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Mapping up-to-Date Paddy Rice Extent at 10 M Resolution in China through the Integration of Optical and Synthetic Aperture Radar Images

Xin Zhang, Bingfang Wu, Guillermo Ponce-Campos, Miao Zhang, Sheng Chang, Fuyou Tian
2018 Remote Sensing  
In this study, by leveraging the computational power of GEE and a large pool of satellite and other geophysical data (e.g., forest and water extent maps, with high accuracy at 30 m), we generated the first  ...  the object-based segmentation (using a simple linear iterative clustering (SLIC) method).  ...  Acknowledgments: We thank the anonymous reviewers for reviewing the manuscript and providing comments to improve the manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs10081200 fatcat:cjbi3dhfcjgijoazkltgqdjn2q

Mapping Rice Paddy Based on Machine Learning with Sentinel-2 Multi-Temporal Data: Model Comparison and Transferability

Weichun Zhang, Hongbin Liu, Wei Wu, Linqing Zhan, Jing Wei
2020 Remote Sensing  
However, it has not been widely used in mapping a rice paddy, and most studies lack the comparison of classification effectiveness and efficiency between CNNs and other classic machine learning models  ...  These experiments were conducted using cloud-free Sentinel-2 multi-temporal data in Banan District and Zhongxian County, typical hilly areas of Southwestern China.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs12101620 fatcat:xecl5las45erzeurbdfiiiejyu

Multi-Temporal SAR Data Large-Scale Crop Mapping Based on U-Net Model

Sisi Wei, Hong Zhang, Chao Wang, Yuanyuan Wang, Lu Xu
2019 Remote Sensing  
Finally, we conducted experiments using multi-temporal Sentinel-1 data from Fuyu City, Jilin Province, China in 2017, and we obtained crop mapping results with an overall accuracy of 85% as well as a Kappa  ...  In this paper, a large-scale crop mapping method using multi-temporal dual-polarization SAR data was proposed.  ...  In this work, we introduced the deep learning semantic segmentation network, U-Net, to the multi-temporal Sentinel-1 SAR data crop mapping, and we obtained a satisfactory result with an overall accuracy  ... 
doi:10.3390/rs11010068 fatcat:45etubwosraorbfvbfm2lnmrl4

Automatic semantic segmentation and classification of remote sensing data for agriculture

Jagannath K. Jadhav, R. P. Singh
2018 Mathematical Models in Engineering  
Su T. [16] proposed an efficient paddy field mapping method by means of object-based image analysis and the bi-temporal data set, which is developed by Landsat-8 operational land imager.  ...  The proposed technique is tested using bi-temporal data set, which is acquired from landsat-8 over the Baoying Xian and the mapping accuracy.  ...  Performance of precision Fig. 17 . 17 Performance of recall Multi-spectral data Scene Semantic Segmented mapping DL-CNN based Semantic Segmentation Radiometric, Atmospheric correction and  ... 
doi:10.21595/mme.2018.19840 fatcat:tijmp7ndvbbflpe5i4ofws25pm

Towards Paddy Rice Smart Farming: A Review on Big Data, Machine Learning and Rice Production Tasks

Rayner Alfred, Joe Henry Obit, Christie Chin Pei Yee, Haviluddin Haviluddin, Yuto Lim
2021 IEEE Access  
Using multi-features fusion (e.g., combining Landsat and SAR Time Series Data) can also improve the accuracy of predicting paddy rice yield using a deep learning approach [112] .  ...  For instance, a SVM classifier can be used to perform segmentation and classification of paddy rice samples [46] .  ...  data mining and cope with the big data problem.  ... 
doi:10.1109/access.2021.3069449 fatcat:7xwca7dtardphl77qsrb6al7tu

Recent Applications of Landsat 8/OLI and Sentinel-2/MSI for Land Use and Land Cover Mapping: A Systematic Review

Michel E. D. Chaves, Michelle C. A. Picoli, Ieda D. Sanches
2020 Remote Sensing  
Recent applications of Landsat 8 Operational Land Imager (L8/OLI) and Sentinel-2 MultiSpectral Instrument (S2/MSI) data for acquiring information about land use and land cover (LULC) provide a new perspective  ...  In particular, we highlight the possibility of using medium-resolution (Landsat-like, 10–30 m) time series and multispectral optical data provided by the harmonization between these sensors and data cube  ...  Acknowledgments: The authors would like to acknowledge the National Institute for Space Research (INPE), the Coordination for the Improvement of Higher Education Personnel (CAPES), and the Brazil Data  ... 
doi:10.3390/rs12183062 doaj:b5d54af4fbbe45518fa7c16a3fe25aa7 fatcat:l5bkzuvjx5eu3e5zt4j2h6cgei

Mapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data

Yaotong Cai, Xinyu Li, Meng Zhang, Hui Lin
2020 International Journal of Applied Earth Observation and Geoinformation  
This study is to obtain an accurate wetland map using an object-based stacked generalization (Stacking) method on the basis of multi-temporal Sentinel-1 and Sentinel-2 data.  ...  Speckle noise inherent in SAR data, resulting in over-segmentation or under-segmentation, can affect image segmentation and degrade the accuracies of wetland classification.  ...  This study was funded by the National Natural Science Foundation of China (41901385), the Forestry Remote Sensing Application System based on GF satellites (Phase 2) (21-Y30B02-9001-19/22), and in part  ... 
doi:10.1016/j.jag.2020.102164 fatcat:ztjhrv4uyrbw3cdkyjb7co6e6u

A Hybrid Model of Bidirectional Long-Short Term Memory and CNN for Multivariate Time Series Classification of Remote Sensing Data

Sawsan Morkos Gharghory
2021 Journal of Computer Science  
The traditional modeling classifiers are complicated patterns and are incompetent to capture the dependencies of multivariate time series data.  ...  The efficacy of the proposed network is verified through its comparison with the-state-of-the-art methods using different cases of training dataset.  ...  Also, I am grateful to the encourage and support of our ERI institute with the required tools and software.  ... 
doi:10.3844/jcssp.2021.789.802 fatcat:7ck4p675xfbx5iqjmwlrxl2ome

Boost Precision Agriculture with Unmanned Aerial Vehicle Remote Sensing and Edge Intelligence: A Survey

Jia Liu, Jianjian Xiang, Yongjun Jin, Renhua Liu, Jining Yan, Lizhe Wang
2021 Remote Sensing  
RS methods can be categorized into classification, object detection and segmentation tasks, and convolutional neural network and recurrent neural network are the mostly common used network architectures  ...  In recent years unmanned aerial vehicles (UAVs) have emerged as a popular and cost-effective technology to capture high spatial and temporal resolution remote sensing (RS) images for a wide range of precision  ...  [152] Frost management in apple orchard CNN YOLOv4 [153] Soil and crop segmentation CNN Customize CNN [154] Semantic segmentation Vegetable mapping Crop classification Semantic segmentation of citrus  ... 
doi:10.3390/rs13214387 fatcat:amrm5blon5hmhnk7arme2vsqwq

2020 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13

2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., +, JSTARS 2020 72-88 Classification of Paddy Rice Using a Stacked Generalization Approach and the Spectral Mixture Method Based on MODIS Time Series.  ...  ., +, JSTARS 2020 4410-4418 Classification of Paddy Rice Using a Stacked Generalization Approach and the Spectral Mixture Method Based on MODIS Time Series.  ...  A New Deep-Learning-Based Approach for Earthquake-Triggered Landslide Detection From Single-Temporal RapidEye Satellite Imagery. Yi, Y., +, JSTARS 2020  ... 
doi:10.1109/jstars.2021.3050695 fatcat:ycd5qt66xrgqfewcr6ygsqcl2y

Bridging the Semantic Gap between Land Tenure and EO Data: Conceptual and Methodological Underpinnings for a Geospatially Informed Analysis

Cheonjae Lee, Walter Timo de Vries
2020 Remote Sensing  
a participatory mapping at the local scale.  ...  However, this first exploration provides a relevant contribution to bridging the semantic gap between land tenure and EO data.  ...  We are also immensely grateful to colleagues who provided insight and expertise that greatly assisted the research, although any errors are our own and should not tarnish the reputations of these esteemed  ... 
doi:10.3390/rs12020255 fatcat:flyxch6245dcnigfdqrpm6b6gu

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.  ...  Results showed that the overall accuracy and kappa coefficient of adaptive-stacking classification were 94.59% and 0.92, respectively, which were higher than those of support vector machine and random  ...  Its main wetland vegetation includes sedge, reed, poplar forest, and constructed wetland paddy rice.  ... 
doi:10.1016/j.jag.2021.102453 fatcat:jg5ldkjb55aexlbtso3zjp27f4

Table of Contents

2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
Wu 2123 Classification of Paddy Rice Using a Stacked Generalization Approach and the Spectral Mixture Method Based on MODIS Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Engdahl 4070 Improving Land Cover Change Detection and Classification With BRDF Correction and Spatial Feature Extraction Using Landsat Time Series: A Case of Urbanization in Tianjin, China . . . . .  ...  He 1551 Classification of High-Spatial-Resolution Remote Sensing Scenes Method Using Transfer Learning and Deep Convolutional Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . W.  ... 
doi:10.1109/jstars.2020.3046663 fatcat:zqzyhnzacjfdjeejvzokfy4qze

UAVs for Vegetation Monitoring: Overview and Recent Scientific Contributions

Ana I. de Castro, Yeyin Shi, Joe Mari Maja, Jose M. Peña
2021 Remote Sensing  
The general goal was proposing UAV-based technological solutions for a better use of agricultural and forestry resources and more efficient production with relevant economic and environmental benefits.  ...  This paper reviewed a set of twenty-one original and innovative papers included in a special issue on UAVs for vegetation monitoring, which proposed new methods and techniques applied to diverse agricultural  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs13112139 fatcat:zbirrq37cjgxbpo5zooplm2jra

Table of Contents

2020 IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium  
PADDY RICE .......................... 3420 HEIGHT WITH TANDEM-X DATA Noelia Romero-Puig, Juan M.  ...  SEGMENTATION OF REMOTE SENSING IMAGES Jiachao Liu, Xinyue Xiong, Jiaojiao Li, Chaoxiong Wu, Rui Song, Xidian University, China TH1-R9.8: MAP-REPAIR: DEEP CADASTRE MAPS ALIGNMENT AND TEMPORAL ...  ... 
doi:10.1109/igarss39084.2020.9323828 fatcat:6aittajt35gufeaugcmemu5cya
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