Estimating forest canopy parameters from satellite waveform LiDAR by inversion of the FLIGHT three-dimensional radiative transfer model

The Geoscience Laser Altimeter System (GLAS) has the potential to accurately map global vegetation heights and fractional cover metrics using active laser pulse emission/reception. However, large uncertainties in the derivation of data products exist, since multiple physically plausible interpretations of the data are possible. In this study a method is described and evaluated to derive vegetation height and fractional cover from GLAS waveforms by inversion of the FLIGHT radiative transfer model. A lookup-table is constructed giving expected waveforms for a comprehensive set of canopy realisations, and is used to determine the most likely set of biophysical parameters describing the forest structure, consistent with any given GLAS waveform. The parameters retrieved are canopy height, leaf area index (LAI), fractional cover and ground slope. The range of possible parameters consistent with the waveform is used to give a per-retrieval uncertainty estimate for each retrieved parameter. The retrieved estimates were evaluated first using a simulated data set and then validated against airborne laser scanning (ALS) products for three forest sites coincident with GLAS overpasses. Results for height retrieval show mean absolute error (MAE) of 3.71 m for a mixed temperate forest site within Forest of Dean (UK), 3.35 m for the Southern Old Aspen Site, Saskatchewan, Canada, and 5.13 m for a boreal coniferous site in Norunda, Sweden. Fractional cover showed MAE of 0.10 for Forest of Dean and 0.23 for Norunda. Coefficient of determination between ALS and GLAS estimates over the combined dataset gave R2 values of 0.71 for height and 0.48 for fractional cover, with biases of −3.4 m and 0.02 respectively. Smallest errors were found where overpass dates for ALS data collection closely matched GLAS overpasses. Explicit instrument parameterisation means the method is readily adapted to future planned spaceborne LiDAR instruments such as GEDI

Quantifying structural change in UK woodland canopies with a dual-wavelength full-waveform terrestrial laser scanner

Vegetation structure provides a direct link between forest ecosystem productivity and earth-atmosphere fluxes, and is both a result and driver of these interactions. Therefore, the ability to collect objective, quantitative and three-dimensional measurements of vegetation structure is essential, particularly in light of climate change. However, a significant challenge still remains as to how to best measure changes in forests and prepare for future climatic scenarios. Terrestrial Laser Scanning (TLS) has shown its potential to provide such measurements, offering a new approach to monitoring how forest systems change through time and space. The overall aim of this thesis was to improve the characterisation of the seasonal dynamics of UK woodland vegetation structure using the Salford Advanced Laser Canopy Analyser (SALCA), a research TLS with dual-wavelength full-waveform capabilities.There were three key objectives to this research: (1) the development of a radiometric calibration for the SALCA instrument to produce an apparent reflectance product, (2) the separation of SALCA point clouds into leaf and wood on a tree and plot scale using dual-wavelength lidar, and (3) the examination of the seasonal dynamics of vegetation structure in a range of UK forest types. To address these objectives, two field campaigns were conducted. SALCA measurements of artificial reflectance targets were acquired from both field campaigns to generate a calibration dataset to address Objective 1. The two field campaigns comprised a tree-scale validation experiment at Alice Holt Forest (to address Objective 2), and a multi-temporal monitoring experiment using SALCA and hemispherical photography at Delamere Forest in five different plots (to address Objective 3).Key findings relating to Objective 1 have highlighted the complexities of SALCA intensity response, such as the effect of internal temperature. As a result, a novel approach to radiometric calibration was developed using artificial neural networks which produced an apparent reflectance product with measured accuracy comparable with other approaches. A key conclusion of this research relating to Objective 2, is that dual-wavelength TLS has the potential to aid separation of leaf and wood material. However, there still remain significant ecological, instrumental, and processing challenges to be overcome. Temporally and vertically resolved plot measurements have provided a quantitative analysis of foliage dynamics to address Objective 3 and results have shown how this differences between species. The research presented in this thesis has explored the use of dual-wavelength full-waveform TLS for improved characterisation of forest vegetation. Future research priorities should focus on the radiometric calibration and investigation of other methods for leaf-wood separation to extend and complement this research

Remote Sensing of Biophysical Parameters

Vegetation plays an essential role in the study of the environment through plant respiration and photosynthesis. Therefore, the assessment of the current vegetation status is critical to modeling terrestrial ecosystems and energy cycles. Canopy structure (LAI, fCover, plant height, biomass, leaf angle distribution) and biochemical parameters (leaf pigmentation and water content) have been employed to assess vegetation status and its dynamics at scales ranging from kilometric to decametric spatial resolutions thanks to methods based on remote sensing (RS) data.Optical RS retrieval methods are based on the radiative transfer processes of sunlight in vegetation, determining the amount of radiation that is measured by passive sensors in the visible and infrared channels. The increased availability of active RS (radar and LiDAR) data has fostered their use in many applications for the analysis of land surface properties and processes, thanks to their insensitivity to weather conditions and the ability to exploit rich structural and texture information. Optical and radar data fusion and multi-sensor integration approaches are pressing topics, which could fully exploit the information conveyed by both the optical and microwave parts of the electromagnetic spectrum.This Special Issue reprint reviews the state of the art in biophysical parameters retrieval and its usage in a wide variety of applications (e.g., ecology, carbon cycle, agriculture, forestry and food security)

Analyse von full-waveform Flugzeuglaserscannerdaten zur volumetrischen Repräsentation in Umweltanwendungen

Wissenschaftliche Untersuchungen von terrestrischen und aquatischen Ökosystemen erfordern präzise Informationen über die dreidimensionale Struktur des ökologischen Systems. Full-waveform Flugzeuglaserscannerdaten eignen sich hervorragend zur Charakterisierung von Ökosystemen und bilden eine ideale Basis für die vollständige volumetrische Repräsentation der Vegetations- und Gewässerstruktur in einem Voxelraum. Die Voxelattribute werden dabei aus der digitalisierten Wellenform abgeleitet. Jeder emittierte Laserpuls wird von Dämpfungseffekten beeinflusst, die durch Teilreflexionen auf seinem Weg durch die unterschiedlichen Vegetations- oder Wasserschichten entstehen. Dadurch ist die Struktur im unteren Bereich der empfangenen Rohsignale unterrepräsentiert. Die im Rahmen dieser Arbeit entwickelten innovativen Methoden zur Analyse von full-waveform Daten ermöglichen die Generierung einer radiometrisch korrigierten Voxelraumrepräsentation. Voraussetzung dafür ist die numerisch stabile Rekonstruktion des effektiven differentiellen Rückstreuquerschnitts mit geeigneten Entfaltungs- und Regularisierungsverfahren. Das Kernstück der Analyse bildet die Beschreibung der Signaldämpfung mit Hilfe geeigneter Modelle. Auf Grundlage dieser Modelle wurden neuartige Korrekturverfahren zur Kompensation der Signaldämpfung erarbeitet, wobei der Korrekturterm direkt aus dem differentiellen Rückstreuquerschnitt abgeleitet wird. Die Grundidee der entwickelten Methode ist das schrittweise Anheben der Signalintensität in Abhängigkeit von der individuellen Historie jedes Laserpulses. Die Resultate der vorliegenden Arbeit tragen dazu bei, die in full-waveform Daten enthaltenen Informationen über die Vegetations- und Gewässerstruktur zugänglich zu machen. Weiterhin zeigen die hier präsentierten Ergebnisse, dass die Limitierungen bestehender Auswertemethoden, welche weitgehend auf die Extraktion diskreter Maxima und die Erzeugung volumetrischer Repräsentationen aus diskreten 3D Punktwolken beschränkt sind, überwunden werden können.The scientific investigation of terrestrial and aquatic ecosystems requires precise information on the three-dimensional structure of the ecologic system. Full-waveform airborne laser scanner data are an ideal basis for the complete volumetric representation of vegetation and water structure in a voxel space. Due to attenuation effects, caused by partial reflections during the laser pulse propagation through the vegetation or water column, each individual laser pulse echo is significantly modified. As a result, the structure in the lower parts of the vegetation or water column is underrepresented in the digitized waveform. Within this research, novel and innovative methods were developed, which enable the generation of a radiometrically correct voxel space representation. Therefore, a numerically stable reconstruction of the effective differential backscattering cross section utilizing appropriate deconvolution and regularization techniques is required. The essential element of the analysis is the description of the signal attenuation using applicable mathematical models. For this purpose, novel correction methods compensating the signal attenuation based on these models were developed. The correction term is directly derived from the differential backscatter cross section. The basic idea is a gradually increase of the signal amplitudes depending on the individual history of each laser pulse. The results gained in this work contribute to an improved access to the information on vegetation and water structure, contained in full-waveform laser scanner data. Furthermore, it is possible to overcome limitations of existing approaches, which are mainly based on the extraction of discrete maxima

Forest Canopy LAI and Vertical FAVD Profile Inversion from Airborne Full-Waveform LiDAR Data Based on a Radiative Transfer Model

Forest canopy leaf area index (LAI) is a critical variable for the modeling of climates and ecosystems over both regional and global scales. This paper proposes a physically based method to retrieve LAI and foliage area volume density (FAVD) profile directly from full-waveform Light Detection And Ranging (LiDAR) data using a radiative transfer (RT) model. First, a physical interaction model between LiDAR and a forest scene was built on the basis of radiative transfer theories. Next, FAVD profile of each laser shot of full-waveform LiDAR was inverted using the physical model. In addition, the missing LiDAR data, caused by high-density forest and LiDAR system limitations, were filled in based on the inverted FAVD and the ancillary CHM data. Finally, LAI of the study area was retrieved from the inverted FAVD at a 10-m resolution. CHM derived LAI based on the Beer-Lambert law was compared with the LAI derived from full-waveform data. Also, we compared the results with the field measured LAI. The values of correlation coefficient r and RMSE of the estimated LAI were 0.73 and 0.67, respectively. The results indicate that full-waveform LiDAR data is a reliable data source and represent a useful tool for retrieving forest LAI