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
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
Forestry
Joshua Carpenter, Daniel Rentauskas, Nikhil Makkar, Jinha Jung, Songlin Fei
Summary: Field-based forest inventory plots are crucial for forest studies, providing valuable information about forests. They are now used for validation and training data in forest feature extraction and machine learning algorithms. However, the uncertainty in plot location measurements has undermined their usefulness. A method for accurately measuring plot center coordinates using low-cost targets and orthoimagery has improved the accuracy by an order of magnitude.
JOURNAL OF FORESTRY
(2023)
Article
Environmental Sciences
Todd A. Schroeder, Shingo Obata, Monica Papes, Benjamin Branoff
Summary: The Forest Inventory and Analysis (FIA) program of the U.S. Forest Service aims to estimate various forest attributes using a design-based network of sampling plots. This study explores the use of digital aerial photogrammetric (DAP) point clouds developed from stereo imagery to improve these estimates in southeastern mixed hardwood forests. The results show that using the DAP point clouds improved the precision of forest volume estimates compared to using tree canopy cover data.
Article
Environmental Sciences
Xiaoyao Fu, Zhengnan Zhang, Lin Cao, Nicholas C. Coops, Tristan R. H. Goodbody, Hao Liu, Xin Shen, Xiangqian Wu
Summary: Assessing changes in forest structure over time is crucial for monitoring forest resources, supporting sustainable forest management practices, and providing key insights into changes in the terrestrial carbon cycle. Recent research interest in unmanned aerial vehicle (UAV)-based digital aerial photogrammetry (DAP) technology has led to high-spatial resolution data that enhances forest inventories and monitoring forest dynamics. Direct methods showed improved accuracy in estimating structural parameter changes compared to indirect methods, with metrics like height percentiles and canopy return density being sensitive to changes in structural parameters.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Tristan R. H. Goodbody, Joanne C. White, Nicholas C. Coops, Antoine LeBoeuf
Summary: Research has shown the utility of digital aerial photogrammetry (DAP) for predicting forest inventory attributes, but the impacts of acquisition parameters like image resolution and across-track overlap need further empirical investigation. Understanding how these parameters affect DAP data is crucial for improving forest inventory programs.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Forestry
Facundo Pessacg, Francisco Gomez-Fernandez, Matias Nitsche, Nicolas Chamo, Sebastian Torrella, Ruben Ginzburg, Pablo De Cristoforis
Summary: Forestry aerial photogrammetry using Unmanned Aerial Systems (UAS) helps bridge the gap between detailed fieldwork and broad-range satellite imagery-based analysis. However, optical sensors face limitations in collecting and classifying ground points in woodlands. This study proposes a novel method to generate accurate Digital Terrain Models (DTMs) in forested environments and develops a realistic simulator for controlled experimentation.
Article
Environmental Sciences
Mei Li, Zengyuan Li, Qingwang Liu, Erxue Chen
Summary: By using ULS and USP data, four kinds of stand heights in plantation forests were estimated using different models. The prediction accuracy of stand heights using USP was comparable to ULS, with Lorey's height having the highest accuracy. The correlation between metrics from ULS and USP increased with height, and canopy height model-based metrics performed slightly better than normalized point cloud-based metrics.
Article
Chemistry, Multidisciplinary
Chenyun Li, Yanfeng Zheng, Xinjie Zhang, Fayun Wu, Linyuan Li, Jingyi Jiang
Summary: This study compared the ability of digital aerial photogrammetry (DAP) and airborne laser scanning (ALS) in predicting canopy structural variables in tropical forests. The results showed that DAP-based methods tended to overestimate canopy cover and leaf area index (LAI) compared to ALS-based methods. ALS-based estimates were also found to be more consistent with satellite retrievals than DAP-based estimates.
APPLIED SCIENCES-BASEL
(2022)
Article
Remote Sensing
Konrad Turlej, Mutlu Ozdogan, Volker C. Radeloff
Summary: This study successfully mapped forest composition under different data availability conditions using a data driven approach with Landsat imagery. The results showed that high accuracy forest type mapping can be achieved even with missing data, and the number of acquisitions and seasonal image availability had an impact on classification accuracy.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Remote Sensing
Cedric Vega, Jean-Pierre Renaud, Ankit Sagar, Olivier Bouriaud
Summary: Integrating NFI data with auxiliary information enables downscaling and improving precision of estimates for small domains. A downsaling algorithm was tested in a hardwood forest area in France, resulting in improved estimation accuracy.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Engineering, Multidisciplinary
Ismail Elkhrachy
Summary: This study aimed to produce accurate geospatial 3D data from UAV images. The solution generated met the 2015 ASPRS accuracy standards, with horizontal RMSE values of 4-6 cm and vertical accuracy of 5-6 cm, which were twice and three times the Ground Sample Distance (GSD), respectively.
ALEXANDRIA ENGINEERING JOURNAL
(2021)
Article
Remote Sensing
Yahya Zefri, Imane Sebari, Hicham Hajji, Ghassane Aniba
Summary: The increasing adoption of photovoltaic technology necessitates efficient and large-scale deployment-ready inspection solutions. In this study, a robust and versatile deep learning model is developed for the classification of defect-related patterns on PV modules.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Environmental Studies
Enrico Borgogno-Mondino, Samuele De Petris, Filippo Sarvia, Evelyn Joan Momo, Fabio Sussio, Paolo Pari
Summary: This paper summarizes the role of digital aerial photogrammetry (DAP) in forest planning and analyzes the main products required. Strategies are proposed to ensure measurement accuracy based on technical features. A practical case study demonstrates the cost-saving capability of DAP in forest planning.
Article
Optics
Xinxing Shao, Kang Wei, Xiaoyuan He
Summary: Calibration of a stereo-DIC system is essential for 3D shape and deformation measurement. A stereo-vision calibration method is proposed based on close-range photogrammetry, which can obtain accurate calibration parameters and has good deformation measurement accuracy. The method does not require high-quality or large-sized calibration objects, making it suitable for on-site calibration.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Remote Sensing
Martin Queinnec, Nicholas C. Coops, Joanne C. White, Verena C. Griess, Naomi B. Schwartz, Grant McCartney
Summary: In this study, dominant species groups in a large boreal forest were mapped by combining area-based and individual tree metrics derived from LiDAR data with multispectral information from Sentinel-2 imagery. The study found that variables such as reflectance in the red edge region, tree crown area and volume, and cumulative distribution of LiDAR returns in the canopy were important for discriminating between species groups.
CANADIAN JOURNAL OF REMOTE SENSING
(2023)
Article
Remote Sensing
Levi Keay, Christopher Mulverhill, Nicholas C. C. Coops, Grant McCartney
Summary: The advent of CubeSat constellations has revolutionized the ability to observe Earth systems through time. This study developed and implemented a method for the spatial and temporal detection of forest harvest operations using images from the PlanetScope constellation. Results indicate that forest harvesting can be detected with relative accuracy, providing previously unavailable levels of spatial and temporal detail for forest stakeholders.
CANADIAN JOURNAL OF REMOTE SENSING
(2023)
Article
Biodiversity Conservation
Morgan A. Crowley, Christopher A. Stockdale, Joshua M. Johnston, Michael A. Wulder, Tianjia Liu, Jessica L. McCarty, Jesse T. Rieb, Jeffrey A. Cardille, Joanne C. White
Summary: Fire seasons have become more extreme and unpredictable due to changing climatic, ecological, and social conditions. Earth observation data is crucial for effective fire monitoring. This study presents a comprehensive framework for identifying and addressing fire monitoring objectives and data requirements throughout the entire fire cycle. Four stages of fire monitoring, including pre-fire vegetation inventories, active-fire monitoring, post-fire assessment, and multi-scale synthesis, are explored. The challenges and opportunities associated with current fire monitoring approaches are discussed, with case studies from North American ecosystems offering insights for global monitoring efforts. The rapid growth of remote sensing technology provides valuable data for fire monitoring, but significant challenges remain in meeting monitoring objectives. Future opportunities lie in data sharing and collaborative development using cloud computing and open-access Earth observation and geospatial data layers.
GLOBAL CHANGE BIOLOGY
(2023)
Article
Remote Sensing
Alexandre Morin-Bernard, Alexis Achim, Nicholas C. Coops
Summary: Non-stand-replacing disturbances play a significant role in northern hardwood forest dynamics, but are more difficult to characterize using satellite imagery than stand-replacing events. This study proposes a hurdle approach that attributes disturbance causal agents to specific sample plots, achieving an overall accuracy of 82.9%. Disturbance-specific models were then developed to assess the severity of partial harvests and damage from ice storms, with r-squared values of 0.57 and 0.59, respectively. These models provide important information for future silvicultural planning by capturing within-stand variability in disturbance severity.
CANADIAN JOURNAL OF REMOTE SENSING
(2023)
Review
Fisheries
Spencer Dakin Kuiper, Nicholas C. C. Coops, Scott G. G. Hinch, Joanne C. C. White
Summary: Remote sensing technology has the potential to revolutionize freshwater fish habitat monitoring by providing information across large geographic areas, but the overwhelming number of platforms, sensors, and software available may hinder its widespread use. This review examines the fundamental characteristics of remote sensing technologies used for freshwater habitat characterization, reviews studies that have utilized these technologies, and identifies key habitat features, fish species, and regions that have been examined. The review also highlights the strengths and weaknesses of different remote sensing technologies, suggests future research directions, and provides important considerations for those interested in utilizing these technologies for freshwater fish habitat characterization.
FISH AND FISHERIES
(2023)
Article
Forestry
Joanne C. White, Txomin Hermosilla, Michael A. Wulder
Summary: Wildfire is a significant factor in driving forest dynamics in boreal forests, with increasing wildfire activity observed in the past 50 years. Post-fire recovery plays a vital role in carbon balance and the provision of ecosystem goods and services in boreal forests. Monitoring recovery is challenging due to the large and inaccessible impacted areas, as well as the variability in post-fire conditions. Remote sensing data can provide assessments of pre- and post-fire conditions and spectral recovery baselines, but the connection between spectral measures and on-ground forest recovery needs to be established.
FOREST ECOLOGY AND MANAGEMENT
(2023)
Article
Forestry
Tristan R. H. Goodbody, Nicholas C. Coops, Martin Queinnec, Joanne C. White, Piotr Tompalski, Andrew T. Hudak, David Auty, Ruben Valbuena, Antoine LeBoeuf, Ian Sinclair, Grant McCartney, Jean-Francois Prieur, Murray E. Woods
Summary: Establishing field inventories can be challenging and expensive. The use of airborne laser scanning (ALS) data as a forest inventory tool is improving understanding of vegetation structure across forested landscapes. The sgsR package provides a toolbox for implementing structurally guided sampling (SGS) and optimizing allocation of sample units and sample size.
Article
Forestry
A. R. Wotherspoon, A. Achim, N. C. Coops
Summary: This study examines the future climate trends in eight ecozones in Canada that contain managed forests. The projections suggest a warming trend and an overall increase in precipitation. The study highlights the potential impacts on dominant species and wood volume for Canada's forestry industry.
CANADIAN JOURNAL OF FOREST RESEARCH
(2023)
Article
Forestry
Jose Riofrio, Joanne C. White, Piotr Tompalski, Nicholas C. Coops, Michael A. Wulder
Summary: By developing age-independent height growth models, using multi-temporal airborne laser scanning (ALS) data, a comprehensive indicator of site quality for complex and irregular stand structures is provided. This approach leverages the accurate, spatially detailed characterization of canopy heights afforded by ALS data and is independent of stand age, increasing the possible geographic extent of height growth estimates.
FOREST ECOLOGY AND MANAGEMENT
(2023)
Article
Forestry
Margaret Penner, Joanne C. White, Murray E. Woods
Summary: Forest canopy vertical layering is important for forest management planning, wood supply analysis, and other applications such as habitat modeling and forest resilience assessment. Utilizing airborne LiDAR data, this study automated the mapping of vertical stand layering in a mixedwood forest, allowing for more accurate partitioning of inventory attributes by canopy layer.
Article
Geography, Physical
Saverio Francini, Txomin Hermosilla, Nicholas C. Coops, Michael A. Wulder, Joanne C. White, Gherardo Chirici
Summary: Remote sensing is a major source of information for monitoring forest dynamics, but accurate surface reflectance data is often difficult to obtain. Pixel-based composites are used to generate complete coverage of the area of interest from multi-temporal images, but a comprehensive methodology for assessing the quality of these composites is currently lacking. In this study, a pixel-based composite assessment methodology based on five criteria was introduced and tested on Landsat images over Europe. The results showed that the assessment approach was effective for evaluating the quality of pixel-based composites and could be applied in various applications.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Ecology
Margaret E. Andrew, Douglas K. Bolton, Gregory J. M. Rickbeil, Nicholas C. Coops
Summary: This study evaluates the effects of niche-based mechanisms, including environmental filtering, niche availability, and niche packing, on biodiversity patterns. The results show that the importance of these mechanisms varies with scale, position on environmental gradients, and taxonomic group.
JOURNAL OF BIOGEOGRAPHY
(2023)