188 related articles for article (PubMed ID: 26571671)
1. [Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].
Wang C; Du HQ; Zhou GM; Xu XJ; Sun SB; Gao GL
Ying Yong Sheng Tai Xue Bao; 2015 May; 26(5):1501-9. PubMed ID: 26571671
[TBL] [Abstract][Full Text] [Related]
2. [Retrieval of leaf net photosynthetic rate of moso bamboo forests using hyperspectral remote sen-sing based on wavelet transform].
Sun SB; Du HQ; Li PH; Zhou GM; Xu XJ; Gao GL; Li XJ
Ying Yong Sheng Tai Xue Bao; 2016 Jan; 27(1):49-58. PubMed ID: 27228592
[TBL] [Abstract][Full Text] [Related]
3. [Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].
Gao L; Li CC; Wang BS; Yang Gui-jun ; Wang L; Fu K
Ying Yong Sheng Tai Xue Bao; 2016 Jan; 27(1):191-200. PubMed ID: 27228609
[TBL] [Abstract][Full Text] [Related]
4. Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system.
Michez A; Piégay H; Lisein J; Claessens H; Lejeune P
Environ Monit Assess; 2016 Mar; 188(3):146. PubMed ID: 26850712
[TBL] [Abstract][Full Text] [Related]
5. [Fractional vegetation cover of invasive Spartina alterniflora in coastal wetland using unmanned aerial vehicle (UAV)remote sensing].
Zhou ZM; Yang YM; Chen BQ
Ying Yong Sheng Tai Xue Bao; 2016 Dec; 27(12):3920-3926. PubMed ID: 29704351
[TBL] [Abstract][Full Text] [Related]
6. [Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].
Yan EP; Lin H; Wang GX; Chen ZX
Ying Yong Sheng Tai Xue Bao; 2015 Nov; 26(11):3433-42. PubMed ID: 26915200
[TBL] [Abstract][Full Text] [Related]
7. The Feasibility of Modelling the Crown Profile of
Quan Y; Li M; Zhen Z; Hao Y; Wang B
Sensors (Basel); 2020 Sep; 20(19):. PubMed ID: 32998340
[TBL] [Abstract][Full Text] [Related]
8. Scots pine stands biomass assessment using 3D data from unmanned aerial vehicle imagery in the Chernobyl Exclusion Zone.
Holiaka D; Kato H; Yoschenko V; Onda Y; Igarashi Y; Nanba K; Diachuk P; Holiaka M; Zadorozhniuk R; Kashparov V; Chyzhevskyi I
J Environ Manage; 2021 Oct; 295():113319. PubMed ID: 34348433
[TBL] [Abstract][Full Text] [Related]
9. [RS estimation of inventory parameters and carbon storage of moso bamboo forest based on synergistic use of object-based image analysis and decision tree].
Du HQ; Sun XY; Han N; Mao FJ
Ying Yong Sheng Tai Xue Bao; 2017 Oct; 28(10):3163-3173. PubMed ID: 29692133
[TBL] [Abstract][Full Text] [Related]
10. [Retrieval of leaf area index of moso bamboo forest with Landsat Thematic Mapper image based on PROSAIL canopy radiative transfer model].
Gu CY; Du HQ; Zhou GM; Han N; Xu XJ; Zhao X; Sun XY
Ying Yong Sheng Tai Xue Bao; 2013 Aug; 24(8):2248-56. PubMed ID: 24380345
[TBL] [Abstract][Full Text] [Related]
11. Remote Estimation of Rice Yield With Unmanned Aerial Vehicle (UAV) Data and Spectral Mixture Analysis.
Duan B; Fang S; Zhu R; Wu X; Wang S; Gong Y; Peng Y
Front Plant Sci; 2019; 10():204. PubMed ID: 30873194
[TBL] [Abstract][Full Text] [Related]
12. Unmanned Aerial Vehicle to Estimate Nitrogen Status of Turfgrasses.
Caturegli L; Corniglia M; Gaetani M; Grossi N; Magni S; Migliazzi M; Angelini L; Mazzoncini M; Silvestri N; Fontanelli M; Raffaelli M; Peruzzi A; Volterrani M
PLoS One; 2016; 11(6):e0158268. PubMed ID: 27341674
[TBL] [Abstract][Full Text] [Related]
13. Estimation of Rice Aboveground Biomass by Combining Canopy Spectral Reflectance and Unmanned Aerial Vehicle-Based Red Green Blue Imagery Data.
Wang Z; Ma Y; Chen P; Yang Y; Fu H; Yang F; Raza MA; Guo C; Shu C; Sun Y; Yang Z; Chen Z; Ma J
Front Plant Sci; 2022; 13():903643. PubMed ID: 35712565
[TBL] [Abstract][Full Text] [Related]
14. Detection of the power lines in UAV remote sensed images using spectral-spatial methods.
Bhola R; Krishna NH; Ramesh KN; Senthilnath J; Anand G
J Environ Manage; 2018 Jan; 206():1233-1242. PubMed ID: 28931461
[TBL] [Abstract][Full Text] [Related]
15. Carbon stock of Moso bamboo (Phyllostachys pubescens) forests along a latitude gradient in the subtropical region of China.
Xu M; Ji H; Zhuang S
PLoS One; 2018; 13(2):e0193024. PubMed ID: 29451911
[TBL] [Abstract][Full Text] [Related]
16. Wheat leaf area index prediction using data fusion based on high-resolution unmanned aerial vehicle imagery.
Wu S; Deng L; Guo L; Wu Y
Plant Methods; 2022 May; 18(1):68. PubMed ID: 35590377
[TBL] [Abstract][Full Text] [Related]
17. A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery.
Huang H; Deng J; Lan Y; Yang A; Deng X; Zhang L
PLoS One; 2018; 13(4):e0196302. PubMed ID: 29698500
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. UAV-Based Digital Terrain Model Generation under Leaf-Off Conditions to Support Teak Plantations Inventories in Tropical Dry Forests. A Case of the Coastal Region of Ecuador.
Aguilar FJ; Rivas JR; Nemmaoui A; Peñalver A; Aguilar MA
Sensors (Basel); 2019 Apr; 19(8):. PubMed ID: 31027155
[TBL] [Abstract][Full Text] [Related]
20. Monitoring the invasion of Spartina alterniflora using very high resolution unmanned aerial vehicle imagery in Beihai, Guangxi (China).
Wan H; Wang Q; Jiang D; Fu J; Yang Y; Liu X
ScientificWorldJournal; 2014; 2014():638296. PubMed ID: 24892066
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
