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科研机构
植物研究所 [6]
遥感与数字地球研究所 [4]
南海海洋研究所 [1]
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期刊论文 [11]
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2020 [1]
2019 [2]
2018 [3]
2016 [4]
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Remote Se... [11]
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学科主题:Remote Sensing
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A Framework for Land Use Scenes Classification Based on Landscape Photos
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 卷号: 13, 页码: 6124-6141
作者:
Xu, Shiwu
;
Zhang, Shihui
;
Zeng, Jue
;
Li, Tingyu
;
Guo, Qinghua
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2022/03/01
Semantics
Remote sensing
Image analysis
Image segmentation
Object recognition
Machine learning
Forestry
Deep convolutional neural networks (DCNNs)
landscape photos
land survey
land use scene classification
A simple and integrated approach for fire severity assessment using bi-temporal airborne LiDAR data
期刊论文
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2019, 卷号: 78, 页码: 25-38
作者:
Hu, Tianyu
;
Ma, Qin
;
Su, Yanjun
;
Battles, John J.
;
Collins, Brandon M.
收藏
  |  
浏览/下载:14/0
  |  
提交时间:2022/01/06
Fire severity
Fire type
Tree canopy
Airborne LiDAR
Profile area change
An Object-Based Strategy for Improving the Accuracy of Spatiotemporal Satellite Imagery Fusion for Vegetation-Mapping Applications
期刊论文
REMOTE SENSING, 2019, 卷号: 11, 期号: 24
作者:
Guan, Hongcan
;
Su, Yanjun
;
Hu, Tianyu
;
Chen, Jin
;
Guo, Qinghua
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2022/01/06
spatiotemporal data fusion
object-based framework
similar pixel
vegetation mapping
The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data
期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 8
作者:
Jin, Shichao
;
Su, Yanjun
;
Gao, Shang
;
Hu, Tianyu
;
Liu, Jin
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2022/02/25
canopy height
Random Forest
LiDAR
multi-source
vegetation type
location
scale
Artificial Mangrove Species Mapping Using Pleiades-1: An Evaluation of Pixel-Based and Object-Based Classifications with Selected Machine Learning Algorithms
期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 2
作者:
Wang, Dezhi
;
Wan, Bo
;
Qiu, Penghua
;
Su, Yanjun
;
Guo, Qinghua
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2022/02/25
artificial mangrove
object-based
pixel-based
decision tree
random forest
support vector machine
VBRT: A novel voxel-based radiative transfer model for heterogeneous three-dimensional forest scenes
期刊论文
REMOTE SENSING OF ENVIRONMENT, 2018, 卷号: 206, 页码: 318-335
作者:
Li, Wenkai
;
Guo, Qinghua
;
Tao, Shengli
;
Su, Yanjun
收藏
  |  
浏览/下载:20/0
  |  
提交时间:2022/02/25
Radiative transfer (RT)
Monte Carlo path tracing
Voxel
High performance computing (HPC)
Light detection and ranging (LiDAR)
Evaluation of the Chinese fine spatial resolution hyperspectral satellite TianGong-1 in urban land-cover classification
期刊论文
Remote Sensing, 2016, 卷号: 8, 期号: 5
作者:
Li, Xueke
;
Wu, Taixia
;
Liu, Kai
;
Li, Yao
;
Zhang, Lifu
收藏
  |  
浏览/下载:28/0
  |  
提交时间:2017/04/24
SURFACE SHORTWAVE RADIATION
CLEAR-SKY DAYS
BROAD-BAND MODELS
LANDSAT-TM DATA
NET-RADIATION
HETEROGENEOUS LANDSCAPE
IRRADIANCE PREDICTIONS
RUGGED TERRAIN
EARTHS SURFACE
SATELLITE DATA
Deriving ice motion patterns in mountainous regions by integrating the intensity-based pixel-tracking and phase-based D-InSAR and MAI approaches: A case study of the chongce glacier
期刊论文
Remote Sensing, 2016, 卷号: 8, 期号: 7
作者:
Yan, Shiyong
;
Ruan, Zhixing
;
Liu, Guang
;
Deng, Kazhong
;
Lv, Mingyang
收藏
  |  
浏览/下载:28/0
  |  
提交时间:2017/04/24
PLANETARY BOUNDARY-LAYER
OCEAN SURFACE
RADAR IMAGES
SAR IMAGES
C-BAND
FIELDS
RETRIEVAL
SATELLITE
VALIDATION
HURRICANES
A multiple-point spatially weighted k-NN method for object-based classification
期刊论文
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2016, 卷号: 52, 页码: 263-274
作者:
Tang, Yunwei
;
Jing, Linhai
;
Li, Hui
;
Atkinson, Peter M.
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2017/04/24
SPARSE SAHELIAN VEGETATION
LAND-SURFACE
EVAPOTRANSPIRATION RATES
CANOPY RESISTANCE
KB(-1) PARAMETER
SOIL
FORMULATION
SEBS
SYSTEMS
LENGTH
A spatio-temporal model for forest fire detection using HJ-IRS satellite data
期刊论文
Remote Sensing, 2016, 卷号: 8, 期号: 5
作者:
Lin, Lei
;
Meng, Yu
;
Yue, Anzhi
;
Yuan, Yuan
;
Liu, Xiaoyi
收藏
  |  
浏览/下载:18/0
  |  
提交时间:2017/04/24
HIGH-RESOLUTION
AMSR-E
RETRIEVAL
IMAGERY
CHINA
SMOS
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