The effect of upper cortex absence on spectral reflectance indices in Antarctic lichens during thallus dehydration

In maritime Antarctica, lichens and mosses represent dominant autotrophs forming community structure of vegetation oases. In our study, we selected 4 most common lichen species (Xanthoria elegans, Rhizoplaca melanophthalma, Leptogium puberulum, Physconia muscigena) and monospecific colony of Nostoc commune typical for James Ross Island (Antarctica) for detailed physiological experiments. We investigated their spectral characteristics in response to hydration status of their thalli. In samples desiccating from fully wet (RWC, relative water content of 100%) to dry state (RWC = 0), photochemical reflectance index (PRI), and normalized difference vegetation index (NDVI) were evaluated for control thalli and those with removed upper cortex. In this way, the effect of presence/absence of the upper cortex on PRI, NDVI was studied. PRI showed either no change or species-specific an increase/decrease with dehydration. Removal of the upper cortex caused both PRI decrease (N. commune, P. muscigena) and increase (R. melanophthalma, L. puberulum). Removal of the upper cortex led to increase in NDVI in all species, typically within the RWC range of 20-100%. Species-specific differences of hydration-response curves of PRI and NDVI are discussed as well as the role of the absence of the upper cortex in the evaluation of spectral characteristics in desiccating lichens.

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Changes in spectral reflectance of selected Antarctic and South American lichens caused by dehydration and artificially-induced absence of secondary compounds

Czech Polar Reports ◽

10.5817/cpr2016-2-20 ◽

2016 ◽

Vol 6 (2) ◽

pp. 221-230 ◽

Cited By ~ 2

Author(s):

Miloš Barták ◽

Josef Hájek ◽

Ana Carolina Amarillo ◽

Jana Hazdrová ◽

Hebe Carreras

Keyword(s):

Secondary Metabolites ◽

Spectral Reflectance ◽

Spectral Characteristics ◽

Great Majority ◽

Secondary Compounds ◽

Hydration Status ◽

Alpine Regions ◽

Species Specific ◽

Reflectance Indices ◽

Spectral Reflectance Indices

Recently, spectral characteristics of lichens are in focus because of increasing number of spectral data applications in remote sensing of treeless polar and alpine regions. Therefore, species-specific spectral reflectance indices are measured in lichen species dominating polar ecosystems. Hydration status of the lichen thalli, as well as the presence of intrathalline secondary metabolites - which are UV-B absorbing compounds - both affects the spectral reflectance curves as well as numeric values of spectral reflectance indices. In the present paper, the reflectance spectra in 380-800 nm was measured in selected lichens to assess the effects of full hydration, and to evaluate the influence of secondary metabolites, they were wash out from lichen thalli with acetone (i.e. acetone rinsing) and then the spectra were also measured. For these experiments, Antarctic (Xanthoria elegans, Leptogium puberulum, Physconia muscigena and Rhizoplaca melanophthalma) and Argentinean lichens from mountain regions (Parmotrema conferendum and Ramalina celastri) were used. Changes in several spectral reflectance indices were evaluated and discussed in relation with hydration status and the absence of secondary metabolites. For the great majority of studied lichens, MCARI (Modified Chlorophyll Absorption in Reflectance Index) was the most effective index to reflect the changes between dry and wet state of thallus.

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Spectral reflectance indices sense desiccation induced changes in the thalli of Antarctic lichen Dermatocarpon polyphyllizum

Czech Polar Reports ◽

10.5817/cpr2018-2-21 ◽

2018 ◽

Vol 8 (2) ◽

pp. 249-259 ◽

Cited By ~ 2

Author(s):

Miloš Barták ◽

Kumud Bandhu Mishra ◽

Michaela Marečková

Keyword(s):

Spectral Reflectance ◽

Vegetation Index ◽

Near Infrared ◽

Normalized Difference Vegetation Index ◽

Spectral Characteristics ◽

Structural Features ◽

Coefficient Of Determination ◽

Curvilinear Relationship ◽

Structural Deterioration ◽

Reflectance Indices

Lichens, in polar and alpine regions, pass through repetitive dehydration and rehydration events over the years. The harsh environmental conditions affect the plasticity of lichen’s functional and structural features for their survival, in a species-specific way, and, thus, their optical and spectral characteristics. For an understanding on how dehydration affects lichens spectral reflectance, we measured visible (VIS) and near infrared (NIR) reflectance spectra of Dermatocarpon polyphyllizum, a foliose lichen species, from James Ross Island (Antarctica), during gradual dehydration from fully wet (relative water content (RWC) = 100%) to dry state (RWC = 0%), under laboratory conditions, and compared several derived reflectance indices (RIs) to RWC. We found a curvilinear relationship between RWC and range of RIs: water index (WI), photochemical reflectance index (PRI), normalized difference vegetation index (NDVI), modified chlorophyll absorption in reflectance indices (MCARI and MCARI1), simple ratio pigment index (SRPI), normalized pigment chlorophyll index (NPCI), and a new NIR shoulder region spectral ratio index (NSRI). The index NDVI was initially increased with maxima around 70% RWC and it steadily declined with further desiccation, whereas PRI in-creased with desiccation and steeply falls when RWC was below 10%. The curvilinear relationship, for RIs versus RWC, was best fitted by polynomial regressions of second or third degree, and it was found that RWC showed very high correlation with WI (R2 = 0.94) that is followed by MCARI (R2 = 0.87), NDVI (R2 = 0.83), and MCARI (R2 = 0.81). The index NSRI, proposed for accessing structural deterioration, was almost invariable during dehydration with the least value of the coefficient of determination (R2 = 0.28). This may mean that lichen, Dermatocarpon polyphyllizum, activates protection mechanisms initially in response to the progression of dehydration; however, severe dehydration causes deactivation of photosynthesis and associated pigments without much affecting its structure.

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Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

Czech Polar Reports ◽

10.5817/cpr2020-2-22 ◽

2020 ◽

Vol 10 (2) ◽

pp. 297-312

Author(s):

Peter Váczi ◽

Miloš Barták ◽

Michaela Bednaříková ◽

Filip Hrbáček ◽

Josef Hájek

Keyword(s):

Vegetation Cover ◽

Remote Sensing Data ◽

Field Research ◽

Alpine Tundra ◽

Vegetation Types ◽

Nostoc Commune ◽

James Ross Island ◽

Bryum Pseudotriquetrum ◽

Reflectance Indices ◽

Multispectral Camera

In this study, we investigated the utility of spectral remote sensing data gathered by a multispectral camera for estimating of vegetation cover in Antarctic vegetation oasis and Arcto-Alpine tundra. The surveys exploiting unmanned aerial vehicles (UAV) and multispectral camera were done in an Antarctic vegetation oasis located at the Northern shore of James Ross Island (Antarctica), and arcto-alpine tundra located in the Jeseníky Mts. (NE Czech Republic, 1 420 m a.s.l.). For the two locations, false colour images of spectral indices (VARI, NGRDI, GLI, RGVI, ExG, NDVI, PRI) were taken and analysis of vegetation types and components of vegetation cover done. Additionally, field research was performed by handheld instruments measuring NDVI, PRI and of selected vegetation components: Bryum pseudotriquetrum, Nostoc commune colonies (Antarctica), lichens grown on flat stones and boulders (the Jeseníky Mts.). The results show UAV photo surveys and imaging of spectral reflectance indices can be used to monitor vegetation types forming Antarctic vegetation oases and arcto-alpine tundra.

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Quantitative Identification of Maize Lodging-Causing Feature Factors Using Unmanned Aerial Vehicle Images and a Nomogram Computation

Remote Sensing ◽

10.3390/rs10101528 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1528 ◽

Cited By ~ 13

Author(s):

Liang Han ◽

Guijun Yang ◽

Haikuan Feng ◽

Chengquan Zhou ◽

Hao Yang ◽

...

Keyword(s):

Unmanned Aerial Vehicle ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Spectral Characteristics ◽

Canopy Structure ◽

Canopy Cover ◽

Structural Features ◽

Discrimination Ability ◽

Maize Varieties ◽

Aerial Vehicle

Maize (zee mays L.) is one of the most important grain crops in China. Lodging is a natural disaster that can cause significant yield losses and threaten food security. Lodging identification and analysis contributes to evaluate disaster losses and cultivates lodging-resistant maize varieties. In this study, we collected visible and multispectral images with an unmanned aerial vehicle (UAV), and introduce a comprehensive methodology and workflow to extract lodging features from UAV imagery. We use statistical methods to screen several potential feature factors (e.g., texture, canopy structure, spectral characteristics, and terrain), and construct two nomograms (i.e., Model-1 and Model-2) with better validation performance based on selected feature factors. Model-2 was superior to Model-1 in term of its discrimination ability, but had an over-fitting phenomenon when the predicted probability of lodging went from 0.2 to 0.4. The results show that the nomogram could not only predict the occurrence probability of lodging, but also explore the underlying association between maize lodging and the selected feature factors. Compared with spectral features, terrain features, texture features, canopy cover, and genetic background, canopy structural features were more conclusive in discriminating whether maize lodging occurs at the plot scale. Using nomogram analysis, we identified protective factors (i.e., normalized difference vegetation index, NDVI and canopy elevation relief ratio, CRR) and risk factors (i.e., Hcv1) related to maize lodging, and also found a problem of terrain spatial variability that is easily overlooked in lodging-resistant breeding trials.

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Reflectance indices as a diagnostic tool for weed control performed by multipurpose equipment in precision agriculture

Planta Daninha ◽

10.1590/s0100-83582012000200024 ◽

2012 ◽

Vol 30 (2) ◽

pp. 437-447 ◽

Cited By ~ 5

Author(s):

A. Merotto JR. ◽

C. Bredemeier ◽

R.A. Vidal ◽

I.C.G.R. Goulart ◽

E.D. Bortoli ◽

...

Keyword(s):

Weed Control ◽

Precision Agriculture ◽

Weed Management ◽

Dry Matter ◽

Vegetation Index ◽

Near Infrared ◽

Normalized Difference Vegetation Index ◽

Weed Interference ◽

Reflectance Indices ◽

The Relationship

Several tools of precision agriculture have been developed for specific uses. However, this specificity may hinder the implementation of precision agriculture due to an increasing in costs and operational complexity. The use of vegetation index sensors which are traditionally developed for crop fertilization, for site-specific weed management can provide multiple utilizations of these sensors and result in the optimization of precision agriculture. The aim of this study was to evaluate the relationship between reflectance indices of weeds obtained by the GreenSeekerTM sensor and conventional parameters used for weed interference quantification. Two experiments were conducted with soybean and corn by establishing a gradient of weed interference through the use of pre- and post-emergence herbicides. The weed quantification was evaluated by the normalized difference vegetation index (NDVI) and the ratio of red to near infrared (Red/NIR) obtained using the GreenSeekerTM sensor, the visual weed control, the weed dry matter, and digital photographs, which supplied information about the leaf area coverage proportions of weed and straw. The weed leaf coverage obtained using digital photography was highly associated with the NDVI (r = 0.78) and the Red/NIR (r = -0.74). The weed dry matter also positively correlated with the NDVI obtained in 1 m linear (r = 0.66). The results indicated that the GreenSeekerTM sensor originally used for crop fertilization could also be used to obtain reflectance indices in the area between rows of crops to support decision-making programs for weed control.

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Feedbacks of Vegetation on Summertime Climate Variability over the North American Grasslands. Part I: Statistical Analysis

Earth Interactions ◽

10.1175/ei196.1 ◽

2006 ◽

Vol 10 (17) ◽

pp. 1-27 ◽

Cited By ~ 15

Author(s):

Weile Wang ◽

Bruce T. Anderson ◽

Nathan Phillips ◽

Robert K. Kaufmann ◽

Christopher Potter ◽

...

Keyword(s):

Soil Moisture ◽

Climate Variability ◽

Time Scales ◽

North American ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Spectral Characteristics ◽

Growing Season ◽

Statistical Technique ◽

The North

Abstract Feedbacks of vegetation on summertime climate variability over the North American Grasslands are analyzed using the statistical technique of Granger causality. Results indicate that normalized difference vegetation index (NDVI) anomalies early in the growing season have a statistically measurable effect on precipitation and surface temperature later in summer. In particular, higher means and/or decreasing trends of NDVI anomalies tend to be followed by lower rainfall but higher temperatures during July through September. These results suggest that initially enhanced vegetation may deplete soil moisture faster than normal and thereby induce drier and warmer climate anomalies via the strong soil moisture–precipitation coupling in these regions. Consistent with this soil moisture–precipitation feedback mechanism, interactions between temperature and precipitation anomalies in this region indicate that moister and cooler conditions are also related to increases in precipitation during the preceding months. Because vegetation responds to soil moisture variations, interactions between vegetation and precipitation generate oscillations in NDVI anomalies at growing season time scales, which are identified in the temporal and the spectral characteristics of the precipitation–NDVI system. Spectral analysis of the precipitation–NDVI system also indicates that 1) long-term interactions (i.e., interannual and longer time scales) between the two anomalies tend to enhance one another, 2) short-term interactions (less than 2 months) tend to damp one another, and 3) intermediary-period interactions (4–8 months) are oscillatory. Together, these results support the hypothesis that vegetation may influence summertime climate variability via the land–atmosphere hydrological cycles over these semiarid grasslands.

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Recent greening driven by species-specific shrub growth characteristics in Nunatsiavut, Labrador, Canada

Arctic Science ◽

10.1139/as-2020-0031 ◽

2021 ◽

Author(s):

Taylor Larking ◽

Emma Davis ◽

Robert Way ◽

Luise Hermanutz ◽

Andrew Trant

Keyword(s):

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Species Identity ◽

Shrub Species ◽

Ecological Processes ◽

Winter Temperatures ◽

Dwarf Birch ◽

Summer Temperatures ◽

Species Specific

Satellite remote sensing is a popular approach for identifying vegetation change in northern environments; however, disentangling ecological processes causing variability in spectral indices remains a challenge. Here, we aim to determine how shrub characteristics differ between low and rapidly greening areas near Nain, Nunatsiavut, Canada. Using a cross-scale approach, we combined remotely sensed spectral greening trends (Normalized Difference Vegetation Index; Landsat Collection 1; 1985-2018) with shrub dynamics derived from ring-widths of green alder (Alnus alnobetula) and dwarf birch (Betula glandulosa). Differentiation of spectral greening classes appears to be driven by the distribution of shrub species. Alder were taller, grew faster, had more recent stem initiation than dwarf birch, and were dominant in rapid greening subplots. In low greening subplots, alders were co-dominant with dwarf birch, whose dominant stems initiated more gradually, were shorter, and had lower rates of vertical growth. The radial growth of both shrub species was favoured by warm winter temperatures and precipitation, whereas rapid greening alder was also favoured by warm summer temperatures. Further shrub growth will likely be enhanced under continued climate warming if moisture does not become limiting. This research demonstrates the importance of species identity in determining rates of spectral greening in northern environments.

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FUSION OF SENTINEL-2 AND PLANETSCOPE IMAGERY FOR VEGETATION DETECTION AND MONITORING

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-1-155-2018 ◽

2018 ◽

Vol XLII-1 ◽

pp. 155-160 ◽

Cited By ~ 9

Author(s):

M. Gašparović ◽

D. Medak ◽

I. Pilaš ◽

L. Jurjević ◽

I. Balenović

Keyword(s):

Land Cover ◽

Spatial Resolution ◽

Satellite Imagery ◽

Urban Areas ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Spectral Characteristics ◽

Land Cover Classification ◽

Vegetation Monitoring ◽

Sentinel 2

<p><strong>Abstract.</strong> Different spatial resolutions satellite imagery with global almost daily revisit time provide valuable information about the earth surface in a short time. Based on the remote sensing methods satellite imagery can have different applications like environmental development, urban monitoring, etc. For accurate vegetation detection and monitoring, especially in urban areas, spectral characteristics, as well as the spatial resolution of satellite imagery is important. In this research, 10-m and 20-m Sentinel-2 and 3.7-m PlanetScope satellite imagery were used. Although in nowadays research Sentinel-2 satellite imagery is often used for land-cover classification or vegetation detection and monitoring, we decided to test a fusion of Sentinel-2 imagery with PlanetScope because of its higher spatial resolution. The main goal of this research is a new method for Sentinel-2 and PlanetScope imagery fusion. The fusion method validation was provided based on the land-cover classification accuracy. Three land-cover classifications were made based on the Sentinel-2, PlanetScope and fused imagery. As expected, results show better accuracy for PS and fused imagery than the Sentinel-2 imagery. PlanetScope and fused imagery have almost the same accuracy. For the vegetation monitoring testing, the Normalized Difference Vegetation Index (NDVI) from Sentinel-2 and fused imagery was calculated and mutually compared. In this research, all methods and tests, image fusion and satellite imagery classification were made in the free and open source programs. The method developed and presented in this paper can easily be applied to other sciences, such as urbanism, forestry, agronomy, ecology and geology.</p>

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Identification of season-dependent relationships between spectral vegetation indices and aboveground phytomass in alpine grassland by using field spectroscopy

Ekológia (Bratislava) ◽

10.2478/eko-2013-0016 ◽

2013 ◽

Vol 32 (2) ◽

Cited By ~ 1

Author(s):

Andrej Halabuk ◽

Katarina Gerhatova ◽

Frantisek Kohut ◽

Zuzana Ponecova ◽

Matej Mojses

Keyword(s):

Regression Models ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Temporal Dynamics ◽

Spectral Characteristics ◽

Vegetation Indices ◽

Alpine Grassland ◽

Aboveground Phytomass ◽

Field Spectroscopy ◽

Spectral Vegetation Indices

AbstractHalabuk A., Gerhatova K., Kohut F., Ponecova Z., Mojses M.: Identification of season-dependent relationships between spectral vegetation indices and aboveground phytomass in alpine grassland by using field spectroscopy. Ekologia (Bratislava), Vol. 32, No. 2, p. 186-196, 2013.Spectral characteristics of alpine grasslands across the vegetation season (from May to September) are presented. The results are based on three year field spectroscopy monitoring of acid, nutrient poor grasslands at Kraľova hoľa research site, Low Tatras, Slovakia. Relationships between commonly used spectral vegetation indices (VIs) and field-based estimation of aboveground green phytomass (AG B) were analysed. Finally, season-dependent regression models were created in order to allow spatially extensive non-destructive monitoring of AG B. Spatial-temporal dynamics of background and standing litter markedly affect seasonal variations of relationships between VIs and AG B and predictability of the regression models. Because of a high proportion of litter during the whole season, this was a plant water-sensitive normalized difference water index (NDWI), which dominates as the predictive variable in the regression models across the whole season; except June, where chlorophyll absorption sensitive in normalized difference vegetation index (NDVI) performed the best (R2 = 0.57; rel. RMSE = 34%). However, the accuracy of the models was quite low (May: R2 = 0.45; rel. RMSE = 49%; July: R2 = 0.47; rel. RMSE = 26%; August: R2 = 0.13; rel. RMSE = 31%; September: R2 = 0.53; rel. RMSE = 40%).

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Dehydration-induced responses of primary photosynthetic processes and spectral reflectance indices in Antarctic Nostoc commune

Czech Polar Reports ◽

10.5817/cpr2016-1-9 ◽

2016 ◽

Vol 6 (1) ◽

pp. 87-95 ◽

Cited By ~ 5

Author(s):

Miloš Barták ◽

Jana Hazdrová ◽

Kateřina Skácelová ◽

Josef Hájek

Keyword(s):

Quantum Yield ◽

Phase I ◽

Phase Ii ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Phase Iii ◽

Photochemical Quenching ◽

Curvilinear Relationship ◽

Effective Quantum Yield ◽

Nostoc Commune

In this study, we investigated the relationship between relative water content (RWC) of N. commune colonies recorded during gradual dehydration and (i) normalized difference vegetation index (NDVI), (ii) photochemical reflectance index (PRI), and (iii) primary photochemical processes of photosynthesis, effective quantum yield of photosynthetic processes (FPSII) in photosystem II particular. PRI increased from -0.05 to 0.02 with RWC decrease from 100% (full hydration) to 0% (dry state). NDVI showed somewhat curvilinear relationship with desiccation with minimum value of 0.25 found at 10% RWC. Negative effect of suprasaturation of N. commune colony with water on effective quantum yield (FPSII) was found at RWC range 80-100%. At the RWC range, FPSII reached only 50 % of maximum found at RWC of 30%. In general, desiccation-response curve of showed polyphasic character with three main phases (phase I – constant FPSII values, phase II – an increase with desiccation at RWC 80-30%, and phase III – sigmoidal decrease with desiccation at RWC 0-30%). Non-photochemical quenching (qN) of absorbed light energy showed triphasic dependence on RWC as well. qN showed constant values in the phase I, an increase (phase II), and constant values at severe dehydration (phase III).

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