ICESat/GLAS Data as a Measurement Tool for Peatland Topography and Peat Swamp Forest Biomass in Kalimantan, Indonesia

Indonesian peatlands are one of the largest near-surface pools of terrestrial organic carbon. Persistent logging, drainage and recurrent fires lead to huge emission of carbon each year. Since tropical peatlands are highly inaccessible, few measurements on peat depth and forest biomass are available. We assessed the applicability of quality filtered ICESat/GLAS (a spaceborne LiDAR system) data to measure peatland topography as a proxy for peat volume and to estimate peat swamp forest Above Ground Biomass (AGB) in a thoroughly investigated study site in Central Kalimantan, Indonesia. Mean Shuttle Radar Topography Mission (SRTM) elevation was correlated to the corresponding ICESat/GLAS elevation. The best results were obtained from the waveform centroid (R2 = 0.92; n = 4,186). ICESat/GLAS terrain elevation was correlated to three 3D peatland elevation models derived from SRTM data (R2 = 0.90; overall difference = −1.0 m, ±3.2 m; n = 4,045). Based on the correlation of in situ peat swamp forest AGB and airborne LiDAR data (R2 = 0.75, n = 36) an ICESat/GLAS AGB prediction model was developed (R2 = 0.61, n = 35). These results demonstrate that ICESat/GLAS data can be used to measure peat topography and to collect large numbers of forest biomass samples in remote and highly inaccessible peatland forests

Abiotic controls on macroscale variations of humid tropical forest height

Spatial variation of tropical forest tree height is a key indicator of ecological processes associated with forest growth and carbon dynamics. Here we examine the macroscale variations of tree height of humid tropical forests across three continents and quantify the climate and edaphic controls on these variations. Forest tree heights are systematically sampled across global humid tropical forests with more than 2.5 million measurements from Geoscience Laser Altimeter System (GLAS) satellite observations (2004–2008). We used top canopy height (TCH) of GLAS footprints to grid the statistical mean and variance and the 90 percentile height of samples at 0.5 degrees to capture the regional variability of average and large trees globally. We used the spatial regression method (spatial eigenvector mapping-SEVM) to evaluate the contributions of climate, soil and topography in explaining and predicting the regional variations of forest height. Statistical models suggest that climate, soil, topography, and spatial contextual information together can explain more than 60% of the observed forest height variation, while climate and soil jointly explain 30% of the height variations. Soil basics, including physical compositions such as clay and sand contents, chemical properties such as PH values and cation-exchange capacity, as well as biological variables such as the depth of organic matter, all present independent but statistically significant relationships to forest height across three continents. We found significant relations between the precipitation and tree height with shorter trees on the average in areas of higher annual water stress, and large trees occurring in areas with low stress and higher annual precipitation but with significant differences across the continents. Our results confirm other landscape and regional studies by showing that soil fertility, topography and climate may jointly control a significant variation of forest height and influencing patterns of aboveground biomass stocks and dynamics. Other factors such as biotic and disturbance regimes, not included in this study, may have less influence on regional variations but strongly mediate landscape and small-scale forest structure and dynamics.The research was funded by Gabon National Park (ANPN) under the contract of 011-ANPN/2012/SE-LJTW at UCLA. We thank IIASA, FAO, USGS, NASA, Worldclim science teams for making their data available. (011-ANPN/2012/SE-LJTW - Gabon National Park (ANPN) at UCLA

Estimating Canopy Gap Fraction Using ICESat GLAS within Australian Forest Ecosystems

Spaceborne laser altimetry waveform estimates of canopy Gap Fraction (GF) vary withrespect to discrete return airborne equivalents due to their greater sensitivity to reflectance differencesbetween canopy and ground surfaces resulting from differences in footprint size, energy thresholding,noise characteristics and sampling geometry. Applying scaling factors to either the ground or canopyportions of waveforms has successfully circumvented this issue, but not at large scales. This studydevelops a method to scale spaceborne altimeter waveforms by identifying which remotely-sensedvegetation, terrain and environmental attributes are best suited to predicting scaling factors basedon an independent measure of importance. The most important attributes were identified as: soilphosphorus and nitrogen contents, vegetation height, MODIS vegetation continuous fields productand terrain slope. Unscaled and scaled estimates of GF are compared to corresponding ALS datafor all available data and an optimized subset, where the latter produced most encouraging results(R2 = 0.89, RMSE = 0.10). This methodology shows potential for successfully refining estimates ofGF at large scales and identifies the most suitable attributes for deriving appropriate scaling factors.Large-scale active sensor estimates of GF can establish a baseline from which future monitoringinvestigations can be initiated via upcoming Earth Observation missions

Quantifying Dynamics in Tropical Peat Swamp Forest Biomass with Multi- Temporal LiDAR Datasets

Tropical peat swamp forests in Indonesia store huge amounts of carbon and are responsible for enormous carbon emissions every year due to forest degradation and deforestation. These forest areas are in the focus of REDD+ (reducing emissions from deforestation, forest degradation, and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks) projects, which require an accurate monitoring of their carbon stocks or aboveground biomass (AGB). Our study objective was to evaluate multi-temporal LiDAR measurements of a tropical forested peatland area in Central Kalimantan on Borneo. Canopy height and AGB dynamics were quantified with a special focus on unaffected, selective logged and burned forests. More than 11,000 ha were surveyed with airborne LiDAR in 2007 and 2011. In a first step, the comparability of these datasets was examined and canopy height models were created. Novel AGB regression models were developed on the basis of field inventory measurements and LiDAR derived height histograms for 2007 (r(2) = 0.77, n = 79) and 2011 (r(2) = 0.81, n = 53), taking the different point densities into account. Changes in peat swamp forests were identified by analyzing multispectral imagery. Unaffected forests accumulated on average 20 t/ha AGB with a canopy height increase of 2.3 m over the four year time period. Selective logged forests experienced an average AGB loss of 55 t/ha within 30 m and 42 t/ha within 50 m of detected logging trails, although the mean canopy height increased by 0.5 m and 1.0 m, respectively. Burned forests lost 92% of the initial biomass. These results demonstrate the great potential of repetitive airborne LiDAR surveys to precisely quantify even small scale AGB and canopy height dynamics in remote tropical forests, thereby featuring the needs of REDD+

Estimates of forest canopy height and aboveground biomass using ICESat

Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. While the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite (ICESat) has collected an unparalleled dataset of lidar waveforms over terrestrial targets, processing of ICESat data to estimate forest height is complicated by the pulse broadening associated with large-footprint, waveform-sampling lidar. We combined ICESat waveforms and ancillary topography from the Shuttle Radar Topography Mission to estimate maximum forest height in three ecosystems; tropical broadleaf forests in Brazil, temperate broadleaf forests in Tennessee, and temperate needleleaf forests in Oregon. Final models for each site explained between 59% and 68% of variance in field-measured forest canopy height (RMSE between 4.85 and 12.66 m). In addition, ICESat-derived heights for the Brazilian plots were correlated with field-estimates of aboveground biomass (r(2) = 73%, RMSE = 58.3 Mgha(-1))

Geographic variability in lidar predictions of forest stand structure in the Pacific Northwest

Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, carbon storage in moderate to high biomass forests is difficult to estimate with conventional optical or radar sensors. Lidar (light detection and ranging) instruments measure the vertical structure of forests and thus hold great promise for remotely sensing the quantity and spatial organization of forest biomass. In this study, we compare the relationships between lidar measured canopy structure and coincident field measurements of forest stand structure at five locations in the Pacific Northwest of the U.S.A. with contrasting composition. Coefficient of determination values (r2) ranged between 41% and 96%. Correlations for two important variables, LAI (81%) and above ground biomass (92%), were noteworthy, as was the fact that neither variable showed an asymptotic response. Of the 17 stand structure variables considered in this study, we were able to develop eight equations that were valid for all sites, including equations for two variables generally considered to be highly important (aboveground biomass and leaf area index). The other six equations that were valid for all sites were either related to height (which is most directly measured by lidar) or diameter at breast height (which should be closely related to height). Four additional equations (a total of 12) were applicable to all sites where either Douglas-fir (Pseudotsuga menziesii), western hemlock (Tsuga heterophylla) or Sitka spruce (Picea sitchensi) were dominant. Stand structure variables in sites dominated by true firs (Abies sp.) or ponderosa pine (Pinus ponderosa) had biases when predicted by these four additional equations. Productivity-related variables describing the edaphic, climatic and topographic environment of the sites where available for every regression, but only two of the 17 equations (maximum diameter at breast height, stem density) incorporated them. Given the wide range of these environmental conditions sampled, we conclude that the prediction of stand structure is largely independent of environmental conditions in this study area. Most studies of lidar remote sensing for predicting stand structure have depended on intensive data collections within a relatively small study area. This study indicates that the relationships between many stand structure indices and lidar measured canopy structure have generality at the regional scale. This finding, if replicated in other regions, would suggest that mapping of stand structure using lidar may be accomplished by distributing field sites extensively over a region, thus reducing the overall inventory effort required

Influence of lithology on hillslope morphology and response to tectonic forcing in the northern Sierra Nevada of California

Many geomorphic studies assume that bedrock geology is not a first-order control on landscape form in order to isolate drivers of geomorphic change (e.g., climate or tectonics). Yet underlying geology may influence the efficacy of soil production and sediment transport on hillslopes. We performed quantitative analysis of LiDAR digital terrain models to examine the topographic form of hillslopes in two distinct lithologies in the Feather River catchment in northern California, a granodiorite pluton and metamorphosed volcanics. The two sites, separated by <2 km and spanning similar elevations, were assumed to have similar climatic histories and are experiencing a transience in landscape evolution characterized by a propagating incision wave in response to accelerated surface uplift c. 5 Ma. Responding to increased incision rates, hillslopes in granodiorite tend to have morphology similar to model predictions for steady state hillslopes, suggesting that they adjust rapidly to keep pace with the incision wave. By contrast, hillslopes in metavolcanics exhibit high gradients but lower hilltop curvature indicative of ongoing transient adjustment to incision. We used existing erosion rate data and the curvature of hilltops proximal to the main channels (where hillslopes have most likely adjusted to accelerated erosion rates) to demonstrate that the sediment transport coefficient is higher in granodiorite (8.8 m2 ka-1) than in metavolcanics (4.8 m2 ka-1). Hillslopes in both lithologies get shorter (i.e., drainage density increases) with increasing erosion rates

Observing the Forest Canopy with a New Ultra-Violet Compact Airborne Lidar

We have developed a new airborne UV lidar for the forest canopy and deployed it in the Landes forest (France). It is the first one that: (i) operates at 355 nm for emitting energetic pulses of 16 mJ at 20 Hz while fulfilling eye-safety regulations and (ii) is flown onboard an ultra-light airplane for enhanced flight flexibility. Laser footprints at ground level were 2.4 m wide for a flying altitude of 300 m. Three test areas of ∼500 × 500 m2 with Maritime pines of different ages were investigated. We used a threshold method adapted for this lidar to accurately extract from its waveforms detailed forest canopy vertical structure: canopy top, tree crown base and undergrowth heights. Good detection sensitivity enabled the observation of ground returns underneath the trees. Statistical and one-to-one comparisons with ground measurements by field foresters indicated a mean absolute accuracy of ∼1 m. Sensitivity tests on detection threshold showed the importance of signal to noise ratio and footprint size for a proper detection of the canopy vertical structure. This UV-lidar is intended for future innovative applications of simultaneous observation of forest canopy, laser-induced vegetation fluorescence and atmospheric aerosols

Fire models and methods to map fuel types: The role of remote sensing.

Understanding fire is essential to improving forest management strategies. More specifically, an accurate knowledge of the spatial distribution of fuels is critical when analyzing, modelling and predicting fire behaviour. First, we review the main concepts and terminology associated with forest fuels and a number of fuel type classifications. Second, we summarize the main techniques employed to map fuel types starting with the most traditional approaches, such as field work, aerial photo interpretation or ecological modelling. We pay special attention to more contemporary techniques, which involve the use of remote sensing systems. In general, remote sensing systems are low-priced, can be regularly updated and are less time-consuming than traditional methods, but they are still facing important limitations. Recent work has shown that the integration of different sources of information andmethods in a complementary way helps to overcome most of these limitations. Further research is encouraged to develop novel and enhanced remote sensing techniques

Forest disturbance and regeneration: a mosaic of discrete gap dynamics and open matrix regimes?

Question: Recent research in boreal forest suggests that an ‘open matrix’ model may be more appropriate than the traditional model of spatially discrete gap dynamics for describing forest disturbance and regeneration, but what is the evidence from temperate broad-leaved deciduous forests concerning the prevalence of these alternative models? Location: Semi-natural temperate broad-leaved deciduous forest in southern England. Methods: Multi-temporal LiDAR data were used to monitor the changes in tree canopy height and canopy gaps over a 10-yr period for a 130-ha area of forest. Gap dynamics were characterized by quantifying gap creation, expansion, contraction and closure. By identifying the types and rates of canopy height transitions, areas of gap contraction and closure were attributed to the processes of lateral crown growth or vertical regeneration. Results: Across the study site there was a zonation in canopy and gap properties and their dynamics. Many areas of the forest had the characteristics of open wood-pasture dominated by large, complex gaps being maintained under a regime of chronic disturbance. In these areas, several characteristics of the gap dynamics indicated that regeneration was restricted and this may be attributable to spatially-focused overgrazing by large herbivores. In contrast, other areas were characterized by high, closed canopy forest with small, discrete gaps where gap creation and infill were balanced. Conclusions: At the landscape-scale broad-leaved deciduous forests contain a spatial mosaic of zones, which conform to different models of disturbance and regeneration dynamics; discrete gap dynamics and open matrix regimes are juxtaposed. It is now important to elucidate the abiotic factors and biotic interactions that determine the spatio-temporal distribution of the different regimes and to examine whether such a ‘regime mosaic’ model is applicable in other forest types