Soil carbon estimation from eucalyptus grandis using canopy spectra

Mapping soil fertility parameters, such as soil carbon (C), is fundamentally important for forest management and research related to forest growth and climate change. This study seeks to establish the link between  Eucalyptus grandis canopy spectra and soil carbon using raw and continuum-removed spectra. Canopy-level  spectra were collected using a hand-held 350-2500nm spectroradiometer and soil samples obtained at depths from 0-1.2m and analysed for carbon content. Partial least squares (PLS) selection was used to selected  optimal bands for soil carbon assessment and further bootstrapped to select 35 Variable Importance in  Projection (VIP) parameters, based on correlation (r) and standard error (SE). Results indicated that  continuum-removed spectra and soil C yielded stronger significant correlations, when compared to soil C and  raw spectra. The predictive models developed for future soil C estimation showed that continuum-removed  spectra exhibited improved adjusted R2 values in both instances, i.e., when using all significant bands and the  most significant 35 VIP bands. The results indicate a distinct potential for forest managers to monitor the  status of soil C in commercial forestry compartments using canopy-level spectra and determine how much  fertilizer is required to optimize tree growth.Keywords: Soil carbon, Canopy spectr

Manned Aircraft Versus Small Unmanned Aerial System—Forestry Remote Sensing Comparison Utilizing Lidar and Structure-From-Motion for Forest Carbon Modeling and Disturbance Detection

Sustainable forest management relies on the acquisition of timely (change detection) and accurate structural information of forest landscapes. Light detection and ranging (lidar) remote sensing platforms enable rapid, three-dimensional (3-D), structural data collection with a high spatial resolution. This study explores a functional carbon model applied to a dense, closed deciduous forest. Data are collected by manned airborne systems and unmanned aerial system, producing both lidar and structure-from-motion (SfM) 3-D mapping. A hybrid approach combining cost-effective SfM-generated data with lidar-derived digital elevation models also is explored, since the SfM fails to produce adequate terrain returns. Carbon modeling results are comparable to those achieved by the initial developers (r2 ¼ 0.64 versus r2 ¼ 0.72), despite the challenging uneven-aged forest environment. Vertical profiles, mapped utilizing a volumetric point density from the manned airborne lidar, are leveraged to train a binary classifier for disturbance detection. Producer’s accuracy, user’s accuracy, and Kappa statistic for disturbance detection are 94.1%, 92.2%, and 89.8%, respectively, showing a high likelihood of detecting disturbances (harvesting). The results bode well for the use of unmanned aerial system (UAS) systems, and either lidar or SfM, to assess forest stocking. Although disturbance detection is successful, further study is required to validate the use of UAS, and especially SfM, for this task

Cryopreservation of the infective larvae of the common nematodes of ruminants

Exsheathed infective larvae (L 3) of 19 species of nematodes were tested for infectivity in either sheep or cattle after they had been frozen in 0, 9% NaCI solution, stored for a relatively short time in the gas phase of liquid nitrogen and subsequently thawed. In addition, 13 of these species were tested after similar storage for up to 18 months. In sheep, Haemonchus contortus, Ostertagia circumcincta, Trichostrongylus axei, Trichostrongylus colubriformis, Nematodirus spathiger and Oesophagostomum columbianum were viable after 2 years of cryopreservation, a mean of > 90% of the L 3 being alive when thawed after this period. Similar results were obtained with Chabertia ovina L 3 after 18 months and with Marshallagia marshalli, Trichostrongylus falculatus and Dictyocaulus filaria, after a short period of freezing. On the other hand, Gaigeria pachyscelis and Strongyloides papillosus survived freezing for up to 7 months but neither was viable at the end of this period, nor was exsheathed G. pachyscelis viable without freezing. Most of these infestations were established by inoculating the infective larvae into the abomasum and/or duodenum. M. marshalli, T. falculatus and C. ovina also proved infective after oral dosing. D. filaria, the only other species tested by this route, was not infective when dosed per os after thawing. The infective larvae of the bovine nematodes, Haemonchus placei, Ostertagia ostertagi, Nematodirus helvetianus, Oesophagostomum radiatum, Cooperia pectinata and Cooperia punctata survived freezing for a mean of 26 months, > 90% being alive on thawing, but infectivity was generally lower than with the same genera in sheep. Even when not frozen, exsheathed Bunostomum phlebotomum was non-infective. When Cooperia spp. after thawing were tested for infectivity by the oral route, more worms developed in one calf infested orally than in another infested by inoculation into the duodenum. Ova of H. contortus, M. marshalli, 0. circumcincta, T. colubnformis, T. falculatus, N. spathiger, C. ovina, H. placei, 0. ostertagi, Cooperia spp. and N. helvetianus were recovered from the faeces of animals infested with cryopreserved L 3. No ova of 0. columbianum or 0 . radiatum were recovered from faeces, because differential larval counts were performed before they were patent. Nevertheless, gravid females were obtained post-mortem. Frozen L 3 of N. helvetianus were used to re-establish a pure strain in calves, 2,3 million ova being recovered from infestations with 10 670 L 3 frozen for 26 months. The infectivity of the progeny of frozen L 3 was tested with M. marshalli and C. ovina. In both instances infectivity was high and the worms which developed also produced ova, thus completing the cycle. This appears to be the first report of infective larvae of parasitic nematodes retaining their infectivity after being frozen in liquid nitrogen (gas phase) for longer than 2 years. This is also apparently the first time that M. marshalli, T. colubriformis, T. falculatus, T. axei, N. spathiger, C. ovina, D. filaria, H. placei, 0. ostertagi, Cooperia spp., N. helvetianus and 0. radiatum have been shown to be infective after freezing in liquid nitrogen (gas phase), and that G. pachyscelis, S. papillosus and B. phlebotomum have been found to survive similar freezing and thawing, even though they do not appear to be infective thereafter.The articles have been scanned in colour with a HP Scanjet 5590; 300dpi. Adobe Acrobat XI Pro was used to OCR the text and also for the merging and conversion to the final presentation PDF-format

Influence of Drone Altitude, Image Overlap, and Optical Sensor Resolution on Multi-View Reconstruction of Forest Images

CITATION: Seifert, E., et al. 2019. Influence of drone altitude, image overlap, and optical sensor resolution on multi-view reconstruction of forest images. Remote Sensing, 11(10):1252, doi:10.3390/rs11101252.The original publication is available at http://www.mdpi.comPublication of this article was funded by the Stellenbosch University Open Access FundRecent technical advances in drones make them increasingly relevant and important toolsfor forest measurements. However, information on how to optimally set flight parameters and choosesensor resolution is lagging behind the technical developments. Our study aims to address this gap,exploring the effects of drone flight parameters (altitude, image overlap, and sensor resolution) onimage reconstruction and successful 3D point extraction. This study was conducted using video footageobtained from flights at several altitudes, sampled for images at varying frequencies to obtain forwardoverlap ratios ranging between 91 and 99%. Artificial reduction of image resolution was used to simulatesensor resolutions between 0.3 and 8.3 Megapixels (Mpx). The resulting data matrix was analysed usingcommercial multi-view reconstruction (MVG) software to understand the effects of drone variables on(1) reconstruction detail and precision, (2) flight times of the drone, and (3) reconstruction times duringdata processing. The correlations between variables were statistically analysed with a multivariategeneralised additive model (GAM), based on a tensor spline smoother to construct response surfaces.Flight time was linearly related to altitude, while processing time was mainly influenced by altitudeand forward overlap, which in turn changed the number of images processed. Low flight altitudesyielded the highest reconstruction details and best precision, particularly in combination with high imageoverlaps. Interestingly, this effect was nonlinear and not directly related to increased sensor resolution athigher altitudes. We suggest that image geometry and high image frequency enable the MVG algorithmto identify more points on the silhouettes of tree crowns. Our results are some of the first estimates ofreasonable value ranges for flight parameter selection for forestry applications.https://www.mdpi.com/2072-4292/11/10/1252Publisher's versio

A Density-Based Approach for Leaf Area Index Assessment in a Complex Forest Environment Using a Terrestrial Laser Scanner

Forests are an important part natural ecosystems, by for example providing food, fiber, habitat, and biodiversity, all of which contribute to stable natural systems. Assessing and modeling the structure and characteristics of forests, e.g., Leaf Area Index (LAI), volume, biomass, etc., can lead to a better understanding and management of these resources. In recent years, Terrestrial Laser Scanning (TLS) has been recognized as a tool that addresses many of the limitations of manual and traditional forest data collection methods. In this study, we propose a density-based approach for estimating the LAI in a structurally-complex forest environment, which contains variable and diverse structural attributes, e.g., non-circular stem forms, dense canopy and below-canopy vegetation cover, and a diverse species composition. In addition, 242 TLS scans were collected using a portable low-cost scanner, the Compact Biomass Lidar (CBL), in the Hawaii Volcanoes National Park (HAVO), Hawaii Island, USA. LAI also was measured for 242 plots in the site, using an AccuPAR LP-80 ceptometer. The first step after cleaning the point cloud involved detecting the higher forest canopy in the light detection and ranging (lidar) point clouds, using normal change rate assessment. We then estimated Leaf Area Density (LAD), using a voxel-based approach, and divided the canopy point cloud into five layers in the Z (vertical) direction. These five layers subsequently were divided into voxels in the X direction, where the size of these voxels were obtained based on inter-quartile analysis and the number of points in each voxel. We hypothesized that the intensity returned to the lidar system from woody materials, like branches, would be higher than from leaves, due to the liquid water absorption feature of the leaves and higher reflectance for woody material at the 905 nm laser wavelength. We also differentiated between foliar and woody materials using edge detection in the images from projected point clouds and evaluated the density of these regions to support our hypothesis. Density of points, or the number of points divided by the volume of a grid, in a 3D grid size of 0.1 m, was calculated for each of the voxels. The grid size was determined by investigating the size of the branches in the lower portion of the canopy. Subsequently, we fitted a Kernel Density Estimator (KDE) to these values, with the threshold set based on half of the area under the curve in each of the density distributions. All the grids with a density below the threshold were labeled as leaves, while those grids above the threshold were identified as non-leaves. Finally, we modeled LAI using the point densities derived from the TLS point clouds and the listed analysis steps. This model resulted in an R 2 value of 0.88. We also estimated the LAI directly from lidar data using the point densities and calculating LAD, which is defined as the total one-sided leaf area per unit volume. LAI can be obtained as the sum of the LAD values in all the voxels. The accuracy of LAI estimation was 90%, with an RMSE value of 0.31, and an average overestimation of 9% in TLS-derived LAI, when compared to field-measured LAI. Algorithm performance mainly was affected by the vegetation density and complexity of the canopy structures. It is worth noting that, since the LAI values cannot be considered spatially independent throughout all the plots in this site, we performed semivariogram analysis on the field-measured LAI data. This analysis showed that the LAI values can be assumed to be independent in plots that are at least 30 m apart. As a result, we divided the data into six subsets in which the plots were 30 m spaced. The R 2 values for these subsets, based on modeling of the field-measured LAI using leaf point density values, ranged between 0.84–0.96. The results bode well for using this method for efficient, automatic, and accurate/precise estimation of LAI values in complex forest environments, using a low-cost, rapid-scan TLS

The use of airborne laser scanning to develop a pixel-based stratification for a verified carbon offset project

Background The voluntary carbon market is a new and growing market that is increasingly important to consider in managing forestland. Monitoring, reporting, and verifying carbon stocks and fluxes at a project level is the single largest direct cost of a forest carbon offset project. There are now many methods for estimating forest stocks with high accuracy that use both Airborne Laser Scanning (ALS) and high-resolution optical remote sensing data. However, many of these methods are not appropriate for use under existing carbon offset standards and most have not been field tested. Results This paper presents a pixel-based forest stratification method that uses both ALS and optical remote sensing data to optimally partition the variability across an ~10,000 ha forest ownership in Mendocino County, CA, USA. This new stratification approach improved the accuracy of the forest inventory, reduced the cost of field-based inventory, and provides a powerful tool for future management planning. This approach also details a method of determining the optimum pixel size to best partition a forest. Conclusions The use of ALS and optical remote sensing data can help reduce the cost of field inventory and can help to locate areas that need the most intensive inventory effort. This pixel-based stratification method may provide a cost-effective approach to reducing inventory costs over larger areas when the remote sensing data acquisition costs can be kept low on a per acre basis

Performance measurement as a tool for software engineering

Some software development teams regard software performance measurement as a mere luxury. When it happens, it often tends to be infrequent, insufficient and subjective. Countless software projects were sent into an uncontrollable spiral of poor management and unsatisfactory results. By revisiting old ideas and policies, many companies have turned themselves around. To ensure that software engineering does the same, technologies and procedures have to be reevaluated. The fact that many companies have decided to cut costs on technology expenditure necessitates software development teams to look for alternative options for deploying high performance software systems. As many companies are moving into the electronic era and evolving to the next stage of evolution, electronic commerce, the more important it has become to apply these concepts on Internet development projects and procedures. The Internet market has shown that two software providers are aiming for worldwide domination of Internet server deployment, being Microsoft and Apache. Currently, the Apache web server is the most commonly used server on the Internet today (60%), with Microsoft's Internet Information Server (25%) in a strong second place. The need for higher throughput and better services is getting more with each passing day. It increases the pressure on these two software vendors to provide the best architecture for their clients' needs. This study intends to provide the reader with an objective view of a basic performance comparison between these two products and tries to find a correlation between the performance tests and the products' popularity standings. The tests for this study were performed on identical hardware architectures with one difference, being the operating system. By comparing the costly proprietary Microsoft solution with its cheaper open source rival, Linux, certain opinions were tested. Would a product developed by a software company that invests millions of dollars in their products perform better than this free-for-all solution, or would the selfless inputs of hundreds of developers all over the world finally payoff through the creation of the world's best Internet server? The results of these tests were evaluated through formal statistical methods, providing overall comparisons of several common uses of web servers. These results were implemented in a small field test to prove the findings in practice with some interesting outcomes in terms of supportive technologies, new rapid application development (RAD) tools and data access models. This research in itself will not change the mind of any Internet programmer. What it hopes to achieve is to demonstrate software engineers that current processes and methods of developing software are not always the right way of doing things. Furthermore, it highlights many important factors often ignored or overlooked while managing software projects. Change management, process re-engineering and risk management form crucial elements of software development projects. By not adhering to certain critical elements of software development, software projects stand the chance of not reaching their goals and could even fail completely. Performance measurement acts as a tool for software engineering, providing guidelines for technological decisions, project management and ultimately, project success.Dissertation (MSc (Computer Science))--University of Pretoria, 2005.Computer Scienceunrestricte

Estimating plot-level forest structural attributes using high spectral resolution ASTER satellite data in even-aged Eucalyptus plantations in southern KwaZulu-Natal, South Africa

This study assessed the suitability of both visible and shortwave infrared of ASTER reflectance bands and various vegetation indices for estimating forest structural attributes of Eucalyptus species. The study was conducted in even-aged monoculture plantations of E. grandis and E. nitens in the southern KwaZulu-Natal Midlands of South Africa. Empirical relationships between forest structural attributes, i.e. stems per hectare (SPHA), diameter at breast height (DBH), mean tree height (MTH), basal area and volume, and ASTER data were derived using correlation and canonical correlation analysis (CCA). The results indicated weak relationships between the studied forest structural attributes and ASTER data. In the younger plantation stands (4–6 years) the adjusted R2 values from CCA regression for SPHA, DBH, MTH, basal area and volume were 54.2, 63.5, 33.8, 25.4 and 30.3, respectively. The adjusted R2 values in the mature stands (7–9 years) were distinctly weaker with values of 50.7, 55.8, 25.1, 20.2 and 27.3 for SPHA, DBH, MTH, basal area and volume, respectively. The results imply that ASTER satellite data are not applicable to forest structural attribute estimation in commercially managed forest stands.Keywords: ASTER data set; forest structural attributes; spectral vegetation indices Southern Forests 2008, 70(3): 227–23

Image-based reflectance conversion of ASTER and IKONOS imagery as precursor to structural assessment of plantation forests in KwaZulu-Natal, South Africa

Reflectance-converted imagery is a requirement for establishing temporally robust remote sensing algorithms, given the reduction of time-specific atmospheric effects. Thus, in this study image-based atmospheric correction methods for ASTER and IKONOS imagery for retrieving surface reflectance of plantation forests in KwaZulu-Natal, South Africa were evaluated. This effort formed part of a larger initiative that focused on retrieval of forest structural attributes from resultant reflectance imagery. Atmospheric correction methods in this study included the apparent reflectance model (AR), dark object subtraction model (DOS), and the cosine approximation model (COST). Spectral signatures derived from different image-based models for ASTER and  IKONOS were inspected visually as first departure. This was followed by comparison of the total accuracy and Kappa index computed from supervised classification of images that were derived from different image-based atmospheric correction of ASTER and IKONOS imagery. The classification accuracy of DOS images derived from ASTER and IKONOS imagery exhibited percentages of 93.3% and 94.7%, respectively. Classification accuracies for images from AR and COST, on  the other hand, resulted in lower accuracy values of 87.9% and 83.6% for ASTER and 90.5% and 92.8% for IKONOS, respectively. We concluded that the image-based DOS model was better suited to  atmospheric correction for ASTER and IKONOS imagery in this study area and for the purpose of forest structural assessment. This has important implications for the operational use of similar imagery types for forest inventory approaches.Keywords: ASTER; IKONOS; image-based atmospheric correction; plantation forests; surface reflectanceSouthern Forests 2009, 71(4): 259–26