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Potential of Sentinel-1 Data for Monitoring Temperate Mixed Forest Phenology

Pierre-Louis Frison, Bénédicte Fruneau, Syrine Kmiha, Kamel Soudani, Eric Dufrêne, Thuy Le Toan, Thierry Koleck, Ludovic Villard, Eric Mougin, Jean-Paul Rudant
2018 Remote Sensing  
In this study, the potential of Sentinel-1 data to seasonally monitor temperate forests was investigated by analyzing radar signatures observed from plots in the Fontainebleau Forest of the Ile de France  ...  These results illustrate the high potential of Sentinel-1 data for monitoring vegetation, and as these data are not sensitive to the atmosphere, the phenology could be estimated with more accuracy than  ...  This study showed the strong potential of Sentinel-1 for monitoring temperate forests.  ... 
doi:10.3390/rs10122049 fatcat:rp5v6ftigveqlnzqh7fd6sk7qi

Potential of Synthetic Aperture Radar Sentinel-1 time series for the monitoring of phenological cycles in a deciduous forest [article]

Kamel SOUDANI, Nicolas Delpierre, Daniel Berveiller, Gabriel Hmimina, Gaelle Vincent, Alexandre Morfin, Eric Dufrene
2021 bioRxiv   pre-print
Annual time-series of the two satellites C-band SAR (Synthetic Aperture Radar) Sentinel-1 A and B data over five years were used to characterize the phenological cycle of a temperate deciduous forest.  ...  This study shows the high potential offered by Sentinel-1 SAR C-band time series for the detection of forest phenology for the first time, thus overcoming the limitations caused by cloud cover in optical  ...  Potential of Sentinel-1 Data for Monitoring 541 Temperate Mixed Forest Phenology. Remote Sens. 2018, 10, 2049. 542 Gielen, B., Acosta, M., Altimir, N. et al., 2018.  ... 
doi:10.1101/2021.02.04.429811 fatcat:escpvbpirffovcookchjniugpi


C. Dubois, M. M. Mueller, C. Pathe, T. Jagdhuber, F. Cremer, C. Thiel, C. Schmullius
2020 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
In this study, we analyze Sentinel-1 time series data to characterize the observed seasonality of different land cover classes in eastern Thuringia, Germany and to identify multi-temporal metrics for their  ...  The novelty of this approach is the determination of phenological parameters, based on a tool that has been originally developed for optical imagery.  ...  ., (2018) analyzed the potential of Sentinel-1 time series for monitoring the phenology of temperate forest showing the example of a mixed forest near Paris.  ... 
doi:10.5194/isprs-annals-v-3-2020-97-2020 fatcat:3ty4cag7zzcnxb5tk2sdetrdj4


M. M. Mueller, C. Dubois, T. Jagdhuber, C. Pathe, C. Schmullius
2021 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
C-band SAR signal in a temperate forest in the Free State of Thuringia, Germany.  ...  Even if signals from the ground below the canopy may not be expected at C-band, previous studies showed seasonal fluctuations of the backscatter for temperate forests without canopy closure, notably for  ...  Special thanks to Mona Reichel for supporting the statistical analysis of the data.  ... 
doi:10.5194/isprs-archives-xliii-b3-2021-127-2021 fatcat:zrlx4dlpsjdjvcp545dvh57w5m

Assessing the Accuracy of Forest Phenological Extraction from Sentinel-1 C-Band Backscatter Measurements in Deciduous and Coniferous Forests

Yuxiang Ling, Shiwen Teng, Chao Liu, Jadunandan Dash, Harry Morris, Julio Pastor-Guzman
2022 Remote Sensing  
Sentinel-1 (S1), a polar orbit satellite with a spatial resolution of 10 m, provides an opportunity to observe high-resolution forest phenology.  ...  The sensitivities of S1 C-band backscatter measurements to vegetation phenology, such as crops, meadows, and mixed forests, have been discussed, whereas their performance for different forest types has  ...  Therefore, further research is required on the potential of S1 data for monitoring coniferous forest phenology. Previous studies have shown the stability of the NDVI for phenological studies [49] .  ... 
doi:10.3390/rs14030674 fatcat:543n27k375bebaw3yu5nnj3qr4

Climate Effects on Vertical Forest Phenology of Fagus sylvatica L., Sensed by Sentinel-2, Time Lapse Camera, and Visual Ground Observations

Lars Uphus, Marvin Lüpke, Ye Yuan, Caryl Benjamin, Jana Englmeier, Ute Fricke, Cristina Ganuza, Michael Schwindl, Johannes Uhler, Annette Menzel
2021 Remote Sensing  
in temperate deciduous forests.  ...  In forests, in which overstory strongly regulates the microclimate beneath, it is not clear if further change equally shifts the timing of leaf unfolding for the over- and understory of main deciduous  ...  Subsequently, two data sets were used as input for Sentinel-2 analysis: 1. Data set 1 was generated for the forest stands in which ground observations were also conducted.  ... 
doi:10.3390/rs13193982 fatcat:2x5nlw2rzraindcc5gaxtzxgae

Coarse-Resolution Satellite Images Overestimate Urbanization Effects on Vegetation Spring Phenology

Jiaqi Tian, Xiaolin Zhu, Jin Wu, Miaogen Shen, Jin Chen
2020 Remote Sensing  
To be exact, we first generated a dense 10 m NDVI time series through harmonizing Sentinel-2 and Landsat-8 images by data fusion method, and then resampled the 10 m time series to coarser resolutions from  ...  Nevertheless, the magnitude of this rural–urban difference is quite different among these studies, especially for studies over the same areas, which implies large uncertainties.  ...  Acknowledgments: We thank Trecia Kay-Ann Williams for improving the quality of this paper. Conflicts of Interest: The authors declare no conflict of interests.  ... 
doi:10.3390/rs12010117 fatcat:f7rfev3go5ccxaes54nxceqzpu

Using Multitemporal Sentinel-1 C-band Backscatter to Monitor Phenology and Classify Deciduous and Coniferous Forests in Northern Switzerland

2017 Remote Sensing  
We demonstrate the potential of using multitemporal C-band VV and VH polarisation data for monitoring phenology and classifying forests in northern Switzerland.  ...  These results show that multitemporal C-band backscatter data have significant potential to supplement optical remote sensing data for ecological studies and mapping of mixed temperate forests.  ...  Further thanks go to the Canton of Zurich for the provision of the aerial image forest stand map, MeteoSwiss for producing the meteorological and phenological data, and swisstopo for providing the aerial  ... 
doi:10.3390/rs10010055 fatcat:3yp7eyn2ojeifaxlmleaqv32ry

Earth Observation and Biodiversity Big Data for Forest Habitat Types Classification and Mapping

Emiliano Agrillo, Federico Filipponi, Alice Pezzarossa, Laura Casella, Daniela Smiraglia, Arianna Orasi, Fabio Attorre, Andrea Taramelli
2021 Remote Sensing  
The procedure integrates forest habitat data in Italy from the European Vegetation Archive (EVA), with Sentinel-2 imagery processing (vegetation indices time series, spectral indices, and single bands  ...  These are providing unprecedented insights for habitat monitoring and for evaluating the Sustainable Development Goals (SDGs) indicators.  ...  Table 1 . 1 The forest types present in Italy according to the National Forest Inventory of 2005 1 and the European Atlas of Forest Tree Species 2 .  ... 
doi:10.3390/rs13071231 fatcat:p63viqeh6vbfbfeubxugw5m6hy

Mapping satellite-derived thermal parameters of canopy onset and assessing their temperature dependency for temperate forests in Korea

Nanghyun Cho, Sinkyu Kang, Bora Lee, Casimir Agossou, Jihye Lee, Jong-Hwan Lim, Eunsook Kim
2021 Ecological Indicators  
This study proposes a satellite-based approach for mapping the canopy-onset thermal traits and analyzing their controlling factors in temperate forests.  ...  Growing degree days (GDD) and chilling requirements (CR) of canopy phenological onset are popular thermal indicators showing forest adaptation to local temperature regimes.  ...  The foliage observational data in the Korea National Phenology Database was collected by the project on "conservation of threatened plants under climate change on Korea forest" (Korea Forest Service)  ... 
doi:10.1016/j.ecolind.2021.107528 fatcat:gwap2b46azdgzm3zm47xra776i

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors

Maximilian Lange, Benjamin Dechant, Corinna Rebmann, Michael Vohland, Matthias Cuntz, Daniel Doktor
2017 Sensors  
This results in mixed pixels, integrating phenological signals of different vegetation and land cover types, e.g., deciduous forests and nearby grasslands.  ...  Although the Normalized Difference Vegetation Index (NDVI) shows saturation effects in dense forest canopies [11] , it is one of the most widely-used indices for this purpose, mainly due to data availability  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s17081855 pmid:28800065 pmcid:PMC5579479 fatcat:3ak3wvgtnjhr7o3o5ginq7v7jm

Monitoring Forest Phenology in a Changing World

Ross E. J. Gray, Robert M. Ewers
2021 Forests  
A range of approaches for monitoring phenology have been developed to increase our understanding on its role in ecosystems, ranging from the use of satellites and drones to collection traps, each with  ...  robust methods for upscaling phenological observations from point locations to biome and global scales and reconciling data from varied sources and environments.  ...  Acknowledgments: The authors would like to thank Terhi Riutta for her valuable comments on a prior draft of the manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/f12030297 doaj:eecfb079c4994151948200d7bc1c601b fatcat:cgnmulr5ivg2rimv6bjjbakoai

Earth Observation for Phenological Metrics (EO4PM): Temporal Discriminant to Characterize Forest Ecosystems

Federico Filipponi, Daniela Smiraglia, Emiliano Agrillo
2022 Remote Sensing  
This study highlights the importance of integrated data and methodologies to support the processes of vegetation recognition and monitoring activities.  ...  Multivariate statistical analysis is performed for the purpose of demonstrating the capacity of the generated smoothed vegetation curve, temporal statistics, and phenological metrics to serve as temporal  ...  As a result, an early detection of onset of greenness for tree species within a mixed-forest pixel can be estimated [35] .  ... 
doi:10.3390/rs14030721 fatcat:edxppgd7h5aivlbakq2icfmt2y

Mapping Plant Diversity Based on Combined SENTINEL-1/2 Data—Opportunities for Subtropical Mountainous Forests

Qichi Yang, Lihui Wang, Jinliang Huang, Lijie Lu, Yang Li, Yun Du, Feng Ling
2022 Remote Sensing  
Timely and accurate monitoring and evaluation of large-area wall-to-wall maps on plant diversity and its spatial heterogeneity are crucial for the conservation and management of forest resources.  ...  Using Sentinel-1 (S-1) and Sentinel-2 (S-2) data at high spatiotemporal scales, combined with and referenced to botanical field surveys, may be the best choice to provide accurate plant diversity distribution  ...  Acknowledgments: We thank to Tingting Li and Zhengxiang Wang (Hubei University) for providing valuable plants distribution information and designing of the sampling plots.  ... 
doi:10.3390/rs14030492 fatcat:y5esudmz3bc2lhsgyt4avcosxi

Integrating Sentinel-1/2 Data and Machine Learning to Map Cotton Fields in Northern Xinjiang, China

Tao Hu, Yina Hu, Jianquan Dong, Sijing Qiu, Jian Peng
2021 Remote Sensing  
Here, we proposed a new framework for mapping cotton fields based on Sentinel-1/2 data for different phenological periods, random forest classifiers, and the multi-scale image segmentation method.  ...  Additionally, Sentinel-1 and the red edge bands in Sentinel-2 are important for cotton field mapping, and there is great potential for the fusion of optical images and microwave images in crop mapping.  ...  Acknowledgments: The authors are grateful to the editors and reviewers for reviewing the manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs13234819 fatcat:3b3bg7t7p5cl7m2den2mquocs4
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