A Classification of Tidal Flat Wetland Vegetation Combining Phenological Features with Google Earth Engine
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Title
A Classification of Tidal Flat Wetland Vegetation Combining Phenological Features with Google Earth Engine
Authors
Keywords
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Journal
Remote Sensing
Volume 13, Issue 3, Pages 443
Publisher
MDPI AG
Online
2021-01-28
DOI
10.3390/rs13030443
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Note: Only part of the references are listed.- Compilation of 1:50,000 vegetation type map with remote sensing images based on mountain altitudinal belts of Taibai Mountain in the North-South transitional zone of China
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- Modeling grass yields in Qinghai Province, China, based on MODIS NDVI data—an empirical comparison
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- (2020) Saeedeh Eskandari et al. Remote Sensing
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- (2020) Hoa T. Le et al. Applied Sciences-Basel
- Quantifying expansion and removal of Spartina alterniflora on Chongming island, China, using time series Landsat images during 1995–2018
- (2020) Xi Zhang et al. REMOTE SENSING OF ENVIRONMENT
- Mapping Mountain Peatlands and Wet Meadows Using Multi-Date, Multi-Sensor Remote Sensing in the Cordillera Blanca, Peru
- (2019) Rodney A. Chimner et al. WETLANDS
- Quantifying coconut palm extent on Pacific islands using spectral and textural analysis of very high resolution imagery
- (2019) Michael W. Burnett et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Spatiotemporal variation in vegetation spring phenology and its response to climate change in freshwater marshes of Northeast China
- (2019) Xiangjin Shen et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Multiple Flights or Single Flight Instrument Fusion of Hyperspectral and ALS Data? A Comparison of their Performance for Vegetation Mapping
- (2019) Łukasz Sławik et al. Remote Sensing
- Integrating LiDAR data and multi-temporal aerial imagery to map wetland inundation dynamics using Google Earth Engine
- (2019) Qiusheng Wu et al. REMOTE SENSING OF ENVIRONMENT
- Determination of Vegetation Thresholds for Assessing Land Use and Land Use Changes in Cambodia using the Google Earth Engine Cloud-Computing Platform
- (2019) Venkatappa et al. Remote Sensing
- Using Landsat observations (1988–2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation
- (2019) Zunyi Xie et al. REMOTE SENSING OF ENVIRONMENT
- Incorporating the Plant Phenological Trajectory into Mangrove Species Mapping with Dense Time Series Sentinel-2 Imagery and the Google Earth Engine Platform
- (2019) Huiying Li et al. Remote Sensing
- Mapping Aboveground Biomass of Four Typical Vegetation Types in the Poyang Lake Wetlands Based on Random Forest Modelling and Landsat Images
- (2019) Rongrong Wan et al. Frontiers in Plant Science
- Vegetation phenology from Sentinel-2 and field cameras for a Dutch barrier island
- (2018) Anton Vrieling et al. REMOTE SENSING OF ENVIRONMENT
- Water footprint and scenario analysis in the transformation of Chongming into an international eco-island
- (2018) Pengzhou Luo et al. RESOURCES CONSERVATION AND RECYCLING
- Mapping Vegetation and Land Use Types in Fanjingshan National Nature Reserve Using Google Earth Engine
- (2018) Yu Tsai et al. Remote Sensing
- Detection of Cropland Change Using Multi-Harmonic Based Phenological Trajectory Similarity
- (2018) Jiage Chen et al. Remote Sensing
- Vegetation species mapping in a coastal-dune ecosystem using high resolution satellite imagery
- (2018) Anabella Medina Machín et al. GIScience & Remote Sensing
- The global distribution and trajectory of tidal flats
- (2018) Nicholas J. Murray et al. NATURE
- Impact of seasonal water-level fluctuations on autumn vegetation in Poyang Lake wetland, China
- (2018) Xue Dai et al. Frontiers of Earth Science
- Mapping tropical disturbed forests using multi-decadal 30 m optical satellite imagery
- (2018) Yunxia Wang et al. REMOTE SENSING OF ENVIRONMENT
- Mapping major land cover dynamics in Beijing using all Landsat images in Google Earth Engine
- (2017) Huabing Huang et al. REMOTE SENSING OF ENVIRONMENT
- Google Earth Engine: Planetary-scale geospatial analysis for everyone
- (2017) Noel Gorelick et al. REMOTE SENSING OF ENVIRONMENT
- Modeling Biomass Production in Seasonal Wetlands Using MODIS NDVI Land Surface Phenology
- (2017) Maria Lumbierres et al. Remote Sensing
- Drivers, trends, and potential impacts of long-term coastal reclamation in China from 1985 to 2010
- (2016) Bo Tian et al. ESTUARINE COASTAL AND SHELF SCIENCE
- Remote sensing of urban growth and landscape pattern changes in response to the expansion of Chongming Island in Shanghai, China
- (2016) Guangrong Shen et al. Geocarto International
- Land Cover Characterization in West Sudanian Savannas Using Seasonal Features from Annual Landsat Time Series
- (2016) Jinxiu Liu et al. Remote Sensing
- Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations
- (2015) Yinghai Ke et al. REMOTE SENSING OF ENVIRONMENT
- Reconstruction of global MODIS NDVI time series: Performance of Harmonic ANalysis of Time Series (HANTS)
- (2015) Jie Zhou et al. REMOTE SENSING OF ENVIRONMENT
- Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images
- (2015) Zhe Zhu et al. REMOTE SENSING OF ENVIRONMENT
- Influence of Multi-Source and Multi-Temporal Remotely Sensed and Ancillary Data on the Accuracy of Random Forest Classification of Wetlands in Northern Minnesota
- (2013) Jennifer Corcoran et al. Remote Sensing
- An assessment of the effectiveness of a random forest classifier for land-cover classification
- (2011) V.F. Rodriguez-Galiano et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Object-based cloud and cloud shadow detection in Landsat imagery
- (2011) Zhe Zhu et al. REMOTE SENSING OF ENVIRONMENT
- Advances in estimation methods of vegetation water content based on optical remote sensing techniques
- (2010) JiaHua Zhang et al. Science China-Technological Sciences
- A Nonlinear Harmonic Model for Fitting Satellite Image Time Series: Analysis and Prediction of Land Cover Dynamics
- (2009) H. Carrao et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Birds and people both depend on China's wetlands
- (2009) Lei Cao et al. NATURE
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