Search Results - "Ke, Yinghai"

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  1. 1

    Urban Land Use and Land Cover Classification Using Novel Deep Learning Models Based on High Spatial Resolution Satellite Imagery by Zhang, Pengbin, Ke, Yinghai, Zhang, Zhenxin, Wang, Mingli, Li, Peng, Zhang, Shuangyue

    Published in Sensors (Basel, Switzerland) (01-11-2018)
    “…Urban land cover and land use mapping plays an important role in urban planning and management. In this paper, novel multi-scale deep learning models, namely…”
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  2. 2

    Synergistic use of QuickBird multispectral imagery and LIDAR data for object-based forest species classification by Ke, Yinghai, Quackenbush, Lindi J., Im, Jungho

    Published in Remote sensing of environment (15-06-2010)
    “…This study evaluated the synergistic use of high spatial resolution multispectral imagery (i.e., QuickBird, 2.4 m) and low-posting-density LIDAR data (3 m) for…”
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  3. 3

    review of methods for automatic individual tree-crown detection and delineation from passive remote sensing by Ke, Yinghai, Quackenbush, Lindi J

    Published in International journal of remote sensing (01-01-2011)
    “…Efficient forest management demands detailed, timely information. As high spatial resolution remotely sensed imagery becomes more available, there is a great…”
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  4. 4

    Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches by Ke, Yinghai, Im, Jungho, Park, Seonyoung, Gong, Huili

    Published in Remote sensing (Basel, Switzerland) (01-03-2016)
    “…This study presented a MODIS 8-day 1 km evapotranspiration (ET) downscaling method based on Landsat 8 data (30 m) and machine learning approaches. Eleven…”
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  5. 5

    Object-Based Urban Tree Species Classification Using Bi-Temporal WorldView-2 and WorldView-3 Images by Li, Dan, Ke, Yinghai, Gong, Huili, Li, Xiaojuan

    Published in Remote sensing (Basel, Switzerland) (01-12-2015)
    “…Urban tree species mapping is an important prerequisite to understanding the value of urban vegetation in ecological services. In this study, we explored the…”
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  6. 6

    Mapping coastal wetlands in the Yellow River Delta, China during 2008-2019: impacts of valid observations, harmonic regression, and critical months by Wang, Zhanpeng, Ke, Yinghai, Chen, Mengmeng, Zhou, Demin, Zhu, Lin, Bai, Junhong

    Published in International journal of remote sensing (18-10-2021)
    “…Spartina alterniflora has become one of the top exotic invasive plants in coastal China. Accurate and timely mapping of coastal wetlands is critical to…”
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  7. 7

    The 3‐D Facies and Geomechanical Modeling of Land Subsidence in the Chaobai Plain, Beijing by Zhu, Lin, Franceschini, Andrea, Gong, Huili, Ferronato, Massimiliano, Dai, Zhenxue, Ke, Yinghai, Pan, Yun, Li, Xiaojuan, Wang, Rong, Teatini, Pietro

    Published in Water resources research (01-03-2020)
    “…The hydrogeologic systems of alluvial fan are characterized by a heterogeneous distribution of various lithological units/facies. The structure (integral scale…”
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  8. 8

    A Simple Phenology-Based Vegetation Index for Mapping Invasive Spartina Alterniflora Using Google Earth Engine by Xu, Ronglong, Zhao, Siqing, Ke, Yinghai

    “…Spartina alterniflora (S. alterniflora) after introduced to China, has rapidly expanded along the coastline and become one of the top invasive plants in…”
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  9. 9

    Spatiotemporal dynamics of suspended particulate matter in the Yellow River Estuary, China during the past two decades based on time-series Landsat and Sentinel-2 data by Li, Peng, Ke, Yinghai, Bai, Junhong, Zhang, Shuangyue, Chen, Mengmeng, Zhou, Demin

    Published in Marine pollution bulletin (01-12-2019)
    “…Twenty-two years of suspended particulate matter (SPM) concentrations in the Yellow River estuary and adjacent sea, China were derived from 532 Landsat and…”
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  10. 10

    Combining Landsat-8 and Sentinel-2 to investigate seasonal changes of suspended particulate matter off the abandoned distributary mouths of Yellow River Delta by Li, Peng, Chen, Shenliang, Ji, Hongyu, Ke, Yinghai, Fu, Yutao

    Published in Marine geology (01-11-2021)
    “…Suspended particulate matter (SPM) is the primary component of coastal waters. The spatiotemporal dynamics of SPM has an important influence on water…”
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  11. 11

    Comparison of Five Spatio-Temporal Satellite Image Fusion Models over Landscapes with Various Spatial Heterogeneity and Temporal Variation by Liu, Maolin, Ke, Yinghai, Yin, Qi, Chen, Xiuwan, Im, Jungho

    Published in Remote sensing (Basel, Switzerland) (01-11-2019)
    “…In recent years, many spatial and temporal satellite image fusion (STIF) methods have been developed to solve the problems of trade-off between spatial and…”
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  12. 12

    Mapping Paddy Rice Planting Area in Northeastern China Using Spatiotemporal Data Fusion and Phenology-Based Method by Yin, Qi, Liu, Maolin, Cheng, Junyi, Ke, Yinghai, Chen, Xiuwan

    Published in Remote sensing (Basel, Switzerland) (18-07-2019)
    “…Accurate paddy rice mapping with fine spatial detail is significant for ensuring food security and maintaining sustainable environmental development. In…”
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  13. 13

    Assessing degradation of lake wetlands in Bashang Plateau, China based on long-term time series Landsat images using wetland degradation index by Zhu, Lijuan, Ke, Yinghai, Hong, Jianming, Zhang, Yuhu, Pan, Yun

    Published in Ecological indicators (01-06-2022)
    “…•Wetland Degradation Index (WDI) was constructed on a pixel-by-pixel basis.•WDI incorporates lake shrinkage index (LSI), vegetation/soil degradation index.•LSI…”
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  14. 14

    Phenological heterogeneities of invasive Spartina alterniflora salt marshes revealed by high-spatial-resolution satellite imagery by Han, Xiaoran, Wang, Yiming, Ke, Yinghai, Liu, Tianqi, Zhou, Demin

    Published in Ecological indicators (01-11-2022)
    “…•Phenological heterogeneity in invasive salt marshes revealed by Sentinel-2 images.•S. alterniflora with shorter invasion period (≤5 years) experienced earlier…”
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  15. 15
  16. 16

    A Novel Super-Resolution Model for 10-m Mangrove Mapping With Landsat-5 by Chen, Wei, Tian, Jinyan, Song, Jie, Li, Xiaojuan, Ke, Yinghai, Zhu, Lin, Yu, Yongxin, Ou, Yang, Gong, Huili

    “…Existing temporal mangrove products are at a 30-m resolution from Landsat, facing challenges such as unclear delineation of mangrove community edges,…”
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  17. 17

    Multi-Scale Analysis of the Relationship between Land Subsidence and Buildings: A Case Study in an Eastern Beijing Urban Area Using the PS-InSAR Technique by Yang, Qin, Ke, Yinghai, Zhang, Dongyi, Chen, Beibei, Gong, Huili, Lv, Mingyuan, Zhu, Lin, Li, Xiaojuan

    Published in Remote sensing (Basel, Switzerland) (01-07-2018)
    “…Beijing is severely affected by land subsidence, and rapid urbanisation and building construction might accelerate the land subsidence process. Based on 39…”
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  18. 18

    Land subsidence along the Beijing-Tianjin Intercity Railway during the period of the South-to-North Water Diversion Project by Zhao, Xiaoxiao, Chen, Beibei, Gong, Huili, Zhou, Chaofan, Li, Xiaojuan, Lei, Kunchao, Ke, Yinghai

    Published in International journal of remote sensing (17-06-2020)
    “…The Beijing-Tianjin Intercity Railway (BTR) passes through the subsidence centre of the Chaoyang Wangsiying-Heizhuanghu subsidence funnel edge, which is the…”
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  19. 19

    Effects of tidal creeks on Spartina Alterniflora expansion: A perspective from multi-scale remote sensing by Cui, Liyue, Ke, Yinghai, Min, Yukui, Han, Yue, Zhang, Mengyao, Zhou, Demin

    Published in Ecological indicators (01-03-2024)
    “…•Effect of tidal creeks on S. alterniflora invasion at both landscape and patch scales.•Medium-resolution images reveal tidal creeks promoting S. alterniflora…”
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  20. 20

    Multilevel Building Detection Framework in Remote Sensing Images Based on Convolutional Neural Networks by Liu, Yibo, Zhang, Zhenxin, Zhong, Ruofei, Chen, Dong, Ke, Yinghai, Peethambaran, Jiju, Chen, Chuqun, Sun, Lan

    “…In this paper, we propose a hierarchical building detection framework based on deep learning model, which focuses on accurately detecting buildings from remote…”
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