Derivation from the Landsat 7 NDVI and ground truth validation of LAI and interception storage capacity for wetland ecosystems in Biebrza Valley, Poland

Suliga, Joanna; Chormański, Jarosław; Szporak-Wasilewska, Sylwia; Kleniewska, Małgorzata; Berezowski, Tomasz; Griensven, Ann van; Verbeiren, Boud

doi:10.1117/12.2194975

Cited by 3 publications

(6 citation statements)

References 19 publications

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“…Maximum canopy storage depends on plant morphology and is highly varied across the same plant types, which can be seen by high standard deviation of field measurements and it is confirmed by different studies carried out in Biebrza Valley [36,45]. In addition, when maximum canopy storage was calculated for the entire plant communities (in the measuring squares) for the selected times of growing season, high variability is still observed where the mean values do not differ significantly.…”

Section: Interception Lossessupporting

confidence: 48%

“…Other values were linearly interpolated assuming that I max is 0 at the beginning and end of the growing season. Previous research on wetland meadow canopy storage in this area [35,36,45,47] also focused only on the growing season. This is due to the negligible height of sedge communities before and after the growing season in this area.…”

Section: Generating Daily Values Of Maximum Canopy Storagementioning

confidence: 99%

“…Those studies focused on determining the spatial distribution of interception capacity based on ground truth measurements of maximum canopy storage and ALS (airborne laser scanning) [35], also ground truth data was used with Landsat 7 ETM+ image [36]. There have also been numerous studies conducted on estimation of interception using remote sensing techniques that have focused on forest [37,38], croplands [39] or grasslands [38].…”

Section: Introductionmentioning

confidence: 99%

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Modelling Wetland Growing Season Rainfall Interception Losses Based on Maximum Canopy Storage Measurements

Ciężkowski

Berezowski

Kleniewska

et al. 2018

Water

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This study estimates rainfall interception losses from natural wetland ecosystems based on maximum canopy storage measurements. Rainfall interception losses play an important role in water balance, which is crucial in wetlands, and has not yet been thoroughly studied in relation to this type of ecosystem. Maximum canopy storage was measured using the weight method. Based on these measurements, daily values of interception losses were estimated and then used to calculate long-term interception losses based on precipitation and potential evapotranspiration data for the 1971-2015 period. Depending mainly on the number of days with precipitation, the results show that total interception losses for the growing season as well as monthly interception losses are around 13% of gross rainfall. This value is similar to the values observed for some forests. Hence, interception losses should not be disregarded in hydrologic models of wetlands, especially because data trends in meteorological conditions (mainly number of days with precipitation) show that interception losses will increase in the future if those trends stay the same.

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Section: Interception Lossessupporting

confidence: 48%

Section: Generating Daily Values Of Maximum Canopy Storagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modelling Wetland Growing Season Rainfall Interception Losses Based on Maximum Canopy Storage Measurements

Ciężkowski

Berezowski

Kleniewska

et al. 2018

Water

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“…Between the first and the second weighting, we left the material for a few seconds to drip and then to be carefully weighted. After subtracting and averaging the mass of wet and fresh samples, we calculated the value of the amount of water intercepted on each species' surface (Suliga et al, 2015). We further used the difference between the weight of plants before (md [g]) and after (mw [g]) water immersion to determine the plant mass storage capacity in [gH2O / g]:…”

Section: Plant Surface Water Storagementioning

confidence: 99%

Leaf wettability and plant surface water storage for common wetland species of the Biebrza peatlands (northeast Poland)

Papierowska

Sikorska

Szporak-Wasilewska

et al. 2023

Journal of Hydrology and Hydromechanics

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Wetlands play a crucial role in buffering the effects of climate change. At the same time, they are one of the most endangered ecosystems on the globe. The knowledge of the water cycle and energy exchange is crucial for the practical preservation and exploiting their capabilities. Leaf wettability is an important parameter characterising the plant's ability to retain water on its surface, and is linked to the ecosystems' hydrological and ecological functioning. This research investigates the relationship between leaves' wettability based on contact angle measurements and water storage capacity (interception) for wetland vegetation. We performed the study for ten common plant species collected from Biebrza peatlands (Poland). We used CAM100 goniometer for the wetting contact angle measurements on the leaves' surface, and the weighing method for the plant surface water storage determination. The wetland plants' initial contact angle values ranged from 64.7° to 139.5° and 62.4° to 134.0° for the leaves' adaxial and abaxial parts, respectively. The average plant surface water storage was equal to 0.31 g·g−1, and values ranged from 0.09 to 0.76 g·g−1. The leaf hydrophobicity contributes to the amount of retained water. With increasing average contact angle, the amount of water retained on the plant decreased.

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“…LAI, an index with a biophysical meaning, is used for improving classification e.g., of alkaline fen habitat [9] and for estimating agriculture productivity [10] or fluxes of transpiration [11] and interception [12]. LAI finds application in energy [13] or water balance-based modeling [14] where for instance in hydrological catchment models LAI determines interception capacity in relation to the beginning and the end of the growing season [15]. LAI maps derived directly from remote sensing can capture unexpected anomalies in foliage cover caused by for example fires, droughts, or deforestation.…”

Section: Introductionmentioning

confidence: 99%

Automatic Proba-V Processor: TREX—Tool for Raster Data Exploration

et al. 2019

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The processing tool TREX, standing for ‘Tool for Raster data EXploration’ is presented and evaluated in the Biebrza wetlands in northeastern Poland. TREX was designed for the automatization of processing satellite data from the Proba-V satellite into maps of NDVI or LAI in any defined by the user projection, spatial resolution, or extent. The open source and access concept of TREX encourages the potential community of users to collaborate, develop, and integrate the tool with other satellite imagery and models. TREX reprojects, shifts, and resamples original data obtained from the Proba-V satellite to deliver reliable maps of NDVI and LAI. Validation of TREX in Biebrza wetlands resulted in correlations between 0.79 and 0.92 for NDVI data (measured with ASD Field Spec 4) and 0.92 for LAI data (measured with LiCOR—LAI-2000 Plant Canopy Analyzer).

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Derivation from the Landsat 7 NDVI and ground truth validation of LAI and interception storage capacity for wetland ecosystems in Biebrza Valley, Poland

Cited by 3 publications

References 19 publications

Modelling Wetland Growing Season Rainfall Interception Losses Based on Maximum Canopy Storage Measurements

Modelling Wetland Growing Season Rainfall Interception Losses Based on Maximum Canopy Storage Measurements

Leaf wettability and plant surface water storage for common wetland species of the Biebrza peatlands (northeast Poland)

Automatic Proba-V Processor: TREX—Tool for Raster Data Exploration

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