David J. Harding

Lidar Remote Sensing for Ecosystem Studies

Articles R emote sensing has facilitated extraordinary advances in the modeling, mapping, and understanding of ecosystems. Typical applications of remote sensing involve either images from passive optical systems, such as aerial photography and Landsat Thematic Mapper (Goward and Williams 1997), or to a lesser degree, active radar sensors such as RADARSAT (Waring et al. 1995). These types of sensors have proven to be satisfactory for many ecological applications , such as mapping land cover into broad classes and, in some biomes, estimating aboveground biomass and leaf area index (LAI). Moreover, they enable researchers to analyze the spatial pattern of these images. However, conventional sensors have significant limitations for ecological applications. The sensitivity and accuracy of these devices have repeatedly been shown to fall with increasing aboveground biomass and leaf area index (Waring et al. 1995, Carlson and Ripley 1997, Turner et al. 1999). They are also limited in their ability to represent spatial patterns: They produce only two-dimensional (x and y) images, which cannot fully represent the three-dimensional structure of, for instance, an old-growth forest canopy.Yet ecologists have long understood that the presence of specific organisms, and the overall richness of wildlife communities, can be highly dependent on the three-dimensional spatial pattern of vegetation (MacArthur and MacArthur 1961), especially in systems where biomass accumulation is significant (Hansen and Rotella 2000). Individual bird species, in particular, are often associated with specific three-dimensional features in forests (Carey et al. 1991). In addition, other functional aspects of forests, such as productivity, may be related to forest canopy structure. Laser altimetry, or lidar (light detection and ranging), is an alternative remote sensing technology that promises to both increase the accuracy of biophysical measurements and extend spatial analysis into the third (z) dimension. Lidar sensors directly measure the three-dimensional distribution of plant canopies as well as subcanopy topography, thus providing high-resolution topographic maps and highly accurate estimates of vegetation height, cover, and canopy structure. In addition , lidar has been shown to accurately estimate LAI and aboveground biomass even in those high-biomass ecosystems where passive optical and active radar sensors typically fail to do so. The basic measurement made by a lidar device is the distance between the sensor and a target surface, obtained by determining the elapsed time between the emission of a short-duration laser pulse and the arrival of the reflection of that pulse (the return signal) at the sensors receiver. Multiplying this …

ICESat's laser measurements of polar ice, atmosphere, ocean, and land

The Ice, Cloud and Land Elevation Satellite (ICESat) mission will measure changes in elevation of the Greenland and Antarctic ice sheets as part of NASA’s Earth Observing System (EOS) of satellites. Timeseries of elevation changes will enable determination of the present-day mass balance of the ice sheets, study of associations between observed ice changes and polar climate, and estimation of the present and future contributions of the ice sheets to global sea level rise. Other scientific objectives of ICESat include: global measurements of cloud heights and the vertical structure of clouds and aerosols; precise measurements of land topography and vegetation canopy heights; and measurements of sea ice roughness, sea ice thickness, ocean surface elevations, and surface reflectivity. The Geoscience Laser Altimeter System (GLAS) on ICESat has a 1064 nm laser channel for surface altimetry and dense cloud heights and a 532 nm lidar channel for the vertical distribution of clouds and aerosols. The predicted accuracy for the surfaceelevation measurements is 15 cm, averaged over 60 m diameter laser footprints spaced at 172 m alongtrack. The orbital altitude will be around 600 km at an inclination of 94 � with a 183-day repeat pattern. The on-board GPS receiver will enable radial orbit determinations to better than 5 cm, and star-trackers will enable footprints to be located to 6 m horizontally. The spacecraft attitude will be controlled to point

Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests

21 of biomass and an LAI of 12, with 90% and like conventional microwave and optical sensors, lidar 75% of variance explained, respectively. Furthermore, we sensors directly measure the distribution of vegetation were able to make accurate estimates of other stand material along the vertical axis and can be used to pro- structure attributes, including the mean and standard devide three-dimensional, or volumetric, characterizations viation of diameter at breast height, the number of stems of vegetation structure. Ecological applications of scan- greater than 100 cm in diameter, and independent estining lidar have hitherto used one-dimensional indices to mates of the basal area of Douglas-fir and western hemcharacterize canopy height. A novel three-dimensional lock. These measurements can be directly related to indianalysis of lidar waveforms was developed to character- ces of forest stand structural complexity, such as those ize the total volume and spatial organization of vegeta- developed for old-growth forest characterization. Indices tion material and empty space within the forest canopy. of canopy structure developed using the novel, threeThese aspects of the physical structure of canopies have dimensional analysis accounted for most of the variables been infrequently measured, from either field or remote used in predictive equations generated by the stepwise methods. We applied this analysis to 22 plots in Douglas- multiple regression. Published by Elsevier Science Inc. fir/western hemlock stands on the west slope of the Cascades Range in Oregon. Each plot had coincident lidar data and field measurements of stand structure. We com- INTRODUCTION pared results from the novel analysis to two earlier methCharacterization of structure in moderate to high bioods of canopy description. Using the indices of canopy mass forests is a major challenge in remote sensing. structure from all three methods of description as inde

Surface lidar remote sensing of basal area and biomass in deciduous forests of eastern Maryland, USA

A method of predicting two forest stand structure attributes, basal area and aboveground biomass, from measurements of forest vertical structure was developed and tested using field and remotely sensed canopy structure measurements. Coincident estimates of the vertical distribution of canopy surface area (the canopy height profile), and field-measured stand structure attributes were acquired for two data sets. The chronosequence data set consists of 48 plots in stands distributed within 25 miles of Annapolis, MD, with canopy height profiles measured in the field using the optical-quadrat method. The stem-map data set consists of 75 plots subsetted from a single 32 ha stem-mapped stand, with measurements of their canopy height profiles made using the SLICER (Scanning Lidar Imager of Canopies by Echo Recovery) instrument, an airborne surface lidar system. Four height indices, maximum, median, mean, and quadratic mean canopy height (QMCH) were calculated from the canopy height profiles. Regressions between the indices and stand basal area and biomass were developed using the chronosequence data set. The regression equations developed from the chronosequence data set were then applied to height indices calculated from the remotely sensed canopy height profiles from the stem map data set, and the ability of the regression equations to predict the stem map plot’s stand structure attributes was then evaluated. The QMCH was found to explain the most variance in the chronosequence data set’s stand structure attributes, and to most accurately predict the values of the same attributes in the stem map data set. For the chronosequence data set, the QMCH predicted 70% of variance in stand basal area, and 80% of variance in aboveground biomass, and remained nonasymptotic with basal areas up to 50 m2 ha−1, and aboveground biomass values up to 450 Mg ha−1. When applied to the stem-map data set, the regression equations resulted in basal areas that were, on average, underestimated by 2.1 m2 ha−1, and biomass values were underestimated by 16 Mg ha−1, and explained 37% and 33% of variance, respectively. Differences in the magnitude of the coefficients of determination were due to the wider range of stand conditions found in the chronosequence data set; the standard deviation of residual values were lower in the stem map data set than on the chronosequence data sets. Stepwise multiple regression was performed to predict the two stand structure attributes using the canopy height profile data directly as independent variables, but they did not improve the accuracy of the estimates over the height index approach.

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)).

Laser altimeter canopy height profiles: methods and validation for closed-canopy, broadleaf forests

Waveform-recording laser altimeter observations of vegetated landscapes provide a time-resolved measure of laser pulse backscatter energy from canopy surfaces and the underlying ground. Airborne laser altimeter waveform data was acquired using the Scanning Lidar Imager of Canopies by Echo Recovery (SLICER) for a successional sequence of four, closed-canopy, deciduous forest stands in eastern Maryland. The four stands were selected so as to include a range of canopy structures of importance to forest ecosystem function, including variation in the height and roughness of the outermost canopy surface and the vertical organization of canopy stories and gaps. The character of the SLICER backscatter signal is described and a method is developed that accounts for occlusion of the laser energy by canopy surfaces, transforming the backscatter signal to a canopy height profile (CHP) that quantitatively represents the relative vertical distribution of canopy surface area. The transformation applies increased weighting to the backscatter amplitude as a function of closure through the canopy and assumes a horizontally random distribution of the canopy components. SLICER CHPs, averaged over areas of overlap where altimeter ground tracks intersect, are shown to be highly reproducible. CHP transects across the four stands reveal spatial variations in vegetation, at the scale of the individual 10-m-diameter laser footprints, within and between stands. Averaged SLICER CHPs are compared to analogous height profile results derived from ground-based sightings to plant intercepts measured on plots within the four stands. The plots were located on the segments of the altimeter ground tracks from which averaged SLICER CHPs were derived, and the ground observations were acquired within 2 weeks of the SLICER data acquisition to minimize temporal change. The differences in canopy structure between the four stands is similarly described by the SLICER and ground-based CHP results. However, a chi-square test of similarity documents differences that are statistically significant. The differences are discussed in terms of measurement properties that define the smoothness of the resulting CHPs and canopy properties that may vertically bias the CHP representations of canopy structure. The statistical differences are most likely due to the more noisy character of the ground-based CHPs, especially high in the canopy where ground-based sightings are rare resulting in an underestimate of canopy surface area and height, and to departures from assumptions of canopy uniformity, particularly regarding lack of clumping and vertically constant canopy reflectance, which bias the CHPs. The results demonstrate that the SLICER observations reliably provide a measure of canopy structure that reveals ecologically interesting structural variations such as those characterizing a successional sequence of closed-canopy, broadleaf forest stands.

Amazon forests maintain consistent canopy structure and greenness during the dry season

The seasonality of sunlight and rainfall regulates net primary production in tropical forests. Previous studies have suggested that light is more limiting than water for tropical forest productivity, consistent with greening of Amazon forests during the dry season in satellite data. We evaluated four potential mechanisms for the seasonal green-up phenomenon, including increases in leaf area or leaf reflectance, using a sophisticated radiative transfer model and independent satellite observations from lidar and optical sensors. Here we show that the apparent green up of Amazon forests in optical remote sensing data resulted from seasonal changes in near-infrared reflectance, an artefact of variations in sun-sensor geometry. Correcting this bidirectional reflectance effect eliminated seasonal changes in surface reflectance, consistent with independent lidar observations and model simulations with unchanging canopy properties. The stability of Amazon forest structure and reflectance over seasonal timescales challenges the paradigm of light-limited net primary production in Amazon forests and enhanced forest growth during drought conditions. Correcting optical remote sensing data for artefacts of sun-sensor geometry is essential to isolate the response of global vegetation to seasonal and interannual climate variability.

The ICESat-2 Laser Altimetry Mission

Satellite and aircraft observations have revealed that remarkable changes in the Earths polar ice cover have occurred in the last decade. The impacts of these changes, which include dramatic ice loss from ice sheets and rapid declines in Arctic sea ice, could be quite large in terms of sea level rise and global climate. NASAs Ice, Cloud and Land Elevation Satellite-2 (ICESat-2), currently planned for launch in 2015, is specifically intended to quantify the amount of change in ice sheets and sea ice and provide key insights into their behavior. It will achieve these objectives through the use of precise laser measurements of surface elevation, building on the groundbreaking capabilities of its predecessor, the Ice Cloud and Land Elevation Satellite (ICESat). In particular, ICESat-2 will measure the temporal and spatial character of ice sheet elevation change to enable assessment of ice sheet mass balance and examination of the underlying mechanisms that control it. The precision of ICESat-2s elevation measurement will also allow for accurate measurements of sea ice freeboard height, from which sea ice thickness and its temporal changes can be estimated. ICESat-2 will provide important information on other components of the Earth System as well, most notably large-scale vegetation biomass estimates through the measurement of vegetation canopy height. When combined with the original ICESat observations, ICESat-2 will provide ice change measurements across more than a 15-year time span. Its significantly improved laser system will also provide observations with much greater spatial resolution, temporal resolution, and accuracy than has ever been possible before.

Rift deflection, migration, and propagation: Linkage of the Ethiopian and Eastern rifts, Africa

The Main Ethiopian and Eastern (Gregory) rifts, sectors of the East African rift system, overlap in a 300-km-wide system of extensional basins that is more than three times the breadth of either rift away from the zone of overlap. The oldest volcanic rocks (Eocene) and possibly the oldest rift basins (Oligocene) of the East African rift system occur in this zone of overlap. The objectives of field, remote sensing, and geochronology (K-Ar and 40 Ar/ 39 Ar) studies in southwestern Ethiopia were to establish a chronology of rifting and volcanism in the zone of overlap, and to correlate stratigraphic sequences with those in the Kenya rift to the south and in the Main Ethiopian rift to the north. Field observations and cross sections show that basins are bounded by steeply dipping faults, stratal dips are <30°, and that extension accommodated by the intrusion of dikes is volumetrically insignificant. Thus, the style of faulting is similar to that elsewhere in East Africa south of the Afar rift. Initial volcanism between ca. 45 and 33 Ma preceded faulting and uplift, except for reactivation of some Mesozoic rift structures near the Sudan-Ethiopia border and in northern Kenya. Extensional basins began to form in late Oligocene time in the Eastern rift, and in early Miocene time in the Main Ethiopian rift. Small degrees of extension and associated volcanism in the broadly rifted zone may have been triggered by extension in the Red Sea, as well as by lithospheric heating above a mantle plume. The anomalous breadth of the zone is a consequence of rift propagation and migration, rather than basin-and-range‐style extension; both the Main Ethiopian rift and Eastern rifts have propagated along north-south lines, and the Eastern rift has migrated ~200 km eastward since late Oligocene time. The distribution of seismicity and Quaternary volcanism suggest that the Eastern and Main Ethiopian rifts are currently linked across a 200-km-wide zone between the Omo and Segen basins.

High-resolution lidar topography of the Puget Lowland, Washington - A bonanza for earth science

More than 10,000 km2 of high-resolution, public-domain topography acquired by the Puget Sound Lidar Consortium is revolutionizing investigations of active faulting, continental glaciation, landslides, and surficial processes in the seismically active Puget Lowland. The Lowland—the population and economic center of the Pacific Northwest—presents special problems for hazards investigations, with its young glacial topography, dense forest cover, and urbanization. Lidar mapping during leaf-off conditions has led to a detailed digital model of the landscape beneath the forest canopy. The surface thus revealed contains a rich and diverse record of previously unknown surface-rupturing faults, deep-seated landslides, uplifted Holocene and Pleistocene beaches, and subglacial and periglacial features. More than half a dozen suspected postglacial fault scarps have been identified to date. Five scarps that have been trenched show evidence of large, Holocene, surfacerupturing earthquakes.