A Review of Wetland Remote Sensing <s> Forest Height <s> The objective of the study was to evaluate the airborne scanning light detection and ranging (lidar) technology for hydrological applications in wetlands, deltas, or other similar areas. A comparison of lidar data with in situ survey data revealed a negative elevation bias of 0.21 m, which was corrected by block adjustment. The evaluation demonstrated that the lidar pulses had difficulties penetrating thick willow cover and dense thatch layers beneath the grasses and sedges (graminoids). After block adjustment, the lidar data achieved a root mean squared error (RMSE) of 0.15 and 0.26 m in graminoid and willow vegetation, respectively. The bare ground points produced an RMSE of 0.07 m. To be useful in hydrologic modelling, elevation data need to be interpolated into an even grid, or a digital elevation model (DEM). Four interpolation algorithms were evaluated for accuracy. The input elevations were best honoured when interpolated into a 0.25 m grid using a kriging algorithm and, thereafter, averaged to a 4... <s> BIB001 </s> A Review of Wetland Remote Sensing <s> Forest Height <s> A new technique for quantifying the geomorphic form of northern forested wetlands from airborne LiDAR surveys is introduced, demonstrating the unprecedented ability to characterize the geomorphic form of northern forested wetlands using high-resolution digital topography. Two quantitative indices are presented, including the lagg width index (LWI) which objectively quantifies the lagg width, and the lateral slope index (LSI) which is a proxy measurement for the dome shape or convexity of the wetland ground surface. For 14 forested wetlands in central Ontario, Canada, northwestern Ontario, Canada, and northern Minnesota, United States, these indices were systematically correlated to metrics of topographic setting computed from LiDAR digital elevation models. In particular, these indices were strongly correlated with a Peatland Topographic Index (PTI, r2 = 0.58 and r2 = 0.64, respectively, p < = 0.001) describing the relative influence of upslope contributing area on the hydrology and biogeochemistry of individual wetlands. The relationship between PTI and the LWI and LSI indices was interpreted as geomorphic evolution in response to the spatially varying influence of upslope runoff on subsurface hydrochemistry. Spatial patterns of near-surface pore water chemistry were consistent with this interpretation. Specifically, at four wetland sites sampled extensively for pore water chemistry, the mean and variance of near-surface pore water methylmercury (MeHg) concentrations were higher within the zone of enhanced upland-wetland interactions, as inferred from the LiDAR-derived LWI estimates. Use of LiDAR surveys to measure subtle topographic gradients within wetlands may therefore help quantify the influence of upland-wetland interactions on biogeochemical cycling and export in northern forested landscapes. <s> BIB002 </s> A Review of Wetland Remote Sensing <s> Forest Height <s> Natural tropical peat swamp forests are important for their rich biodiversity and serve as a huge carbon pool. However, peat swamp forests are decreasing due to deforestation, conversion into farm land, excessive draining, the use of shifting cultivation on a large scale, illegal logging, forest fire and palm oil plantation. Airborne laser scanning (ALS) also termed airborne Light Detection and Ranging (LiDAR) data is nowadays a good single sensor to investigate bio-geophysical parameters in remote tropical rain forest areas (e.g. tree canopy height which is strongly correlated with above ground biomass). Bi-temporal airborne LiDAR data acquired in August 2007 and August 2011 were used to characterize peat swamp forest changes located in Central Kalimantan, Indonesia. We measured the tree height and Canopy Height Model (CHM) with LiDAR, segmented the canopies and then compared the tree height with the field measurements. Additionally, we collected ground field measurements at Sabangau forest transect in order to characterize some biophysical properties of different peat swamp forest physiognomies such as diameter at breast height (DBH), tree-height, leaf area index (LAI), crown coverage and above ground biomass (AGB). From the bi-temporal LiDAR Data we analyzed the forest regrowth and the peat subsidence. This work can be promising in the REDD+ (Reducing Emissions from Deforestation and forest Degradation) framework of knowledge of tropical PSF. The LiDAR technology supports the MRV (Monitoring, Reporting, and Verification) aspect of REDD+. <s> BIB003
LiDAR data have been successfully used in mapping the elevation of forest ecosystems using the advantage of obtaining an accurate DEM. For full waveform LiDAR, the first returned signal is thought to be reflected from the canopy and the last returned signal is from the ground surface  . Wetland researches based on LiDAR are a challenge because of the difficulties of LiDAR pulses in penetrating the thick vegetation cover BIB001 . Richardson et al. BIB002 proposed a new method to quantify the geomorphic forms of forested wetland using LiDAR data; they report the feasibility of LiDAR data with respect to this purpose. They also presented two quantitative indices: lagg width index (LWI) and lateral slope index (LSI). The former index is used to quantify the width of the mixed areas between the wetland and upland and the latter one is used to measure the shape of the wetland ground surface. The gaps in the forest generated by disturbance play a key role in the forest ecosystem recovery. Zhang  used LiDAR to derive the elevation difference between the ground surface and canopy and then identified the gaps in the mangrove forest. In their study, which was successful, alternative sequential filtering and black top-hat mathematical morphological transformation were used to determine the forest gaps. Boehm et al. BIB003 used two temporal LiDAR datasets from August 2007 and August 2011 to monitor peat swamp forest changes. They used LiDAR to measure the height of forest and compared the results with field survey. They reported an average regrowth of 1.9 m and a peat decrease of 18 cm within the four years.