Understanding the measurement of forests with waveform lidar

The measurement of forests is essential for monitoring and predicting the role and response of the land surface to global climate change. Globally consistent and frequent measurements can only be made by satellites; unfortunately many current system’s measurements saturate at moderate canopy densities and are not directly related to forest properties, requiring tenuous empirical relationships that are insensitive to many of the Earth’s most important, Carbon rich forests. Lidar (laser radar) is a relatively new technology that offers the potential to make direct measurements of forest height, vertical density and, when ground based, explicit measurements of structure. In addition measurements do not saturate until much higher forest densities. In recent years there has been much interest in the measurement of forests by lidar, with a number of airborne and terrestrial and one spaceborne lidar developed. Measuring a forest leaf by leaf is impractical and very tedious, so more rapid ground based methods are needed to collect data to validate satellite derived estimates. These rapid methods are themselves not directly related to forest properties causing uncertainty in any validation of remotely sensed estimates. This thesis uses Monte Carlo ray tracing to simulate the measurement of forests by full waveform lidars over explicit geometric forest models for both above and below canopy instruments. Existing methods for deriving forest properties from measurements are tested against the known truth of these simulated forests, a process impossible in reality. Causes of disagreements are explored and new methods developed to attempt to overcome any shortcomings. These new methods include dual wavelength lidar for correcting satellite based measurements for topography and a voxel based method for more directly relating terrestrial lidar signals to forest properties

Remote sensing of leaf area index : enhanced retrieval from close-range and remotely sensed optical observations

A wide range of models used in agriculture, ecology, carbon cycling, climate and other related studies require information on the amount of leaf material present in a given environment to correctly represent radiation, heat, momentum, water, and various gas exchanges with the overlying atmosphere or the underlying soil. Leaf area index (LAI) thus often features as a critical land surface variable in parameterisations of global and regional climate models, e.g., radiation uptake, precipitation interception, energy conversion, gas exchange and momentum, as all areas are substantially determined by the vegetation surface. Optical wavelengths of remote sensing are the common electromagnetic regions used for LAI estimations and generally for vegetation studies. The main purpose of this dissertation was to enhance the determination of LAI using close-range remote sensing (hemispherical photography), airborne remote sensing (high resolution colour and colour infrared imagery), and satellite remote sensing (high resolution SPOT 5 HRG imagery) optical observations. The commonly used light extinction models are applied at all levels of optical observations. For the sake of comparative analysis, LAI was further determined using statistical relationships between spectral vegetation index (SVI) and ground based LAI. The study areas of this dissertation focus on two regions, one located in Taita Hills, South-East Kenya characterised by tropical cloud forest and exotic plantations, and the other in Gatineau Park, Southern Quebec, Canada dominated by temperate hardwood forest. The sampling procedure of sky map of gap fraction and size from hemispherical photographs was proven to be one of the most crucial steps in the accurate determination of LAI. LAI and clumping index estimates were significantly affected by the variation of the size of sky segments for given zenith angle ranges. On sloping ground, gap fraction and size distributions present strong upslope/downslope asymmetry of foliage elements, and thus the correction and the sensitivity analysis for both LAI and clumping index computations were demonstrated. Several SVIs can be used for LAI mapping using empirical regression analysis provided that the sensitivities of SVIs at varying ranges of LAI are large enough. Large scale LAI inversion algorithms were demonstrated and were proven to be a considerably efficient alternative approach for LAI mapping. LAI can be estimated nonparametrically from the information contained solely in the remotely sensed dataset given that the upper-end (saturated SVI) value is accurately determined. However, further study is still required to devise a methodology as well as instrumentation to retrieve on-ground green leaf area index . Subsequently, the large scale LAI inversion algorithms presented in this work can be precisely validated. Finally, based on literature review and this dissertation, potential future research prospects and directions were recommended.Ei saatavill

Estimating the leaf area index of Eucalyptus dunnii in the Midlands area, KwaZulu-Natal province over two seasons using vegetation indices and image texture measures derived from Worldview-3 imagery.

Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.Abstract available in PDF

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)

Terrestrial laser scanning for forest monitoring

Remote sensing data worden beschouwd als één van de belangrijkste databronnen voor het observeren van uitgestrekte bosgebieden. Het belangrijkste doel van dit proefschrift is om het potentieel van terrestrische LiDAR voor het monitoren van bossen te onderzoeken en om methoden te ontwikkelen voor het afleiden van accurate in-situ referentiedata voor bos monitoring

Remote Sensing of Plant Biodiversity

At last, here it is. For some time now, the world has needed a text providing both a new theoretical foundation and practical guidance on how to approach the challenge of biodiversity decline in the Anthropocene. This is a global challenge demanding global approaches to understand its scope and implications. Until recently, we have simply lacked the tools to do so. We are now entering an era in which we can realistically begin to understand and monitor the multidimensional phenomenon of biodiversity at a planetary scale. This era builds upon three centuries of scientific research on biodiversity at site to landscape levels, augmented over the past two decades by airborne research platforms carrying spectrometers, lidars, and radars for larger-scale observations. Emerging international networks of fine-grain in-situ biodiversity observations complemented by space-based sensors offering coarser-grain imagery—but global coverage—of ecosystem composition, function, and structure together provide the information necessary to monitor and track change in biodiversity globally. This book is a road map on how to observe and interpret terrestrial biodiversity across scales through plants—primary producers and the foundation of the trophic pyramid. It honors the fact that biodiversity exists across different dimensions, including both phylogenetic and functional. Then, it relates these aspects of biodiversity to another dimension, the spectral diversity captured by remote sensing instruments operating at scales from leaf to canopy to biome. The biodiversity community has needed a Rosetta Stone to translate between the language of satellite remote sensing and its resulting spectral diversity and the languages of those exploring the phylogenetic diversity and functional trait diversity of life on Earth. By assembling the vital translation, this volume has globalized our ability to track biodiversity state and change. Thus, a global problem meets a key component of the global solution. The editors have cleverly built the book in three parts. Part 1 addresses the theory behind the remote sensing of terrestrial plant biodiversity: why spectral diversity relates to plant functional traits and phylogenetic diversity. Starting with first principles, it connects plant biochemistry, physiology, and macroecology to remotely sensed spectra and explores the processes behind the patterns we observe. Examples from the field demonstrate the rising synthesis of multiple disciplines to create a new cross-spatial and spectral science of biodiversity. Part 2 discusses how to implement this evolving science. It focuses on the plethora of novel in-situ, airborne, and spaceborne Earth observation tools currently and soon to be available while also incorporating the ways of actually making biodiversity measurements with these tools. It includes instructions for organizing and conducting a field campaign. Throughout, there is a focus on the burgeoning field of imaging spectroscopy, which is revolutionizing our ability to characterize life remotely. Part 3 takes on an overarching issue for any effort to globalize biodiversity observations, the issue of scale. It addresses scale from two perspectives. The first is that of combining observations across varying spatial, temporal, and spectral resolutions for better understanding—that is, what scales and how. This is an area of ongoing research driven by a confluence of innovations in observation systems and rising computational capacity. The second is the organizational side of the scaling challenge. It explores existing frameworks for integrating multi-scale observations within global networks. The focus here is on what practical steps can be taken to organize multi-scale data and what is already happening in this regard. These frameworks include essential biodiversity variables and the Group on Earth Observations Biodiversity Observation Network (GEO BON). This book constitutes an end-to-end guide uniting the latest in research and techniques to cover the theory and practice of the remote sensing of plant biodiversity. In putting it together, the editors and their coauthors, all preeminent in their fields, have done a great service for those seeking to understand and conserve life on Earth—just when we need it most. For if the world is ever to construct a coordinated response to the planetwide crisis of biodiversity loss, it must first assemble adequate—and global—measures of what we are losing

Remote Sensing of Plant Biodiversity

This Open Access volume aims to methodologically improve our understanding of biodiversity by linking disciplines that incorporate remote sensing, and uniting data and perspectives in the fields of biology, landscape ecology, and geography. The book provides a framework for how biodiversity can be detected and evaluated—focusing particularly on plants—using proximal and remotely sensed hyperspectral data and other tools such as LiDAR. The volume, whose chapters bring together a large cross-section of the biodiversity community engaged in these methods, attempts to establish a common language across disciplines for understanding and implementing remote sensing of biodiversity across scales. The first part of the book offers a potential basis for remote detection of biodiversity. An overview of the nature of biodiversity is described, along with ways for determining traits of plant biodiversity through spectral analyses across spatial scales and linking spectral data to the tree of life. The second part details what can be detected spectrally and remotely. Specific instrumentation and technologies are described, as well as the technical challenges of detection and data synthesis, collection and processing. The third part discusses spatial resolution and integration across scales and ends with a vision for developing a global biodiversity monitoring system. Topics include spectral and functional variation across habitats and biomes, biodiversity variables for global scale assessment, and the prospects and pitfalls in remote sensing of biodiversity at the global scale

Field spectroscopy and spectral reflectance modelling of Calluna vulgaris

Boreal peatlands store carbon sequestered from the atmosphere over millennia and the importance of this and the other ecosystem services these areas provide is now widely recognised. However, a changing climate will affect these environments and, consequently, the services they provide to the global population. The rate and direction of environmental change to peatlands is currently unclear and they have not yet been included in many climate models. This may in part be due to the ecological heterogeneity and spatial extent of these areas and the sparse sampling survey methods currently adopted. Hyperspectral remote sensing from satellite platforms may in future offer an approach to surveying and do so at the high spectral and spatial resolutions necessary to infer ecological change in these peatlands. However, work is required to develop methods of analysis to determine if hyperspectral data can be used to measure the overstorey vegetation of these areas. This will require an understanding of how annual and inter-annual cyclical changes affect the peatland plant canopy reflectances that would be recorded by hyperspectral sensors and how these reflectances can be related to state variable of interest to climate scientists, ecologists and peatland managers. There are significant areas of peatland within Scotland and, as it is towards the southern extreme of the boreal peatlands, these may be an early indicator of environment change to the wider boreal region. Calluna vulgaris, a hardy dwarf shrub, is the dominant overstorey species over much of these peatlands and could serve as a proxy for ecological, and consequently, environmental change. However, little has been done to understand how variations in leaf pigments or canopy structural parameters influence the spectral reflectance of Calluna through annual and inter-annual growth and senescence cycles. Nor has much work been done to develop methods of analysis to enable images acquired by hyperspectral remote sensing to be utilised to monitor change to these Calluna dominated peatlands over time. To advance understanding of the optical properties of Calluna leaves and canopies and develop methods to analyse hyperspectral images laboratory, field and modelling studies have been carried out in time series over a number of years. The leaf and canopy parameters significantly affecting reflectance have been identified and quantified. Differences between published Chlorophyll(a+b) in vivo absorption spectra and those determined were found. Carotenoids and Anthocyanins were also identified and quantified. The absorption spectra of these pigments were incorporated into a canopy reflectance model and this was coupled to a Calluna growth model. This combined model enabled the reflectance of Calluna canopies to be modelled in daily increments through annual and inter-annual growth and senescence cycles. Reasonable results were achieved in spectral regions where reflectance changed systematically but only for homogeneous Calluna stands. However, it was noted during this research that the area of support for the spectral measurements appeared to differ from that assumed from the specification provided by the spectroradiometer manufacturers. The directional response functions (DRFs) of two spectroradiometers were investigated and wavelength, or wavelength region, specific spatial dependences were noted. The effect that the DRFs of the spectroradiometers would have on reflectances recorded from Calluna canopies was investigated through a modelling study. Errors and inaccuracies in the spectra that would be recorded from these canopies, and commonly used biochemical indices derived from them, have been quantified

The global tree carrying capacity (keynote)

editorial reviewe