Teja Kattenborn

University of Leipzig · Remote Sensing Center for Earth System Research

Question Do spatial gradients of plant strategies correspond to patterns of plant traits obtained from a physically based model and hyperspectral imagery? It has previously been shown that reflectance can be used to map plant strategies according to the established CSR scheme. So far, these approaches have been based on empirical links and lacked t...

Optical remote sensing is potentially highly informative to track Earth’s plant functional diversity. Yet, causal explanations of how and why plant functioning is expressed in canopy reflectance remain limited. Variation in canopy reflectance can be described by radiative transfer models (here PROSAIL) that incorporate plant traits affecting light...

Photosynthesis is essential for life on earth as it, inter alia, influences the composition of the atmosphere and is the driving mechanism of primary production. Photosynthesis is particularly controlled by leaf pigments such as chlorophyll, carotenoids or anthocyanins. Incoming solar radiation is mainly captured by chlorophyll, whereas plant organ...

Recent technological advances in remote sensing sensors and platforms, such as high-resolution satellite imagers or unmanned aerial vehicles (UAV), facilitate the availability of fine-grained earth observation data. Such data reveal vegetation canopies in high spatial detail. Efficient methods are needed to fully harness this unpreceded source of i...

Climate extremes are on the rise. Impacts of extreme climate and weather events on ecosystem services and ultimately human well-being can be partially attenuated by the organismic, structural, and functional diversity of the affected land surface. However, the ongoing transformation of terrestrial ecosystems through intensified exploitation and man...

Processes that drive plant invasions play out across multiple spatial and temporal scales. Understanding individual steps along the introduction-naturalization-invasion continuum and its drivers is crucial for management. This review, targeting the broad audience of invasion scientists, field ecologists and land managers, summarizes the state-of-th...

Progress in Earth system science is accelerating rapidly, due to the increasing availability of multivariate datasets, often global, with moderate to high spatio-temporal resolutions. Turning these data into knowledge presents interoperability, technical, analytical, and other challenges. Earth System Data Cubes (ESDCs) have surfaced as essential t...

In high-latitude and high-altitude environments, periglacial landforms created and shaped by freeze-thaw processes are a key geomorphic feature. Many periglacial landforms, such as solifluction lobes, can be vegetated and provide habitats for many different plant species. We know that plant cover and roots affect freezing, thawing and transport of...

Solifluction is the slow downslope movement of soil mass due to freeze-thaw processes. It is widespread on hillslopes in Polar and Alpine regions and contributes substantially to sediment transport. As solifluction lobe movement is in the order of millimeters to centimeters per year, it is difficult to measure with high spatial and temporal resolut...

Large-scale information on several vegetation properties ('plant traits') is critical to assess ecosystem functioning, functional diversity and their role in the Earth system. Hyperspectral remote sensing of plant canopies offers a key tool to map multiple plant traits. However, we are still lacking generalized methods to translate hyper-spectral r...

Foliar traits such as specific leaf area (SLA), leaf nitrogen (N) and phosphorus (P) concentrations play an important role in plant economic strategies and ecosystem functioning. Various global maps of these foliar traits have been generated using statistical upscaling approaches based on in-situ trait observations.Here, we intercompare such global...

Increasing tree mortality due to climate change has been observed globally. Remote sensing is a suitable means for detecting tree mortality and has been proven effective for the assessment of abrupt and large-scale stand-replacing disturbances, such as those caused by windthrow, clear-cut harvesting, or wildfire. Non-stand replacing tree mortality...

Unoccupied aerial vehicles (UAV) with RGB-cameras are affordable and versatile devices for the generation of a series of remote sensing products that can be used for forest inventory tasks, such as creating high-resolution orthomosaics and canopy height models. The latter may serve purposes including tree species identification, forest damage asses...

Global maps of plant functional traits are essential for studying the dynamics of the terrestrial biosphere, yet the spatial distribution of trait measurements remains sparse. With the increasing popularity of species identification apps, citizen scientists contribute to growing vegetation data collections. The question emerges whether such opportu...

Ecosystem restoration and reforestation often operate at large scales, whereas monitoring practices are usually limited to spatially restricted field measurements that are (i) time-and labour-intensive, and (ii) unable to accurately quantify restoration success over hundreds to thousands of hectares. Recent advances in remote sensing technologies p...

Vertical leaf angles and their variation through time are directly related to several ecophysiological processes and properties. However, there is no efficient method for tracking leaf angles of plant canopies under field conditions. Here, we present AngleCam, a deep learning‐based approach to predict leaf angle distributions from horizontal photog...

Deep learning and particularly Convolutional Neural Networks (CNN) in concert with remote sensing are becoming standard analytical tools in the geosciences. A series of studies has presented the seemingly outstanding performance of CNN for predictive modelling. However, the predictive performance of such models is commonly estimated using random cr...

Concerted use of CNN + UAV can close the gap in reference data scarcity Multitemporal, large-scale maps of standing deadwood with high spatial resolution (10 m) Best model with all S1 + S2 bands R² = 0.38 after 5-fold CV Model slope: y = 0.45x + 0.26 Error equally distributed across range Optimization of co-registration improved results Robust acro...

Accurate information on the spatial distribution of plant species and communities is in high demand for various fields of application, such as nature conservation, forestry, and agriculture. A series of studies has shown that Convolutional Neural Networks (CNNs) accurately predict plant species and communities in high-resolution remote sensing data...

Solifluction is the slow downslope movement of soil mass due to freeze-thaw processes. It is widespread on hillslopes in Polar and Alpine regions and contributes substantially to sediment transport. As solifluction lobe movement is in the order of millimeters to centimeters per year, it is tricky to measure with a high spatial and temporal resoluti...

Leaf mass per area (LMA), leaf dry matter content (LDMC) and leaf water content/ equivalent water thickness (EWT) are commonly used functional plant traits in ecology. Whereas spectroscopy has recently proven to be a powerful tool to collect such functional trait information across large scales, it remains unclear whether these reflectance-based tr...

Plant functional traits (‘traits’) are essential for assessing biodiversity and ecosystem processes, but cumbersome to measure. To facilitate trait measurements, we test if traits can be predicted through visible morphological features by coupling heterogeneous photographs from citizen science (iNaturalist) with trait observations (TRY database) th...

Characterizing the spatial variability of the severity of wildfires is important to assess ecological and economic consequences and to coordinate mitigation strategies. Vegetation indices such as the differenced Normalized Burn Ratio (dNBR) have become a standard tool to assess burn or fire severity across larger areas and are being used operationa...

Identifying and characterizing vascular plants in time and space is required in various disciplines, e.g. in forestry, conservation and agriculture. Remote sensing emerged as a key technology revealing both spatial and temporal vegetation patterns. Harnessing the ever growing streams of remote sensing data for the increasing demands on vegetation a...

The use of unmanned aerial vehicles (UAVs) in vegetation remote sensing allows a time-flexible and cost-effective acquisition of very high-resolution imagery. Still, current methods for the mapping of forest tree species do not exploit the respective, rich spatial information. Here, we assessed the potential of convolutional neural networks (CNNs)...

Plant functional traits play a key role in the assessment of ecosystem processes and properties. Optical remote sensing is ascribed a high potential in capturing those traits and their spatiotemporal patterns. In vegetation remote sensing, reflectance-based retrieval methods are either statistical (relying on empirical observations) or physically-b...

Sections ePDFPDF Tools Share Abstract Solifluction is one of the most widespread periglacial processes with low annual movement rates in the range of —millimeters to centimeters. Traditional methods to assess solifluction movement usually have low spatial resolution, which hampers our understanding of spatial movement patterns and the factors cont...

Xylella fastidiosa (Xf) is a harmful plant pathogenic bacterium, able to infect over 500 plant species worldwide. Successful eradication and containment strategies for harmful pathogens require large-scale monitoring techniques for the detection of infected hosts, even when they do not display visual symptoms. Although a previous study using airbor...

Unmanned Aerial Vehicles (UAV) greatly extended our possibilities to acquire high resolution remote sensing data for assessing the spatial distribution of species composition and vegetation characteristics. Yet, current pixel‐ or texture‐based mapping approaches do not fully exploit the information content provided by the high spatial resolution. H...

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research sp...

Peatlands are key reservoirs of belowground carbon (C) and their monitoring is important to assess the rapid changes in the C cycle caused by climate change and direct anthropogenic impacts. Frequently, information of peatland area and vegetation type estimated by remote sensing has been used along with soil measurements and allometric functions to...

The Tibetan Plateau is a unique, biodiverse ecosystem with an important role in the climate and hydrological system of Asia. Its vegetation supports important functions including fodder provision, erosion prevention and water retention. Assessing vegetation trends of the Tibetan Plateau is crucial to understand effects of recent climate and land-us...

With the advent of Sentinel-2, it is now possible to generate large-scale chlorophyll content maps with unprecedented spatial and temporal resolution, suitable for monitoring ecological processes such as vegetative stress and/or decline. However methodological gaps exist for adapting this technology to heterogeneous natural vegetation and for trans...

Plant invasions can result in serious threats for biodiversity and ecosystem functioning. Reliable maps at very‐high spatial resolution are needed to assess invasions dynamics. Field sampling approaches could be replaced by unmanned aerial vehicles (UAVs) to derive such maps. However, pixel‐based species classification at high spatial resolution is...

Feedbacks between geomorphic and vegetation dynamics create spatial patterns of vegetation, soils and landforms in biogeomorphic ecosystems and determine their structure and functioning. In glacier forelands, it was shown that these biogeomorphic feedbacks link paraglacial adjustment and vegetation succession and control landscape development and s...

Introduction Peatlands are key reservoirs of belowground carbon (C) stock and their monitoring is important to assess the rapid changes in the C cycle caused by climate change and anthropogenic impacts. We assessed the use of aboveground vegetation traits as proxies to predict peatland belowground C stock. First, the ecological relations between re...

From tropics to tundra plant life diversified on the basis of adaptations to the local environmental conditions. These adaptations are manifested in the functioning of plants, which among others includes growth, reproduction, competitive abilities or persistence. Plant functioning not only directly relates to community assembly, but also to large s...

Many water quality parameters such as concentrations of suspended matter, nutrients and algae directly or indirectly change the electromagnetic reflectance and transmission properties of surface water bodies. Optical measurement approaches have shown great potential to partially substitute water sampling and laboratory analyses, but are obstructed...

One fundamental metric to characterize trees and forest stands is the diameter at breast height (DBH). However, the vertical geometry of tree stems hampers a direct measurement by means of orthographic aerial imagery. Nevertheless, the DBH in deciduous forest stands could be measured from UAV-based imagery using the width of a stem´s cast shadow pr...

Europe’s major X. fastidiosa outbreaks have progressed steadily in the past years as data on the bacterial strains causing them, and on the host range and vectors of the pathogen in various regions, became available. The initial uncertainty around these critical epidemiological aspects of the X. fastidiosa invasions hampered estimates of their rate...

Abiotic ecosystem properties together with plant species interaction create differences in structural and physiological traits among plant species. Certain plant traits cause a spatial and temporal variation in canopy reflectance that enables the differentiation of plant functional types, using earth observation data. However , it often remains unc...

Plant pathogens cause significant losses to agricultural yields and increasingly threaten food security 1 , ecosystem integrity and societies in general2-5. Xylella fastidiosa is one of the most dangerous plant bacteria worldwide, causing several diseases with profound impacts on agriculture and the environment 6 . Primarily occurring in the Americ...

Solifluction is a widespread periglacial process, resulting in the downslope movement of soil mass with rates of cms/year. Movement is usually determined using point measurements, however, both movement and its controls are spatially variable. To determine spatial movement patterns, we test the applicability of repeated UAV-flights (2014, 2017) and...

Many water quality parameters such as concentrations of suspended matter, nutrients and algae directly or indirectly change the electromagnetic reflectance and transmission properties of surface water bodies. Optical measurement approaches have shown great potential to partially substitute water sampling and laboratory analyses, but are obstructed...

The estimation of various forest inventory attributes from high spatial resolution airborne remote sensing data has been widely examined and proved to be successful at the experimental level. Nevertheless, the operational use of these data in automated procedures to support forest inventories and forest management is still limited to a small number...

Supplementary data for "Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications?"

We used spectral, textural and photogrammetric information from very-high resolution (VHR) stereo satellite data (Pléiades and WorldView-2) to estimate forest biomass across two test sites located in Chile and Germany. We compared Random Forest model performances of different predictor sets (spectral, textural, and photogrammetric), forest inventor...

Spaceborne sensors allow for wide-scale assessments of forest ecosystems. Combining the products of multiple sensors is hypothesized to improve the estimation of forest biomass. We applied interferometric (Tandem-X) and photogrammetric (WorldView-2) based predictors, e.g. canopy height models, in combination with hyperspectral predictors (EO1-Hyper...

For reasons of documentation, management and certification there is a high interest in efficient inventories of palm plantations on the single plant level. Recent developments in unmanned aerial vehicle (UAV) technology facilitate spatial and temporal flexible acquisition of high resolution 3D data. Common single tree detection approaches are based...