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An Object-Based Paddy Rice Classification Using Multi-Spectral Data and Crop Phenology in Assam, Northeast India

Mrinal Singha, Bingfang Wu, Miao Zhang
2016 Remote Sensing  
Phenology was extracted from MODIS NDVI time series, and the distribution of rice was mapped from China's Environmental Satellite (HJ-1A/B) data.  ...  This study investigates the effect of phenology for rice mapping using an object-based image analysis (OBIA) approach.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs8060479 fatcat:5wdnmmftwnev7fn2ycdet4ywj4

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data

Mrinal Singha, Bingfang Wu, Miao Zhang
2016 Sensors  
The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data.  ...  The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%.  ...  Many studies utilized fused time series vegetation index datasets for cropland mapping and phenology studies [34, 35] .  ... 
doi:10.3390/s17010010 pmid:28025525 pmcid:PMC5298583 fatcat:o2j3baeggbhrxouuewsletep4u

Rice Fields Mapping in Fragmented Area Using Multi-Temporal HJ-1A/B CCD Images

Jing Wang, Jingfeng Huang, Kangyu Zhang, Xinxing Li, Bao She, Chuanwen Wei, Jian Gao, Xiaodong Song
2015 Remote Sensing  
In this study, the applicability of the Chinese HJ-1A/B satellites and a two-band enhanced vegetation index (EVI2) was investigated.  ...  A stepwise classification strategy utilizing the EVI2 signatures during key phenology stages, i.e., the transplanting and the vegetative to reproductive transition phases, of the SCR was proposed, and  ...  Jingfeng Huang supervised the process of field campaign and data analysis. Kangyu Zhang provided partial source codes for image analysis. Xinxing Li was responsible for image data collection.  ... 
doi:10.3390/rs70403467 fatcat:ioydpg3uwjbq5lchxbol5anydy

ChinaCropPhen1km: a high-resolution crop phenological dataset for three staple crops in China during 2000–2015 based on leaf area index (LAI) products

Yuchuan Luo, Zhao Zhang, Yi Chen, Ziyue Li, Fulu Tao
2020 Earth System Science Data  
the retrieved phenological date being less than 10 d, and represented the spatiotemporal patterns of the observed phenological dynamics at the site scale fairly well.  ...  In this study, we produced a 1 km grid crop phenological dataset for three main crops from 2000 to 2015 based on Global Land Surface Satellite (GLASS) leaf area index (LAI) products, called ChinaCropPhen1km  ...  We would like to thank the highperformance computing support from the Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University (https://gda.bnu.edu.cn/, last access:  ... 
doi:10.5194/essd-12-197-2020 fatcat:dxk3avlgsjcgxelv5fppwmqscq

Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost

Zhen Zhou, Jingfeng Huang, Jing Wang, Kangyu Zhang, Zhaomin Kuang, Shiquan Zhong, Xiaodong Song, Frank Alexander Feltus
2015 PLoS ONE  
In addition, time-series Chinese HJ-1 CCD images were obtained during the sugarcane growing period.  ...  The prediction model was applied to the HJ-1 CCD time-series image objects, and then a map of the sugarcane planting area was produced.  ...  Acknowledgments We thank the China Center for Resources Satellite Data and Application for providing the free HJ-1 CCD data and the USGS for providing the free Landsat-8 OLI data.  ... 
doi:10.1371/journal.pone.0142069 pmid:26528811 pmcid:PMC4631514 fatcat:645fg46325bczl7a2tqtrgxfvu

Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology

Tianjiao Liu, Xiangnan Liu, Meiling Liu, Ling Wu
2018 Sensors  
In this study, we used an integrated Normalized Difference Vegetation Index (NDVI) time-series image set to extract remote sensing phenology.  ...  This finding provides scientific evidence for combining rice phenology and physiological characteristics in time and space, and the method is useful to monitor heavy metal stress in rice.  ...  of time series images.  ... 
doi:10.3390/s18030860 pmid:29538350 pmcid:PMC5877332 fatcat:6l7g2xgrfbcptchvhjkcfxv7cu

Tracking the dynamics of paddy rice planting area in 1986–2010 through time series Landsat images and phenology-based algorithms

Jinwei Dong, Xiangming Xiao, Weili Kou, Yuanwei Qin, Geli Zhang, Li Li, Cui Jin, Yuting Zhou, Jie Wang, Chandrashekhar Biradar, Jiyuan Liu, Berrien Moore
2015 Remote Sensing of Environment  
In this study, we developed an automated, Landsat-based paddy rice mapping (Landsat-RICE) system that uses time series Landsat images and a phenology-based algorithm based on the unique spectral characteristics  ...  Air temperature was used to define phenology timing and crop calendar, which were then used to select Landsat images in the phenology-based algorithms for paddy rice and masks.  ...  The high resolution images were provided by NASA for use in the NASA projects with the terms of the National Geospatial-Intelligence Agency's (NGA) Nextview License Agreement.  ... 
doi:10.1016/j.rse.2015.01.004 fatcat:73g6nbuw5bh4tdvjjjqwl674r4

Crops Planting Information Retrieval at Farmland Plot Scale Using Multi-Sources Satellite Data

Huang Qiting, State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China, Luo Jiancheng, Dong Wen
2017 Journal of Advanced Agricultural Technologies  
effective data which served as the source of properties for plot objects is obtained; thirdly, the specific NDVI time-series and phenological parameters for each farmland plot are further derived from  ...  This experiment illustrated the effectiveness and usefulness of the proposed method, and was referential to finely planting information extraction for other crops.  Index Terms-remote sensing, crop identification  ...  Project of Guangxi Province (14125008-1-6).  ... 
doi:10.18178/joaat.4.2.96-103 fatcat:b6dgdjbcfbgexfk2kknbzyiam4

Automated cropping intensity extraction from isolines of wavelet spectra

Bingwen Qiu, Zhuangzhuang Wang, Zhenghong Tang, Chongcheng Chen, Zhanling Fan, Weijiao Li
2016 Computers and Electronics in Agriculture  
To test its efficiency, the CIIWS method is applied to China's Henan province using 250 m 8 days composite Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series  ...  The mapping result is also evaluated with 30 m Chinese Environmental Disaster Reduction Satellite (HJ-1)-derived data and an overall accuracy of 86.7% is obtained.  ...  This work is supported by the National Natural Science Foundation of China (Grant Nos. 41471362 and 41071267).  ... 
doi:10.1016/j.compag.2016.04.015 fatcat:eb2dkytmhveubdphidtsg7boou

WHEAT AREA MAPPING AND PHENOLOGY DETECTION USING SYNTHETIC APERTURE RADAR AND MULTI MULTI-SPECTRAL REMOTE SENSING OBSERVATIONS

J. D. Mohite, S. A. Sawant, S. Rana, S. Pappula
2019 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Further, we propose a method to estimate the crop phenology parameter viz. sowing date using the early time series of Normalized Difference Vegetation Index (NDVI).  ...  However, accuracy drops to 87.19 % and 79.16 % while using NDVI and VV-VH respectively. Further, to estimate the sowing date we have considered the NDVI time-series during Oct.  ...  The Sentinel 1&2 remote sensing observations were obtained from ESA Copernicus Open Access Hub and GEE platform.  ... 
doi:10.5194/isprs-archives-xlii-3-w6-123-2019 fatcat:s6g65r4zrbb3noovww3z6ztmyq

Forecasting Transplanted Rice Yield at the Farm Scale Using Moderate-Resolution Satellite Imagery and the AquaCrop Model: A Case Study of a Rice Seed Production Community in Thailand

Kulapramote Prathumchai, Masahiko Nagai, Nitin Tripathi, Nophea Sasaki
2018 ISPRS International Journal of Geo-Information  
The rice yield simulated using the AquaCrop model and assimilated with the results of HJ-1A/B, produced a satisfactory outcome when implemented into the validated rice plots, with RMSE = 0.18 t ha −1 and  ...  In addition, the optimal rice constant value for conversion of CC was investigated. HJ-1A/B satellite images were used to calculate the CC value, which was then used to simulate yield.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijgi7020073 fatcat:pmgrhcqjxvgdvcn6wsgvwgjxwq

Early Season Mapping of Sugarcane by Applying Machine Learning Algorithms to Sentinel-1A/2 Time Series Data: A Case Study in Zhanjiang City, China

Hao Jiang, Dan Li, Wenlong Jing, Jianhui Xu, Jianxi Huang, Ji Yang, Shuisen Chen
2019 Remote Sensing  
First, we proposed a framework consisting of two procedures: initial sugarcane mapping using the S1A SAR imagery time series, followed by non-vegetation removal using Sentinel-2 optical imagery.  ...  More than 90% of the sugar production in China comes from sugarcane, which is widely grown in South China. Optical image time series have proven to be efficient for sugarcane mapping.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs11070861 fatcat:qxdkbu5xnjdxlgjgp23bijseoq

Rapid Extraction of Regional-Scale Agricultural Disasters by the Standardized Monitoring Model Based on Google Earth Engine

Zhengrong Liu, Huanjun Liu, Chong Luo, Haoxuan Yang, Xiangtian Meng, Yongchol Ju, Dong Guo
2020 Sustainability  
Three types of disaster monitoring and scope extraction models are proposed: the normalized difference vegetation index (NDVI) median time standardization model (RNDVI_TM(i)), the NDVI median phenology  ...  series.  ...  MODIS NDVI time series can be used to analyze the spatiotemporal evolution of droughts and ENSO events in order to estimate the associated yield loss [29] [30] [31] .  ... 
doi:10.3390/su12166497 fatcat:wreorxyz4jcafbrwzgafk5q4qm

Land Cover Classification Based on Fused Data from GF-1 and MODIS NDVI Time Series

Fanjie Kong, Xiaobing Li, Hong Wang, Dengfeng Xie, Xiang Li, Yunxiao Bai
2016 Remote Sensing  
We developed four classification scenarios based on different combinations of GF-1 spectral features, the fused NDVI time-series, and the phenological parameters.  ...  We extracted seven phenological parameters (including the start, end, and length of the growing season, base value, mid-season date, maximum NDVI, seasonal NDVI amplitude) from a fused NDVI time-series  ...  We thank CRESDA for providing the GF-1 dataset, and the National Aeronautic and Space Administration for providing the MODIS dataset.  ... 
doi:10.3390/rs8090741 fatcat:pfe3ohypqvagjazp55i437zu5q

Changes in rice cropping systems in the Poyang Lake Region, China during 2004–2010

Peng Li, Zhiming Feng, Luguang Jiang, Yujie Liu, Xiangming Xiao
2012 Journal of Geographical Sciences  
The results revealed that: (1) from 2004 to 2010, the decrement of paddy rice field was 46.76 km 2 due to the land use change. (2) The temporal dynamics of NDVI derived from Landsat historical images could  ...  temporal windows, the spatial variation of rice cropping systems was very obvious, with an increased multiple cropping index of rice about 20.2% from 2004 to 2010.  ...  The time-series MODIS vegetation index data holds great potential for describing the growth dynamics of rice fields over large area with relative simple cropping systems.  ... 
doi:10.1007/s11442-012-0954-x fatcat:v4sidkdm3vaczckmzmi6sofdxa
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