Article
Environmental Sciences
Hamed Gholizadeh, Michael S. Friedman, Nicholas A. McMillan, William M. Hammond, Kianoosh Hassani, Aisha Sams, Makyla D. Charles, DeAndre R. Garrett, Omkar Joshi, Robert G. Hamilton, Samuel D. Fuhlendorf, Amy M. Trowbridge, Henry D. Adams
Summary: In this study, airborne imaging spectroscopy was used to map sericea in the Tallgrass Prairie Preserve. The research investigated the remotely observable vegetation functional traits that contribute to distinguishing sericea from native species and developed a classification model to detect sericea. The results showed that certain functional traits, such as total carotenoids, chlorophyll a + b, and total nitrogen, were key factors in detecting sericea, with an overall accuracy of approximately 94%. This research demonstrates the importance of airborne remote sensing in mapping invasive plants and quantifying their functional traits.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Multidisciplinary Sciences
Sebastien Rapinel, Lea Panhelleux, Guillaume Gayet, Rachel Vanacker, Blandine Lemercier, Bertrand Laroche, Francois Chambaud, Anis Guelmami, Laurence Hubert-Moy
Summary: This study used remote sensing and field data, combined with artificial intelligence technology, to classify and map wetlands in mainland France. The results show that this approach can accurately reveal the spatial distribution and fuzzy boundaries of wetlands, providing important reference for spatial planning and environmental management.
Article
Geochemistry & Geophysics
[Anonymous]
Summary: This issue of the publication presents the institutional listings for GRSS.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Ecology
Xiaoquan Pan, Jinbao Jiang, Yiming Xiao
Summary: Natural gas is an important clean energy source, but its leakage during transportation can have negative impacts. This study used hyperspectral remote sensing technology to indirectly detect natural gas leakage by analyzing the spectral characteristics of vegetation. The experiment found specific spectral bands sensitive to gas stress, which can be used to identify stressed plants. The proposed index showed promising results in identifying gas-stressed plants.
ECOLOGICAL INFORMATICS
(2022)
Editorial Material
Environmental Sciences
Yongguang Zhang, Mirco Migliavacca, Josep Penuelas, Weimin Ju
Summary: This article introduces the recent advances in remote sensing of plant traits and functions, including the shift from monitoring structural parameters to functional traits and the use of hyperspectral techniques to monitor vegetation status across various scales. The eight papers mentioned in this editorial focus on developing new remote sensing techniques and algorithms for retrieving plant functional traits, which will help improve the estimation of vegetation processes such as photosynthesis, water cycle, and carbon cycle.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Biodiversity Conservation
Xiaoai Dai, Haipeng Feng, Lixiao Xiao, Jiayun Zhou, Zekun Wang, Junjun Zhang, Tianzhang Fu, Yunfeng Shan, Xianhua Yang, Yakang Ye, Li Xu, Xiaoli Jiang, Shibo Fang, Yuanzhi Yao
Summary: Mining activities in mining cities cause significant ecological stresses to the environment, threatening the health of vegetation and human. This study used hyperspectral remote sensing data to assess the ecological vulnerability of Panzhihua city, a representative mining city in China. The results showed that hyperspectral imaging performed better in precision and concentration, allowing more accurate monitoring of vegetation growth and restoration, and providing guidance for ecological conservation measures.
ECOLOGICAL INDICATORS
(2022)
Review
Environmental Sciences
Milos Rusnak, Tomas Goga, Lukas Michaleje, Monika Sulc Michalkova, Zdenek Macka, Laszlo Bertalan, Anna Kidova
Summary: Riparian zones are important ecosystems that are shaped by interactions between river systems and their surrounding environments. This paper provides an overview of studies that have used remote sensing techniques to understand riparian form, function, and change over time. The majority of studies used aerial and satellite imagery, with unmanned aerial vehicles (UAVs) being increasingly used for low-cost monitoring. However, the challenge remains in effectively transferring remote sensing data to managers and stakeholders for decision making and successful management of riparian zones.
Article
Environmental Sciences
A. M. Raiho, K. Cawse-Nicholson, A. Chlus, J. Dozier, M. Gierach, K. Miner, F. Schneider, D. Schimel, S. Serbin, A. N. Shiklomanov, D. R. Thompson, P. A. Townsend, S. Zareh, M. Skiles, B. Poulter
Summary: The retrieval algorithms used for optical remote sensing satellite data to estimate Earth's geophysical properties have specific requirements for spatial resolution, temporal revisit, spectral range and resolution, and instrument signal-to-noise ratio (SNR) performance. Different scientific fields may have varying sensitivity to mission architecture choices that affect spectral, spatial, or temporal resolutions and spectrometer SNR. The interplay between spatial resolution, temporal revisit, and SNR can be quantitatively assessed for imaging spectroscopy missions and used to identify key components of algorithm performance and mission observing criteria.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
(2023)
Article
Environmental Sciences
Narayan Kayet, Khanindra Pathak, C. P. Singh, V. M. Chowdary, Bimal K. Bhattacharya, Dheeraj Kumar, Subodh Kumar, Ibrahim Shaik
Summary: This paper focuses on assessing and mapping vegetation health conditions (VHC) using high resolution airborne hyperspectral imagery, with a specific focus on coal mining sites. The study develops and modifies vegetation indices (VIs) based models for VHC assessment and mapping, and compares the results to other classification methods. The findings indicate a significant relationship between VHC classes and distance from mines, providing important guidance for geoenvironmental impact assessment in coal mining sites.
ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
(2022)
Article
Environmental Sciences
Marcos Rafael Nanni, Jose Alexandre Melo Dematte, Marlon Rodrigues, Glaucio Leboso Alemparte Abrantes dos Santos, Amanda Silveira Reis, Karym Mayara de Oliveira, Everson Cezar, Renato Herrig Furlanetto, Luis Guilherme Teixeira Crusiol, Liang Sun
Summary: This study evaluated the use of airborne hyperspectral imaging and non-imaging sensors to assess particle size and soil organic matter in tropical soils. By applying Partial Least Square Regression (PLSR), predictive maps for clay, sand, and soil organic matter were successfully developed, demonstrating strong correlations between the predictor variables and actual measurements.
Article
Environmental Sciences
Zihaohan Sang, Andreas Hamann
Summary: Remote sensing-based vulnerability assessments to climate change are crucial for landscape-scale conservation and management. This study analyzes time series of enhanced vegetation index data and uses lagged monthly correlation analysis to assess vulnerability. The results reveal drought vulnerabilities across the continent, including a distinct band in the western boreal forest. The approach provides detailed climate dependencies and helps address the threat of climate change to species and ecosystems, guiding targeted management interventions.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Environmental Sciences
Xiaoping Wang, Jingming Shi, Chenfeng Wang, Chao Gao, Fei Zhang
Summary: This study uses remote sensing inversion and mapping techniques to estimate forest stand age, taking into account the remote sensing mechanism of vegetation indices and the physiological function and canopy structure of the forest. Multiple linear regression and random forest models are used for the estimation, and the accuracy of the models is evaluated. The results show that the reflectance of the canopy decreases with the increase of forest stand age, and the relationship between forest stand age and red edge is the most significant. The random forest model has a higher accuracy in estimating forest stand age.
Article
Environmental Sciences
Bing Lu, Yuhong He
Summary: Chlorophyll is a crucial vegetation pigment influencing plant photosynthesis rate. Remote sensing images are used for mapping vegetation chlorophyll content in diverse ecosystems. Species composition impacts prediction accuracy of chlorophyll estimation. Species-specific models outperform universal models in mapping chlorophyll content.
Article
Ecology
Darren Turner, Emiliano Cimoli, Arko Lucieer, Ryan S. Haynes, Krystal Randall, Melinda J. Waterman, Vanessa Lucieer, Sharon A. Robinson
Summary: This study develops a model to predict water content in Antarctic moss beds using laboratory experiments and spectroscopy analysis. The model is then applied to high-resolution images taken by unmanned aerial systems (UAS) to monitor water content in different conditions. The study demonstrates the potential of UAS-borne short-wave infrared (SWIR) imaging for mapping and quantifying water content in Antarctic moss beds.
REMOTE SENSING IN ECOLOGY AND CONSERVATION
(2023)
Article
Environmental Sciences
Li Chen, Xinxin Sui, Rongyuan Liu, Hong Chen, Yu Li, Xian Zhang, Haomin Chen
Summary: This study investigates the application of hyperspectral data in CBM enrichment areas and proposes a method for mineral extraction based on spectral feature matching and diagnostic characteristic parameters. The extraction results are verified through X-ray diffraction analysis, and it is found that both ZY-1 02D and Hyperion hyperspectral data yield favorable extraction results for clay and carbonate minerals, with the higher accuracy of ZY-1 02D data.
Article
Ecology
Jeannine Cavender-Bares, Anna K. Schweiger, John A. Gamon, Hamed Gholizadeh, Kimberly Helzer, Cathleen Lapadat, Michael D. Madritch, Philip A. Townsend, Zhihui Wang, Sarah E. Hobbie
Summary: The study shows that imaging spectroscopy can detect vegetation information and predict belowground plant and soil processes. There are contrasting relationships between aboveground vegetation quantity and quality with belowground soil attributes, indicating differences in influencing factors for belowground processes in different grassland systems.
ECOLOGICAL MONOGRAPHS
(2022)
Article
Environmental Sciences
Gerard Sapes, Cathleen Lapadat, Anna K. Schweiger, Jennifer Juzwik, Rebecca Montgomery, Hamed Gholizadeh, Philip A. Townsend, John A. Gamon
Summary: The study developed a PLS-DA model using airborne hyperspectral reflectance to detect oak wilt disease. The use of SWIR wavelengths and a phylogenetic approach improved the accuracy of the model. Multispectral indices associated with physiological decline were important for detecting oak wilt, particularly those related to canopy photosynthetic activity and water status.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Casey B. Engstrom, Scott N. Williamson, John A. Gamon, Lynne M. Quarmby
Summary: This study used field spectroradiometer measurements and direct counts of algal cell abundance to monitor and analyze snow algal blooms. The results showed that the blooms had a significant impact on albedo and glacial melt, with the largest bloom areas covering one third of the total surface area of the glaciers.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Ran Wang, John A. Gamon, Gabriel Hmimina, Sergio Cogliati, Arthur I. Zygielbaum, Timothy J. Arkebauer, Andrew Suyker
Summary: In this study, airborne and ground SIF data were combined to generate comparable SIF signals across instruments, methods, and platforms. Several SIF extraction methods were tested and the accuracy of ground level downwelling irradiance estimation was improved to enhance the agreement between airborne and ground SIF retrievals. This experimental approach is important for understanding the SIF-GPP relationship and cross-validating different platforms used for satellite products calibration and validation.
REMOTE SENSING OF ENVIRONMENT
(2022)
Review
Engineering, Environmental
Broghan M. Erland, Andrew K. Thorpe, John A. Gamon
Summary: This review focuses on recent advances in methane detection for reducing uncertainty in source attribution and evaluating progress in emissions reductions. Complementary methods in the oil and gas industry are discussed, allowing rapid detection of large point sources and addressing inconsistencies of emissions inventories. The development of airborne and satellite imaging spectrometers provides new assessment methods.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2022)
Article
Plant Sciences
John A. Gamon, Ran Wang, Sabrina E. Russo
Summary: The Photochemical Reflectance Index (PRI) is an optical indicator of photosynthetic light-use efficiency, photoprotection, and stress in plants. However, its interpretation depends on irradiance, which is difficult to obtain from remote sensing imagery. In this study, we developed a framework for modeling and interpreting PRI-light responses using airborne imaging spectrometry and forest inventory data. Our findings show that tree photoprotective strategies can be quantified using airborne hyperspectral data in complex forests.
Editorial Material
Biodiversity Conservation
John A. Gamon
GLOBAL CHANGE BIOLOGY
(2023)
Article
Plant Sciences
Lena Hunt, Zuzana Lhotakova, Eva Neuwirthova, Karel Klem, Michal Oravec, Lucie Kupkova, Lucie Cervena, Howard E. E. Epstein, Petya Campbell, Jana Albrechtova
Summary: This study used the relict arctic-alpine tundra as a natural laboratory to investigate the impacts of climate change and anthropogenic disturbance on tundra vegetation. The Nardus stricta-dominated tundra grasslands in the Krkonose Mountains have shown changes in species dynamics over the past few decades. Using orthophotos, changes in the cover of four competing grasses (Nardus stricta, Calamagrostis villosa, Molinia caerulea, and Deschampsia cespitosa) were successfully detected.
Article
Environmental Sciences
K. Fred Huemmrich, John Gamon, Petya Campbell, Marianna Mora, Z. Sergio Vargas, Brenda Almanza, Craig Tweedie
Summary: In 2022, we conducted a resampling of the normalized difference vegetation index (NDVI) along a 100 m transect in the tundra near Utqiagvik, AK. The results showed spatial variability in the multidecadal NDVI change, with around 50% of the transect showing greening, about a third not showing conclusive change, and approximately 20% browning. The study highlighted the importance of microtopography and hydrology in mediating vegetation change in a warming Arctic.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Biodiversity Conservation
Ran Wang, Kyle R. Springer, John A. Gamon
Summary: Boreal forests at northern latitudes are sensitive to climate change, and spectral reflectance-based optical remote sensing can effectively monitor their response. Snow coverage in high-altitude regions poses challenges for satellite-based vegetation indices, impacting the accuracy of monitoring vegetation productivity. This study revealed significant impacts of snow on canopy reflectance and vegetation indices, with different effects observed among species and functional groups.
GLOBAL CHANGE BIOLOGY
(2023)
Article
Meteorology & Atmospheric Sciences
Broghan M. Erland, Cristen Adams, Andrea Darlington, Mackenzie L. Smith, Andrew K. Thorpe, Gregory R. Wentworth, Steve Conley, John Liggio, Shao-Meng Li, Charles E. Miller, John A. Gamon
Summary: To combat global warming, Canada has committed to reducing greenhouse gases (GHGs) to 40%-45% below 2005 emission levels by 2025. This study compares two airborne mass-balance box-flight algorithms and finds that they produce similar estimates under ideal conditions. However, the algorithms may disagree under non-ideal conditions. The study also highlights the importance of increased sampling to understand the variability of emissions.
ATMOSPHERIC MEASUREMENT TECHNIQUES
(2022)
Proceedings Paper
Geography, Physical
L. Cervena, G. Pinlova, Z. Lhotakova, E. Neuwirthova, L. Kupkova, M. Potuckova, J. Lysak, P. Campbell, J. Albrechtova
Summary: This study focuses on the determination of chlorophyll content in grasses in the Krkonose Mountains National Park, Czech Republic. Two methods, spectrophotometric determination and portable chlorophyll meter, were compared. Relationships were established between chlorophyll content and vegetation indices calculated from leaf spectra. Canopy chlorophyll contents were computed and modeled based on field spectra and hyperspectral images. The correlations based on June datasets had the best performance. The weak model performance can be attributed to leaf structure, LAI variability, and sampling design.
XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION III
(2022)
Proceedings Paper
Geography, Physical
P. E. K. Campbell, K. F. Huemmrich, E. M. Middleton, J. Alfieri, C. van Der Tol, C. S. R. Neigh
Summary: This study evaluates the potential of DESIS and Hyperion spectrometers in capturing surface reflectance and variability. It compares the VNIR reflectance of the two sensors and demonstrates the feasibility of combining historic and current space-based reflectance data.
1ST DESIS USER WORKSHOP - IMAGING SPECTROMETER SPACE MISSION, CALIBRATION AND VALIDATION, APPLICATIONS, METHODS
(2022)
Proceedings Paper
Geography, Physical
K. F. Huemmrich, P. E. K. Campbell, D. J. Harding, K. J. Ranson, R. Wynne, V Thomas, E. M. Middleton
Summary: This study successfully developed and tested multiple algorithms using data from the DLR Earth Sensing Imaging Spectrometer (DESIS) to remotely retrieve ecosystem productivity based on spectral reflectance. The algorithms demonstrated good accuracy across different locations, years, and times of observation.
1ST DESIS USER WORKSHOP - IMAGING SPECTROMETER SPACE MISSION, CALIBRATION AND VALIDATION, APPLICATIONS, METHODS
(2022)
