Remote sensing of canopy nitrogen at regional scale in Mediterranean forests using the spaceborne MERIS Terrestrial Chlorophyll Index

Loozen, Yasmina; Rebel, Karin T.; Karssenberg, Derek; Wassen, Martin J.; Sardans, Jordi; Peñuelas, Josep; Jong, S.M. de

doi:10.5194/bg-15-2723-2018

Cited by 15 publications

(9 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Three decades ago, researchers began using remote sensing to estimate leaf and canopy traits. While particular nutrients (mainly N; Filella, Serrano, Serra, & Peñuelas, ; Kokaly et al, ; Loozen et al, ; Serrano, Peñuelas, & Ustin, ) have been estimated frequently, other traits relevant to the nutrient status, such as LDMC, can be estimated as well but with low accuracy (Homolova, Maenovsky, Clevers, Garcia‐Santos, & Schaepman, ). For this reason, the focus in this review section is merely on stoichiometry.…”

Section: Remote Sensing‐derived Indicators Of the Nutrient Statusmentioning

confidence: 99%

“…Mitchell, Glenn, Sankey, Derryberry, & Germino, ; Serrano et al, ; Wang, Skidmore, Skidmore, Darvishzadeh, & Wang, ) or satellites (e.g. Loozen et al, ; Ollinger et al, ), depending on the desired resolution and scope of the study. Typically, concentrations of a particular element are estimated per pixel after an empirical calibration procedure in which reflectance in the 400–2400 nm range is matched with concentrations determined by standard laboratory procedures (Homolova et al, ).…”

Section: Remote Sensing‐derived Indicators Of the Nutrient Statusmentioning

confidence: 99%

See 1 more Smart Citation

Towards comparable assessment of the soil nutrient status across scales—Review and development of nutrient metrics

Sundert

Radujković

Cools

et al. 2019

Global Change Biology

Self Cite

View full text Add to dashboard Cite

Nutrient availability influences virtually every aspect of an ecosystem, and is a critical modifier of ecosystem responses to global change. Although this crucial role of nutrient availability in regulating ecosystem structure and functioning has been widely acknowledged, nutrients are still often neglected in observational and experimental synthesis studies due to difficulties in comparing the nutrient status across sites. In the current study, we explain different nutrient‐related concepts and discuss the potential of soil‐, plant‐ and remote sensing‐based metrics to compare the nutrient status across space. Based on our review and additional analyses on a dataset of European, managed temperate and boreal forests (ICP [International Co‐operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests] Forests dataset), we conclude that the use of plant‐ and remote sensing‐based metrics that rely on tissue stoichiometry is limited due to their strong dependence on species identity. The potential use of other plant‐based metrics such as Ellenberg indicator values and plant‐functional traits is also discussed. We conclude from our analyses and review that soil‐based metrics have the highest potential for successful intersite comparison of the nutrient status. As an example, we used and adjusted a soil‐based metric, previously developed for conifer forests across Sweden, against the same ICP Forests data. We suggest that this adjusted and further adaptable metric, which included the organic carbon concentration in the upper 20 cm of the soil (including the organic fermentation‐humus [FH] layer), the C:N ratio and pHCaCl2 of the FH layer, can be used as a complementary tool along with other indicators of nutrient availability, to compare the background nutrient status across temperate and boreal forests dominated by spruce, pine or beech. Future collection and provision of harmonized soil data from observational and experimental sites is crucial for further testing and adjusting the metric.

show abstract

Section: Remote Sensing‐derived Indicators Of the Nutrient Statusmentioning

confidence: 99%

Section: Remote Sensing‐derived Indicators Of the Nutrient Statusmentioning

confidence: 99%

Towards comparable assessment of the soil nutrient status across scales—Review and development of nutrient metrics

Sundert

Radujković

Cools

et al. 2019

Global Change Biology

Self Cite

View full text Add to dashboard Cite

show abstract

“…The average reflectance I and reflectance variability σ were calculated for the five bands. This dataset with known N and P concentrations was used as the learning set [42][43][44] in the linear regression with multiple variables (LRMV) algorithm which is one of the machine learning methods [45][46][47][48][49][50]. The main goal of LRMV method is to find the linear dependencies between reflectance intensity and variability in five optical channels and parameters we want to estimate for all trees, P and N concentrations in this particular case.…”

Section: Machine Learningmentioning

confidence: 99%

Monitoring Effects of Drought on Nitrogen and Phosphorus in Temperate Oak Forests Using Machine Learning Techniques

Kotlarz¹,

Siwiński²,

Spiralski³

et al. 2021

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

Pedunculate oak (Quercus robur. L) is a European tree species highly sensitive to drought. If declining symptoms appear they are often detectable at the crown (such as dieback) enabling monitoring using aerial images and remote sensing methods. Here, we analyzed the impact of short and long-term drought on oaks located in western Poland, between the years of 2014 and 2017. We used both leaf nitrogen (N) and leaf phosphorus (P) concentrations measured in the laboratory, aerial images collected in the range of 460-880 nm and machine learning techniques to estimate nutrient concentrations on the > 4000 oaks growing on stagnic luvisols in the study area. We determined a negative impact on N and P concentrations during both types of drought stress (-23% and -19% for N concentration in leaves; -27% and -10% for P concentration in leaves). Decreased water availability had inconsiderable impact on N:P values (3% increase of N:P ratio during short and 7% decrease of N:P ratio during long-term drought stress). We found that the long-term drought impact was spatially diverse, possibly depending on the presence of drainage ditches and competing species.

show abstract

“…Using hyperspectral images of the canopy, model qualities to predict the P content in the perennial grass Holcus lanatus reached values of r²=0.33 respectively 0.26 depending on the algorithm chosen (van Buul, 2017). For forest sites, the model quality was considerably lower and reached an r² of 0.269 for P (van Buul, 2017) and 0.69 for N (Loozen et al, 2018) in a Catalonian pine dominated mixed species stand.…”

Section: Foliage P Concentrations In Relation To Soil P Poolsmentioning

confidence: 99%

Distribution of phosphorus fractions of different plant availability in German forest soils and their relationship to common soil properties and foliar P concentrations

Niederberger¹,

Köhler²,

Bauhus³

2018

Preprint

View full text Add to dashboard Cite

Abstract. Repeated, grid-based forest soil inventories such as the nationwide German forest soil survey (GFSI) aim, among other things, at detecting changes in soil properties and plant nutrition. In these types of inventories, the only information on soil phosphorus (P) is commonly the total P content. However, total P content in mineral soils of forests is usually not a meaningful variable to predict the availability of P to trees. Here we tested a modified sequential P extraction ac-cording to Hedley to determine the distribution of different plant available P fractions in soil samples (0–5 and 10–30 cm depth) from 146 GFSI sites, capturing a wide variety of soil conditions. In addition, we analyzed relationships between these P fractions and common soil proper-ties such as pH, texture, and organic Carbon content (SOC). Total P content among our samples ranged from approximately 60 up to 2800 mg kg−1. The labile, moderately labile, and stable P fractions contributed to 27 %, 51 % and 22 % of total P content, respectively, at 0–5 cm depth. At 10–30 cm depth, the labile P fractions decreased to 15 %, whereas the stable P fractions in-creased to 30 %. These changes with depth were accompanied by a decrease in the organic P fractions. High P contents were related with high pH-values. Whereas the labile P pool increased with decreasing pH in absolute and relative terms, the stable P pool decreased in absolute and relative terms. Increasing SOC in soils led to significant increases in all P pools and in total P. In sandy soils, the P content across all fractions was lower than in other soil texture types. Multiple linear regressions indicated that P pools and P fractions were moderately well related to soil properties (r2 mostly above 0.5), and sand content of soils had the strongest influence. Foliage P concentrations in Pinus sylvestris were reasonably well explained by the labile and moderately labile P pool (r

show abstract

Remote sensing of canopy nitrogen at regional scale in Mediterranean forests using the spaceborne MERIS Terrestrial Chlorophyll Index

Cited by 15 publications

References 61 publications

Towards comparable assessment of the soil nutrient status across scales—Review and development of nutrient metrics

Towards comparable assessment of the soil nutrient status across scales—Review and development of nutrient metrics

Monitoring Effects of Drought on Nitrogen and Phosphorus in Temperate Oak Forests Using Machine Learning Techniques

Distribution of phosphorus fractions of different plant availability in German forest soils and their relationship to common soil properties and foliar P concentrations

Contact Info

Product

Resources

About