Estimating carbon dioxide fluxes from temperate mountain grasslands using broad-band vegetation indices

Wohlfahrt, Georg; Pilloni, S.; Hörtnagl, Lukas; Hammerle, Albin

doi:10.5194/bg-7-683-2010

Cited by 44 publications

(27 citation statements)

References 43 publications

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“…In line with this, the LCC in our study was significantly and linearly related to both (Table 3). This concurs with frequently reported positive effects of increased crop N uptake on dry matter yield and IPAR (Andersen et al, 1996;Shah, McKenzie, Gaunt, Marshall, & Frampton, 2004) and may also explain the increase of RUE by biochar amendment (Kuzyakov & Gavrichkova, 2010;Wohlfahrt, Pilloni, Hörtnagl, & Hammerle, 2010). The RUE only increased significantly in 2018.…”

Section: Crop Growth Dry Matter Yield Ipar and Rue As Affected Bysupporting

confidence: 91%

Effect of rice straw biochar and irrigation on growth, dry matter yield and radiation‐use efficiency of maize grown on an Acrisol in Ghana

Danso

Yakubu

Arthur

et al. 2019

J Agronomy Crop Science

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In order to determine whether the current low productivity associated with rainfed cultivation on degraded soils in Ghana can be improved by biochar amendment and irrigation, field experiments with maize were conducted over two seasons in 2017 and 2018. Rice straw biochar at rates of 0 t/ha (B0), 15 t/ha (B15) and 30 t/ha (B30) was combined with irrigation regimes of full irrigation (I100), deficit irrigation (I60) and no irrigation (I0). The I100 treatment was irrigated to field capacity every 3–4 days according to time domain reflectometry measurements while the I60 treatment received 60% of the irrigation amount given to I100 but with the same irrigation frequency. The I0 treatment was not irrigated. In both seasons, the B30 treatment recorded the highest total dry matter yield (TDMY), intercepted photosynthetically active radiation (IPAR) and radiation‐use efficiency (RUE) and these were significantly (p ≤ .05) higher than B0 except for RUE in 2017. Irrigation regimes did not significantly affect TDMY, IPAR and RUE in 2017 but compared to I100, I0 significantly reduced TDMY, IPAR and RUE in the relatively dryer 2018 season. Measured ratio vegetation indices differentiated biochar treatments earlier in the 2018 season than during 2017 and increase of leaf chlorophyll content indices with biochar rate in both seasons indicated that biochar amendment improved nitrogen uptake. Our study demonstrated that rice straw biochar is capable of increasing TDMY, IPAR and RUE of maize grown on degraded soils in Ghana. The study further showed that TDMY, IPAR and RUE of deficit irrigated maize for two seasons were similar to the counterpart fully irrigated maize and may be a viable water management option for farmers in Ghana to save irrigation water resources.

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Section: Crop Growth Dry Matter Yield Ipar and Rue As Affected Bysupporting

confidence: 91%

Effect of rice straw biochar and irrigation on growth, dry matter yield and radiation‐use efficiency of maize grown on an Acrisol in Ghana

Danso

Yakubu

Arthur

et al. 2019

J Agronomy Crop Science

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“…Although several studies have already compared VIs obtained from in situ observations against EC CO 2 fluxes (Gitelson et al, 2003b;Inoue et al, 2008;Peng and Gitelson, 2012;Peng et al, 2011;Rossini et al, 2010;Sims et al, 2006), and a few studies have focused on very similar canopies (Gianelle et al, 2009;Rossini et al, 2012;Wohlfahrt et al, 2010), we are not aware of any study based on such a long time series, acquired on a continuous basis during the growing seasons.…”

Section: Discussionmentioning

confidence: 99%

“…The implementation of VIs into the light response model might help to improve the gap-filling results, especially in very dynamic ecosystems such as croplands, grasslands or deciduous forests. This could be particularly useful in case of long gaps in the EC data, which are inherently associated with a large degree of uncertainty (Moffat et al, 2007;Richardson and Hollinger, 2007;Wohlfahrt et al, 2010) and in case of managed ecosystems, where carbon dioxide uptake depends not only on the incoming radiation seasonality but also on cutting and grazing events. The results of a simple gap-filling approach presented in this study (based on creating and superimposing randomly distributed artificial gaps of three different lengths on the real data set and comparing GEP m values derived from EC with GEP m values filled with the best performing spectral models) encourage the use of spectral data in the gap-filling procedures of EC flux time series.…”

Section: Discussionmentioning

confidence: 99%

Monitoring of carbon dioxide fluxes in a subalpine grassland ecosystem of the Italian Alps using a multispectral sensor

et al. 2014

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Abstract. The study investigates the potential of a commercially available proximal sensing system -based on a 16-band multispectral sensor -for monitoring mean midday gross ecosystem production (GEP m ) in a subalpine grassland of the Italian Alps equipped with an eddy covariance flux tower. Reflectance observations were collected for 5 consecutive years, characterized by different climatic conditions, together with turbulent carbon dioxide fluxes and their meteorological drivers. Different models based on linear regression (vegetation indices approach) and on multiple regression (reflectance approach) were tested to estimate GEP m from optical data. The overall performance of this relatively low-cost system was positive. Chlorophyll-related indices including the red-edge part of the spectrum in their formulation (rededge normalized difference vegetation index, NDVI red-edge ; chlorophyll index, CI red-edge ) were the best predictors of GEP m , explaining most of its variability during the observation period. The use of the reflectance approach did not lead to considerably improved results in estimating GEP m : the adjusted R 2 (adjR 2 ) of the model based on linear regression -including all the 5 years -was 0.74, while the adjR 2 for the multiple regression model was 0.79. Incorporating mean midday photosynthetically active radiation (PAR m ) into the model resulted in a general decrease in the accuracy of estimates, highlighting the complexity of the GEP m response to incident radiation. In fact, significantly higher photosynthesis rates were observed under diffuse as regards direct radiation conditions. The models which were observed to perform best were then used to test the potential of optical data for GEP m gap filling. Artificial gaps of three different lengths (1, 3 and 5 observation days) were introduced in the GEP m time series. The values of adjR 2 for the three gap-filling scenarios showed that the accuracy of the gap filling slightly decreased with gap length. However, on average, the GEP m gaps were filled with an accuracy of 73 % with the model fed with NDVI red-edge , and of 76 % with the model using reflectance at 681, 720 and 781 nm and PAR m data.

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“…While several studies have evaluated the possibility of modelling grassland GPP based on RS indexes derived from satellite data (Sims et al, 2006b;Li et al, 2007;Harris and Dash, 2010), we are aware of only one study, by Wohlfahrt et al (2010), that investigated the relationship between EC-derived carbon fluxes and ground measurement of NDVI collected at similar temporal (i.e. daily) and spatial scale in a mountain grassland.…”

Section: Rossini Et Al: Remote Estimation Of Gross Primary Producmentioning

confidence: 99%

Remote sensing-based estimation of gross primary production in a subalpine grassland

et al. 2012

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Abstract. This study investigates the performances in a terrestrial ecosystem of gross primary production (GPP) estimation of a suite of spectral vegetation indexes (VIs) that can be computed from currently orbiting platforms. Vegetation indexes were computed from near-surface field spectroscopy measurements collected using an automatic system designed for high temporal frequency acquisition of spectral measurements in the visible near-infrared region. Spectral observations were collected for two consecutive years in Italy in a subalpine grassland equipped with an eddy covariance (EC) flux tower that provides continuous measurements of net ecosystem carbon dioxide (CO 2 ) exchange (NEE) and the derived GPP. Different VIs were calculated based on ESA-MERIS and NASA-MODIS spectral bands and correlated with biophysical (Leaf area index, LAI; fraction of photosynthetically active radiation intercepted by green vegetation, f IPAR g ), biochemical (chlorophyll concentration) and ecophysiological (green light-use efficiency, LUE g ) canopy variables. In this study, the normalized difference vegetation index (NDVI) was the index best correlated with LAI and f IPAR g (r = 0.90 and 0.95, respectively), the MERIS terrestrial chlorophyll index (MTCI) with leaf chlorophyll content (r = 0.91) and the photochemical reflectance index (PRI 551 ), computed as (R 531 − R 551 )/(R 531 + R 551 ) with LUE g (r = 0.64).Subsequently, these VIs were used to estimate GPP using different modelling solutions based on Monteith's lightuse efficiency model describing the GPP as driven by the photosynthetically active radiation absorbed by green vegetation (APAR g ) and by the efficiency (ε) with which plants use the absorbed radiation to fix carbon via photosynthesis. Results show that GPP can be successfully modelled with a combination of VIs and meteorological data or VIs only. Vegetation indexes designed to be more sensitive to chlorophyll content explained most of the variability in GPP in the ecosystem investigated, characterised by a strong seasonal dynamic of GPP. Accuracy in GPP estimation slightly improves when taking into account high frequency modulations of GPP driven by incident PAR or modelling LUE g with the PRI in model formulation. Similar results were obtained for both measured daily VIs and VIs obtained as 16-day composite time series and then downscaled from the compositing period to daily scale (resampled data). However, the use of resampled data rather than measured daily input data decreases the accuracy of the total GPP estimation on an annual basis.

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Estimating carbon dioxide fluxes from temperate mountain grasslands using broad-band vegetation indices

Cited by 44 publications

References 43 publications

Effect of rice straw biochar and irrigation on growth, dry matter yield and radiation‐use efficiency of maize grown on an Acrisol in Ghana

Effect of rice straw biochar and irrigation on growth, dry matter yield and radiation‐use efficiency of maize grown on an Acrisol in Ghana

Monitoring of carbon dioxide fluxes in a subalpine grassland ecosystem of the Italian Alps using a multispectral sensor

Remote sensing-based estimation of gross primary production in a subalpine grassland

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