Environmental Sensing Systems

Melbourne, Australia

Environmental Sensing Systems

Melbourne, Australia
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Moore C.E.,Monash University | Moore C.E.,Urbana University | Brown T.,Australian National University | Keenan T.F.,Macquarie University | And 15 more authors.
Biogeosciences | Year: 2016

Phenology is the study of periodic biological occurrences and can provide important insights into the influence of climatic variability and change on ecosystems. Understanding Australia's vegetation phenology is a challenge due to its diverse range of ecosystems, from savannas and tropical rainforests to temperate eucalypt woodlands, semiarid scrublands, and alpine grasslands. These ecosystems exhibit marked differences in seasonal patterns of canopy development and plant life-cycle events, much of which deviates from the predictable seasonal phenological pulse of temperate deciduous and boreal biomes. Many Australian ecosystems are subject to irregular events (i.e. drought, flooding, cyclones, and fire) that can alter ecosystem composition, structure, and functioning just as much as seasonal change. We show how satellite remote sensing and ground-based digital repeat photography (i.e. phenocams) can be used to improve understanding of phenology in Australian ecosystems. First, we examine temporal variation in phenology on the continental scale using the enhanced vegetation index (EVI), calculated from MODerate resolution Imaging Spectroradiometer (MODIS) data. Spatial gradients are revealed, ranging from regions with pronounced seasonality in canopy development (i.e. tropical savannas) to regions where seasonal variation is minimal (i.e. tropical rainforests) or high but irregular (i.e. arid ecosystems). Next, we use time series colour information extracted from phenocam imagery to illustrate a range of phenological signals in four contrasting Australian ecosystems. These include greening and senescing events in tropical savannas and temperate eucalypt understorey, as well as strong seasonal dynamics of individual trees in a seemingly static evergreen rainforest. We also demonstrate how phenology links with ecosystem gross primary productivity (from eddy covariance) and discuss why these processes are linked in some ecosystems but not others. We conclude that phenocams have the potential to greatly improve the current understanding of Australian ecosystems. To facilitate the sharing of this information, we have formed the Australian Phenocam Network (http://phenocam.org.au/). © Author(s) 2016.


Yang X.,University of Massachusetts Boston | Schaaf C.,University of Massachusetts Boston | Strahler A.,Boston University | Li Z.,Boston University | And 15 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2013

This study presents a three-dimensional (3-D) forest reconstruction methodology using the new and emerging science of terrestrial full-waveform lidar scanning, which can provide rapid and efficient measurements of canopy structure. A 3-D forest reconstruction provides a new pathway to estimate forest structural parameters such as tree diameter at breast height, tree height, crown diameter, and stem count density (trees per hectare). It enables the study of the detailed structure study with respect to the canopy (foliage or branch/trunk), as well as the generation of a digital elevation model (DEM) and a canopy height model (CHM) at the stand level. Leaf area index (LAI) and Foliage area volume density profile directly estimated from voxelized 3-D reconstruction agree with measurements from field and airborne instrument. A 3-D forest reconstruction allows virtual direct representation of forest structure, and provides consistent and reliable validation data sources for airborne or spaceborne data. © 2013 IEEE.


Li Z.,Boston University | Douglas E.,Boston University | Strahler A.,Boston University | Schaaf C.,University of Massachusetts Boston | And 15 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2013

Terrestrial laser scanning combining both near-infrared (NIR) and shortwave-infrared (SWIR) wavelengths can readily distinguish broad leaves from trunks, branches, and ground surfaces. Merging data from the 1548 nm SWIR laser in the Dual-Wavelength Echidna® Lidar (DWEL) instrument in engineering trials with data from the 1064 nm NIR laser in the Echidna ® Validation Instrument (EVI), we imaged a deciduous forest scene at the Harvard Forest, Petersham, Massachusetts, and showed that trunks are about twice as bright as leaves at 1548 nm, while they have about equal brightness at 1064 nm. The reduced return of leaves in the SWIR is also evident in merged point clouds constructed from the two laser scans. This distinctive difference between leaf and trunk reflectance in the two wavelengths validates the principle of effective discrimination of leaves from other targets using the new dual-wavelength instrument. © 2013 IEEE.


Yang X.,University of Massachusetts Boston | Yang X.,Boston University | Strahler A.H.,Boston University | Schaaf C.B.,University of Massachusetts Boston | And 10 more authors.
Remote Sensing of Environment | Year: 2013

Three-dimensional (3-D) reconstructions of forest stands, constructed from scans of the Echidna® full-waveform terrestrial lidar, provide a new pathway to estimate forest structural parameters such as tree diameter at breast height, tree height, crown diameter, and stem count density (trees per hectare). We provide such reconstructions using data from the Echidna® Validation Instrument (EVI), which emits laser pulses at 1064nm wavelength and digitizes the full return waveform. We reconstructed four stands from the Sierra National Forest and two stands from Harvard Experimental Forest of 50m by 50m size, with varying tree density and species, using data acquired in 2008 and 2009. Our procedure processes each lidar pulse return to identify one or multiple "hits" and their associated peak return power; converts peak power to apparent reflectance; locates hits in Cartesian coordinate space and stores them as points in a point cloud with associated attributes; registers and merges five (Sierra) or nine (Harvard) overlapping scans into a single point cloud; identifies the ground plane and classifies ground hits; produces a local digital elevation model; classifies non-ground hits as trunk/branch or foliage hits using the relative width of the return pulse; and uses commercial software tools to display, manipulate, and interact with the point cloud to make direct measurements of trees in the virtual space of the reconstruction. Results show good to very good agreement between virtual and manual measurements of tree diameter, height, and crown size, with R2 values ranging from 0.70 to 0.99. © 2013 Elsevier Inc.


Soto-Berelov M.,RMIT University | Jones S.,RMIT University | Mellor A.,Australian Department of Primary Industries and Fisheries | Culvenor D.,Environmental Sensing Systems | And 5 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2013

Collaborative ventures in research infrastructure can allow multiple stakeholders to benefit from outcomes that may otherwise be cost prohibitive. In this study, we discuss how the investment in research infrastructure by various sectors of the academic, scientific, and land management community is promoting high end forest ecosystem research in Australia. Three 25km2 woodland and open canopy forests that are representative of Victoria's 8 million hectares of public forests were incorporated into the Terrestrial Ecosystem Research Network's calibration/validation campaign. The sites are being used to develop algorithms that will assist land management agencies across various states to characterize fundamental forest attributes at a landscape level. Wireless technology (VegNet) is also being trialed at these sites to investigate forest condition over time. This study provides an example of how the establishment and co-investment in research infrastructure amongst different sectors of the scientific community promote data sharing and ultimately expand our understanding of forest ecosystems, which can in turn be used for monitoring and to inform policy and land management decision making. © 2013 IEEE.


Zhao F.,Boston University | Zhao F.,University of Maryland University College | Yang X.,Boston University | Yang X.,University of Massachusetts Boston | And 15 more authors.
Remote Sensing of Environment | Year: 2013

Foliage profiles retrieved from a scanning, terrestrial, near-infrared (1064. nm), full-waveform lidar, the Echidna Validation Instrument (EVI), agree well with those obtained from an airborne, near-infrared, full-waveform, large footprint lidar, the Lidar Vegetation Imaging Sensor (LVIS). We conducted trials at 5 plots within a conifer stand at Sierra National Forest in August, 2008. Foliage profiles retrieved from these two lidar systems are closely correlated (e.g., r = 0.987 at 100. m horizontal distances) at large spatial coverage while they differ significantly at small spatial coverage, indicating the apparent scanning perspective effect on foliage profile retrievals. Also we noted the obvious effects of local topography on foliage profile retrievals, particularly on the topmost height retrievals. With a fine spatial resolution and a small beam size, terrestrial lidar systems complement the strengths of the airborne lidars by making a detailed characterization of the crowns from a small field site, and thereby serving as a validation tool and providing localized tuning information for future airborne and spaceborne lidar missions. © 2013.


Calders K.,Wageningen University | Newnham G.,CSIRO | Burt A.,University College London | Murphy S.,University of Melbourne | And 9 more authors.
Methods in Ecology and Evolution | Year: 2015

Summary: Allometric equations are currently used to estimate above-ground biomass (AGB) based on the indirect relationship with tree parameters. Terrestrial laser scanning (TLS) can measure the canopy structure in 3D with high detail. In this study, we develop an approach to estimate AGB from TLS data, which does not need any prior information about allometry. We compare these estimates against destructively harvested AGB estimates and AGB derived from allometric equations. We also evaluate tree parameters, diameter at breast height (DBH) and tree height, estimated from traditional field inventory and TLS data. Tree height, DBH and AGB data are collected through traditional forest inventory, TLS and destructive sampling of 65 trees in a native Eucalypt Open Forest in Victoria, Australia. Single trees are extracted from the TLS data and quantitative structure models are used to estimate the tree volume directly from the point cloud data. AGB is inferred from these volumes and basic density information and is then compared with the estimates derived from allometric equations and destructive sampling. AGB estimates derived from TLS show a high agreement with the reference values from destructive sampling, with a concordance correlation coefficient (CCC) of 0·98. The agreement between AGB estimates from allometric equations and the reference is lower (CCC = 0·68-0·78). Our TLS approach shows a total AGB overestimation of 9·68% compared to an underestimation of 36·57-29·85% for the allometric equations. The error for AGB estimates using allometric equations increases exponentially with increasing DBH, whereas the error for AGB estimates from TLS is not dependent on DBH. The TLS method does not rely on indirect relationships with tree parameters or calibration data and shows better agreement with the reference data compared to estimates from allometric equations. Using 3D data also enables us to look at the height distributions of AGB, and we demonstrate that 80% of the AGB at plot level is located in the lower 60% of the trees for a Eucalypt Open Forest. This method can be applied in many forest types and can assist in the calibration and validation of broad-scale biomass maps.s © 2014 British Ecological Society.


Sims N.C.,CSIRO | Culvenor D.,Environmental Sensing Systems | Newnham G.,CSIRO | Coops N.C.,University of British Columbia | Hopmans P.,Timberlands Research Pty Ltd
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Year: 2013

EO-1/Hyperion data can potentially reduce the cost of nutrition assessments in plantation forests, supplementing standard point-based measurements with comprehensive and repeated broad-acre coverage. We present a synopsis of studies using EO-1/Hyperion data for foliar nutrition assessments in Australia. The earliest study compared modeling methods and calculated models in the order of r^{2} = 0.7 for Nitrogen, Phosphorus and Boron in Eucalyptus and Pinus species. Several recommendations of that work were adopted in a subsequent project which concluded that observing stand structure may improve nutrient prediction models calibrated from image data over those calibrated from laboratory spectra. The most recent study examined the range of age classes over which nutrients could be accurately predicted in P. radiata from Hyperion images. Canopy cover fraction, calculated using spectral mixture analysis, ranged from 69% in unthinned 5 year old stands to 43% and 41% in stands 10 to 20 years old that had been thinned once or twice respectively. The r2 value when predicting Nitrogen across all age classes was 0.45 increasing to 0.87 when calibrated on only the 5 year old trees. Collectively, these studies demonstrate that several important nutrients can be accurately mapped from Hyperion data at ages that are critical for the management of plantation forests. However, some of Hyperion's spatial and radiometric characteristics limit its practical operational application. This manuscript discusses potential improvements that might be provided by the HyspIRI mission, and the key challenges in developing hyperspectral image data as an operational tool for forest nutrition assessments in Australia. © 2008-2012 IEEE.


Yang X.,University of Massachusetts Boston | Schaaf C.,University of Massachusetts Boston | Strahler A.,Boston University | Kunz T.,Boston University | And 9 more authors.
Canadian Journal of Remote Sensing | Year: 2013

The nature of forest structure plays an important role in the study of foraging behaviors of bats. In this study, we demonstrate a new combined methodology that uses both thermal imaging technology and a ground-based LiDAR system to record and reconstruct Eptesicus fuscus (big brown bats) flight trajectories in three-dimensional (3-D) space. The combination of the two 3-D datasets provided a fine-scale reconstruction of the flight characteristics adjacent to and within the forests. A 3-D forest reconstruction, assembled from nine Echidna Validation Instrument LiDAR scans over the 1 ha site area, provided the essential environmental variables for the study of bat foraging behaviors, such as the canopy height, terrain, location of the obstacles, and canopy openness at a bat roosting and maternity site in Petersham, Massachusetts. Flight trajectories of 24 bats were recorded over the 25 m × 37.5 m region within the LiDAR forest reconstruction area. The trajectories were reconstructed using imaging data from multiple FLIR ThermoVision SC8000 cameras and were co-registered to the 3-D forest reconstruction. Twenty-four of these flight trajectories were categorized into four different behavior groups according to velocity and altitude analysis of the flight trajectories. Initial results showed that although all bats were guided by echolocation and avoided hitting a tree that was in all of their flight paths, different bats chose different flight routes. This study is an initial demonstration of the power of coupling thermal image analysis and LiDAR forest reconstructions. Our goal was to break ground for future ecological studies, where more extensive flight trajectories of bats can be coupled with the canopy reconstructions to better establish responses of bats to different habitat characteristics and clutter, which includes both static (trees) and dynamic (other bats) obstacles. © 2013 CASI.


Portillo-Quintero C.,University of Alberta | Sanchez-Azofeifa A.,University of Alberta | Culvenor D.,Environmental Sensing Systems
Forests | Year: 2014

The use of ceptometers and digital hemispherical photographs to estimate Plant Area Index (PAI) often include biases and errors from instrument positioning, orientation and data analysis. As an alternative to these methods, we used an In-Situ Monitoring LiDAR system that provides indirect measures of PAI and Plant Area Volume Density (PAVD) at a fixed angle, based on optimized principles and algorithms for PAI retrieval. The instrument was installed for 22 nights continuously from September 26 to October 17, 2013 during leaf-fall in an Aspen Parkland Forest. A total of 85 scans were performed (̃4 scans per night). PAI measured decreased from 1.27 to 0.67 during leaf-fall, which is consistent with values reported in the literature. PAVD profiles allowed differentiating the contribution of PAI per forest strata. Phenological changes were captured in four ways: number of hits, maximum cumulative and absolute PAI values, time series of PAVD profiles and PAI values per forest strata. We also found that VEGNET IML Canopy PAI and MODIS LAI values showed a similar decreasing trend and differed by 2%-15%. Our results indicate that the VEGNET IML has great potential for rapid forest structural characterization and for ground validation of PAI/LAI at a temporal frequency compatible with earth observation satellites. © 2014 by the authors.

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