The problems which are mentioned before in first and last pulse systems for vegetated regions can be solved with full waveform technology making an important contribution to biomass estimation (Shan and Toth, 2009). The waveform is usually digitized by recording the amplitude of the return signal at fixed time intervals (figure 2). To analyze the signal of emitted short duration laser pulse with only a few ns pulse-width, higher digitizer sampling rate is required. These devices have been primarily designed for measuring vegetation properties. Extensive researches (Harding et al, 2001; Lefsky et al., 2001, 2002; Reitberger et al., 2009) have shown that waveform shape is directly related to canopy biophysical parameters including canopy height, crown size, vertical distribution of canopy, biomass, and leaf area index.

Harding et al. (2001) discussed about canopy height profile detection from full waveform raw data provided by SLICER. They studied the laser energy from the full waveform Gaussian distribution. The advantages of full waveform recording include an enhanced ability to characterize canopy structure, the ability to concisely describe canopy information over increasingly large areas, and the availability of global data sets. The examples of these data are airborne like SLICER and LVIS, and satellite data like GLAS. The other advantage of full waveform systems is that they record the entire time varying power of the return signal from all illuminated surfaces on canopy structure. It should also be stated that Lidar data, which is collected from space globally, provides only full waveform recordings (Lefsky et al., 2002).

2. Methods and models for Biomass estimation

This section is organized in terms of three subsections containing data pre-processing, methods and models, and applications.

Data pre-processing methods in turn are divided into four parts. For the filtering methods some efficient algorithms are explained. Apart from different interpolation methods the generation of the digital terrain model (DTM), digital surface model (DSM), and canopy height model (CHM) is treated. Quality assessment of laser data is carried out within another subsection. Additionally, the quality of filtering methods, interpolation methods, DTMs, DSMs, CHMs results and their performances are also evaluated. The subsection "methods and models" consider the methods and models in biomass estimation, among others single tree and tree characteristics detection. The last subsection presents applications of Lidar using the models for biomass estimation to recognize the advantages of Lidar systems in the biomass estimation.