**8. References**

20 Remote Sensing of Biomass – Principles and Applications

NASA's forthcoming ICESat II mission is due for launch in early 2016 (GSFC, 2011). In contrast to ICESat I, its successor will carry a medium footprint, photon-counting profiling lidar operating at 532nm wavelength. This instrument is named ATLAS, the Advanced Topographic Laser Altimeter System. The current planned configuration is for a single emitted pulse which is split into six beams, arranged as three adjacent pairs. Each pair will have a stronger and a weaker beam (100μJ and 25μJ respectively) which aims to address issues of detector sensitivity when alternating between bright and dark surfaces such as ice and water. A distance of 3.3km is anticipated between each pair and members of the pair will be separated by 90m. The high repetition rate of 10kHz from an altitude of ~496km will produce overlapping footprints of 10m diameter which will be distanced at 0.7m intervals. 1-3 photons are anticipated to be detected per footprint and, although the spatial location of photons within the footprint will be unknown, the aggregation of returns along the ground tracks will allow a vertical profile to be created. Although, like with its predecessor, the primary objective of ICESat II is not the retrieval of vegetation, one of its science objectives is measuring vegetation height as a basis for estimating large-scale biomass and biomass change (GSFC, 2011). This new technology will offer a new perspective of the world and

Laser altimetry is currently the only technique capable of measuring tree heights in closed canopies and therefore offers a remote and non-destructive means of estimating vegetation volume, biomass or carbon content to account for vegetation distribution. This avoids

The replacement of current field-based methods is not contemplated as a realistic option, however, data collection in the field can be made more effective and targeted as a result of lidarbased inventories. This is already happening in Norway for example, where 90% of stand inventories are being made in relation to lidar surveys (E. Næsset, personal communication). At present, the retrieval of stand and individual tree parameters is highly dependent on field data collection for the calibration and validation of a sensor's estimates. However, the most efficient use of lidar will require a deeper understanding of the phenomenology of tree interception of the laser hits and how this relates to the physical characteristics of the vegetation being monitored. This understanding can be improved using lidar simulation models. This may offer the possibility to construct more widely applicable height and diameter recovery models using current allometric relationships derived from models or by

The recognition of the importance of biomass mapping and the significant contribution of lidar data for this purpose are demonstrated by the investment and commitment by the US Congress to research in this field at both county and national scales through the NASA-led Carbon Monitoring System initiative (NASA, 2010). This project integrates the use of multiple datasets to generate national and county level biomass products. Elsewhere, the investment in airborne lidar by several governments for national scale campaigns further demonstrates the

Such means of identifying areas of forest biomass change can offer important contributions to efforts to inform and encourage practices of Reducing Emissions from Deforestation and forest Degradation in developing countries – REDD (Asner *et al.*, 2010; FAO *et al.*, 2008) and

open opportunities for different approaches to global vegetation analysis.

difficulties posed by inaccessibility, time or cost-intensive field campaigns.

observations from a network of nationwide permanent sample plots.

important role that this technology can play in forest inventory and monitoring.

to report on Land Use, Land Use Change and Forestry – LULUCF (IPCC, 2003).

**7. Discussion and conclusion** 


Lidar Remote Sensing for Biomass Assessment 23

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**0**

**2**

*Italy*

**Forest Structure Retrieval from**

The vertical structure of the forested areas has been recognized by the scientific community as one major element in the assessment of forest biomass. Dealing with a volumetric object, the remote sensing techniques that are best suited to infer information about the forest structure are those that guarantee under foliage penetration capabilities. One important, widely popular technology used to investigate the forest vertical structure from the above (typically on board aircrafts) is given by high resolution LIDAR (Light Detection and Ranging) sensors, whose signals penetrate down to the ground trough the gaps within the vegetation layer. In the recent years, however, the attention of the scientific community has been drawn by the use of SAR (Synthetic Aperture Radar) techniques. As opposed to LIDARs, for which high resolution is crucial, the signals emitted by SARs propagate down to the ground by virtue of the under foliage penetration capabilities of microwaves. This different way of sensing the volumetric structure of the imaged objects determines many peculiarities of SAR imaging with respect to LIDAR, some of which are advantages and other drawbacks. The most remarkable advantage is perhaps the one due to the ability of microwaves to penetrate into semi-transparent media, which makes lower wavelength (L-Band and P-Band, typically) SARs capable of acquiring data almost independently of weather conditions and vegetation density. Conversely, the most relevant drawback is that the three dimensional (3D) reconstruction of the imaged objects requires the exploitation of multiple (at least two, but preferable many) images acquired from different points of view, and hence multiple passes

The aim of this chapter is to discuss relevant topics associated with the employment of a multi-baseline SAR system for the reconstruction of the 3D structure of the imaged targets,

The first topic considered is the design of a multi-baseline SAR system for 3D reconstruction in the framework of Fourier Tomography (FT), also referred to as 3D focusing. Even though seldom used in practical applications due to poor imaging quality, FT allows to discuss quite easily the design and overall features of a SAR tomographic system, and represents the basis

The next part of this chapter will focus on operative methods the generation of high-resolution tomographic imaging from sparse data-sets. This is the case of interest in practical applications, due to the costs associated with flying a high number of passes and platform trajectory accuracy. T-SAR will be cast here in terms of an estimation problem, considering both non-parametric and parametric, or model based, approaches. Non-parametric

**1. Introduction**

over the scene to be investigated.

with particular attention to the case of forested areas.

for all of the developments presented in the remainder of this chapter.

**Multi-Baseline SARs**

Stefano Tebaldini *Politecnico di Milano*

