Long-short-term-memory-based crop classification using high-resolution optical images and multi-temporal SAR data
出版年份 2019 全文链接
标题
Long-short-term-memory-based crop classification using high-resolution optical images and multi-temporal SAR data
作者
关键词
-
出版物
GIScience & Remote Sensing
Volume -, Issue -, Pages 1-22
出版商
Informa UK Limited
发表日期
2019-06-25
DOI
10.1080/15481603.2019.1628412
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Mapping cropland fallow areas in myanmar to scale up sustainable intensification of pulse crops in the farming system
- (2018) Murali Krishna Gumma et al. GIScience & Remote Sensing
- Rice crop phenology mapping at high spatial and temporal resolution using downscaled MODIS time-series
- (2018) Alex O. Onojeghuo et al. GIScience & Remote Sensing
- Beyond one-hot encoding: Lower dimensional target embedding
- (2018) Pau Rodríguez et al. IMAGE AND VISION COMPUTING
- Time-series classification of Sentinel-1 agricultural data over North Dakota
- (2018) Tracy Whelen et al. Remote Sensing Letters
- Classification and Mapping of Paddy Rice by Combining Landsat and SAR Time Series Data
- (2018) Seonyoung Park et al. Remote Sensing
- Monitoring canopy growth and grain yield of paddy rice in South Korea by using the GRAMI model and high spatial resolution imagery
- (2017) Mijeong Kim et al. GIScience & Remote Sensing
- Crop classification and acreage estimation in North Korea using phenology features
- (2017) Huanxue Zhang et al. GIScience & Remote Sensing
- Adaptive Scale Selection for Multiscale Segmentation of Satellite Images
- (2017) Yanan Zhou et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Energy crop mapping with enhanced TM/MODIS time series in the BCAP agricultural lands
- (2017) Cuizhen Wang et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community
- (2017) John E. Ball et al. Journal of Applied Remote Sensing
- Deep belief echo-state network and its application to time series prediction
- (2017) Xiaochuan Sun et al. KNOWLEDGE-BASED SYSTEMS
- A new method for crop classification combining time series of radar images and crop phenology information
- (2017) Damian Bargiel REMOTE SENSING OF ENVIRONMENT
- Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications
- (2017) Amanda Veloso et al. REMOTE SENSING OF ENVIRONMENT
- Toward mapping crop progress at field scales through fusion of Landsat and MODIS imagery
- (2017) Feng Gao et al. REMOTE SENSING OF ENVIRONMENT
- Static Memory Deduplication for Performance Optimization in Cloud Computing
- (2017) Gangyong Jia et al. SENSORS
- LSTM: A Search Space Odyssey
- (2017) Klaus Greff et al. IEEE Transactions on Neural Networks and Learning Systems
- Geo-Parcel Based Crop Identification by Integrating High Spatial-Temporal Resolution Imagery from Multi-Source Satellite Data
- (2017) Yingpin Yang et al. Remote Sensing
- Efficient paddy field mapping using Landsat-8 imagery and object-based image analysis based on advanced fractel net evolution approach
- (2016) Tengfei Su GIScience & Remote Sensing
- Efficiency Assessment of Multitemporal C-Band Radarsat-2 Intensity and Landsat-8 Surface Reflectance Satellite Imagery for Crop Classification in Ukraine
- (2016) Sergii Skakun et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Evaluation of the discrimination capability of full polarimetric SAR data for crop classification
- (2016) Hind H. Zeyada et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Interferometric SAR Coherence Models for Characterization of Hemiboreal Forests Using TanDEM-X Data
- (2016) Aire Olesk et al. Remote Sensing
- Improved Early Crop Type Identification By Joint Use of High Temporal Resolution SAR And Optical Image Time Series
- (2016) Jordi Inglada et al. Remote Sensing
- A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring
- (2016) Neha Joshi et al. Remote Sensing
- Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art
- (2016) Liangpei Zhang et al. IEEE Geoscience and Remote Sensing Magazine
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Early season monitoring of corn and soybeans with TerraSAR-X and RADARSAT-2
- (2014) H. McNairn et al. International Journal of Applied Earth Observation and Geoinformation
- Analysis of L-band SAR backscatter and coherence for delineation of land-use/land-cover
- (2014) N. Parihar et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Object-oriented crop mapping and monitoring using multi-temporal polarimetric RADARSAT-2 data
- (2014) Xianfeng Jiao et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Combined Use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring
- (2014) Pauline Dusseux et al. Remote Sensing
- Object-Based Fusion of Multitemporal Multiangle ENVISAT ASAR and HJ-1B Multispectral Data for Urban Land-Cover Mapping
- (2013) Yifang Ban et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Mapping deciduous rubber plantations through integration of PALSAR and multi-temporal Landsat imagery
- (2013) Jinwei Dong et al. REMOTE SENSING OF ENVIRONMENT
- Crop classification in rain-fed and irrigated agricultural areas using Landsat TM and ALOS/PALSAR data
- (2011) A. Larrañaga et al. CANADIAN JOURNAL OF REMOTE SENSING
- Crop Classification by Multitemporal C- and L-Band Single- and Dual-Polarization and Fully Polarimetric SAR
- (2011) Henning Skriver IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Crop classification using multi-configuration SAR data in the North China Plain
- (2011) Kun Jia et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Discrimination of agricultural crops in a tropical semi-arid region of Brazil based on L-band polarimetric airborne SAR data
- (2008) Wagner F. Silva et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started