116 related articles for article (PubMed ID: 29891814)
1. Partial Least Square Discriminant Analysis Based on Normalized Two-Stage Vegetation Indices for Mapping Damage from Rice Diseases Using PlanetScope Datasets.
Shi Y; Huang W; Ye H; Ruan C; Xing N; Geng Y; Dong Y; Peng D
Sensors (Basel); 2018 Jun; 18(6):. PubMed ID: 29891814
[TBL] [Abstract][Full Text] [Related]
2. Using satellite multispectral imagery for damage mapping of armyworm (Spodoptera frugiperda) in maize at a regional scale.
Zhang J; Huang Y; Yuan L; Yang G; Chen L; Zhao C
Pest Manag Sci; 2016 Feb; 72(2):335-48. PubMed ID: 25761201
[TBL] [Abstract][Full Text] [Related]
3. The Extraction Model of Paddy Rice Information Based on GF-1 Satellite WFV Images.
Yang YJ; Huang Y; Tian QJ; Wang L; Geng J; Yang RR
Guang Pu Xue Yu Guang Pu Fen Xi; 2015 Nov; 35(11):3255-61. PubMed ID: 26978945
[TBL] [Abstract][Full Text] [Related]
4. Spatial Analysis of Rice Blast in China at Three Different Scales.
Guo F; Chen X; Lu M; Yang L; Wang S; Wu BM
Phytopathology; 2018 Nov; 108(11):1276-1286. PubMed ID: 29787350
[TBL] [Abstract][Full Text] [Related]
5. Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images.
Wang J; Huang JF; Wang XZ; Jin MT; Zhou Z; Guo QY; Zhao ZW; Huang WJ; Zhang Y; Song XD
J Zhejiang Univ Sci B; 2015 Oct; 16(10):832-44. PubMed ID: 26465131
[TBL] [Abstract][Full Text] [Related]
6. Predicting grain protein content of field-grown winter wheat with satellite images and partial least square algorithm.
Tan C; Zhou X; Zhang P; Wang Z; Wang D; Guo W; Yun F
PLoS One; 2020; 15(3):e0228500. PubMed ID: 32160185
[TBL] [Abstract][Full Text] [Related]
7. Mapping plastic-covered greenhouse farming areas using high-resolution PlanetScope and RapidEye imagery: studies from Loukkos perimeter (Morocco) and Dalat City (Vietnam).
Acharki S; Kozhikkodan Veettil B
Environ Sci Pollut Res Int; 2023 Feb; 30(9):23012-23022. PubMed ID: 36308647
[TBL] [Abstract][Full Text] [Related]
8. Detection of rice sheath blight using an unmanned aerial system with high-resolution color and multispectral imaging.
Zhang D; Zhou X; Zhang J; Lan Y; Xu C; Liang D
PLoS One; 2018; 13(5):e0187470. PubMed ID: 29746473
[TBL] [Abstract][Full Text] [Related]
9. Identification of Rice Sheath Blight through Spectral Responses Using Hyperspectral Images.
Lin F; Guo S; Tan C; Zhou X; Zhang D
Sensors (Basel); 2020 Nov; 20(21):. PubMed ID: 33147714
[TBL] [Abstract][Full Text] [Related]
10. Integration of Radiometric Ground-Based Data and High-Resolution QuickBird Imagery with Multivariate Modeling to Estimate Maize Traits in the Nile Delta of Egypt.
Elmetwalli AH; Tyler AN; Moghanm FS; Alamri SAM; Eid EM; Elsayed S
Sensors (Basel); 2021 Jun; 21(11):. PubMed ID: 34204099
[TBL] [Abstract][Full Text] [Related]
11. Identifying rice stress on a regional scale from multi-temporal satellite images using a Bayesian method.
Liu M; Wang T; Skidmore AK; Liu X; Li M
Environ Pollut; 2019 Apr; 247():488-498. PubMed ID: 30703682
[TBL] [Abstract][Full Text] [Related]
12. Chlorophyll Fluorescence and Reflectance-Based Non-Invasive Quantification of Blast, Bacterial Blight and Drought Stresses in Rice.
Šebela D; Quiñones C; Cruz CV; Ona I; Olejnícková J; Jagadish KSV
Plant Cell Physiol; 2018 Jan; 59(1):30-43. PubMed ID: 29370434
[TBL] [Abstract][Full Text] [Related]
13. The germin-like protein OsGLP2-1 enhances resistance to fungal blast and bacterial blight in rice.
Liu Q; Yang J; Yan S; Zhang S; Zhao J; Wang W; Yang T; Wang X; Mao X; Dong J; Zhu X; Liu B
Plant Mol Biol; 2016 Nov; 92(4-5):411-423. PubMed ID: 27631432
[TBL] [Abstract][Full Text] [Related]
14. Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements.
Chavana-Bryant C; Malhi Y; Wu J; Asner GP; Anastasiou A; Enquist BJ; Cosio Caravasi EG; Doughty CE; Saleska SR; Martin RE; Gerard FF
New Phytol; 2017 May; 214(3):1049-1063. PubMed ID: 26877108
[TBL] [Abstract][Full Text] [Related]
15. Classification of Rice Heavy Metal Stress Levels Based on Phenological Characteristics Using Remote Sensing Time-Series Images and Data Mining Algorithms.
Liu T; Liu X; Liu M; Wu L
Sensors (Basel); 2018 Dec; 18(12):. PubMed ID: 30558149
[TBL] [Abstract][Full Text] [Related]
16. Application of remote sensors in mapping rice area and forecasting its production: a review.
Mosleh MK; Hassan QK; Chowdhury EH
Sensors (Basel); 2015 Jan; 15(1):769-91. PubMed ID: 25569753
[TBL] [Abstract][Full Text] [Related]
17. A hyper-temporal remote sensing protocol for high-resolution mapping of ecological sites.
Maynard JJ; Karl JW
PLoS One; 2017; 12(4):e0175201. PubMed ID: 28414731
[TBL] [Abstract][Full Text] [Related]
18. Assessing the Impact of Spatial Resolution on the Estimation of Leaf Nitrogen Concentration Over the Full Season of Paddy Rice Using Near-Surface Imaging Spectroscopy Data.
Zhou K; Cheng T; Zhu Y; Cao W; Ustin SL; Zheng H; Yao X; Tian Y
Front Plant Sci; 2018; 9():964. PubMed ID: 30026750
[TBL] [Abstract][Full Text] [Related]
19. Integrated Satellite, Unmanned Aerial Vehicle (UAV) and Ground Inversion of the SPAD of Winter Wheat in the Reviving Stage.
Zhang S; Zhao G; Lang K; Su B; Chen X; Xi X; Zhang H
Sensors (Basel); 2019 Mar; 19(7):. PubMed ID: 30934683
[TBL] [Abstract][Full Text] [Related]
20. A random forest model for the classification of wheat and rye leaf rust symptoms based on pure spectra at leaf scale.
Wójtowicz A; Piekarczyk J; Czernecki B; Ratajkiewicz H
J Photochem Photobiol B; 2021 Oct; 223():112278. PubMed ID: 34416475
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
