Article
Ecology
Marc Fuhr, Etienne Lalechere, Jean-Matthieu Monnet, Laurent Berges
Summary: Building a network of interconnected overmature forests is crucial for biodiversity conservation. LiDAR technology can accurately assess forest structural parameters and identify overmature forest patches over large areas. In this study, an index combining forest structural maturity attributes was developed to characterize the maturity of field plots. LiDAR metrics, along with elevation, slope, and echo intensity distribution, were important for predicting forest maturity. The model showed a high correlation between observed and predicted maturity values, indicating accurate ranking of field plots.
REMOTE SENSING IN ECOLOGY AND CONSERVATION
(2022)
Article
Geosciences, Multidisciplinary
James J. Guilinger, Efi Foufoula-Georgiou, Andrew B. Gray, James T. Randerson, Padhraic Smyth, Nicolas C. Barth, Michael L. Goulden
Summary: Predicting sediment yield from recently burned areas is important for hazard and resource management, and we studied this by using lidar-based monitoring of two fires in southern California. We found that terrain, vegetation, burn severity, and rainfall amounts were relatively important factors influencing sediment yield during pre-rainfall periods and postfire periods of flooding and debris flows. Our observations helped us develop models to predict sediment yield in small steep headwater catchments in southern California.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Geosciences, Multidisciplinary
James J. Guilinger, Efi Foufoula-Georgiou, Andrew B. Gray, James T. Randerson, Padhraic Smyth, Nicolas C. Barth, Michael L. Goulden
Summary: This study examines the movement of sediment during pre-rainfall periods and postfire periods of flooding and debris flows in two fires in southern California, USA using lidar-based monitoring. The relative importance of terrain, vegetation, burn severity, and rainfall amounts on sediment yield is analyzed. Random forest regression models are developed to predict dry ravel and incipient runoff-driven sediment yield applicable to small steep headwater catchments in southern California.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Grigorijs Goldbergs
Summary: This study compared the performance of large-format airborne and satellite imagery, as well as airborne laser scanning (ALS) data, in estimating growing stock in Latvian hemiboreal forests. The results showed that ALS and image-based height metrics had comparable effectiveness in predicting growing stock in dense closed-canopy forests. The research suggests that regularly collected airborne imagery and image-based CHMs can be an efficient solution for forest growing stock calculations and updates. VHRSI can also be a fast and affordable solution for monitoring forest growing stock changes in vast and dense forestland.
Article
Environmental Sciences
Manuela Hirschmugl, Florian Lippl, Carina Sobe
Summary: This study examines the options for assessing vertical forest structure in a mountainous near-natural forest in the Austrian Alps using airborne and spaceborne LiDAR data. The indicators of foliage height diversity (FHD) and number of layers (NoL) are investigated. Expert-based assessment (EBA) outperforms break-detection algorithm (BDA) in terms of overall accuracy (OA) for estimating NoL. ALS data shows better OA for NoL than GEDI data. The usability of waveform-based structure parameters shows promise and should be further tested on larger areas.
Article
Environmental Sciences
James E. Lamping, Harold S. J. Zald, Buddhika D. Madurapperuma, Jim Graham
Summary: This study evaluated the ability of low-cost UAS DAP and HPGPS to accurately predict key forest attributes in various forest conditions in California, USA. The results showed that UAS DAP models were comparable to lidar models, and when combined with low-cost HPGPS, could accurately predict key forest attributes across a range of forest types.
Article
Environmental Sciences
K. C. Cushman, Sassan Saatchi, Ronald E. McRoberts, Kristina J. Anderson-Teixeira, Norman A. Bourg, Bruce Chapman, Sean M. McMahon, Christopher Mulverhill
Summary: Emerging satellite radar and lidar platforms can provide valuable information on aboveground biomass (AGB), but there is a need to estimate and propagate uncertainties in AGB maps due to the spatial resolution limitations. This study presents a workflow to estimate AGB uncertainty using lidar-based models and small field plots, and recommends measuring larger field plots for better calibration or validation of satellite-based map products.
Article
Biodiversity Conservation
Tristan R. H. Goodbody, Nicholas C. Coops, Cornelius Senf, Rupert Seidl
Summary: Effective forest stewardship relies on comprehensive field-inventories. This study explores the benefits of incorporating airborne laser scanning (ALS) data as an auxiliary dataset in forest inventory campaigns. The research evaluates sampling approaches and methods to allocate new field plots, demonstrating the value of ALS in improving data availability and sampling efficiency.
ECOLOGICAL INDICATORS
(2023)
Article
Environmental Sciences
Carli J. Morgan, Matthew Powers, Bogdan M. Strimbu
Summary: Traditional inventories can be resource-intensive and require a trained workforce, but the use of handheld LiDAR and SfM algorithms show potential for efficient tree detection and measurement of dimensions and characteristics, such as defects and damages.
Article
Environmental Sciences
Kleydson Diego Rocha, Carlos Alberto Silva, Diogo N. Cosenza, Midhun Mohan, Carine Klauberg, Monique Bohora Schlickmann, Jinyi Xia, Rodrigo Leite, Danilo Roberti Alves de Almeida, Jeff W. Atkins, Adrian Cardil, Eric Rowell, Russ Parsons, Nuria Sanchez-Lopez, Susan J. Prichard, Andrew T. Hudak
Summary: This study compared crown metrics derived from terrestrial and airborne laser scanners, as well as a combination of both, for describing the crown structure and fuel attributes of longleaf pine forest in Florida, USA. The results showed that both terrestrial and airborne laser scanner data accurately predicted tree attributes with good correlation and low errors.
Article
Chemistry, Analytical
Carlotta Ferrara, Nicola Puletti, Matteo Guasti, Roberto Scotti
Summary: This study used terrestrial and airborne laser scanning data to characterize the understory in a European beech and black pine forest in Italy. The results showed that upper understory density is associated with two specific airborne laser scanning metrics, while lower understory metrics are more related to one metric. Additionally, the study demonstrated the power of hand-held mobile TLS as a tool for measuring forest structural attributes and obtaining relevant ecological data.
Article
Ecology
Aaron G. Kamoske, Kyla M. Dahlin, Shawn P. Serbin, Scott C. Stark
Summary: Plant functional diversity is closely linked to photosynthetic carbon assimilation, but traits regulating photosynthetic capacity exhibit significant spatial heterogeneity. Combining hyperspectral imagery and lidar data can help understand the influence of forest structure on the spatial patterns of plant functional traits.
ECOLOGICAL APPLICATIONS
(2021)
Article
Geosciences, Multidisciplinary
Jakob J. Assmann, Jesper E. Moeslund, Urs A. Treier, Signe Normand
Summary: Biodiversity studies can benefit greatly from three-dimensional data on ecosystem structure obtained from remote sensing technologies such as lidar. This study utilized Denmark's publicly available airborne laser scanning data set to compute 70 descriptors of ecological interest, producing a high-resolution data set that provides information on vegetation height, structure, density, and topography for biodiversity research in Denmark.
EARTH SYSTEM SCIENCE DATA
(2022)
Article
Environmental Sciences
Megan Winsen, Grant Hamilton
Summary: LiDAR has been the preferred tool for 3D dense point cloud reconstructions of forest canopy, but structure from motion (SfM) photogrammetry based on aerial imagery has emerged as a powerful and low-cost alternative. However, comparing and assessing the accuracy of different reconstructions remains a challenge. This study compared LiDAR and SfM-NIR reconstructions of a native eucalypt forest and found that neither method accurately reproduced canopy cover or predicted tree heights. The LiDAR product showed better representation of the eucalypt canopy compared to SfM-NIR, which was affected by a lack of data and sub-optimal feature matching. Future studies could explore combining NIR imagery captured at different solar elevations and optimize image feature matching.
Article
Multidisciplinary Sciences
Ernandes M. Da Cunha Netod, Hudson F. P. Veras, Marks M. Moura, Andre L. Berti, Carlos R. Sanquetta, Allan L. Pelissari, Paula D. Corte
Summary: This study evaluated the hypothesis that the combination of an Airborne Laser Scanner (ALS) and an Unmanned Aerial Vehicle (UAV) can provide accurate quantitative information on tree height, volume, and aboveground biomass of the Araucaria angustifolia species in Atlantic Rain Forests. The results showed that ALS and UAV+ALS provided more accurate height, volume, and aboveground biomass predictions, while UAV produced biased estimates.
ANAIS DA ACADEMIA BRASILEIRA DE CIENCIAS
(2023)
Article
Forestry
M. Lisa Floyd, William H. Romme, Monique E. Rocca, Dustin P. Hanna, David D. Hanna
FOREST ECOLOGY AND MANAGEMENT
(2015)
Article
Plant Sciences
Katherine M. Renwick, Monique E. Rocca, Thomas J. Stohlgren
JOURNAL OF VEGETATION SCIENCE
(2016)
Article
Forestry
Paula J. Fornwalt, Monique E. Rocca, Mike A. Battaglia, Charles C. Rhoades, Michael G. Ryan
FOREST ECOLOGY AND MANAGEMENT
(2017)
Article
Geosciences, Multidisciplinary
Qichao Yao, Peter M. Brown, Shirong Liu, Monique E. Rocca, Valerie Trouet, Ben Zheng, Haonan Chen, Yinchao Li, Duanyang Liu, Xiaochun Wang
GEOPHYSICAL RESEARCH LETTERS
(2017)
Article
Ecology
Micah Wright, Monique Rocca
Article
Forestry
Monique E. Rocca, Peter M. Brown, Lee H. MacDonald, Christian M. Carrico
FOREST ECOLOGY AND MANAGEMENT
(2014)
Review
Ecology
Katherine M. Renwick, Monique E. Rocca
GLOBAL ECOLOGY AND BIOGEOGRAPHY
(2015)
Article
Ecology
Kellen N. Nelson, Monique E. Rocca, Matthew Diskin, Carissa F. Aoki, William H. Romme
Article
Ecology
Emily Kachergis, Monique E. Rocca, Maria E. Fernandez-Gimenez
RANGELAND ECOLOGY & MANAGEMENT
(2014)
Article
Plant Sciences
Gregory S. Pappas, Daniel B. Tinker, Monique E. Rocca
Article
Ecology
Katherine M. Nigro, Monique E. Rocca, Mike A. Battaglia, Jonathan D. Coop, Miranda D. Redmond
Summary: The study found that aspen seedlings established upslope of their previous range within burns, but not in unburned areas, despite severe beetle-driven canopy mortality across all sites before the fire. The presence of nearby seed sources was less relevant to aspen seedling establishment than the light and mineral soil created by fire.
JOURNAL OF BIOGEOGRAPHY
(2022)
Article
Plant Sciences
Gregory S. Pappas, Daniel B. Tinker, Monique E. Rocca
Summary: This study provides a comprehensive assessment of the changes in understory species and communities following severe mountain pine beetle-induced lodgepole pine mortality. The results show that more species appeared than disappeared 5 years after the peak of the outbreak, with new species comprising both early- and late-successional species. There was an increase in the number of highly common species and a decrease in the number of exceedingly rare species. Some species were able to take advantage of the new stand conditions and expand throughout the study area through various dispersal methods. Although shifts in community composition were minimal, there was a slight convergence of plant community groups, indicating a trend towards community homogenization.
JOURNAL OF VEGETATION SCIENCE
(2022)
Article
Ecology
Jesse T. Wooten, Camille S. Stevens-Rumann, Zoe H. Schapira, Monique E. Rocca
Summary: This study investigated the forest recovery after a large wildfire in southern Colorado in 2018. The results showed that post-fire logging led to changes in stand structure, fuels, vegetation, and soil microsite conditions. Logging resulted in a decrease in standing dead wood and loss of canopy cover, negatively impacting early post-fire conifer regeneration.
Article
Plant Sciences
Kyle C. Rodman, Robert A. Andrus, Amanda R. Carlson, Trevor A. Carter, Teresa B. Chapman, Jonathan D. Coop, Paula J. Fornwalt, Nathan S. Gill, Brian J. Harvey, Ashley E. Hoffman, Katharine C. Kelsey, Dominik Kulakowski, Daniel C. Laughlin, Jenna E. Morris, Jose F. Negron, Katherine M. Nigro, Gregory S. Pappas, Miranda D. Redmond, Charles C. Rhoades, Monique E. Rocca, Zoe H. Schapira, Jason S. Sibold, Camille S. Stevens-Rumann, Thomas T. Veblen, Jianmin Wang, Xiaoyang Zhang, Sarah J. Hart
Summary: Recent outbreaks of native bark beetles have significantly impacted tree mortality in subalpine forests of the US Rocky Mountains. Although most areas are likely to recover to pre-outbreak tree densities, changes in species composition may persist due to regional variability.
JOURNAL OF ECOLOGY
(2022)
Article
Environmental Sciences
Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher
Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg
Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen
Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang
Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie
Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick
Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong
Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin
Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li
Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Stephen Stehman, John E. Wagner
Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi
Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.
REMOTE SENSING OF ENVIRONMENT
(2024)