1 |
中华人民共和国国家统计局. 国家数据[EB/OL]. (2021-12-06)[2023-01-29] .
|
2 |
ISLAM M S, PENG S B, VISPERAS R M, et al. Lodging-related morphological traits of hybrid rice in a tropical irrigated ecosystem[J]. Field crops research, 2007, 101(2): 240-248.
|
3 |
BERRY P M, STERLING M, BAKER C J, et al. A calibrated model of wheat lodging compared with field measurements[J]. Agricultural and forest meteorology, 2003, 119(3/4): 167-180.
|
4 |
CHAUHAN S, DARVISHZADEH R, BOSCHETTI M, et al. Remote sensing-based crop lodging assessment: Current status and perspectives[J]. ISPRS journal of photogrammetry and remote sensing, 2019, 151: 124-140.
|
5 |
李宗南, 陈仲新, 任国业, 等. 基于Worldview-2影像的玉米倒伏面积估算[J]. 农业工程学报, 2016, 32(2): 1-5.
|
|
LI Z N, CHEN Z X, REN G Y, et al. Estimation of maize lodging area based on Worldview-2 image[J]. Transactions of the Chinese society of agricultural engineering, 2016, 32(2): 1-5.
|
6 |
晏磊, 廖小罕, 周成虎, 等. 中国无人机遥感技术突破与产业发展综述[J]. 地球信息科学学报, 2019, 21(4): 476-495.
|
|
YAN L, LIAO X H, ZHOU C H, et al. The impact of UAV remote sensing technology on the industrial development of China: A review[J]. Journal of geo-information science, 2019, 21(4): 476-495.
|
7 |
TIAN M L, BAN S T, YUAN T, et al. Assessing rice lodging using UAV visible and multispectral image[J]. International journal of remote sensing, 2021, 42(23): 8840-8857.
|
8 |
赵静, 潘方江, 兰玉彬, 等. 无人机可见光遥感和特征融合的小麦倒伏面积提取[J]. 农业工程学报, 2021, 37(3): 73-80.
|
|
ZHAO J, PAN F J, LAN Y B, et al. Wheat lodging area extraction using UAV visible light remote sensing and feature fusion[J]. Transactions of the Chinese society of agricultural engineering, 2021, 37(3): 73-80.
|
9 |
SUN Q, SUN L, SHU M Y, et al. Monitoring maize lodging grades via unmanned aerial vehicle multispectral image[J]. Plant phenomics, 2019, 2019: ID 5704154.
|
10 |
FLORES P, 张昭. 基于无人机图像以及不同机器学习和深度学习模型的小麦倒伏率检测[J]. 智慧农业(中英文), 2021, 3(2): 23-34.
|
|
FLORES P, ZHANG Z. Wheat lodging ratio detection based on UAS imagery coupled with different machine learning and deep learning algorithms[J]. Smart agriculture, 2021, 3(2): 23-34.
|
11 |
黄艳伟, 朱红雷, 郭宁戈, 等. 基于无人机多光谱影像的冬小麦倒伏提取适宜空间分辨率研究[J]. 麦类作物学报, 2021, 41(2): 254-261.
|
|
HUANG Y W, ZHU H L, GUO N G, et al. Study on the suitable resolution of winter wheat lodging extraction based on UAV multispectral image[J]. Journal of triticeae crops, 2021, 41(2): 254-261.
|
12 |
YU J, CHENG T, CAI N, et al. Wheat lodging extraction using Improved_Unet network[J]. Frontiers in plant science, 2022, 13: ID 1009835.
|
13 |
GUYON I, ELISSEEFF A. An introduction to variable and feature selection[J]. Journal of machine learning research, 2003, 3: 1157-1182.
|
14 |
CHAUHAN S, DARVISHZADEH R, BOSCHETTI M, et al. Discriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data[J]. ISPRS journal of photogrammetry and remote sensing, 2020, 164: 138-151.
|
15 |
INOUE Y, SAKAIYA E, ZHU Y, et al. Diagnostic mapping of canopy nitrogen content in rice based on hyperspectral measurements[J]. Remote sensing of environment, 2012, 126: 210-221.
|
16 |
HUNT E R, DAUGHTRY C S T, EITEL J U H, et al. Remote sensing leaf chlorophyll content using a visible band index[J]. Agronomy journal, 2011, 103(4): 1090-1099.
|
17 |
AHAMED T, TIAN L, ZHANG Y, et al. A review of remote sensing methods for biomass feedstock production[J]. Biomass and bioenergy, 2011, 35(7): 2455-2469.
|
18 |
S S K P, S D V. Extraction of texture features using GLCM and shape features using connected regions[J]. International journal of engineering and technology, 2016, 8(6): 2926-2930.
|
19 |
支俊俊, 董娅, 鲁李灿, 等. 基于无人机RGB影像的玉米种植信息高精度提取方法[J]. 农业工程学报, 2021, 37(18): 48-54.
|
|
ZHI J J, DONG Y, LU L C, et al. High-precision extraction method for maize planting information based on UAV RGB images[J]. Transactions of the Chinese society of agricultural engineering, 2021, 37(18): 48-54.
|
20 |
AGJEE N H, ISMAIL R, MUTANGA O. Identifying relevant hyperspectral bands using Boruta: A temporal analysis of water hyacinth biocontrol[J]. Journal of applied remote sensing, 2016, 10(4): ID 042002.
|
21 |
GHOSH I, CHAUDHURI T D. Integrating Navier-Stokes equation and neoteric iForest-BorutaShap-Facebook's prophet framework for stock market prediction: An application in Indian context[J]. Expert systems with applications, 2022, 210: ID 118391.
|
22 |
王吉川, 刘艺. 特征选择稳定性方法研究[J]. 数字技术与应用, 2021, 39(9): 19-21.
|
|
WANG J C, LIU Y. Research on methods for feature selection stability[J]. Digital technology & application, 2021, 39(9): 19-21.
|
23 |
崔鸿雁, 徐帅, 张利锋, 等. 机器学习中的特征选择方法研究及展望[J]. 北京邮电大学学报, 2018, 41(1): 1-12.
|
|
CUI H Y, XU S, ZHANG L F, et al. The key techniques and future vision of feature selection in machine learning[J]. Journal of Beijing university of posts and telecommunications, 2018, 41(1): 1-12.
|
24 |
尚志刚, 董永慧, 李蒙蒙, 等. 基于偏最小二乘回归的鲁棒性特征选择与分类算法[J]. 计算机应用, 2017, 37(3): 871-875.
|
|
SHANG Z G, DONG Y H, LI M M, et al. Robust feature selection and classification algorithm based on partial least squares regression[J]. Journal of computer applications, 2017, 37(3): 871-875.
|
25 |
刘艺, 曹建军, 刁兴春, 等. 特征选择稳定性研究综述[J]. 软件学报, 2018, 29(9): 2559-2579.
|
|
LIU Y, CAO J J, DIAO X C, et al. Survey on stability of feature selection[J]. Journal of software, 2018, 29(9): 2559-2579.
|
26 |
周小成, 郑磊, 黄洪宇. 基于多特征优选的无人机可见光遥感林分类型分类[J]. 林业科学, 2021, 57(6): 24-36.
|
|
ZHOU X C, ZHENG L, HUANG H Y. Classification of forest stand based on multi-feature optimization of UAV visible light remote sensing[J]. Scientia silvae sinicae, 2021, 57(6): 24-36.
|
27 |
刘良云, 王纪华, 宋晓宇, 等. 小麦倒伏的光谱特征及遥感监测[J]. 遥感学报, 2005, 9(3): 323-327.
|
|
LIU L Y, WANG J H, SONG X Y, et al. The canopy spectral features and remote sensing of wheat lodging[J]. Journal of remote sensing, 2005, 9(3): 323-327.
|
28 |
李广, 张立元, 宋朝阳, 等. 小麦倒伏信息无人机多时相遥感提取方法[J]. 农业机械学报, 2019, 50(4): 211-220.
|
|
LI G, ZHANG L Y, SONG C Y, et al. Extraction method of wheat lodging information based on multi-temporal UAV remote sensing data[J]. Transactions of the Chinese society for agricultural machinery, 2019, 50(4): 211-220.
|