Related references
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Summary: Climate, topography, and forest structure play important roles in shaping local species communities, but little is known about how environmental characteristics affect the functional traits of wood-living beetles involved in wood recycling. In this study, we used ecological and morphological traits of saproxylic beetles and airborne laser scanning data to investigate the factors driving the distributions of over 230 species in European temperate forests. We found that elevation and the proportion of conifers were important factors determining species occurrences, while habitat heterogeneity and forest complexity had less influence. Ecological traits, such as canopy niche, wood decay niche, and host preference, were found to be more important in shaping species responses to forest structure and environmental variation, while morphological traits showed little association with environmental characteristics. These findings highlight the potential impacts of climate and tree species composition changes on saproxylic beetle communities, and the importance of ecological traits in predicting species responses to future environmental change.
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Nico Lang et al.
Summary: NASA's GEDI mission aims to advance understanding of forests' role in the global carbon cycle. A novel supervised machine learning approach has been developed to interpret GEDI waveforms and regress canopy top height globally with reliable predictive uncertainty estimates.
REMOTE SENSING OF ENVIRONMENT
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Environmental Sciences
Christoph Pucher et al.
Summary: This study presents a freely available pan-European forest structure dataset that is consistent and comparable. By combining harmonized inventory data with remote sensing data, the study addresses the issue of inconsistent and missing forest structure data in Europe. The results indicate that the chosen methodology is able to produce robust and accurate forest structure data across Europe.
Article
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Frank Thonfeld et al.
Summary: Central Europe experienced several severe droughts and heatwaves between 2018 and 2020, leading to significant impacts on forest ecosystems. In Germany, bark beetle infestations compounded the damage, resulting in extensive forest loss. This study utilized dense time-series data from Sentinel-2 and Landsat-8 to assess canopy cover loss in Germany from January 2018 to April 2021. The results revealed a total loss of 501,000 hectares, with varying levels of impact across different regions.
Article
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Suzanne M. Marselis et al.
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ENVIRONMENTAL RESEARCH LETTERS
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Environmental Sciences
Laura Duncanson et al.
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
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Khaldoun Rishmawi et al.
Summary: This study aims to achieve consistent and spatially explicit annual monitoring of forest structure in the conterminous United States (CONUS) using NASA's GEDI waveform LiDAR and VIIRS data, as well as high-resolution images. The accuracy of the annual maps was assessed by comparing them with airborne laser scanning (ALS) data, and the results showed high accuracy in canopy height and percent canopy cover. These methods contribute to the multi-decadal analysis of forest structure and its dynamics using satellite observations from sensors such as VIIRS.
Article
Environmental Sciences
Oldrich Rakovec et al.
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Environmental Sciences
Ralph Dubayah et al.
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ENVIRONMENTAL RESEARCH LETTERS
(2022)
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Cangjiao Wang et al.
Summary: The study evaluated the performance of NASA's GEDI spaceborne LiDAR system in different forest types and identified factors influencing its performance. The results showed that GEDI achieved accurate measurements of ground elevation and forest height, with variations observed among different forest profiles. Land surface attributes, observing sensor system characteristics, and collection time differences were found to be important factors affecting GEDI performance, with geolocation error being particularly influential for canopy height estimation.
GISCIENCE & REMOTE SENSING
(2022)
Review
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Patrick Kacic et al.
Summary: Forests are vital for global environmental well-being, but they face increasing pressure from climate change, resource extraction, and human disturbances. Remote sensing technology offers a promising method for monitoring forest biodiversity at large scales. This review focuses on the application of remote sensing technology in forest biodiversity monitoring and analyzes its spatial-temporal distribution, sensors used, temporal scales, and thematic foci.
Article
Environmental Sciences
Camile Sothe et al.
Summary: This study compared the performance of two spaceborne LiDAR sensors, GEDI and ICESat-2, for continuous canopy height estimation in Canada. The results showed that both sensors overestimated canopy height, but GEDI performed better than ICESat-2. However, for hemi-boreal forests, ICESat-2 captured the expected tall canopy heights better than GEDI, as both sensors have limited coverage in these areas.
Article
Environmental Sciences
Torsten Welle et al.
Summary: Having knowledge about the distribution of tree species at a national scale is beneficial for forest management practices and decision making regarding the selection of suitable tree species for specific locations. The accurate identification of tree species in relation to their locations enables assessments of their resilience or vulnerability to various factors. This study used data from the national forest inventory in Germany to develop a machine-learning approach that classified a dense time series of satellite imagery, resulting in a map showing the dominant tree species in German forests. The accuracy of the model was validated through tests and comparisons with independent forest stand inventories and statistics from the national forest inventory.
Review
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Duccio Rocchini et al.
Summary: This paper reviews the spectral species concept and discusses the complexities, challenges, and opportunities to apply this concept given current and future scientific advances in remote sensing.
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
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Review
Ecology
Duccio Rocchini et al.
Summary: Given the unprecedented global changes in biodiversity, it is crucial to have real-time and accurate ecosystem and biodiversity assessments to inform policies and sustainable development. Biodiversity monitoring is particularly challenging for large areas like entire continents, but spaceborne and airborne sensors have provided us with information that cannot be seen by the human eye and at unprecedented spatial resolutions. Through different modeling techniques, it is now possible to study the changes in functional diversity at different scales. This paper aims to summarize the power of remote sensing in directly estimating plant species diversity, with a focus on the concept of spectral species.
Article
Environmental Sciences
Jakob Wernicke et al.
Summary: Knowledge about the forest canopy stratification is crucial for forest management, and remote sensing techniques, such as LiDAR and Sentinel-2, show great potential for differentiating forest strata. This study examined the classification abilities of six approaches using fused and unfused LiDAR and Sentinel-2 metrics for classifying five forest strata in Central Germany. The Random Forest classifier achieved the highest accuracy, and the importance of certain LiDAR metrics in the classification process was identified. The classification solely based on Sentinel-2 metrics had a lower overall accuracy.
REMOTE SENSING OF ENVIRONMENT
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Jakob Wernicke et al.
Summary: This study investigated the potential of using LiDAR and Sentinel-2 metrics for forest canopy classification, and found that the Random Forest classifier most accurately separated the five forest strata, highlighting the important contribution of LiDAR metrics to classification accuracy.
REMOTE SENSING OF ENVIRONMENT
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Jamis M. Bruening et al.
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REMOTE SENSING OF ENVIRONMENT
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Khaldoun Rishmawi et al.
Summary: Accurate information on global forest distribution and 3D structure is crucial for assessing forest biomass stocks and future terrestrial Carbon sink projections. The GEDI LiDAR sensor provides unprecedented sampling of forest structural properties, with VIIRS data successfully extrapolating GEDI measurements for wall-to-wall forest structure maps in the conterminous US. Validation results demonstrate the robustness of the VIIRS data for monitoring forest structural changes over large areas.
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Patrick Kacic et al.
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Summary: This study explores the potential of satellite data combined with harmonic analyses in quantifying vegetation response to drought events in German forests. Harmonic modelling technique shows highest correlation scores at the 6th harmonic degree, especially with soil moisture and the self-calibrated Palmer Drought Severity Index (scPDSI). MODIS imagery with NDVI generates the best results for measuring spectral response to drought conditions.
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Adugna Mullissa et al.
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Andrew K. Skidmore et al.
Summary: Remote sensing of geospatial biodiversity patterns is crucial as a complement to field observations, with high potential to enhance our understanding of global biodiversity. By compiling a prioritized list of remote sensing biodiversity products, it is possible to further improve monitoring and applicability of the EBV framework. Linking remote sensing products to EBVs will accelerate product generation and improve reporting on biodiversity from local to global scales.
NATURE ECOLOGY & EVOLUTION
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Summary: The paper reviews the use of Synthetic Aperture Radar (SAR) measurements for mapping forest 3D structure, focusing on the L-band TomoSAR reflectivity reconstructions and their potential for forest structure mapping. Experimental results obtained from airborne acquisitions over temperate forest sites in Germany support the analysis.
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David P. Roy et al.
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