Proceedings Article10.1109/WHISPERS.2015.8075503
An analysis of shadow effects on spectral vegetation indices using a ground-based imaging spectrometer
Taixia Wu,Lifu Zhang,Changping Huang +2 more
- 02 Jun 2015
- pp 1-4
5
TL;DR: To investigate the effects of shadows on different indices, 14 hyperspectral vegetation indices were calculated and the results show that shadows affect not only each narrow band of a vegetation index, but also vegetation parameters.
read more
Abstract: Sunlit vegetation and shaded vegetation are inseparable parts of remote sensing images. Shadows can lead to either a reduction or total loss of information in an image. This can potentially lead to corruption of biophysical parameters derived from pixels values, such as vegetation indices. One of the major reasons that the effects of shadows easy to be ignored in remote sensing is the spatial resolution of the measurement. High spatial resolution and spectral resolution are typically difficult to achieve simultaneously, and images that have one tend not to have the other. A ground-based imaging spectrometer brings a turning point to solve this problem, as it can obtain both high spatial and high spectral resolutions to obtain feature and shadow images simultaneously. The spectral curve of the image was almost a pure pixel spectral curve, which allowed the differentiation of sunlit and shaded areas. To investigate the effects of shadows on different indices, 14 hyperspectral vegetation indices were calculated. The results show that shadows affect not only each narrow band of a vegetation index, but also vegetation parameters.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Potential of using spectral vegetation indices for corn green biomass estimation based on their relationship with the photosynthetic vegetation sub-pixel fraction
Luan Peroni Venancio,Everardo Chartuni Mantovani,Cibele Hummel do Amaral,Christopher M. U. Neale,Ivo Zution Gonçalves,Roberto Filgueiras,Fernando Coelho Eugenio +6 more
TL;DR: In this paper, the potential capacity of spectral vegetation indices in estimating corn green biomass based on their relationship with the photosynthetic vegetation sub-pixel fraction derived from spectral mixture analysis was analyzed.
34
An Empirical Approach on Shadow Reduction of UAV Imagery in Forests
Xavier Pons,Joan-Cristian Padró +1 more
- 01 Jul 2019
TL;DR: A method to reduce the effects of the shadows and to recover information based on in-situ spectral reflectance measurements is presented, which can be very useful in forested areas sensed by drones.
10
An Operational Radiometric Correction Technique for Shadow Reduction in Multispectral UAV Imagery
Xavier Pons,Joan-Cristian Padró +1 more
TL;DR: In this article, the spectral reflectance of a given surface is used to distinguish between shadowed and non-shadowed areas by using a twin set of spectrally characterized target sets, and then a smoothing filter was applied to the penumbra transitions.
8
Survey on ML Investment in UAV Based Cellular Network
Mustafa Abbas Shober,P. R. Twil +1 more
- 20 Mar 2023
TL;DR: Survey on ML Investment in UAV Based Cellular Network focuses on the use of ML to solve problems arising from the integration of UAVs into cellular networks. The survey aims to highlight the use of AI/ML in each method and identify the most promising approach for the UAV to reach the desired results.
Transforming unmanned aerial vehicle (UAV) and multispectral sensor into a practical decision support system for precision nitrogen management in corn
Laura Thompson,Laila A. Puntel +1 more
TL;DR: A practical decision support system (DSS) to translate spatial field characteristics and normalized difference red edge (NDRE) values into an in-season N application recommendation and identifies five avenues for further improvement of the proposed DSS.
References
Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy
Pablo J. Zarco-Tejada,Alberto Berjón,Raúl López-Lozano,John R. Miller,Pedro Martín,Victoria E. Cachorro,M. R. González,A. M. de Frutos +7 more
TL;DR: In this article, a Li-Cor 1800-12 Integrating Sphere coupled with a 200 Am diameter single mode fiber to an Ocean Optics model USB2000 spectrometer was used for measuring the optical properties of reflectance and transmittance with a subsample of 605 leaves.
703
Shadow Analysis in High-Resolution Satellite Imagery of Urban Areas
TL;DR: In this article, the authors present a solution to the problem of automatic detection and removal of shadow features in high-resolution satellite imagery of urban areas, which can lead to improved image quality.
384
Shadow detection in very high spatial resolution aerial images: A comparative study
TL;DR: In this article, state-of-the-art methods on shadow detection were surveyed and categorized into six classes: histogram thresholding, invariant color models, object segmentation, geometrical methods, physics-based methods, unsupervised and supervised machine learning methods.
210
Development of a two-leaf light use efficiency model for improving the calculation of terrestrial gross primary productivity
Mingzhu He,Mingzhu He,Weimin Ju,Weimin Ju,Yanlian Zhou,Jingming Chen,Jingming Chen,Honglin He,Shaoqiang Wang,Huimin Wang,Dexin Guan,Junhua Yan,Yingnian Li,Yanbin Hao,Fenghua Zhao +14 more
TL;DR: Li et al. as mentioned in this paper developed a two-leaf light use efficiency (TL-LUE) model based on the MOD 17 algorithm to improve the calculation of GPP, which separates the canopy into sunlit and shaded leaf groups with different maximum light use efficiencies.
202
Analyzing the effect of structural variability and canopy gaps on forest BRDF using a geometric-optical model
F. Gerard,Peter North +1 more
TL;DR: In this article, a geometric-optical reflectance model is presented which estimates the bidirectional reflectance distribution function (BRDF) of forest canopies by modeling four shadowing pattern components (i.e., illuminated crown, illuminated ground, shadowed crown, and shadowed ground).
111