Relevant bibliographies by topics / Leaf reflectance modeling

Journal articles
Dissertations / Theses
Book chapters
Conference papers

Academic literature on the topic 'Leaf reflectance modeling'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Leaf reflectance modeling.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Leaf reflectance modeling"

Hu, Hao, Guangzhi Zhang, and Kefeng Zheng. "Modeling Leaf Image, Chlorophyll Fluorescence, Reflectance From SPAD Readings." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7, no. 11 (2014): 4368–73. http://dx.doi.org/10.1109/jstars.2014.2325812.

Full text

APA, Harvard, Vancouver, ISO, and other styles

HOUBORG, R., and E. BOEGH. "Mapping leaf chlorophyll and leaf area index using inverse and forward canopy reflectance modeling and SPOT reflectance data." Remote Sensing of Environment 112, no. 1 (2008): 186–202. http://dx.doi.org/10.1016/j.rse.2007.04.012.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Bhadra, Sourav, Vasit Sagan, Maitiniyazi Maimaitijiang, et al. "Quantifying Leaf Chlorophyll Concentration of Sorghum from Hyperspectral Data Using Derivative Calculus and Machine Learning." Remote Sensing 12, no. 13 (2020): 2082. http://dx.doi.org/10.3390/rs12132082.

Full text

Abstract:

Leaf chlorophyll concentration (LCC) is an important indicator of plant health, vigor, physiological status, productivity, and nutrient deficiencies. Hyperspectral spectroscopy at leaf level has been widely used to estimate LCC accurately and non-destructively. This study utilized leaf-level hyperspectral data with derivative calculus and machine learning to estimate LCC of sorghum. We calculated fractional derivative (FD) orders starting from 0.2 to 2.0 with 0.2 order increments. Additionally, 43 common vegetation indices (VIs) were calculated from leaf spectral reflectance factor to make com

APA, Harvard, Vancouver, ISO, and other styles

Dawson, Terence P., Paul J. Curran, and Stephen E. Plummer. "LIBERTY—Modeling the Effects of Leaf Biochemical Concentration on Reflectance Spectra." Remote Sensing of Environment 65, no. 1 (1998): 50–60. http://dx.doi.org/10.1016/s0034-4257(98)00007-8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Ebengo, Dav M., Florian de Boissieu, Grégoire Vincent, Christiane Weber, and Jean-Baptiste Féret. "Simulating Imaging Spectroscopy in Tropical Forest with 3D Radiative Transfer Modeling." Remote Sensing 13, no. 11 (2021): 2120. http://dx.doi.org/10.3390/rs13112120.

Full text

Abstract:

Optical remote sensing can contribute to biodiversity monitoring and species composition mapping in tropical forests. Inferring ecological information from canopy reflectance is complex and data availability suitable to such a task is limiting, which makes simulation tools particularly important in this context. We explored the capability of the 3D radiative transfer model DART (Discrete Anisotropic Radiative Transfer) to simulate top of canopy reflectance acquired with airborne imaging spectroscopy in a complex tropical forest, and to reproduce spectral dissimilarity within and among species,

APA, Harvard, Vancouver, ISO, and other styles

Temizel, Kadir, Mehmet Odabas, Nurettin Senyer, et al. "Comparision of some models for estimation of reflectance of hypericum leaves under stress conditions." Open Life Sciences 9, no. 12 (2014): 1226–34. http://dx.doi.org/10.2478/s11535-014-0356-4.

Full text

Abstract:

AbstractLack of water resources and high water salinity levels are among the most important growth-restricting factors for plants species of the world. This research investigates the effect of irrigation levels and salinity on reflectance of Saint John’s wort leaves (Hypericum perforatum L.) under stress conditions (water and salt stress) by multiple linear regression (MLR), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). Empirical and heuristics modeling methods were employed in this study to relate stress conditions to leaf reflectance. It was found that th

APA, Harvard, Vancouver, ISO, and other styles

Lu, Bu, and Lu. "Estimating Chlorophyll Content of Leafy Green Vegetables from Adaxial and Abaxial Reflectance." Sensors 19, no. 19 (2019): 4059. http://dx.doi.org/10.3390/s19194059.

Full text

Abstract:

As a primary pigment of leafy green vegetables, chlorophyll plays a major role in indicating vegetable growth status. The application of hyperspectral remote sensing reflectance offers a quick and nondestructive method to estimate the chlorophyll content of vegetables. Reflectance of adaxial and abaxial leaf surfaces from three common leafy green vegetables: Pakchoi var. Shanghai Qing (Brassica chinensis L. var. Shanghai Qing), Chinese white cabbage (Brassica campestris L. ssp. Chinensis Makino var. communis Tsen et Lee), and Romaine lettuce (Lactuca sativa var longifoliaf. Lam) were measured

APA, Harvard, Vancouver, ISO, and other styles

Yin, Tiangang, Jianbo Qi, Bruce D. Cook, Douglas C. Morton, Shanshan Wei, and Jean-Philippe Gastellu-Etchegorry. "Modeling Small-Footprint Airborne Lidar-Derived Estimates of Gap Probability and Leaf Area Index." Remote Sensing 12, no. 1 (2019): 4. http://dx.doi.org/10.3390/rs12010004.

Full text

Abstract:

Airborne lidar point clouds of vegetation capture the 3-D distribution of its scattering elements, including leaves, branches, and ground features. Assessing the contribution from vegetation to the lidar point clouds requires an understanding of the physical interactions between the emitted laser pulses and their targets. Most of the current methods to estimate the gap probability ( P gap ) or leaf area index (LAI) from small-footprint airborne laser scan (ALS) point clouds rely on either point-number-based (PNB) or intensity-based (IB) approaches, with additional empirical correlations with f

APA, Harvard, Vancouver, ISO, and other styles

Wang, Ce, Xiuhua Li, Lijia Wang, et al. "Prediction of N, P, and K Contents in Sugarcane Leaves by VIS-NIR Spectroscopy and Modeling of NPK Interaction Effects." Transactions of the ASABE 62, no. 6 (2019): 1427–33. http://dx.doi.org/10.13031/trans.13086.

Full text

Abstract:

Abstract. Methods were studied to predict the N, P, and K contents in sugarcane leaves quickly and accurately at the seedling, tillering, and elongation stages from leaf spectral reflectance. A total of 117 valid leaf samples were used to obtain leaf spectral reflectance with an indoor VIS-NIR spectrophotometer. Using the spectral data processed by CARS-PCA as an independent variable, a six-fold cross-validated PLS model for N, P, and K contents was established. The R2 values of the CARS-PCA-PLS models for N, P, and K prediction were 0.859, 0.677, and 0.932, respectively. Correlation analysis

APA, Harvard, Vancouver, ISO, and other styles

Hikosaka, Kouki, and Hibiki M. Noda. "Modeling leaf CO2 assimilation and Photosystem II photochemistry from chlorophyll fluorescence and the photochemical reflectance index." Plant, Cell & Environment 42, no. 2 (2018): 730–39. http://dx.doi.org/10.1111/pce.13461.

Full text

APA, Harvard, Vancouver, ISO, and other styles

More sources

Dissertations / Theses on the topic "Leaf reflectance modeling"

Yang, Yang. "Non-contacting techniques for detecting plant drought stress in a closed environment." Connect to this title online, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1068499233.

Full text

Abstract:

Thesis (Ph. D.)--Ohio State University, 2003.<br>Title from first page of PDF file. Document formatted into pages; contains xx, 245 p.; also includes graphics. Includes bibliographical references (p. 206-216).

APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Leaf reflectance modeling"

Xiao, Chun-Hua, Shao-Kun Li, Ke-Ru Wang, et al. "The Response of Canopy Direction Reflectance Spectrum for the Wheat Vertical Leaf Distributing." In Crop Modeling and Decision Support. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01132-0_9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Benabdelouahab, Tarik, Hayat Lionboui, Rachid Hadria, Riad Balaghi, Abdelghani Boudhar, and Bernard Tychon. "Support Irrigation Water Management of Cereals Using Optical Remote Sensing and Modeling in a Semi-Arid Region." In Geospatial Technologies for Effective Land Governance. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5939-9.ch008.

Full text

Abstract:

Irrigated agriculture is an important strategic sector for Morocco, contributing to food security and employment. Nowadays, irrigation scheme managers shall ensure that water is optimally used. The main objective was to support the irrigation monitoring and management of wheat in the irrigated perimeter using optical remote sensing and crop modeling. The potential of spectral indices derived from SPOT-5 images was explored for quantifying and mapping surface water content changes at large scale. Indices were computed using the reflectance in red, near infrared, and shortwave infrared bands. A field crop model (AquaCrop) was adjusted and tested to simulate the grain yield and the temporal evolution of soil moisture status. This research aimed at providing a scientific and technical approach to assist policymakers and stakeholders to improve monitoring irrigation and mitigating wheat water stress at field and irrigation perimeter levels in semi-arid areas. The approach could lead to operational management tools for an efficient irrigation at field and regional levels.

APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Leaf reflectance modeling"

Shahrimie, M. A. Mohd, Puneet Mishra, Stien Mertens, Stijn Dhondt, Nathalie Wuyts, and Paul Scheunders. "Modeling effects of illumination and plant geometry on leaf reflectance spectra in close-range hyperspectral imaging." In 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2016. http://dx.doi.org/10.1109/whispers.2016.8071753.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Houborg, Rasmus, and Martha C. Anderson. "Utility of an Image-Based Canopy Reflectance Modeling Tool for Remote Estimation of LAI and Leaf Chlorophyll Content in Crop Systems." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4778947.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Lange, H., and S. Solberg. "Leaf Area Index Estimation using Lidar and Forest Reflectance Modelling of Airborne Hyperspectral Data." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4779387.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!