Factors affecting the spectral response of forest canopies: A review

Guyot, G.; Guyon, Dominique; Riom, J.

doi:10.1080/10106048909354217

Cited by 103 publications

(42 citation statements)

References 25 publications

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“…Atmospheric noise in the NDVI caused by clouds, dust, and aerosols is generally considered negatively biased. This is because additive path radiance causes an increase in red reflectance, while lower atmospheric transmission reduces near-infrared reflectance (Guyot et al 1989). NDVI has been widely used across diverse biomes as a proxy for rainfall (Barbosa et al 2006), as a substitute for vegetation growth and health (Schmidt and Karnieli 2000) and in ecological studies (Pettorelli et al 2005).…”

Section: Application Of Geoinformatics In Biodiversity and Climate Chmentioning

confidence: 99%

Biodiversity Status and Climate Change Scenario in Northeast India

Saikia

Kumar

Khan

2016

Climate Change Challenge (3C) and Social-Economic-Ecological Interface-Building

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Conservation of biodiversity and impacts of climate change are perhaps the most critical challenges faced by all sectors of the society. The patterns and processes related to climate change and biodiversity are so complex that corrective measures are often taken with an imperfect scientific knowledge base. This article addresses the biodiversity status and climate change scenario in Northeast India. The normalized difference vegetation index (NDVI) is used to explain the vegetation pattern of Northeast India and majority of area (58 %) are under tropical climatic zone, followed by subtropical (23 %), alpine (10 %), and temperate (9 %) zones. Although the Northeastern India is very susceptible to climate change because of its ecological fragility, the forest cover is reported increasing in the past few years because of the successful implementation of the different plantation and community development schemes. In order to avoid rapid and irreversible change in biodiversity, conservation strategies needed to focus on supporting the species' natural capacity to adapt to climate change.

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Section: Application Of Geoinformatics In Biodiversity and Climate Chmentioning

confidence: 99%

Biodiversity Status and Climate Change Scenario in Northeast India

Saikia

Kumar

Khan

2016

Climate Change Challenge (3C) and Social-Economic-Ecological Interface-Building

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“…De acordo com Guyot et al (1989), a variação do valor da reflectância, na região espectral do infravermelho próximo, é proporcional ao número de camadas e tamanho das células, bem como a orientação das paredes da folha. Desta forma, a absortância da folha nesta região espectral é baixa, e a reflectância está relacionada com a sua estrutura interna.…”

Section: Ecologia E Nutrição Florestal Santaunclassified

“…No que se refere à resposta espectral de uma folha típica Knipling (1970) e Guyot et al (1989), consideram três faixas do espectro eletromagnético: a região do visível (0,4 -0,7µm); do infravermelho próximo (0,7 -1,3 µm) e do infravermelho médio (1,3 -2,6 µm). Além disso, o comportamento espectral das folhas também pode ser caracterizado pela banda "red edge" no intervalo de comprimento de onda entre 0,68 -0,75 µm.…”

Section: Introductionunclassified

Comportamento espectral de espécies utilizadas em arborização urbana

et al. 2016

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Spectral behavior of species used in urban afforestationAbstract: The aim of this research was to characterize and measure the spectral behavior of six tree species grown at the Federal University of Santa Maria/RS. The studied species were Eucalyptus sp., Ficus benjamina, Inga marginata, Schinus terebinthifolius, Psidium cattleyanum and Handroanthus chrysotrichus. Were randomly collected seven healthy leaves for each specie, andanalyzed with FieldSpec3 Spectroradiometer, in the wavelength range from 350 to 2.500 nm. Were calculated 61 vegetation indices based on the mean average reflectances. Was applied a principal component analysis based on array x species matrice. The differences between the spectral behavior of the species were tested with a variance analysis (Tukey) by each spectral band of the Worldview 2 satellite sensor. The statistical analyses were performed with R software. Hierarchical clustering analysis was performed with PC-ORD 6.0 taking into account the Euclidean distance as measure of dissimilarity. To obtain and process spectral data were used ASD ViewSpecPro 4.05 and SAMS 3.2 softwares. The first component comprehended 90.94% of the variance for the dataset. The lowest ratio between the group and the average differences per specie was in the Red band. The Coastal, Blue, Green, Yellow and Red bands obtained similar behaviors, with differences in the species F. benjamina (except Green's band), I. marginata (Green and Yellow), and P. cattleyanum (Green). The Red Edge band presented no distinction between species. Reflectance differences were more visible in the Near Infrared 1 and 2 bands. Optimized Vegetation Index 1 and Simple Ratio 8 were the most effective indices to study the species.

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“…The terrain geometry and the season of the year in which measurements are made are essential for the correct interpretation of results. Guyot et al (1989) and Civco (1989) discuss this problem in detail.…”

Section: Typical Forms Of Experimental Semivariograms and Their Intermentioning

confidence: 99%

Applying geostatistics for investigations of forest ecosystems using remote sensing imagery

Zawadzki¹,

Cieszewski²,

Zasada³

et al. 2005

Silva Fenn.

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. 2005. Applying geostatistics for investigations of forest ecosystems using remote sensing imagery. Silva Fennica 39(4): 599-617.Geostatistically based methods that utilize textural information are frequently used to analyze remote sensing (RS) images. The role of these methods in analyzing forested areas increased rapidly during the last several years following advancements in highresolution RS technology. The results of numerous applications of geostatistical methods for processing RS forest images are encouraging. This paper summarizes such results. Three closely related topics are reviewed: 1) specific properties of geostatistical measures of spatial variability calculated from digital images of forested areas, 2) determination of biophysical forest parameters using semivariograms and characterization of forest ecosystem structure at the stand level, and 3) forest classification methods based on spatial information.

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Factors affecting the spectral response of forest canopies: A review

Cited by 103 publications

References 25 publications

Biodiversity Status and Climate Change Scenario in Northeast India

Biodiversity Status and Climate Change Scenario in Northeast India

Comportamento espectral de espécies utilizadas em arborização urbana

Applying geostatistics for investigations of forest ecosystems using remote sensing imagery

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