficient has a relatively large integrated backscatter and a cloud with a small effective size or a large extinction coefficient has a large integrated volume depolarization ratio. The present results also show that optically thin water clouds may not obey the empirical relationship derived by Y. X. Hu. and co-authors.Item Studying Clouds and Aerosols with Lidar Depolarization Ratio and Backscatter Relationships(2012-02-14) Cho, Hyoun-MyoungThis dissertation consists of three parts, each devoted to a particular issue of significant importance for CALIPSO lidar observation of depolarization ratio (delta) and backscatter (gamma?) to improve current understanding of the microphysical properties of clouds and aerosols. The relationships between depolarization ratio and backscatter allow us to retrieve particle thermodynamic phase and shape and/or orientation of aerosols and clouds. The first part is devoted to the investigation of the relationships between lidar backscatter and the corresponding depolarization ratio for different cloud classifications and aerosol types. For each cloud and aerosol types, layer-averaged backscatter and backscattering depolarization ratio from the CALIPSO measurements are discussed. The present results demonstrate the unique capabilities of the CALIPSO lidar instrument for determining cloud phase and aerosols subtypes. In the second part, we evaluate the MODIS IR cloud phase with the CALIPSO cloud products. The three possible misclassifications of MODIS IR cloud phasealgorithm, which are studied by Nasiri and Kahn (2008) with radiative transfer modeling, are tested by comparing between MODIS IR phase and CALIOP observations. The current results support their hypotheses, which is that the MODIS phase algorithm may tend to classify thin cirrus clouds as water clouds or mixed phase clouds or unknown, and classify midlevel and/or mid-temperature clouds as mixed or unknown phase. In the third part, we present a comparison of mineral dust aerosol retrievals from two instruments, MODIS and CALIPSO lidar. And, we implement and evaluate a new mineral dust detection algorithm based on the analysis of thin dust radiative signature. In comparison, three commonly used visible and IR mineral dust detection algorithms, including BTD procedure, D parameter method, and multi-channel image algorithm, are evaluated with CALIPSO aerosol classification. The comparison reveals that those dust detection algorithms are not effective for optically thin dust layers, but for thick dust storm. The new algorithm using discriminant analysis with CALIPSO observation is much better in detecting thin dust layer of optical thickness between 0.1 and 2.