150 related articles for article (PubMed ID: 32765638)
1. THEMS: an automated thermal and hyperspectral proximal sensing system for canopy reflectance, radiance and temperature.
Woodgate W; van Gorsel E; Hughes D; Suarez L; Jimenez-Berni J; Held A
Plant Methods; 2020; 16():105. PubMed ID: 32765638
[TBL] [Abstract][Full Text] [Related]
2. Plant ecophysiological processes in spectral profiles: perspective from a deciduous broadleaf forest.
Noda HM; Muraoka H; Nasahara KN
J Plant Res; 2021 Jul; 134(4):737-751. PubMed ID: 33970379
[TBL] [Abstract][Full Text] [Related]
3. Mapping multi-scale vascular plant richness in a forest landscape with integrated LiDAR and hyperspectral remote-sensing.
Hakkenberg CR; Zhu K; Peet RK; Song C
Ecology; 2018 Feb; 99(2):474-487. PubMed ID: 29231965
[TBL] [Abstract][Full Text] [Related]
4. Multi-scale datasets for monitoring Mediterranean oak forests from optical remote sensing during the SENTHYMED/MEDOAK experiment in the north of Montpellier (France).
Adeline K; Féret JB; Clenet H; Limousin JM; Ourcival JM; Mouillot F; Alleaume S; Jolivot A; Briottet X; Bidel L; Aria E; Defossez A; Gaubert T; Giffard-Carlet J; Kempf J; Longepierre D; Lopez F; Miraglio T; Vigouroux J; Debue M
Data Brief; 2024 Apr; 53():110185. PubMed ID: 38406250
[TBL] [Abstract][Full Text] [Related]
5. EcoSpec: Highly Equipped Tower-Based Hyperspectral and Thermal Infrared Automatic Remote Sensing System for Investigating Plant Responses to Environmental Changes.
Hamada Y; Cook D; Bales D
Sensors (Basel); 2020 Sep; 20(19):. PubMed ID: 32977652
[TBL] [Abstract][Full Text] [Related]
6. Scaling photosynthetic function and CO
Campbell P; Middleton E; Huemmrich K; Ward L; Julitta T; Yang P; van der Tol C; Daughtry C; Russ A; Alfieri J; Kustas W
Data Brief; 2021 Dec; 39():107600. PubMed ID: 34901341
[TBL] [Abstract][Full Text] [Related]
7. Forest floor temperature and greenness link significantly to canopy attributes in South Africa's fragmented coastal forests.
Pfeifer M; Boyle MJW; Dunning S; Olivier PI
PeerJ; 2019; 7():e6190. PubMed ID: 30648017
[TBL] [Abstract][Full Text] [Related]
8. A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.
Lausch A; Pause M; Merbach I; Zacharias S; Doktor D; Volk M; Seppelt R
Environ Monit Assess; 2013 Feb; 185(2):1215-35. PubMed ID: 22527462
[TBL] [Abstract][Full Text] [Related]
9. Assessment and statistical modeling of the relationship between remotely sensed aerosol optical depth and PM2.5 in the eastern United States.
Paciorek CJ; Liu Y;
Res Rep Health Eff Inst; 2012 May; (167):5-83; discussion 85-91. PubMed ID: 22838153
[TBL] [Abstract][Full Text] [Related]
10. In-situ and airborne hyperspectral data for detecting agricultural activities in a dense forest landscape.
Rajesh CB; Kumar CVSSM; Jha SS; Ramachandran KI; Nidamanuri RR
Data Brief; 2023 Oct; 50():109510. PubMed ID: 37663764
[TBL] [Abstract][Full Text] [Related]
11. Tracking plant physiological properties from multi-angular tower-based remote sensing.
Hilker T; Gitelson A; Coops NC; Hall FG; Black TA
Oecologia; 2011 Apr; 165(4):865-76. PubMed ID: 21221647
[TBL] [Abstract][Full Text] [Related]
12. TSWIFT: Tower Spectrometer on Wheels for Investigating Frequent Timeseries for high-throughput phenotyping of vegetation physiology.
Wong CYS; Jones T; McHugh DP; Gilbert ME; Gepts P; Palkovic A; Buckley TN; Magney TS
Plant Methods; 2023 Mar; 19(1):29. PubMed ID: 36978119
[TBL] [Abstract][Full Text] [Related]
13. Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product.
Wang Z; Schaaf CB; Sun Q; Kim J; Erb AM; Gao F; Román MO; Yang Y; Petroy S; Taylor JR; Masek JG; Morisette JT; Zhang X; Papuga SA
Int J Appl Earth Obs Geoinf; 2017 Jul; 59():104-117. PubMed ID: 33154713
[TBL] [Abstract][Full Text] [Related]
14. MSGF-GLP: fusion method of visible and hyperspectral data for early detection of discolored standing trees.
Zhou H; Wu Y; Wang W; Song J; Liu G; Shi J; Sun H
Front Plant Sci; 2023; 14():1280445. PubMed ID: 38078083
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. [An Analysis of the Spectrums between Different Canopy Structures Based on Hyperion Hyperspectral Data in a Temperate Forest of Northeast China].
Yu QZ; Wang SQ; Huang K; Zhou L; Chen DC
Guang Pu Xue Yu Guang Pu Fen Xi; 2015 Jul; 35(7):1980-5. PubMed ID: 26717763
[TBL] [Abstract][Full Text] [Related]
17. Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery.
Zarco-Tejada PJ; Hornero A; Hernández-Clemente R; Beck PSA
ISPRS J Photogramm Remote Sens; 2018 Mar; 137():134-148. PubMed ID: 29551855
[TBL] [Abstract][Full Text] [Related]
18. Hyperspectral remote sensing of foliar nitrogen content.
Knyazikhin Y; Schull MA; Stenberg P; Mõttus M; Rautiainen M; Yang Y; Marshak A; Latorre Carmona P; Kaufmann RK; Lewis P; Disney MI; Vanderbilt V; Davis AB; Baret F; Jacquemoud S; Lyapustin A; Myneni RB
Proc Natl Acad Sci U S A; 2013 Jan; 110(3):E185-92. PubMed ID: 23213258
[TBL] [Abstract][Full Text] [Related]
19. WhiteRef: a new tower-based hyperspectral system for continuous reflectance measurements.
Sakowska K; Gianelle D; Zaldei A; MacArthur A; Carotenuto F; Miglietta F; Zampedri R; Cavagna M; Vescovo L
Sensors (Basel); 2015 Jan; 15(1):1088-105. PubMed ID: 25580905
[TBL] [Abstract][Full Text] [Related]
20. Leaf traits and canopy structure together explain canopy functional diversity: an airborne remote sensing approach.
Kamoske AG; Dahlin KM; Serbin SP; Stark SC
Ecol Appl; 2021 Mar; 31(2):e02230. PubMed ID: 33015908
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
