Article
Multidisciplinary Sciences
Kevin Nota, Jonatan Klaminder, Pascal Milesi, Richard Bindler, Alessandro Nobile, Tamara van Steijn, Stefan Bertilsson, Brita Svensson, Shun K. Hirota, Ayumi Matsuo, Urban Gunnarsson, Heikki Seppa, Minna M. Valiranta, Barbara Wohlfarth, Yoshihisa Suyama, Laura Parducci
Summary: Based on evidence from ancient sedimentary DNA and modern population genomics, the authors provide support for the recolonization of Fennoscandia by Norway spruce shortly after the last glaciation, with migration from the east during the early Holocene.
NATURE COMMUNICATIONS
(2022)
Article
Remote Sensing
Janne Raty, Johannes Breidenbach, Marius Hauglin, Rasmus Astrup
Summary: This study predicted timber volume damaged by butt rot at the stand-level in Norway using harvester information, remotely sensed, and environmental data. Forest attributes characterizing the maturity of the forest were found to be important predictor variables for butt rot damages, with remotely sensed variables being more crucial than the environmental ones. The results show that knowledge about the butt rot status of spatially close stands is important for obtaining satisfactory error rates in mapping the damages.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Forestry
Fleur Longuetaud, Rudolf Schraml, Frederic Mothe, Tojo Ravoajanahary, Remi Decelle, Thiery Constant, Phuc Ngo, Isabelle Debled-Rennesson, Karl Entacher, Alexander Petutschnigg, Franka Bruechert, Andreas Uhl
Summary: The TreeTrace_spruce database contains images and measurements of 100 Norway spruce logs from Northeastern France. The database includes RGB images, hyperspectral and CT images of wood discs, as well as X-ray and LiDAR scans. Measurements of wood density, growth rings, and pith location were performed on the discs. This complementary database differs in acquisition protocols and conditions from another database called TreeTrace_Douglas. The TreeTrace_spruce dataset and associated metadata are available at XXXX.
ANNALS OF FOREST SCIENCE
(2023)
Article
Forestry
Mostarin Ara, Mattias Berglund, Nils Fahlvik, Ulf Johansson, Urban Nilsson
Summary: This study aimed to investigate the effect of pre-commercial thinning (PCT) and timing of PCT on the production and profitability of Norway spruce stands. The results showed that PCT has a positive effect on the long-term profitability of Norway spruce plantations, but the timing of PCT has little effect on profitability. Additionally, retaining a certain number of Norway spruce and birch trees can lead to profitable mixed forests with little or no economic loss compared to pure Norway spruce stands.
Article
Plant Sciences
Pushan Bag, Jenna Lihavainen, Nicolas Delhomme, Thomas Riquelme, Kathryn M. Robinson, Stefan Jansson
Summary: Boreal conifers like Norway spruce have the ability to survive harsh winter conditions and remain evergreen, with changes in the global transcriptome of the needles reflecting acclimation processes throughout the year.
Article
Environmental Sciences
Mahmoud Omer Mahmoud Awadallah, Christian Malmquist, Morten Stickler, Knut Alfredsen
Summary: This study evaluates the performance of three different bathymetric LiDAR sensors (CZMIL Supernova, Riegl VQ880-G, and Riegl VQ840-G) in mapping the bathymetry of the Laerdal River in Norway. The results show that all the LiDAR instruments provide high-quality representations of the river geometry and create a solid foundation for planning, modeling, or other work that requires detailed bathymetry.
Article
Forestry
Jan Holeksa, Magdalena Zywiec, Michal Bogdziewicz, Przemyslaw Kurek, Fiona Milne-Rostkowska, Lukasz Piechnik, Barbara Seget
Summary: The regeneration of coniferous tree species, specifically Norway spruce, is dependent on forest structures related to tree death such as canopy gaps and decaying wood. Sapling mortality rates differ significantly between different microsites, with the highest mortality on dead wood, intermediate on undisturbed soil, and lowest on mounds. Canopy openness and decay class of the wood were found to influence sapling mortality.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Plant Sciences
Alexander Vergara, Julia C. Haas, Tuuli Aro, Paulina Stachula, Nathaniel R. Street, Vaughan Hurry
Summary: The conifer-dominated boreal forest is expected to experience warmer winter air temperatures and reduced snow cover depth and duration due to climate change. Norway spruce exhibits unique mechanisms for cold tolerance, utilizing early response transcription factors and showing delayed response compared to Arabidopsis. Regulatory network analysis identified both conserved transcription factors and species-specific responses in Norway spruce cold stress adaptation.
PLANT CELL AND ENVIRONMENT
(2022)
Article
Environmental Sciences
Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung, Luke A. Brown, Jadunandan Dash
Summary: Remote sensing technology is an effective method for LAI estimation, especially for inaccessible areas like mangrove forests. This study explored the potential of Sentinel-2 imagery, airborne hyperspectral imagery, and LiDAR data for estimating the LAI of overstory and understory in a multi-layered mangrove stand. The results showed that the models for overstory estimation performed better than understory estimation. A red-edge VI derived from hyperspectral imagery delivered the highest accuracy for overstory estimation, while the combination of LiDAR metrics and Sentinel-2 VIs performed best for understory estimation. It was found that HSI was less affected by the understory, and LiDAR data provided separate information for upper and lower canopy, reducing noise and improving understory estimation.
Article
Materials Science, Paper & Wood
Michael Altgen, Lauri Rautkari
Summary: This study aimed to understand the role of hydroxyl accessibility in wood-water interaction during humidity-dependent changes in moisture content. The results showed that changes in hydroxyl accessibility were not the driving force for these changes, although a slow re-protonation rate at low relative humidity was observed.
Article
Plant Sciences
Tuija Aronen, Susanna Virta, Saila Varis
Summary: Studies have shown that stress factors during somatic embryogenesis initiation can lead to telomere shortening in Norway spruce. The length of telomeres in embryogenic tissues (ETs) and embryos remains stable up to one year of culture but shows genotypic variation. Successful cryopreservation treatment can preserve telomere length, while prolonged in vitro culture may lead to telomere shortening.
Article
Plant Sciences
Sonali Sachin Ranade, Maria Rosario Garcia-Gil
Summary: Transcriptomic and exome capture analysis in Norway spruce showed an adaptive cline for shade tolerance. Genes involved in the lignin pathway and immunity may contribute to local adaptation to light quality.
Article
Forestry
Pauls Zeltins, Ahto Kangur, Juris Katrevics, Aris Jansons
Summary: The clonal effects on diameter growth function parameters were examined in a 50-year-old clonal plantation of Norway spruce. The study found significant variance in all model parameters, with the highest variance in growth rate. The heritability of diameter at breast height reached 0.35 at the age of 40, with a decrease in genetic variation between the ages of 20 and 45.
Article
Environmental Sciences
Maxime Soma, Francois Pimont, Jean-Luc Dupuy
Summary: The need for fine scale description of vegetation structure is increasing as the importance of Leaf Area Density (LAD) as a critical parameter to understand ecosystem functioning is recognized. Terrestrial Laser Scanning (TLS) has shown great potential for retrieving foliage area at various scales, but measurements remain sensitive to factors like voxel size and heterogeneity in sampling. The study aimed at disentangling biases and errors in plot-scale measurements of LAD with TLS in a simulated vegetation scene, finding that no scenario was unbiased and that an intermediate voxel size of 0.5m was the best option for reasonable measurement errors.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
P. E. Karlsson, C. Akselsson, S. Hellsten, G. Pihl Karlsson
Summary: This study estimated the yearly, total (dry+wet) deposition of inorganic nitrogen to Norway spruce forests in Sweden for a twenty-year period using a novel method. The results showed that spruce forests in south Sweden receive more nitrogen deposition than previously estimated, and there is a clear time trend of decreased deposition of inorganic nitrogen in all parts of Sweden. The findings emphasize the importance of estimating total deposition in order to map levels and follow the development of nitrogen deposition in forests.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Forestry
Tomi Karjalainen, Lauri Mehtatalo, Petteri Packalen, Jukka Malinen, Erik Naesset, Terje Gobakken, Matti Maltamo
Summary: Forest management inventories assisted by airborne laser scanning can be calibrated with local measurements to improve the accuracy of stand level merchantable and sawlog volumes predictions.
Article
Forestry
Johannes Breidenbach, David Ellison, Hans Petersson, Kari T. Korhonen, Helena M. Henttonen, Jorgen Wallerman, Jonas Fridman, Terje Gobakken, Rasmus Astrup, Erik Naesset
Summary: Using satellite-based maps and National Forest Inventory observations, this study finds that the ability of the maps to detect harvested areas abruptly increased after 2015 in Finland and Sweden, rather than the actual harvested area.
ANNALS OF FOREST SCIENCE
(2022)
Article
Forestry
Ioan Dutca, Ronald E. McRoberts, Erik Naesset, Viorel N. B. Blujdea
Summary: Allometric models for predicting forest biomass often take nonlinear powerlaw forms and accommodating heteroscedasticity in the residual variance is necessary for accurate estimates. Weighting procedures and transformations were tested on biomass models, with some procedures showing more effectiveness in accommodating heteroscedasticity. Adding height as an additional predictor variable was recommended for better estimation accuracy.
FOREST ECOLOGY AND MANAGEMENT
(2022)
Article
Environmental Sciences
Stephen V. Stehman, John Mousoupetros, Ronald E. McRoberts, Erik Naesset, Bruce W. Pengra, Dingfan Xing, Josephine A. Horton
Summary: Area estimates of land cover and land cover change are often determined by analysts interpreting satellite imagery and aerial photography. However, there is variability in the reference class labels assigned by different interpreters to the same sample units, which is not usually considered in variance estimators. By using a simple measurement model and repeated measurements by independent analysts, it was found that interpreter variance can significantly contribute to the total variance, and the standard variance estimator may underestimate the total variance due to this variability. The repeated measurements approach offers a practical way to incorporate interpreter variability into the total variance estimator, highlighting the importance of accounting for interpreter variance in land cover area estimation.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Biodiversity Conservation
Hans Ole Orka, Marie-Claude Jutras-Perreault, Erik Naesset, Terje Gobakken
Summary: This study presents a framework for a remote sensing-based forest ecological base map in Norway, which provides spatial information about the extent, condition, and pressures of forest ecosystems. The framework combines optical satellite imagery with airborne laser scanning data to predict forest condition and map pressures on the ecosystems using change detection algorithms. The accuracy of the predicted forest extent and condition attributes is relatively high, and the maps are aggregated at a local level for ecosystem indicator development.
ECOLOGICAL INDICATORS
(2022)
Article
Environmental Sciences
Laura Duncanson, James R. Kellner, John Armston, Ralph Dubayah, David M. Minor, Steven Hancock, Sean P. Healey, Paul L. Patterson, Svetlana Saarela, Suzanne Marselis, Carlos E. Silva, Jamis Bruening, Scott J. Goetz, Hao Tang, Michelle Hofton, Bryan Blair, Scott Luthcke, Lola Fatoyinbo, Katharine Abernethy, Alfonso Alonso, Hans-Erik Andersen, Paul Aplin, Timothy R. Baker, Nicolas Barbier, Jean Francois Bastin, Peter Biber, Pascal Boeckx, Jan Bogaert, Luigi Boschetti, Peter Brehm Boucher, Doreen S. Boyd, David F. R. P. Burslem, Sofia Calvo-Rodriguez, Jerome Chave, Robin L. Chazdon, David B. Clark, Deborah A. Clark, Warren B. Cohen, David A. Coomes, Piermaria Corona, K. C. Cushman, Mark E. J. Cutler, James W. Dalling, Michele Dalponte, Jonathan Dash, Sergio de-Miguel, Songqiu Deng, Peter Woods Ellis, Barend Erasmus, Patrick A. Fekety, Alfredo Fernandez-Landa, Antonio Ferraz, Rico Fischer, Adrian G. Fisher, Antonio Garcia-Abril, Terje Gobakken, Jorg M. Hacker, Marco Heurich, Ross A. Hill, Chris Hopkinson, Huabing Huang, Stephen P. Hubbell, Andrew T. Hudak, Andreas Huth, Benedikt Imbach, Kathryn J. Jeffery, Masato Katoh, Elizabeth Kearsley, David Kenfack, Natascha Kljun, Nikolai Knapp, Kamil Kral, Martin Krucek, Nicolas Labriere, Simon L. Lewis, Marcos Longo, Richard M. Lucas, Russell Main, Jose A. Manzanera, Rodolfo Vasquez Martinez, Renaud Mathieu, Herve Memiaghe, Victoria Meyer, Abel Monteagudo Mendoza, Alessandra Monerris, Paul Montesano, Felix Morsdorf, Erik Naesset, Laven Naidoo, Reuben Nilus, Michael O'Brien, David A. Orwig, Konstantinos Papathanassiou, Geoffrey Parker, Christopher Philipson, Oliver L. Phillips, Jan Pisek, John R. Poulsen, Hans Pretzsch, Christoph Rudiger, Sassan Saatchi, Arturo Sanchez-Azofeifa, Nuria Sanchez-Lopez, Robert Scholes, Carlos A. Silva, Marc Simard, Andrew Skidmore, Krzysztof Sterenczak, Mihai Tanase, Chiara Torresan, Ruben Valbuena, Hans Verbeeck, Tomas Vrska, Konrad Wessels, Joanne C. White, Lee J. T. White, Eliakimu Zahabu, Carlo Zgraggen
Summary: This paper presents the development of models used by NASA's Global Ecosystem Dynamics Investigation (GEDI) to estimate forest aboveground biomass density (AGBD). The models were developed using globally distributed field and airborne lidar data, with simulated relative height metrics as predictor variables. The study found that stratification by geographic domain and the use of square root transformation improved model performance.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Ecology
Jussi Juola, Aarne Hovi, Miina Rautiainen
Summary: The woody material of forest canopies affects the interpretation of remotely sensed data. This study developed a novel measurement setup and used a mobile hyperspectral camera to measure the stem bark reflectance spectra of ten tree species. The results showed that there was similarity in the visible region, but large interspecific variation in the near-infrared region.
ECOLOGY AND EVOLUTION
(2022)
Article
Agronomy
Petri R. Forsstrom, Aarne Hovi, Jussi Juola, Miina Rautiainen
Summary: The study investigates the relationship between light availability at forest floor and its spectral reflectance properties and fractional cover across boreal and temperate Europe. The results show that tree canopy structure is linked to the vegetation composition and spectral reflectance properties of forest floor, and these relationships differ between forest biomes.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Forestry
Ana de Lera Garrido, Terje Gobakken, Marius Hauglin, Erik Naesset, Ole Martin Bollandsas
Summary: The aim of this study was to analyze the accuracy of forest attribute predictions from the nationwide forest attribute map (SR16). Field observations from 33 forest inventory projects in Norway were used for validation. The overall results showed satisfactory accuracy, but there were large differences in accuracy among different inventory projects, with forest structure being the most influential factor.
SCANDINAVIAN JOURNAL OF FOREST RESEARCH
(2023)
Article
Forestry
Marie-Claude Jutras-Perreault, Erik Naesset, Terje Gobakken, Hans Ole Orka
Summary: This study utilized ALS data and vegetation indices from optical images to predict the presence of standing dead trees in a managed forest in Southern Norway. Area-based regression models were initially tested but proved to be statistically insignificant due to limited ground reference information. A tree-based approach, however, successfully identified standing dead trees based on ALS point cloud data and vegetation indices.
SCANDINAVIAN JOURNAL OF FOREST RESEARCH
(2023)
Article
Ecology
Sini-Selina Salko, Jussi Juola, Iuliia Burdun, Harri Vasander, Miina Rautiainen
Summary: The study highlights the importance of using spectral data in the shortwave infrared region (1100-2500 nm) for remote sensing applications, especially in monitoring the changes in wetland conditions.
ECOLOGY AND EVOLUTION
(2023)
Article
Environmental Sciences
Marie-Claude Jutras-Perreault, Terje Gobakken, Erik Naesset, Hans Ole orka
Summary: This study proposes a tree-based approach that combines remote sensing data to predict the presence of standing dead trees (SDT) in forests. By comparing different remotely sensed data sources, it was found that NDVI calculated from aerial images accurately predicts the presence of SDT, while NDVI calculated from satellite images is less accurate.
Article
Agronomy
Daniel Schraik, Di Wang, Aarne Hovi, Miina Rautiainen
Summary: In this study, a method was developed to measure the clumping index (CI) of forest stands using terrestrial lidar data. Measurements of CI and STARf were conducted on 38 forest stands in Finland, Estonia, and Czechia to study their natural range and relationships with other forest variables and Landsat 8 OLI surface reflectance. It was found that CI was closely correlated with surface reflectance in conifer forests.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Environmental Sciences
Sofia Junttila, Jonas Ardo, Zhanzhang Cai, Hongxiao Jin, Natascha Kljun, Leif Klemedtsson, Alisa Krasnova, Holger Lange, Anders Lindroth, Meelis Molder, Steffen M. Noe, Torbern Tagesson, Patrik Vestin, Per Weslien, Lars Eklundh
Summary: Monitoring local-scale gross primary production (GPP) of northern forest is crucial for understanding climatic change impacts on carbon sequestration and assessing management practices. This study evaluates and compares four methods for estimating GPP using Sentinel-2 data, finding that most models perform well with good agreement with eddy covariance-derived GPP. Regression models based on vegetation indices show good performance in evergreen needleleaf forest, while the LRF and MOD17 models perform slightly worse. In deciduous broadleaf forest, all models except the LRF show close agreement with observed GPP.
SCIENCE OF REMOTE SENSING
(2023)
Article
Forestry
Lennart Noordermeer, Erik Naesset, Terje Gobakken
Summary: Newly developed positioning systems in cut-to-length harvesters enable georeferencing of individual trees with submeter accuracy, which has emerged as a valuable tool for forest inventory. The study found that larger grid cells result in more accurate timber volume predictions and are less affected by positioning errors.
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)
