Filters








488 Hits in 7.8 sec

Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys

Andrew T. Hudak, Eva K. Strand, Lee A. Vierling, John C. Byrne, Jan U.H. Eitel, Sebastián Martinuzzi, Michael J. Falkowski
2012 Remote Sensing of Environment  
Traditional stand exam data were used to independently validate 2003 and 2009 tree aboveground biomass predictions and tree aboveground biomass change estimates at the stand level.  ...  A 30-fold difference in LiDAR sampling density between the 2003 and 2009 collections did not affect plot-scale biomass estimation.  ...  For example, forest stand age and rates of ecosystem carbon exchange often exhibit a non-linear relationship, which differs according to species or climate.  ... 
doi:10.1016/j.rse.2012.02.023 fatcat:doi6uj5bnvgv3emm73yed4bs3y

Research Pathways of Forest Above-Ground Biomass Estimation Based on SAR Backscatter and Interferometric SAR Observations

Maurizio Santoro, Oliver Cartus
2018 Remote Sensing  
The use of multi-temporal or multi-frequency data improved the biomass estimates when compared to single-image retrieval. Low frequency SAR backscatter contributed the most to the biomass estimates.  ...  Some studies argued that estimating compartment biomass (in stems, branches, foliage) with different types of SAR observations would lead to an improved estimate of total biomass.  ...  The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.  ... 
doi:10.3390/rs10040608 fatcat:wlv2fd7wgbgzjnrsdcc2hw4u6e

Evaluating the potential to monitor aboveground biomass in forest and oil palm in Sabah, Malaysia, for 2000–2008 with Landsat ETM+ and ALOS-PALSAR

Alexandra C. Morel, Joshua B. Fisher, Yadvinder Malhi
2012 International Journal of Remote Sensing  
Acknowledgements We would like to thank Przemyslaw Zelazowski for the use of his LandCor atmospheric correction algorithm and the helpful suggestions of Heiko Balzter, Julia McMorrow and two anonymous  ...  The latter finding is consistent with McMorrow's (2001) study where she found estimating stand age of oil palm the most difficult for mature plantations.  ...  Table 3 . 3 R 2 and RMSE values for linear regression analysis of each VI to the logarithm of biomass for all oil palm plots and 1 ha forest plots.  ... 
doi:10.1080/01431161.2011.631949 fatcat:262ci54sfvfzzjqshkueo5aicm

Estimating Changes in Forest Attributes and Enhancing Growth Projections: a Review of Existing Approaches and Future Directions Using Airborne 3D Point Cloud Data

Piotr Tompalski, Nicholas C. Coops, Joanne C. White, Tristan R.H. Goodbody, Chris R. Hennigar, Michael A. Wulder, Jarosław Socha, Murray E. Woods
2021 Current Forestry Reports  
By reviewing the relevant findings, we highlight the potential that bi- and multi-temporal point clouds have for enhanced analysis of forest growth.  ...  Recent Findings Existing research across a broad range of forest types has demonstrated that those analyses can be performed using different approaches, levels of detail, or source data.  ...  Linear regression was used to predict H, and nonlinear regression was used to predict BA and V.  ... 
doi:10.1007/s40725-021-00135-w fatcat:cfrjvj3vo5h7paqhm27as3y3zy

Small-footprint lidar estimation of sub-canopy elevation and tree height in a tropical rain forest landscape

Matthew L Clark, David B Clark, Dar A Roberts
2004 Remote Sensing of Environment  
On flatter slopes, variation in vegetation complexity associated with land use caused highly significant differences in DTM error distribution across the landscape.  ...  Linear-regression models explained 51% (4.15-m RMSE) and 95% (2.41-m RMSE) of the variance, respectively.  ...  FLI-MAP data was graciously donated to OTS by the U.S. Army Corps of Engineers Topographic Engineering Center.  ... 
doi:10.1016/j.rse.2004.02.008 fatcat:54mvic7ufnahvnnuyttudrtf5a

Recent Advances in Unmanned Aerial Vehicles Forest Remote Sensing—A Systematic Review. Part II: Research Applications

Riccardo Dainelli, Piero Toscano, Salvatore Filippo Di Gennaro, Alessandro Matese
2021 Forests  
in the Web of Science database by searching for "UAV"+"forest".  ...  Forest sustainable management aims to maintain the income of woody goods for companies, together with preserving non-productive functions as a benefit for the community.  ...  Among the reviewed studies, they are indeed collected and used for dataset validation, accuracy assessment, result comparison, and regression analysis in biomass estimation.  ... 
doi:10.3390/f12040397 fatcat:6mtlejuku5c3xbx2eq7inpdjse

Remote sensing of forest biophysical variables using HyMap imaging spectrometer data

Martin Schlerf, Clement Atzberger, Joachim Hill
2005 Remote Sensing of Environment  
Cross-validation procedure was used to assess the prediction power of the regression models. Analyses were performed on the entire data set or on subsets stratified according to stand age.  ...  It can be stated that the hyperspectral data set contains more information relevant to the estimation of the forest stand variables LAI and VOL than multispectral data.  ...  We greatly acknowledge the compilation of the Forest-GIS by Michael Vohland. We thank Thomas Udelhoven for the valuable guidelines concerning the factor analysis.  ... 
doi:10.1016/j.rse.2004.12.016 fatcat:c3iey2qcjjczxfxizwpimurabu

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America

Christine R. Rollinson, Yao Liu, Ann Raiho, David J. P. Moore, Jason McLachlan, Daniel A. Bishop, Alex Dye, Jaclyn H. Matthes, Amy Hessl, Thomas Hickler, Neil Pederson, Benjamin Poulter (+4 others)
2017 Global Change Biology  
Individual model evaluation and multi-model comparisons with 40 data have largely focused on individual processes at sub-annual to decadal scales.  ...  We compared the sensitivity of net primary productivity 43 (NPP) to temperature, precipitation, and CO2 in ten ecosystem models with the sensitivities 44 found in tree-ring reconstructions of NPP and raw  ...  processes among models on NPP 271 sensitivity to climate and CO2 using linear regression.  ... 
doi:10.1111/gcb.13626 pmid:28084043 fatcat:oie3zwjvrzbqliiyvvwhtni2r4

The Central Amazon biomass sink under current and future atmospheric CO 2 : Predictions from big‐leaf and demographic vegetation models

Jennifer A. Holm, Ryan G. Knox, Qing Zhu, Rosie A. Fisher, Charles D. Koven, Adriano J. Nogueira Lima, William J. Riley, Marcos Longo, Robinson I. Negrón‐Juárez, Alessandro C. Araujo, Lara M. Kueppers, Paul R. Moorcroft (+2 others)
2020 Journal of Geophysical Research - Biogeosciences  
Hence, we simulated an old-growth tropical forest using six versions of four terrestrial models differing in scale of vegetation structure and representation of biogeochemical (BGC) cycling, all driven  ...  With a doubling of CO 2 , three of the four models predicted an appreciable biomass sink (0.77 to 1.24 Mg ha −1 year −1 ).  ...  the sign of the flux (Friedlingstein et al., 2014) , with estimates from tropical forests contributing to a large portion of the uncertainty.  ... 
doi:10.1029/2019jg005500 fatcat:rizvimj2zjgytg4ky7224lanya

Country-wide high-resolution vegetation height mapping with Sentinel-2 [article]

Nico Lang, Konrad Schindler, Jan Dirk Wegner
2019 arXiv   pre-print
Sentinel-2 multi-spectral images collected over periods of several months were used to estimate vegetation height for Gabon, respectively Switzerland.  ...  The resulting maps have a mean absolute error (MAE) of 1.7m in Switzerland, respectively 4.3m in Gabon, and correctly reproduce vegetation heights up to >50m.  ...  For instance, Baccini et al. (2008) map biomass in tropical Africa by tree-based regression from MODIS, using in-situ observations from forest inventories and logging as ground truth.  ... 
arXiv:1904.13270v1 fatcat:ij5i7wevnzh5lnp6kcxf2q2jw4

Influence of UAS Flight Altitude and Speed on Aboveground Biomass Prediction

Neal C. Swayze, Wade T. Tinkham, Matthew B. Creasy, Jody C. Vogeler, Chad M. Hoffman, Andrew T. Hudak
2022 Remote Sensing  
The management of low-density savannah and woodland forests for carbon storage presents a mechanism to offset the expense of ecologically informed forest management strategies.  ...  The reduced cost of UAS data collection and processing and improved biomass modeling accuracy over airborne LiDAR approaches could make carbon monitoring viable in low productivity forest systems.  ...  Acknowledgments: The authors would like to thank Mike Battaglia, Wayne Shepperd, and Lance Asherin for establishing and maintaining the stem-mapped study sites.  ... 
doi:10.3390/rs14091989 fatcat:zqbsnugv3ndcrlfbev6wpj2h7y

Enhanced carbon storage through management for old-growth characteristics in northern hardwood-conifer forests

Sarah E. Ford, William S. Keeton
2017 Ecosphere  
Species group-specific allometric equations were used to estimate live and standing dead biomass, and downed log biomass was estimated volumetrically.  ...  We used the Forest Vegetation Simulator to project "no-treatment" baselines specific to treatment units, allowing measured carbon responses to be normalized against differences in site characteristics  ...  ACKNOWLEDGMENTS This research was supported by grants from the USDA McIntire-Stennis Forest Research Program, the Northeastern States Research Cooperative, the Vermont Monitoring Cooperative, and the USDA  ... 
doi:10.1002/ecs2.1721 fatcat:gp36qhchvjbqzekodkyacndwai

Optical data-driven multi-source forest inventory setups for boreal and tropical forests

Eero Muinonen
2018 Dissertationes Forestales  
ACKNOWLEDGEMENTS The research material of the first study was collected during a research project funded by the Finnish Ministry of Agriculture and Forestry.  ...  The first study was conducted in the University of Joensuu, Faculty of Forestry (involved in the University of Eastern Finland since 2010).  ...  The stand area ranged from 0.30 ha to 11.11 ha with a mean area of 1.87 ha, and the stand age ranged between 18-107 years, with a mean age of 63 years (study I).  ... 
doi:10.14214/df.256 fatcat:allu4hth2vcytke7i54zbda6tu

General Poster Sessions

2014 International forestry review  
The results showed that the species diversity of understory vegetation was higher in thinned than in unmanaged forests. Lichen biomass increased three-fold in thinned forests.  ...  This study explores the infl uence of forest management practices including thinning, nitrogen fertilization, and unmanaged control on the multi-use potential of pine (Pinus sylvestris) dominated forests  ...  The carbon footprint of forestry in east Norway: a life cycle analysis. Lange, H., Timmermann, V., Dibdiakova, J., Gobakken, L.  ... 
doi:10.1505/146554814814281701 fatcat:tkm4o67rtvbjban3fbhbcayvqa

The role of remote sensing in process-scaling studies of managed forest ecosystems

Jeffrey G. Masek, Daniel J. Hayes, M. Joseph Hughes, Sean P. Healey, David P. Turner
2015 Forest Ecology and Management  
For example, in 83 their book-keeping approach to estimate the forest-sector greenhouse gas budget of 84 Mexico, de Jong et al. (2010) developed a nation-wide initial biomass estimate by 85 extrapolating  ...  In the greenhouse gas accounting example cited above, de Jong et al. (2010) 105 calculated the change in Mexico forest-sector carbon stocks by updating their initial area-106 based biomass estimate with  ...  The site consists of a mosaic of planted loblolly pine with known stand age (a-c), as well as patches of older, unmanaged forest (d).  ... 
doi:10.1016/j.foreco.2015.05.032 fatcat:46scvkdhtvcjnoosfd6ol5gjmy
« Previous Showing results 1 — 15 out of 488 results