Article
Multidisciplinary Sciences
Yanli Lu, Xiaoyu Zhang, Yuezhi Cui, Yaru Chao, Guipei Song, Caie Nie, Lei Wang
Summary: Spectral technology is effective in diagnosing N stress in maize, but it is affected by varietal differences. The responses to N stress, leaf N spectral diagnostic models, and varietal differences were analyzed in this study. The diagnostic stages for Jiyu 5817 and Zhengdan 958 were identified, and considering varietal effect in the diagnostic model improved its fit and RMSE.
SCIENTIFIC REPORTS
(2023)
Article
Chemistry, Analytical
Mariana A. Soppa, Brenner Silva, Francois Steinmetz, Darryl Keith, Daniel Scheffler, Niklas Bohn, Astrid Bracher
Summary: This study investigates the performance of Polymer AC for hyperspectral remote sensing over coastal waters, demonstrating its potential in providing lower uncertainties and greater data coverage compared to the standard AC algorithm. Polymer shows very good performance in the green spectral region and higher spectral similarity to in situ measurements.
Article
Environmental Sciences
Zhijun Zhen, Shengbo Chen, Tiangang Yin, Jean-Philippe Gastellu-Etchegorry
Summary: Recent studies have shown that using BRDF signatures captured by multi-angle observation data can enhance land cover classification and retrieve vegetation architectures. In this study, we proposed using BRDF signatures to improve crop mapping precision. We compared the accuracy of four supervised machine learning classifiers and found that using BRDF signatures moderately improves classification results compared to using reflectance data from a single observation direction. Our study contributes to the development of crop mapping and the application of multi-angle observation satellites.
Article
Geochemistry & Geophysics
Anxin Ding, Shunlin Liang, Ziti Jiao, Han Ma, Alexander A. Kokhanovsky, Jouni Peltoniemi
Summary: This study proposes an improved model, ARTF, by multiplying by a correction term in the asymptotic radiative transfer (ART) model to enhance the accuracy in characterizing snow bidirectional reflectance. Compared to the ART and ARTS models, the ARTF model exhibits higher accuracy and is more effective in representing snow hyperspectral reflectance.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Plant Sciences
Dominic Williams, Alison Karley, Avril Britten, Susan McCallum, Julie Graham
Summary: Monitoring plant responses to stress is a challenge, especially below-ground stress. Hyperspectral imaging can help identify stress responses in plants by analyzing the relationship between plant spectral data and specific stresses.
Article
Remote Sensing
Sam Cooper, Akpona Okujeni, Dirk Pflugmacher, Sebastian van der Linden, Patrick Hostert
Summary: This study successfully mapped forest AGB using EnMAP imagery and Landsat time series, with the two-date EnMAP model performing the best and outperforming the corresponding Landsat models. Combining the two datasets further improved AGB mapping efforts, demonstrating the synergies between spectral and temporal data sources can effectively enhance global forest AGB mapping.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Green & Sustainable Science & Technology
Luis Guilherme Teixeira Crusiol, Liang Sun, Zheng Sun, Ruiqing Chen, Yongfeng Wu, Juncheng Ma, Chenxi Song
Summary: This research aims to evaluate the relationship between maize leaf water content (LWC) and ground-based and UAV-based hyperspectral data. The study finds that ground-based hyperspectral data outperforms UAV-based data for LWC monitoring, and HVIs and PLSR models are more suitable for LWC monitoring. The complementary use of ground-based and UAV-based hyperspectral data has the potential for maize LWC monitoring.
Article
Environmental Sciences
Yi Lin, Siyuan Liu, Lei Yan, Kai Yan, Yelu Zeng, Bin Yang
Summary: Directional area scattering factor (DASF) is a critical parameter for vegetation monitoring. The current method to estimate DASF has biases due to neglecting variations in biochemical constituents. This study proposes a new approach that accounts for variations in concentrations and improves DASF estimation.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Horticulture
Renan Tosin, Isabel Pocas, Helena Novo, Jorge Teixeira, Natacha Fontes, Antonio Graca, Mario Cunha
Summary: This study developed two models to estimate Psi(pd) in a commercial vineyard, utilizing spectral data and machine learning algorithms. The first model estimated Psi(pd) based on vine canopy reflectance and selected suitable vegetation indices, while the second model optimized variables for Psi(pd) estimation based on pigments' concentrations assessed through hyperspectral reflectance. The B-MARS algorithm produced the best results with a RRMSE between 13-14% in validation.
SCIENTIA HORTICULTURAE
(2021)
Article
Environmental Sciences
Martin Bachmann, Kevin Alonso, Emiliano Carmona, Birgit Gerasch, Martin Habermeyer, Stefanie Holzwarth, Harald Krawczyk, Maximilian Langheinrich, David Marshall, Miguel Pato, Nicole Pinnel, Raquel de losReyes, Mathias Schneider, Peter Schwind, Tobias Storch
Summary: Ground segments of Landsat and Sentinel missions provide well-calibrated datasets which are orthorectified and corrected for atmospheric effects. Initiatives like CEOS ARD propose guidelines for easily using such datasets and ensuring interoperability. The increasing availability of hyperspectral sensor data from EnMAP, DESIS, PRISMA, and upcoming missions like CHIME and SBG make analysis ready hyperspectral data more valuable.
Article
Remote Sensing
Lei Deng, Yong Chen, Yun Zhao, Lin Zhu, Hui-Li Gong, Li-Jie Guo, Han-Yue Zou
Summary: This study utilized UAV-based oblique photography technology to obtain high-spatial resolution and high-accuracy continuous RA data, optimizing the selection of multi-angle observation data using the Monte Carlo method. The accuracy and applicability of two BRDF inversion models were thoroughly analyzed and compared, expanding the research and application of RA measurement.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Ecology
Qiaoli Wu, Shenhui Yang, Jie Jiang
Summary: The product of leaf area index (LAI) and clumping index (CI) quantifies the effective leaf abundance and distribution across the landscape. This study simulated how canopy bidirectional reflectance distribution function (BRDF) responds to changes in CI in Qinghai spruce forests and found that the red band BRF showed higher sensitivity to changes in CI than the near-infrared (NIR) band.
FRONTIERS IN FORESTS AND GLOBAL CHANGE
(2023)
Article
Environmental Sciences
Zhongbin Li, David P. Roy, Hankui K. Zhang
Summary: The study found that hot-spot sensing conditions on the GOES-16 ABI occurred in different geographic regions of North America during spring and autumn, with the phenomenon not being negligible. Furthermore, the analysis revealed significant differences in reflectance in ABI data under hot-spot conditions.
REMOTE SENSING OF ENVIRONMENT
(2021)
Review
Plant Sciences
Rijad Saric, Viet D. Nguyen, Timothy Burge, Oliver Berkowitz, Martin Trtilek, James Whelan, Mathew G. Lewsey, Edhem Custovic
Summary: Our ability to manipulate the genome exceeds our capacity to measure genetic changes on plant traits. Plant scientists have been using imaging approaches, specifically hyperspectral imaging, to define plant responses to environmental conditions and optimize crop management.
TRENDS IN PLANT SCIENCE
(2022)
Article
Ecology
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Gruenwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppanen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukes, Lars Lundin, Riccardo Marzuoli, Meelis Molder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, Caroline Vincke
Summary: The study suggests that accurate retrievals of forest understory NDVI can be obtained using MODIS data and a specific method, with better performance in forest types with open canopies, but limitations in forests with closed canopies and high foliage cover.
Article
Remote Sensing
Clemens Jaenicke, Akpona Okujeni, Sam Cooper, Matthew Clark, Patrick Hostert, Sebastian van der Linden
REMOTE SENSING LETTERS
(2020)
Article
Environmental Sciences
Niklas Bohn, Luis Guanter, Theres Kuester, Rene Preusker, Karl Segl
REMOTE SENSING OF ENVIRONMENT
(2020)
Article
Agriculture, Multidisciplinary
Philippe Rufin, Daniel Mueller, Marcel Schwieder, Dirk Pflugmacher, Patrick Hostert
Summary: Long-term monitoring of irrigation systems is crucial for tracking crop water consumption and adapting land use to changing climate. Mapping the expansion and changes in the intensity of irrigated dry season cropping in Turkey's Southeastern Anatolia Project revealed a significant increase in planting area in 2018, with pronounced spatial variability in planting frequency. The presented maps can identify land use intensity hotspots, aiding in assessments of water consumption and environmental degradation.
JOURNAL OF LAND USE SCIENCE
(2021)
Article
Environmental Sciences
Esther Shupel Ibrahim, Philippe Rufin, Leon Nill, Bahareh Kamali, Claas Nendel, Patrick Hostert
Summary: This study used Sentinel-2A/B and SkySat data to map crop types in the Jos Plateau, Nigeria, showing maize as the dominant crop, followed by mixed cropping systems, and potato as the least prevalent class. Analyses of mixed crop classes were conducted, revealing regional variations in the distribution of crop types.
Article
Environmental Sciences
David Frantz, Patrick Hostert, Philippe Rufin, Stefan Ernst, Achim Roeder, Sebastian van der Linden
Summary: Open and analysis-ready data, as well as methodological advances, have greatly improved our ability to observe the Earth's land surfaces. Careful selection of static images may introduce uncertainties, and using all available data with phenology-based approaches can provide more reliable results.
Article
Ecology
Mirela G. Tulbure, Patrick Hostert, Tobias Kuemmerle, Mark Broich
Summary: Unprecedented amounts of analysis-ready Earth Observation data, combined with increased computational power and new algorithms, provide novel opportunities for ecosystem analysis and conservation planning. There are inherent trade-offs between regional and global EO products in terms of class legends, data availability, and accuracy. Recognizing and understanding these trade-offs is crucial for developing EO products and addressing science questions relevant to ecology and conservation.
REMOTE SENSING IN ECOLOGY AND CONSERVATION
(2022)
Article
Remote Sensing
Franz Schug, David Frantz, Akpona Okujeni, Patrick Hostert
Summary: This study examined the suitability of machine learning regression-based unmixing for accurate mapping of building areas in high-resolution remote sensing imagery with centimeter resolution. A hierarchical approach was proposed to improve the estimation accuracy of building areas by increasing the spatial resolution.
REMOTE SENSING LETTERS
(2022)
Article
Green & Sustainable Science & Technology
Franz Schug, David Frantz, Dominik Wiedenhofer, Helmut Haberl, Doris Virag, Sebastian van der Linden, Patrick Hostert
Summary: This study assessed the dynamics of material stock and its relation to population in Germany using Landsat imagery and a spatial resolution of 30 m. The results showed that material stock and population in Germany grew by 13% and 4% respectively, with highly variable spatial patterns. The reunification of East and West Germany in 1990 led to a rapid growth of material stock per capita in East Germany, despite a decline in population. Possible over- or underestimations of stock growth due to methodological assumptions require further research.
JOURNAL OF INDUSTRIAL ECOLOGY
(2023)
Article
Biodiversity Conservation
Katarzyna Ewa Lewinska, Anthony R. Ives, Clay J. Morrow, Natalia Rogova, He Yin, Paul R. Elsen, Kirsten de Beurs, Patrick Hostert, Volker C. Radeloff
Summary: Grassland ecosystems cover a large portion of global land area, and monitoring their long-term changes is crucial for various purposes. Existing remote sensing-based monitoring methods often fail to consider temporal and spatial autocorrelation, leading to inaccurate identification of trends. In this study, we analyzed trends in Eurasian grasslands using a new statistical approach that accounts for autocorrelation. The results showed significant changes in Eurasian grasslands over the past two decades, with an increase in non-photosynthetic vegetation and local changes in green vegetation and soil cover. Environmental variables significantly affected these trends, but their effects varied across regions.
GLOBAL CHANGE BIOLOGY
(2023)
Article
Agriculture, Multidisciplinary
Benjamin Jakimow, Matthias Baumann, Caroline Salomao, Hugo Bendini, Patrick Hostert
Summary: The increasing deforestation and fires since 2019 in the Brazilian Amazon have raised concerns about irreversible destruction. This study aimed to understand these changes in south-west Para under different presidencies and land-tenure systems. The results showed a significant increase in deforestation and fires during Bolsonaro's presidency, particularly in undesignated areas and conservation units on medium-sized farms.
JOURNAL OF LAND USE SCIENCE
(2023)
Article
Multidisciplinary Sciences
Franz Schug, Dominik Wiedenhofer, Helmut Haberl, David Frantz, Doris Virag, Sebastian van der Linden, Patrick Hostert
Summary: This study provides high-resolution maps of material stocks in buildings and infrastructures in Austria, showing a 33-year time series. These data are important for studies on societal resource use, transport studies, and land system science.
Article
Multidisciplinary Sciences
Franz Schug, Avi Bar-Massada, Amanda R. Carlson, Heather Cox, Todd J. Hawbaker, David Helmers, Patrick Hostert, Dominik Kaim, Neda K. Kasraee, Sebastian Martinuzzi, Miranda H. Mockrin, Kira A. Pfoch, Volker C. Radeloff
Summary: This study presents a global map of the wildland-urban interface (WUI) in 2020, showing its widespread existence and identifying previously undocumented hotspots. The WUI covers a small percentage of land surface but is home to a significant portion of the global population. This research highlights the importance of understanding housing growth and vegetation patterns as drivers of WUI change.
Article
Environmental Sciences
Kira Anjana Pfoch, Dirk Pflugmacher, Akpona Okujeni, Patrick Hostert
Summary: Precise quantification of forest fire impacts is crucial for post-fire mitigation strategies. Optical remote sensing imagery combined with spectral unmixing has been widely used to measure fire severity. However, most previous studies only used post-fire imagery without considering the pre-fire state. This study presents a bi-temporal spectral unmixing analysis using Sentinel-2 data, which includes pre-fire and post-fire information, to provide a quantitative description of fire impact.
SCIENCE OF REMOTE SENSING
(2023)
Article
Environmental Sciences
Katarzyna Ewa Lewinska, Johanna Buchner, Benjamin Bleyhl, Patrick Hostert, He Yin, Tobias Kuemmerle, Volker C. Radeloff
Summary: Grasslands play a crucial role in global biodiversity, food security, and climate change analyses, highlighting the importance of mapping and monitoring vegetation changes. This study evaluated long-term positive changes in grassland vegetation cover in the Caucasus Ecoregion, particularly in the early 2000s, with negative changes pathways being more common before the year 2000. Results showed strong spatial heterogeneity in vegetation dynamics among neighboring fields and pastures, demonstrating the capability of the approach for grassland management at local levels.
SCIENCE OF REMOTE SENSING
(2021)
Article
Environmental Studies
Michelle C. A. Picoli, Ana Rorato, Pedro Leitao, Gilberto Camara, Adeline Maciel, Patrick Hostert, Ieda Del'Arco Sanches