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。Crop type mapping in the central part of the North China Plain using Sentinel-2 time series and machine learning
Ke Luo et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2023)
Crop type identification and spatial mapping using Sentinel-2 satellite data with focus on field-level information
Murali Krishna Gumma et al.
GEOCARTO INTERNATIONAL (2022)
Crop-type mapping and acreage estimation in smallholding plots using Sentinel-2 images and machine learning algorithms: Some comparisons
Manas Hudait et al.
EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES (2022)
An Adaptive Image Segmentation Method with Automatic Selection of Optimal Scale for Extracting Cropland Parcels in Smallholder Farming Systems
Zhiwen Cai et al.
REMOTE SENSING (2022)
Crop type mapping using time-series Sentinel-2 imagery and U-Net in early growth periods in the Hetao irrigation district in China
Guang Li et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2022)
National-Scale Cropland Mapping Based on Phenological Metrics, Environmental Covariates, and Machine Learning on Google Earth Engine
Abdelaziz Htitiou et al.
REMOTE SENSING (2021)
Pre-harvest classification of crop types using a Sentinel-2 time-series and machine learning
Mmamokoma Grace Maponya et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2020)
Assessing the Accuracy of Multiple Classification Algorithms for Crop Classification Using Landsat-8 and Sentinel-2 Data
Amal Chakhar et al.
REMOTE SENSING (2020)
A novel method for automatic potato mapping using time series of Sentinel-2 images
Davoud Ashourloo et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2020)
Early-season crop type mapping using 30-m reference time series
Hao Peng-yu et al.
JOURNAL OF INTEGRATIVE AGRICULTURE (2020)
Automatic High-Resolution Land Cover Production in Madagascar Using Sentinel-2 Time Series, Tile-Based Image Classification and Google Earth Engine
Meinan Zhang et al.
REMOTE SENSING (2020)
Improved Mapping Results of 10 m Resolution Land Cover Classification in Guangdong, China Using Multisource Remote Sensing Data With Google Earth Engine
Ying Tu et al.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2020)
A comparison of object-based image analysis approaches for field boundary delineation using multi-temporal Sentinel-2 imagery
Barry Watkins et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2019)
Feature Comparison and Optimization for 30-M Winter Wheat Mapping Based on Landsat-8 and Sentinel-2 Data Using Random Forest Algorithm
Yuanhuizi He et al.
REMOTE SENSING (2019)
Using of Multi-Source and Multi-Temporal Remote Sensing Data Improves Crop-Type Mapping in the Subtropical Agriculture Region
Chuanliang Sun et al.
SENSORS (2019)
Crop Type Identification and Mapping Using Machine Learning Algorithms and Sentinel-2 Time Series Data
Siwen Feng et al.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2019)
Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis
Mariana Belgiu et al.
REMOTE SENSING OF ENVIRONMENT (2018)
Estimating smallholder crops production at village level from Sentinel-2 time series in Mali's cotton belt
Marie-Julie Lambert et al.
REMOTE SENSING OF ENVIRONMENT (2018)
Early identification of cotton fields using mosaicked aerial multispectral imagery
Chenghai Yang et al.
JOURNAL OF APPLIED REMOTE SENSING (2017)
Google Earth Engine: Planetary-scale geospatial analysis for everyone
Noel Gorelick et al.
REMOTE SENSING OF ENVIRONMENT (2017)
Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine
Jun Xiong et al.
REMOTE SENSING (2017)
Object-Based Image Classification of Summer Crops with Machine Learning Methods
Jose M. Pena et al.
REMOTE SENSING (2014)
Impact of feature selection on the accuracy and spatial uncertainty of per-field crop classification using Support Vector Machines
F. Loew et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2013)
Evaluation of random forest method for agricultural crop classification
Asli Ozdarici Ok et al.
EUROPEAN JOURNAL OF REMOTE SENSING (2012)
Field-based crop classification using SPOT4, SPOT5, IKONOS and QuickBird imagery for agricultural areas: a comparison study
Mustafa Turker et al.
INTERNATIONAL JOURNAL OF REMOTE SENSING (2011)
Per-Field Irrigated Crop Classification in Arid Central Asia Using SPOT and ASTER Data
Christopher Conrad et al.
REMOTE SENSING (2010)
Efficiency and accuracy of per-field classification for operational crop mapping
AJW De Wit et al.
INTERNATIONAL JOURNAL OF REMOTE SENSING (2004)
Crop discrimination with multitemporal SPOT/HRV data in the Saga Plains, Japan
T Murakami et al.
INTERNATIONAL JOURNAL OF REMOTE SENSING (2001)
Land cover mapping in an agricultural setting using multiseasonal Thematic Mapper data
DR Oetter et al.
REMOTE SENSING OF ENVIRONMENT (2001)
分享论文
