Windthrow Detection in European Forests with Very High-Resolution Optical Data
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Windthrow Detection in European Forests with Very High-Resolution Optical Data
Authors
Keywords
-
Journal
Forests
Volume 8, Issue 1, Pages 21
Publisher
MDPI AG
Online
2017-01-06
DOI
10.3390/f8010021
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Use of WorldView-2 stereo imagery and National Forest Inventory data for wall-to-wall mapping of growing stock
- (2016) Markus Immitzer et al. FOREST ECOLOGY AND MANAGEMENT
- Mapping Prosopis spp. with Landsat 8 data in arid environments: Evaluating effectiveness of different methods and temporal imagery selection for Hargeisa, Somaliland
- (2016) Wai-Tim Ng et al. International Journal of Applied Earth Observation and Geoinformation
- Climate change amplifies the interactions between wind and bark beetle disturbances in forest landscapes
- (2016) Rupert Seidl et al. LANDSCAPE ECOLOGY
- Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?
- (2016) Paul Schumacher et al. Remote Sensing
- First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe
- (2016) Markus Immitzer et al. Remote Sensing
- Stable Mean-Shift Algorithm and Its Application to the Segmentation of Arbitrarily Large Remote Sensing Images
- (2015) Julien Michel et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics
- (2015) Txomin Hermosilla et al. REMOTE SENSING OF ENVIRONMENT
- A critical synthesis of remotely sensed optical image change detection techniques
- (2015) Andrew P. Tewkesbury et al. REMOTE SENSING OF ENVIRONMENT
- Identification of Forested Landslides Using LiDar Data, Object-based Image Analysis, and Machine Learning Algorithms
- (2015) Xianju Li et al. Remote Sensing
- Self-Guided Segmentation and Classification of Multi-Temporal Landsat 8 Images for Crop Type Mapping in Southeastern Brazil
- (2015) Bruno Schultz et al. Remote Sensing
- The Time Variable in Data Fusion: A Change Detection Perspective
- (2015) Francesca Bovolo et al. IEEE Geoscience and Remote Sensing Magazine
- Detecting Stand-Replacing Disturbance using RapidEye Imagery: a Tasseled Cap Transformation and Modified Disturbance Index
- (2014) John T. T. R. Arnett et al. CANADIAN JOURNAL OF REMOTE SENSING
- Object-based change detection in wind storm-damaged forest using high-resolution multispectral images
- (2014) N. Chehata et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery
- (2014) Benoit Beguet et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Improving Land Cover Maps in Areas of Disagreement of Existing Products using NDVI Time Series of MODIS – Example for EuropeVerbesserung von Landbedeckungskarten in Gebieten widersprüchlicher Grundlagen mit Hilfe der NDVI-Zeitreihe von MODIS – Beispiel für Europa
- (2014) Francesco Vuolo et al. Photogrammetrie Fernerkundung Geoinformation
- Method Analysis for Collecting and Processing in-situ Hyperspectral Needle Reflectance Data for Monitoring Norway Spruce Methodenanalyse zur Erfassung und Prozessierung hyperspektraler in-situ Nadelreflexionsdaten zum Monitoring von Fichten
- (2014) Kathrin Einzmann et al. Photogrammetrie Fernerkundung Geoinformation
- Early Detection of Bark Beetle Infestation in Norway Spruce (Picea abies, L.) using WorldView-2 Data Frühzeitige Erkennung von Borkenkä ferbefall an Fichten mittels WorldView-2 Satellitendaten
- (2014) Markus Immitzer et al. Photogrammetrie Fernerkundung Geoinformation
- Object-based extraction of bark beetle (Ips typographus L.) infestations using multi-date LANDSAT and SPOT satellite imagery
- (2014) Hooman Latifi et al. PROGRESS IN PHYSICAL GEOGRAPHY
- Landsat remote sensing of forest windfall disturbance
- (2014) Matthias Baumann et al. REMOTE SENSING OF ENVIRONMENT
- Increasing forest disturbances in Europe and their impact on carbon storage
- (2014) Rupert Seidl et al. Nature Climate Change
- Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance
- (2014) Muhammad Hasan Ali Baig et al. Remote Sensing Letters
- Forest Cover Database Updates Using Multi-Seasonal RapidEye Data—Storm Event Assessment in the Bavarian Forest National Park
- (2014) Alata Elatawneh et al. Forests
- Change detection from remotely sensed images: From pixel-based to object-based approaches
- (2013) Masroor Hussain et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Wavelet-based texture measures for object-based classification of aerial images
- (2013) Philipp Toscani et al. Photogrammetrie Fernerkundung Geoinformation
- Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data
- (2013) D Jonikavičius et al. iForest-Biogeosciences and Forestry
- Radiometric Normalization of Temporal Images Combining Automatic Detection of Pseudo-Invariant Features from the Distance and Similarity Spectral Measures, Density Scatterplot Analysis, and Robust Regression
- (2013) Osmar de Carvalho et al. Remote Sensing
- Combined Edge Segment Texture Analysis for the Detection of Damaged Buildings in Crisis Areas
- (2012) S. Klonus et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Regional estimation of savanna grass nitrogen using the red-edge band of the spaceborne RapidEye sensor
- (2012) A. Ramoelo et al. International Journal of Applied Earth Observation and Geoinformation
- Object-based change detection
- (2012) Gang Chen et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Continuous monitoring of forest disturbance using all available Landsat imagery
- (2012) Zhe Zhu et al. REMOTE SENSING OF ENVIRONMENT
- Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data
- (2012) Markus Immitzer et al. Remote Sensing
- Forest cover disturbances in the South Taiga of West Siberia
- (2011) E A Dyukarev et al. Environmental Research Letters
- A New Approach to Change Vector Analysis Using Distance and Similarity Measures
- (2011) Osmar A. Carvalho Júnior et al. Remote Sensing
- Improving Discrimination of Savanna Tree Species Through a Multiple-Endmember Spectral Angle Mapper Approach: Canopy-Level Analysis
- (2010) Moses Azong Cho et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Assessing hurricane-induced tree mortality in U.S. Gulf Coast forest ecosystems
- (2010) Robinson Negrón-Juárez et al. JOURNAL OF GEOPHYSICAL RESEARCH
- Sources of variability in canopy reflectance and the convergent properties of plants
- (2010) S. V. Ollinger NEW PHYTOLOGIST
- Variable selection using random forests
- (2010) Robin Genuer et al. PATTERN RECOGNITION LETTERS
- Comparison of remote sensing change detection techniques for assessing hurricane damage to forests
- (2009) Fugui Wang et al. ENVIRONMENTAL MONITORING AND ASSESSMENT
- Monitoring forest changes in the southwestern United States using multitemporal Landsat data
- (2009) James E. Vogelmann et al. REMOTE SENSING OF ENVIRONMENT
- Detecting wind disturbance severity and canopy heterogeneity in boreal forest by coupling high-spatial resolution satellite imagery and field data
- (2009) Roy. L. Rich et al. REMOTE SENSING OF ENVIRONMENT
- Assessment of radiometric correction techniques in analyzing vegetation variability and change using time series of Landsat images
- (2008) S VICENTESERRANO et al. REMOTE SENSING OF ENVIRONMENT
- Development of a two-band enhanced vegetation index without a blue band
- (2008) Z JIANG et al. REMOTE SENSING OF ENVIRONMENT
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started