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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.  ...  The large-area forest plant diversity indices maps add spatially explicit information to the ground-truthing data.  ...  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

Examining rice distribution and cropping intensity in a mixed single- and double-cropping region in South China using all available Sentinel 1/2 images

Yingli He, Jinwei Dong, Xiaoyong Liao, Li Sun, Zhipan Wang, Nanshan You, Zhichao Li, Ping Fu
2021 International Journal of Applied Earth Observation and Geoinformation  
The results showed the combined data from Sentinel-1/2 generally outperformed classifications using only a single sensor (Sentinel-1/2), but the contribution of different sensors to certain rice types  ...  The random forest classifier was used for the classification in the Google Earth Engine (GEE) platform, and a reference map in 2017 based on visual interpretation on the GaoFen-2 images were used for collecting  ...  All these studies have indicated the potential of the combination of Sentinel-1/2 in rice mapping.  ... 
doi:10.1016/j.jag.2021.102351 fatcat:7pzrt76gfrdzxkcifehkpbd4ym

Mapping the vegetation distribution and dynamics of a wetland using adaptive-stacking and Google Earth Engine based on multi-source remote sensing data

Xiangren Long, Xinyu Li, Hui Lin, Meng Zhang
2021 International Journal of Applied Earth Observation and Geoinformation  
In this paper, an adaptive-stacking algorithm based on Google Earth Engine was proposed to map the vegetation distribution of Dongting Lake wetland using Sentinel-1/2 and DEM data.  ...  Subsequently, LandTrendr was utilized to analyze vegetation dynamics over the 1999-2018 based on Landsat normalized combustion ratio time-series.  ...  However, classification result using adaptive-stacking and sentinel-1/2 proposed in this paper has a higher spatial resolution (10 m) and accuracy (94.59%).  ... 
doi:10.1016/j.jag.2021.102453 fatcat:jg5ldkjb55aexlbtso3zjp27f4

Knowledge Extracted from Copernicus Satellite Data

Dumitru Octavian, Schwarz Gottfried, Eltoft Torbjørn, Kræmer Thomas, Wagner Penelope, Hughes Nick, Arthus David, Fleming Andrew, Koubarakis Manolis, Datcu Mihai
2019 Zenodo  
Such a combination approach already demonstrated its applicability for monitoring seasonal snow cover [1].  ...  ExtremeEarth is a European H2020 project; it aims at developing analytics techniques and technologies that combine Copernicus satellite data with information and knowledge extraction, and exploiting them  ...  Automatic glaciers lake mapping, normalized different water index and modify normalized water difference index with on screen digitization (1, 2).  ... 
doi:10.5281/zenodo.3941573 fatcat:zzifwgljifck5bpjnboetsftfu

Evaluating Effects of Medium-Resolution Optical Data Availability on Phenology-Based Rice Mapping in China

Ruoqi Liu, Geli Zhang, Jinwei Dong, Yan Zhou, Nanshan You, Yingli He, Xiangming Xiao
2022 Remote Sensing  
rice mapping based on phenology-based approaches.  ...  Here, we compare the effects of data availability of different sensors in the critical phenology phase, thereby supporting paddy rice mapping based on phenology-based approaches.  ...  Thus, advanced satellite imagery (Sentinel-1/2) and multiple data fusion are necessary for the further extensive application of pixel-and phenology-based rice mapping in the whole China, which will alleviate  ... 
doi:10.3390/rs14133134 fatcat:b3ohth44xrh3zh6okedyzzqldm

Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review

Meisam Amani, Arsalan Ghorbanian, Seyed Ali Ahmadi, Mohammad Kakooei, Armin Moghimi, S. Mohammad Mirmazloumi, Sayyed Hamed Alizadeh Moghaddam, Sahel Mahdavi, Masoud Ghahremanloo, Saeid Parsian, Qiusheng Wu, Brian Brisco
2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
In particular, this platform facilitates processing big geo data over large areas and monitoring the environment for long periods of time.  ...  Moreover, supervised machine learning algorithms, such as Random Forest (RF), were more widely applied to image classification tasks.  ...  More recently, Gorbanian et al [126] produced an improved version of the land cover map of Iran using Sentinel-1/2 imagery within GEE.  ... 
doi:10.1109/jstars.2020.3021052 fatcat:pudllv5h2ve4lfvqtx3p4qikju

Signals of Weather Extremes in Soil Moisture and Terrestrial Water Storage from Multi-Sensor Earth Observations and Hydrological Modeling Signals of Weather Extremes in Soil Moisture and Terrestrial Water Storage from Multi-Sensor Earth Observations and Hydrological Modeling

Sarah Abelen, Ingenieurfakultät Bau, Geo Umwelt, Sarah Abelen
unpublished
Another objective is to gain insight about the drivers of soil moisture on global scale, and to find out whether the combined analysis of both parameters creates added value for their application in the  ...  The global mapping of soil moisture and TWS is a relatively new field of research because operational satellite products, which provide information on both parameters on large scales, have just emerged  ...  From 2002 onwards the operational availability of global soil moisture products was made possible with the launch of at least five major satellite missions (AMSR-E, ASCAT, SMOS, SMAP and Sentinel-1). 2  ... 
fatcat:lybwk5blcvbqhe4cyurbfk7ina