Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

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Removal of soil biota alters soil feedback effects on plant growth and defense chemistry
Wang, Minggang ; Ruan, Weibin ; Kostenko, Olga ; Carvalho, Sabrina ; Hannula, S.E. ; Mulder, Patrick P.J. ; Bu, Fengjiao ; Putten, Wim H. van der; Bezemer, T.M. - \ 2019
New Phytologist 221 (2019)3. - ISSN 0028-646X - p. 1478 - 1491.
fractionation - Jacobaea vulgaris - plant–soil feedback (PSF) - pyrrolizidine alkaloids (PAs) - soil biota - spectral reflectance

We examined how the removal of soil biota affects plant–soil feedback (PSF) and defense chemistry of Jacobaea vulgaris, an outbreak plant species in Europe containing the defense compounds pyrrolizidine alkaloids (PAs). Macrofauna and mesofauna, as well as fungi and bacteria, were removed size selectively from unplanted soil or soil planted with J. vulgaris exposed or not to above- or belowground insect herbivores. Wet-sieved fractions, using 1000-, 20-, 5- and 0.2-μm mesh sizes, were added to sterilized soil and new plants were grown. Sieving treatments were verified by molecular analysis of the inocula. In the feedback phase, plant biomass was lowest in soils with 1000- and 20-μm inocula, and soils conditioned with plants gave more negative feedback than without plants. Remarkably, part of this negative PSF effect remained present in the 0.2-μm inoculum where no bacteria were present. PA concentration and composition of plants with 1000- or 20-μm inocula differed from those with 5- or 0.2-μm inocula, but only if soils had been conditioned by undamaged plants or plants damaged by aboveground herbivores. These effects correlated with leaf hyperspectral reflectance. We conclude that size-selective removal of soil biota altered PSFs, but that these PSFs were also influenced by herbivory during the conditioning phase.

Comparison of remote sensing and plant trait-based modelling to predict ecosystem services in subalpine grasslands
Homolova, L. ; Schaepman, M.E. ; Lamarque, P. ; Clevers, J.G.P.W. ; Bello, F. de; Thuiller, W. ; Lavorel, S. - \ 2014
Ecosphere 5 (2014)8. - ISSN 2150-8925
land-use change - leaf chlorophyll content - imaging spectroscopy - water-content - aviris data - spectral reflectance - hyperspectral data - species richness - area index - vegetation
There is a growing demand for spatially explicit assessment of multiple ecosystem services (ES) and remote sensing (RS) can provide valuable data to meet this challenge. In this study, located in the Central French Alps, we used high spatial and spectral resolution RS images to assess multiple ES based on underpinning ecosystem properties (EP) of subalpine grasslands. We estimated five EP (green biomass, litter mass, crude protein content, species diversity and soil carbon content) from RS data using empirical RS methods and maps of ES were calculated as simple linear combinations of EP. Additionally, the RS-based results were compared with results of a plant trait-based statistical modelling approach that predicted EP and ES from land use, abiotic and plant trait data (modelling approach). The comparison between the RS and the modelling approaches showed that RS-based results provided better insight into the fine-grained spatial distribution of EP and thereby ES, whereas the modelling approach reflected the land use signal that underpinned trait-based models of EP. The spatial agreement between the two approaches at a 20-m resolution varied between 16 and 22% for individual EP, but for the total ecosystem service supply it was only 7%. Furthermore, the modelling approach identified the alpine grazed meadows land use class as areas with high values of multiple ES (hot spots) and mown-grazed permanent meadows as areas with low values and only few ES (cold spots). Whereas the RS-based hot spots were a small subset of those predicted by the modelling approach, cold spots were rather scattered, small patches with limited overlap with the modelling results. Despite limitations associated with timing of assessment campaigns and field data requirements, RS offers valuable data for spatially continuous mapping of EP and can thus supply RS-based proxies of ES. Although the RS approach was applied to a limited area and for one type of ecosystem, we believe that the broader availability of high fidelity airborne and satellite RS data will promote RS-based assessment of ES to larger areas and other ecosystems.
Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3
Clevers, J.G.P.W. ; Gitelson, A.A. - \ 2013
International Journal of applied Earth Observation and Geoinformation 23 (2013). - ISSN 0303-2434 - p. 344 - 351.
higher-plant leaves - spectral reflectance - vegetation indexes - canopy chlorophyll - leaf reflectance - mission - meris - wheat - lai
Sentinel-2 is planned for launch in 2014 by the European Space Agency and it is equipped with the Multi Spectral Instrument (MSI), which will provide images with high spatial, spectral and temporal resolution. It covers the VNIR/SWIR spectral region in 13 bands and incorporates two new spectral bands in the red-edge region, which can be used to derive vegetation indices using red-edge bands in their formulation. These are particularly suitable for estimating canopy chlorophyll and nitrogen (N) content. This band setting is important for vegetation studies and is very similar to the ones of the Ocean and Land Colour Instrument (OLCI) on the planned Sentinel-3 satellite and the Medium Resolution Imaging Spectrometer (MERIS) on Envisat, which operated from 2002 to early 2012. This paper focuses on the potential of Sentinel-2 and Sentinel-3 in estimating total crop and grass chlorophyll and N content by studying in situ crop variables and spectroradiometer measurements obtained for four different test sites. In particular, the red-edge chlorophyll index (CIred-edge), the green chlorophyll index (CIgreen) and the MERIS terrestrial chlorophyll index (MTCI) were found to be accurate and linear estimators of canopy chlorophyll and N content and the Sentinel-2 and -3 bands are well positioned for deriving these indices. Results confirm the importance of the red-edge bands on particularly Sentinel-2 for agricultural applications, because of the combination with its high spatial resolution of 20 m
Photosynthetic bark: use of chlorophyll absorption continuum index to estimate Boswellia papyrifera bark chlorophyll content
Girma, A. ; Skidmore, A.K. ; Bie, C.A.J.M. de; Bongers, F. ; Schlerf, M. - \ 2013
International Journal of applied Earth Observation and Geoinformation 23 (2013)August. - ISSN 0303-2434 - p. 71 - 80.
least-squares regression - red edge position - hyperspectral measurements - spectral reflectance - vegetation indexes - leaves - stems - frankincense - performance - prospect
Quantification of chlorophyll content provides useful insight into the physiological performance of plants. Several leaf chlorophyll estimation techniques, using hyperspectral instruments, are available. However, to our knowledge, a non-destructive bark chlorophyll estimation technique is not available. We set out to assess Boswellia papyrifera tree bark chlorophyll content and to provide an appropriate bark chlorophyll estimation technique using hyperspectral remote sensing techniques. In contrast to the leaves, the bark of B. papyrifera has several outer layers masking the inner photosynthetic bark layer. Thus, our interest includes understanding how much light energy is transmitted to the photosynthetic inner bark and to what extent the inner photosynthetic bark chlorophyll activity could be remotely sensed during both the wet and the dry season. In this study, chlorophyll estimation using the chlorophyll absorption continuum index (CACI) yielded a higher R2 (0.87) than others indices and methods, such as the use of single band, simple ratios, normalized differences, and conventional red edge position (REP) based estimation techniques. The chlorophyll absorption continuum index approach considers the increase or widening in area of the chlorophyll absorption region, attributed to high concentrations of chlorophyll causing spectral shifts in both the yellow and the red edge. During the wet season B. papyrifera trees contain more bark layers than during the dry season. Having less bark layers during the dry season (leaf off condition) is an advantage for the plants as then their inner photosynthetic bark is more exposed to light, enabling them to trap light energy. It is concluded that B. papyrifera bark chlorophyll content can be reliably estimated using the chlorophyll absorption continuum index analysis. Further research on the use of bark signatures is recommended, in order to discriminate the deciduous B. papyrifera from other species during the dry season.
Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices
Hamzeh, S. ; Naseri, A.A. ; Alavi Panah, S.K. ; Mojaradi, B. ; Bartholomeus, H. ; Clevers, J.G.P.W. ; Behzad, M. - \ 2013
International Journal of applied Earth Observation and Geoinformation 21 (2013). - ISSN 0303-2434 - p. 282 - 290.
salt-affected soils - difference water index - spectral reflectance - precision agriculture - chlorophyll content - canopy reflectance - plant-leaves - fresh-water - hyperion - leaf
The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R2 = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.
Using hyperspectral remote sensing data for retrieving canopy chlorophyll and nitrogen content
Clevers, J.G.P.W. ; Kooistra, L. - \ 2012
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5 (2012)2. - ISSN 1939-1404 - p. 574 - 583.
band vegetation indexes - higher-plant leaves - red-edge - spectral reflectance - leaf reflectance - narrow-band - model - meter - corn - management
Plant stress is often expressed as a reduction in amount of biomass or leaf area index (LAI). In addition, stress may affect the plant pigment system, influencing the photosynthetic capacity of plants. Chlorophyll content is the main driver for this primary production. The chlorophyll content is indirectly related to the nitrogen (N) content. In this paper emphasis is on estimation of canopy chlorophyll content and N content using remote sensing techniques. Hyperspectral reflectance data representing a range of canopies were simulated using the PROSAIL radiative transfer model at a 1 nm sampling interval. Various indices were tested for estimating canopy chlorophyll content. Subsequently, tests with field data were performed for sampling locations within an extensively grazed fen meadow using ASD FieldSpec measurements and within a potato field with a Cropscan radiometer for estimating canopy N content. PROSAIL simulations showed that the red-edge chlorophyll index (CIred edge) was linearly related to the canopy chlorophyll content over the full range of potential values (R-2 = 0.94). In contrast, highly non-linear relationships of chlorophyll content with most traditional red-edge indices were found. At the study sites the CIred edge was found to be a good and linear estimator of canopy N content (no chlorophyll was measured) for both the grassland site (R-2 = 0.77) and for the potato field (R-2 = 0.88). The latter number refers to plots showing no "luxury" N consumption. However, for the full potato data set, including highly fertilized plants, an exponential relationship yielded a better fit (R-2 = 0.85) as compared to a linear fit (R-2 = 0.65). Currently, this approach can, e. g., be applied with MERIS and Hyperion data and with the upcoming Sentinel-2 and -3 systems.
Ground-Based Optical Measurements at European Flux Sites:
Balzarolo, M. ; Anderson, K. ; Nichol, C. ; Elbers, J.A. ; Rossini, M. ; Vescovo, L. - \ 2011
Sensors 11 (2011). - ISSN 1424-8220 - p. 7954 - 7981.
vegetation indexes - spectral reflectance - co2 fluxes - photosynthetic efficiency - ndvi measurements - resolution ndvi - carbon-dioxide - ecosystem - validation - footprint
This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903—“Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe” that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites
Combining novel monitoring tools and precision application technologies for integrated high-tech crop protection in the future (a discussion document)
Zijlstra, C. ; Lund, I. ; Justesen, A. ; Nicolaisen, M. ; Bianciotto, V. ; Posta, K. ; Balestrini, R. ; Przetakiewicz, A. ; Czembor, E. ; Zande, J. van de - \ 2011
Pest Management Science 67 (2011)6. - ISSN 1526-498X - p. 616 - 625.
real-time pcr - polymerase-chain-reaction - term pest-management - soil seed bank - weed-control - temporal stability - mycosphaerella-brassicicola - sclerotinia-sclerotiorum - spectral reflectance - spatial-distribution
The possibility of combining novel monitoring techniques and precision spraying for crop protection in the future is discussed. A generic model for an innovative crop protection system has been used as a framework. This system will be able to monitor the entire cropping system and identify the presence of relevant pests, diseases and weeds online, and will be location specific. The system will offer prevention, monitoring, interpretation and action which will be performed in a continuous way. The monitoring is divided into several parts. Planting material, seeds and soil should be monitored for prevention purposes before the growing period to avoid, for example, the introduction of disease into the field and to ensure optimal growth conditions. Data from previous growing seasons, such as the location of weeds and previous diseases, should also be included. During the growing season, the crop will be monitored at a macroscale level until a location that needs special attention is identified. If relevant, this area will be monitored more intensively at a microscale level. A decision engine will analyse the data and offer advice on how to control the detected diseases, pests and weeds, using precision spray techniques or alternative measures. The goal is to provide tools that are able to produce high-quality products with the minimal use of conventional plant protection products. This review describes the technologies that can be used or that need further development in order to achieve this goal
Soil organic carbon mapping of partially vegetated agricultural fields with imaging spectroscopy
Bartholomeus, H. ; Kooistra, L. ; Stevens, A. ; Leeuwen, M. van; Wesemael, B. van; Ben-Dor, E. ; Tychon, B. - \ 2011
International Journal of applied Earth Observation and Geoinformation 13 (2011)1. - ISSN 0303-2434 - p. 81 - 88.
infrared reflectance spectroscopy - least-squares regression - spectral reflectance - aviris data - indexes - tm - spectrometry - parameters - prospect - nitrogen
Soil Organic Carbon (SOC) is one of the key soil properties, but the large spatial variation makes continuous mapping a complex task. Imaging spectroscopy has proven to be an useful technique for mapping of soil properties, but the applicability decreases rapidly when fields are partially covered with vegetation. In this paper we show that with only a few percent fractional maize cover the accuracy of a Partial Least Square Regression (PLSR) based SOC prediction model drops dramatically. However, this problem can be solved with the use of spectral unmixing techniques. First, the fractional maize cover is determined with linear spectral unmixing, taking the illumination and observation angles into account. In a next step the influence of maize is filtered out from the spectral signal by a new procedure termed Residual Spectral Unmixing (RSU). The residual soil spectra resulting from this procedure are used for mapping of SOC using PLSR, which could be done with accuracies comparable to studies performed on bare soil surfaces (Root Mean Standard Error of Calibration = 1.34 g/kg and Root Mean Standard Error of Prediction = 1.65 g/kg). With the presented RSU approach it is possible to filter out the influence of maize from the mixed spectra, and the residual soil spectra contain enough information for mapping of the SOC distribution within agricultural fields. This can improve the applicability of airborne imaging spectroscopy for soil studies in temperate climates, since the use of the RSU approach can extend the flight-window which is often constrained by the presence of vegetation.
Evaluating variations of physiology-based hyperspectral features along a soil water gradient in a Eucalyptus grandis plantation
Cho, M.A. ; Aardt, J. van; Main, R. ; Majeke, B. - \ 2010
International Journal of Remote Sensing 31 (2010)12. - ISSN 0143-1161 - p. 3143 - 3159.
multiple linear-regression - red edge position - chlorophyll content - vegetation indexes - reflectance indexes - steady-state - precision agriculture - spectral reflectance - absorption features - leaf reflectance
Remote sensing is viewed as a cost-effective alternative to intensive field surveys in assessing site factors that affect growth of Eucalyptus grandis over broad areas. The objective of this study was to assess the utility of hyperspectral remote sensing to discriminate between site qualities in E. grandis plantation in KwaZulu-Natal, South Africa. The relationships between physiology-based hyperspectral indicators and site quality, as defined by total available water (TAW), were assessed for E. grandis plantations through one-way analysis of variance (ANOVA). Canopy reflectance spectra for 68 trees (25 good, 25 medium and 18 poor sites) were collected on clear-sky days using an Analytical Spectral Device (ASD) spectroradiometer (350-2500 nm) from a raised platform. Foliar macronutrient concentrations for N, P, K, S, Ca, Mg and Na and their corresponding spectral features were also evaluated. The spectral signals for leaf water - normalized difference water index (NDWI), water band index (WBI) and moisture stress index (MSI) - exhibited significant differences (p 0.05) between sites. The magnitudes of these indices showed distinct gradients from the poor to the good sites. Similar results were observed for chlorophyll indices. These results show that differences in site quality based on TAW could be detected via imaging spectroscopy of canopy water or chlorophyll content. Among the macronutrients, only K and Ca exhibited significant differences between sites. However, a Tukey post-hoc test showed differences between the good and medium or medium and poor sites, a trend not consistent with the TAW gradient. The study also revealed the capability of continuum-removed spectral features to provide information on the physiological state of vegetation. The normalized band depth index (NBDI), derived from continuum-removed spectra in the region of the red-edge, showed the highest potential to differentiate between sites in this study. The study thus demonstrated the capability of hyperspectral remote sensing of vegetation canopies in identifying the site factors that affect growth of E. grandis in KwaZulu Natal, South Africa.
Effects of woody elements on simulated canopy reflectance: implications for forest chlorophyll content retrieval
Verrelst, J. ; Schaepman, M.E. ; Malenovsky, Z. ; Clevers, J.G.P.W. - \ 2010
Remote Sensing of Environment 114 (2010)3. - ISSN 0034-4257 - p. 647 - 656.
leaf optical-properties - light-use efficiency - resolution satellite imagery - radiative-transfer models - high-spatial-resolution - spectral reflectance - imaging spectroscopy - vegetation indexes - hyperspectral reflectance - sensitivity-analysis
An important bio-indicator of actual plant health status, the foliar content of chlorophyll a and b (Cab), can be estimated using imaging spectroscopy. For forest canopies, however, the relationship between the spectral response and leaf chemistry is confounded by factors such as background (e.g. understory), canopy structure, and the presence of non-photosynthetic vegetation (NPV, e.g. woody elements)—particularly the appreciable amounts of standing and fallen dead wood found in older forests. We present a sensitivity analysis for the estimation of chlorophyll content in woody coniferous canopies using radiative transfer modeling, and use the modeled top-of-canopy reflectance data to analyze the contribution of woody elements, leaf area index (LAI), and crown cover (CC) to the retrieval of foliar Cab content. The radiative transfer model used comprises two linked submodels: one at leaf level (PROSPECT) and one at canopy level (FLIGHT). This generated bidirectional reflectance data according to the band settings of the Compact High Resolution Imaging Spectrometer (CHRIS) from which chlorophyll indices were calculated. Most of the chlorophyll indices outperformed single wavelengths in predicting Cab content at canopy level, with best results obtained by the Maccioni index ([R780 - R710] / [R780 - R680]). We demonstrate the performance of this index with respect to structural information on three distinct coniferous forest types (young, early mature and old-growth stands). The modeling results suggest that the spectral variation due to variation in canopy chlorophyll content is best captured for stands with medium dense canopies. However, the strength of the up-scaled Cab signal weakens with increasing crown NPV scattering elements, especially when crown cover exceeds 30%. LAI exerts the least perturbations. We conclude that the spectral influence of woody elements is an important variable that should be considered in radiative transfer approaches when retrieving foliar pigment estimates in heterogeneous stands, particularly if the stands are partly defoliated or long-lived
Leaf Area Index derivation from hyperspectral vegetation indices and the red edge position
Darvishzadeh, R. ; Atzberger, C. ; Skidmore, A.K. ; Abkar, A. - \ 2009
International Journal of Remote Sensing 30 (2009)23. - ISSN 0143-1161 - p. 6199 - 6218.
canopy chlorophyll density - spectral reflectance - biophysical variables - imaging spectrometer - boreal forests - winter-wheat - broad-band - lai - photosynthesis - information
The aim of this study was to compare the performance of various narrowband vegetation indices in estimating Leaf Area Index (LAI) of structurally different plant species having different soil backgrounds and leaf optical properties. The study uses a dataset collected during a controlled laboratory experiment. Leaf area indices were destructively acquired for four species with different leaf size and shape. Six widely used vegetation indices were investigated. Narrowband vegetation indices involved all possible two band combinations which were used for calculating RVI, NDVI, PVI, TSAVI and SAVI2. The red edge inflection point (REIP) was computed using three different techniques. Linear regression models as well as an exponential model were used to establish relationships. REIP determined using any of the three methods was generally not sensitive to variations in LAI (R-2 <0.1). However, LAI was estimated with reasonable accuracy from red/near-infrared based narrowband indices. We observed a significant relationship between LAI and SAVI2 (R-2 = 0.77, RMSE = 0.59 (cross validated)). Our results confirmed that bands from the SWIR region contain relevant information for LAI estimation. The study verified that within the range of LAI studied (0.3
The effects of high soil CO2 concentrations on leaf reflectance of maize plants
Noomen, M.F. ; Skidmore, A.K. - \ 2009
International Journal of Remote Sensing 30 (2009)2. - ISSN 0143-1161 - p. 481 - 497.
red edge position - carbon-dioxide - chlorophyll concentration - nitrogen concentration - spectral reflectance - model simulation - root respiration - wheat genotypes - area index - leaves
Carbon dioxide gas at higher concentrations is known to kill vegetation and can also lead to asphyxiation in humans and animals. The objective of this study is to test whether soil CO2 concentrations ranging from 2% to 50% can be detected using vegetative spectral reflectance. A greenhouse experiment was performed to measure the reflectance of maize plants growing in soil contaminated with high concentrations of CO2. The correlation between leaf chlorophyll and reflectance in both the red edge and the yellow region was studied using different methods. The method that resulted in the strongest correlation between leaf reflectance and chlorophyll was subsequently used to study the effects of CO2 on plant health. The results showed that the method developed by Cho and Skidmore (2006) was the most accurate in predicting leaf chlorophyll (R 2 of 0.72). This index in combination with a new index proposed in this study¿named the yellow edge position or YEP¿showed that an increase in CO2 concentration corresponds to a decrease in leaf chlorophyll. Two first derivative water absorption features at 1400 and 1900 nm indicate that a concentration of 50% CO2 decreased leaf water content. Although upscaling to canopy reflectance is necessary, this experiment shows that leaf reflectance can be used to detect high soil CO2 concentrations, particularly halfway through the growing season.
Estimation of vegetation LAI from hyperspectral reflectance data: Effects of soil type and plant architecture
Darvishzadeh, R. ; Skidmore, A.K. ; Atzberger, C. ; Wieren, S.E. van - \ 2008
International Journal of applied Earth Observation and Geoinformation 10 (2008)3. - ISSN 0303-2434 - p. 358 - 373.
leaf-area index - canopy chlorophyll density - radiative-transfer models - satellite data - broad-band - biophysical variables - spectral reflectance - thematic mapper - wheat canopies - winter-wheat
The retrieval of canopy biophysical variables is known to be affected by confounding factors such as plant type and background reflectance. The effects of soil type and plant architecture on the retrieval of vegetation leaf area index (LAI) from hyperspectral data were assessed in this study. In situ measurements of LAI were related to reflectances in the red and near-infrared and also to five widely used spectral vegetation indices (VIs). The study confirmed that the spectral contrast between leaves and soil background determines the strength of the LAI¿reflectance relationship. It was shown that within a given vegetation species, the optimum spectral regions for LAI estimation were similar across the investigated VIs, indicating that the various VIs are basically summarizing the same spectral information for a given vegetation species. Cross-validated results revealed that, narrow-band PVI was less influenced by soil background effects (0.15 ¿ RMSEcv ¿ 0.56). The results suggest that, when using remote sensing VIs for LAI estimation, not only is the choice of VI of importance but also prior knowledge of plant architecture and soil background. Hence, some kind of landscape stratification is required before using hyperspectral imagery for large-scale mapping of vegetation biophysical variables.
Hyperspectral indices for detecting changes in canopy reflectance as a result of underground natural gas leakage
Noomen, M.F. ; Smith, K.L. ; Colls, J.J. ; Steven, M.D. ; Skidmore, A.K. ; Meer, F.D. van der - \ 2008
International Journal of Remote Sensing 29 (2008)20. - ISSN 0143-1161 - p. 5987 - 6008.
leaf pigment content - vegetation indexes - red-edge - chlorophyll content - plant stress - precision agriculture - spectral reflectance - wheat genotypes - water index - leaves
Natural gas leakage from underground pipelines is known to affect vegetation adversely, probably by displacement of the soil oxygen needed for respiration. This causes changes in plant and canopy reflectance, which may serve as indicators of gas leakage. In this study, a covariance analysis was performed between reflectance indices of maize (Zea mays) and wheat (Triticum aestivum) canopies and oxygen concentrations in a simulated natural gas leak. Twenty-nine days after oxygen shortage occurred, the reflectance indices had the highest correlation with oxygen concentrations in the soil, for both species. The effect was consistent within species but the absolute values varied between the species. Normalization by adding a constant value to the control index of one species resulted in significant linear regression models for several indices. The indices with the highest regression coefficients were used to predict the oxygen concentration in the soil. This showed that the gas leakage caused reflectance changes up to 0.5m from the source. As it could not be proven that oxygen shortage was the cause of the reflectance changes, further work is needed to study the side-effects of gas leakage, such as bacterial oxygen depletion, on plant growth and reflectance.
Angular sensitivity of vegetation indices derived from CHRIS/PROBA data
Verrelst, J. ; Schaepman, M.E. ; Kötz, B. ; Kneubühler, M. - \ 2008
Remote Sensing of Environment 112 (2008)5. - ISSN 0034-4257 - p. 2341 - 2353.
light-use efficiency - photochemical reflectance index - imaging-spectroradiometer misr - leaf pigment content - boreal forest - spectral reflectance - surface reflectance - biophysical variables - factor distributions - information-content
View angle effects present in spectral vegetation indices can either be regarded as an added source of uncertainty for variable retrieval or as a source of additional information, enhancing the variable retrieval; however, the magnitude of these angular effects remains for most indices unknown or unquantified. We use the ESA-mission CHRIS-PROBA (Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy) providing spaceborne imaging spectrometer and multiangular data to assess the reflectance anisotropy of broadband as well as recently developed narrowband indices. Multiangular variability of Hemispherical Directional Reflectance Factor (HDRF) is a prime factor determining the indices´ angular response. Two contrasting structural vegetation types, pine forest and meadow, were selected to study the effect of reflectance anisotropy on the angular response. Calculated indices were standardized and statistically evaluated for their varying HDRF. Additionally we employ a coupled radiative transfer model (PROSPECT/FLIGHT) to quantify and substantiate the findings beyond an incidental case study. Nearly all tested indices manifested a prominent anisotropic behaviour. Apart from the conventional broadband greenness indices [e.g. Simple Ratio Index (SRI), Normalized Difference Vegetation Index (NDVI)], light use efficiency and leaf pigment indices [e.g. Structure Insensitive Pigment Index (SIPI), Photochemical Reflectance Index (PRI) and Anthocyanin Reflectance Index (ARI)] did express significant different angular responses depending on the vegetation type. Following the quantification of the impact, we conclude that the angular-dependent fraction of non-photosynthetic material is of critical importance shaping the angular signature of these VIs. This work highlights the influence of viewing geometry and surface reflectance anisotropy, particularly when using light use efficiency and leaf pigment indices.
Remote sensing of nitrogen and water stress in wheat
Tilling, A.K. ; O'Leary, G.J. ; Ferwerda, J.G. ; Jones, S.D. ; Fitzgerald, G.J. ; Rodriguez, D. ; Belford, R. - \ 2007
Field Crops Research 104 (2007)1-3. - ISSN 0378-4290 - p. 77 - 85.
spectral reflectance - crop - chlorophyll - indexes - temperature - leaves - plants - area
Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P <0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers.
Spectrodirectional Remote Sensing: From Pixels to Processes
Schaepman, M.E. - \ 2007
International Journal of applied Earth Observation and Geoinformation 9 (2007)2. - ISSN 0303-2434 - p. 204 - 223.
radiative-transfer models - net primary productivity - imaging spectrometer aviris - comparing global-models - leaf-area index - terrestrial ecosystem - multiangular measurements - spectral reflectance - forest ecosystems - data assimilation
This paper discusses the historical evolution of imaging spectroscopy in Earth observation as well as directional (or multiangular) research leading to current achievements in spectrodirectional remote sensing. It elaborates on the evolution from two separate research areas into a common approach to quantify the interaction of light with the Earth surface. The contribution of spectrodirectional remote sensing towards an improved understanding of the Earth System is given by discussing the benefits of converging from individual pixel analysis to process models in the land-biosphere domain. The paper concludes with an outlook of research focus and upcoming areas of interest emphasizing towards multidisciplinary approaches using integrated system solutions based on remote and in situ sensing, data assimilation, and state space estimation algorithms.
Integrating remote sensing and spatial statistics to model herbaceous biomass distribution in a tropical savanna
Mutanga, O. ; Rugege, D. - \ 2006
International Journal of Remote Sensing 27 (2006)16. - ISSN 0143-1161 - p. 3499 - 3514.
ground-based radiometry - kruger-national-park - spectral reflectance - absorption features - vegetation indexes - south-africa - quality - environment - derivation - imagery
Modelling herbaceous biomass is critical for an improved understanding of wildlife feeding patterns and distribution as well as for the development of early warning systems for fire management. Most savannas in South Africa are characterized by complex stand structure and abundant vegetation species. This has prohibited accurate estimation of biomass in such environments. We investigated the possibility of improving biomass predictions in tropical savannas using cokriging. Individual bands and ratios computed from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery were correlated with field measurements of biomass covering the Kruger National Park, South Africa. The band that yielded the highest correlation with biomass was then used for further analysis using cokriging. Three variogram models were developed: one for the herbaceous biomass, one for the best MODIS band and a cross variogram between all pairs of variables involved in the estimation. The variogram models were then used in cokriging to predict biomass distribution over the whole study area. Results indicate that a combination of remotely sensed data with field biomass measurements through cokriging improves the estimation accuracy compared to ordinary kriging and stepwise linear regression. Given the high temporal resolution of the freely available MODIS imagery, the result is critical for the improved monitoring and management of wildlife habitats.
Continuum removed band depth analysis for detecting the effects of natural gas, methane and ethane on maize reflectance
Noomen, M.F. ; Skidmore, A.K. ; Meer, F.D. van der; Prins, H.H.T. - \ 2006
Remote Sensing of Environment 105 (2006)3. - ISSN 0034-4257 - p. 262 - 270.
leaf water-content - spectral reflectance - absorption features - red-edge - pasture quality - plant stress - vegetation - leaves - resolution - responses
It is known that natural gas in the soil affects vegetation health, which may be detected through analysis of reflectance spectra. Since natural gas is invisible, changes in the vegetation could potentially indicate gas leakage. Although it is known that gas in soil affects plant reflectance, the relationship between natural gas and the development and reflectance properties of plants has not been studied. The objective of this study was to test whether natural gas and its two main components, methane and ethane, affect vegetation reflectance in the chlorophyll and water absorption regions. An experiment was carried out in which maize (Zea mays) plants were grown in pots that were flushed with 10 l of gas per day for 39 ±4 days. Leaf reflectance was measured once a week with a spectrophotometer. The reflectance was analysed using continuum removal of the blue (400-550 nm), red (550-750 nm) and two water absorption features (1370-1570 nm and 1870-2170 nm), after which the band depths and normalized band depths were analyzed for each treatment. The band depth analysis showed that ethane caused an initial increase of 10% in reflectance between 560 and 590 nm, followed by a decrease during the course of the experiment. Normalized band depth analysis showed that ethane caused a reflectance shift of 1 to 5 nm towards longer wavelengths compared to the control reflectance in the visible region. All gases caused an increase in reflectance in the water absorption bands. The physiological reflectance index, PRI, which has previously linked water stress to photosynthetic activity, suggested that the hydrocarbon gases (particularly ethane) decreased the photosynthetic activity of the plants. The combination of reduced band depths in the chlorophyll and water absorption regions and the increased PRI suggests that ethane gas in the soil hampered a normal water uptake by maize plants in an early stage of their growth. Although further research is necessary to upscale the results from the laboratory to the field, the increased reflectance in the 560-590 nm region caused by ethane together with the increased PRI are promising indicators for gas leakage.
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