Biologist, Senior Scientist at the Helmholtz Centre of Environmental Research-UFZ, phd in Geography, Habilitation in Geography at Humboldt University Berlin, Scientific Interests: Hyperspectral RS, close-range, air-spaceborne RS, spectral traits in RS in Biodiversity and in Geodiversity, Data Sciences, Linked Open Data approaches, Semantic Data Integration, EcoSystem Integrity - Modelling, Quantitative Landscape Ecology, EBV, GeoEssentials, Licence for microlite and drones, Forest, Ecosystem and Human health monitoring and modelling.
It is a well-known fact that water bodies are crucial for human life, ecosystems and biodiversity... more It is a well-known fact that water bodies are crucial for human life, ecosystems and biodiversity. Therefore, they are subject to regulatory monitoring in terms of water quality. However, land-use intensification, such as open-cast mining activities, can have a direct impact on water quality. Unfortunately, in situ measurements of water quality parameters are spatially limited, costly and time-consuming, which is why we proposed a combination of hyperspectral data, in situ data and simple regression models in this study to estimate and thus monitor various water quality parameters. We focused on the variables of total iron, ferrous iron, ferric iron, sulphate and chlorophyll-a. Unlike other studies, we used a combination of airborne hyperspectral and RGB data to ensure a very high spatial resolution of the data. To investigate the potential of our approach, we conducted simultaneous in situ measurements and airborne hyperspectral/RGB aircraft campaigns at different sites of the Spre...
Inferring conditions about the earth’s surface using remotely sensed electro-optical measurements... more Inferring conditions about the earth’s surface using remotely sensed electro-optical measurements almost always requires the use of ground truth data. Due to the heterogeneity and diversity of the land cover, as well as the distinctions in spectral and geometric resolution of various remote sensing applications an adaptive ground-based reference system is required for an adequate calibration and Validation of the data. Wireless sensor networks are a promising application for a sufficient solution of ground truthing multispectral remotely sensed data. Due to the quick installation and their self-organising behaviour iterative optimal sampling strategies can be performed straightforward. Especially the improvement of atmospheric corrections as well as resampling algorithms of single multispectral channels or derived vegetation indices are great potentials for the data quality management of remote sensing products.
Biodiversity includes multiscalar and multitemporal structures and processes, with different leve... more Biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organization, from genetic to ecosystemic levels. One of the mostly used methods to infer bio- diversity is based on taxonomic approaches and community ecology theories. However, gathering extensive data in the field is difficult due to logistic problems, especially when aiming at modelling biodiversity changes in space and time, which assumes statistically sound sampling schemes. In this context, airborne or satellite remote sensing allow information to be gathered over wide areas in a reasonable time. Most of the biodiversity maps obtained from remote sensing have been based on the inference of species richness by regression analysis. On the contrary, estimating compositional turnover (β-diversity) might add crucial information related to relative abundance of dif- ferent species instead of just richness. Presently, few studies have addressed the measurement of species compositional turnover from space. Extending on previous work, in this manuscript we propose novel techniques to measure β-diversity from airborne or satellite remote sensing, mainly based on: i) multivariate statistical analysis, ii) the spectral species concept, iii) self-organizing feature maps, iv) multi- dimensional distance matrices, and the v) Rao’s Q diversity. Each of these measures addresses one or several issues related to turnover measurement. This manuscript is the first methodological example encompassing (and enhancing) most of the available methods for estimating β-diversity from remotely sensed imagery and potentially relating them to species diversity in the field
While held to be a means for climate change adaptation and mitigation, nature-based solutions (Nb... more While held to be a means for climate change adaptation and mitigation, nature-based solutions (NbS) themselves are vulnerable to climate change. To find ways of compensating for this vulnerability we combine a focused literature review on how information technology has been used to strengthen positive social–ecological–technological feedback, with the development of a prototype decision-support tool. Guided by the literature review, the tool integrates recent advances in using globally available remote sensing data to elicit information on functional diversity and ecosystem service provisioning with information on human service demand and population vulnerability. When combined, these variables can inform climate change adaptation strategies grounded in local social–ecological realities. This type of integrated monitoring and packaging information to be actionable have potential to support NbS management and local knowledge building for context-tailored solutions to societal challen...
The heat waves and droughts of 2018 / 2019 and in 2020 have had a devastating impact on the funct... more The heat waves and droughts of 2018 / 2019 and in 2020 have had a devastating impact on the functioning of ecosystems and have led to an increasing vulnerability beyond the duration of heat waves (e.g. degradation and increased erosion, reduced carbon uptake by vegetation, modulated energy balance). Such impacts also include loss of agricultural production. A better understanding of the progression and the consequences of heatwaves and droughts is essential for the development and improvement of adaptation and protection measures. The airborne remote sensing event campaign performed in the agricultural area of the 'Magdeburger Boerde' in Central Germany aimed at providing remote sensing data sets from different platforms to derive high quality data for improving the understanding of influences and lag effects on hydrologic, biological/biogeochemical and atmospheric processes induced by the summer drought 2020. Multiple recurrences of drought periods in previous years may hav...
The identification of spatial and temporal patterns of soil properties and moisture structures is... more The identification of spatial and temporal patterns of soil properties and moisture structures is an important challenge in environmental and soil monitoring as well as for soil landscape model approaches. This work examines the use of hyperspectral remote sensing techniques for quantifying geophysical parameters from the hyperspectral reflectance of the vegetation canopy. These can be used as proxies of the underlying soil and soil water conditions. Different spectral index derivatives, single band reflectance, and spectral indices from the airborne hyperspectral sensor AISA were quantified and tested in univariate and multivariate regression models for their correlation with geophysical measurements with electromagnetic induction (EMI) and gamma-ray spectrometry. The best univariate models for predicting electrical conductivity based on spectral information were based on the vertical dipole of an EM38DD with an R2 = 0.54 with the spectral index Normalized Pigments Reflectance Inde...
Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring o... more Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. To implement and better understand RS techniques and the spectral indicators derived from them in the monitoring of geomorphology, this paper presents a new perspective for the definition and recording of five characteristics of geomorphodiversity with RS, namely: geomorphic genesis diversity, geomorphic trait diversity, geomorphic structural diversity, geomorphic taxonomic diversity, and geomorphic functional diversity. In this respect, geomorphic trait diversity is the cornerstone and is essential for recording the other four characteristics using RS technologies. All five characteristics are discussed in detail in this paper and reinforced with numerous examples from various RS technologies. Methods for classifying the five characteristics of geomorphodiversity using RS, as well ...
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Birds strongly respond to vegetation structure and composition, yet typical habitat models based ... more Birds strongly respond to vegetation structure and composition, yet typical habitat models based on earth observation (EO) data use pre-classified data such as land use state classes for the habitat modelling. Since this neglects factors of internal spatial composition of the land use classes, we propose a new scheme of deriving multiple continuous indicators of urban vegetation heterogeneity using high-resolution earth observation datasets. The deployed concepts encompass spectral trait variations for the quantification of vegetation heterogeneity as well as subpixel vegetation fractions for the determination of the density of vegetation. Both indicators are derived from RapidEye data, thus featuring a continuous resolution of 5 meters. Using these indicators of plant heterogeneity and quantity as predictors, we can model the breeding bird habitats with a random forest machine learning classifier for our case study Leipzig while exclusively using one input dataset. Separate models ...
Vegetation diversity and health is multidimensional and only partially understood due to its comp... more Vegetation diversity and health is multidimensional and only partially understood due to its complexity. So far there is no single monitoring approach that can sufficiently assess and predict vegetation health and resilience. To gain a better understanding of the different remote sensing (RS) approaches that are available, this chapter reviews the range of Earth observation (EO) platforms, sensors, and techniques for assessing vegetation diversity. Platforms include close-range EO platforms, spectral laboratories, plant phenomics facilities, ecotrons, wireless sensor networks (WSNs), towers, air- and spaceborne EO platforms, and unmanned aerial systems (UAS). Sensors include spectrometers, optical imaging systems, Light Detection and Ranging (LiDAR), and radar. Applications and approaches to vegetation diversity modeling and mapping with air- and spaceborne EO data are also presented. The chapter concludes with recommendations for the future direction of monitoring vegetation divers...
Modelling dataset and fractional vegetation cover dataset used in the study "Earth observati... more Modelling dataset and fractional vegetation cover dataset used in the study "Earth observation based indication for avian species distribution models using the spectral trait concept and machine learning in an urban setting" Wellmann et al. 2020.
Presentations of the Scientific Colloquium 'Perspectives on the Use of Remote Sensing in Plan... more Presentations of the Scientific Colloquium 'Perspectives on the Use of Remote Sensing in Plant Health' organised by the European and Mediterranean Plant Protection Organization and the Euphresco network for phytosanitary research coordination and funding. Presentation Brown: Remote Sensing, an overview Presentation Lausch: Understanding forest health by remote sensing Presentation Beck: Early detection of diseases in forests and agricultural crops using advanced aircraft-based imaging Presentation D'Onghia: The application of remote sensing in the official monitoring of Citrus tristeza virus and Xylella fastidiosa Presentation Nelson: Developments in remote sensing platforms, data and services Presentation Christiaens: The use of remote sensing:complex regulation and economic feasibility Presentation Skoneczny: Life+ HESOFF Presentation D'Onghia and Brown: The applications of remote sensing in plant health
Hyperspektraldaten stellen für die Forschung eine sehr bedeutsame Auswertegrundlage dar, da sie a... more Hyperspektraldaten stellen für die Forschung eine sehr bedeutsame Auswertegrundlage dar, da sie aufgrund ihrer geometrischen als auch spektralen Eigenschaften eine Vielzahl unterschiedlicher Anwendungsgebiete (z.B. Gewässerzustandserfassung, Vegetationsklassifizierungen, Charakterisierung physikalisch-biochemischer Vegetationsparameter, Strukturierung und Zusammensetzung des Bodens, Erfassung von großflächigen Bodenkontaminationen) eröffnen. Es besteht somit ein sehr hoher Bedarf an Hyperspektralinformationen. Der Einsatz von kommerziellen Hyperspektraldaten ist jedoch mit einer Vielzahl von Problemen verbunden. So sind Forschungen hinsichtlich unterschiedlichen räumlich/hierarchischer als auch zeitlichen Skalen mit Hyperspektraldaten nur sehr schwer möglich, andererseits existieren keine Untersuchungen zu kausalen Zusammenhängen zwischen abbildenden Hyperspektralsignalen und interessierenden Zielgrößen. Am HELMHOLTZ Zentrum für Umweltforschung UFZ Leipzig wurde eine skalenspezifisc...
Heterogeneity of agricultural landscapes is supposed to be of significant importance for species ... more Heterogeneity of agricultural landscapes is supposed to be of significant importance for species diversity in agroecosystems (Weibull et al. 2003). Thus it is necessary to account for structural aspects of landscapes in land management decision processes. Spatial optimization models of land use can serve as tools for decision support. These models can aim at various landscape functions like nutrient leaching and economical aspects (Seppelt and Voinov 2002), water quality (Randhir et al. 2000) or habitat suitability (Nevo and Garcia 1996). However neighbourhood effects stay unconsidered in these approaches. In this paper we present an optimization model concept that aims at maximizing habitat suitability of selected species by identifying optimum spatial configurations of agricultural land use patterns. Bird species with diverging habitat requirements were chosen as target species. Habitat suitability models for these species are used to set up the performance criterion. Landscape st...
It is a well-known fact that water bodies are crucial for human life, ecosystems and biodiversity... more It is a well-known fact that water bodies are crucial for human life, ecosystems and biodiversity. Therefore, they are subject to regulatory monitoring in terms of water quality. However, land-use intensification, such as open-cast mining activities, can have a direct impact on water quality. Unfortunately, in situ measurements of water quality parameters are spatially limited, costly and time-consuming, which is why we proposed a combination of hyperspectral data, in situ data and simple regression models in this study to estimate and thus monitor various water quality parameters. We focused on the variables of total iron, ferrous iron, ferric iron, sulphate and chlorophyll-a. Unlike other studies, we used a combination of airborne hyperspectral and RGB data to ensure a very high spatial resolution of the data. To investigate the potential of our approach, we conducted simultaneous in situ measurements and airborne hyperspectral/RGB aircraft campaigns at different sites of the Spre...
Inferring conditions about the earth’s surface using remotely sensed electro-optical measurements... more Inferring conditions about the earth’s surface using remotely sensed electro-optical measurements almost always requires the use of ground truth data. Due to the heterogeneity and diversity of the land cover, as well as the distinctions in spectral and geometric resolution of various remote sensing applications an adaptive ground-based reference system is required for an adequate calibration and Validation of the data. Wireless sensor networks are a promising application for a sufficient solution of ground truthing multispectral remotely sensed data. Due to the quick installation and their self-organising behaviour iterative optimal sampling strategies can be performed straightforward. Especially the improvement of atmospheric corrections as well as resampling algorithms of single multispectral channels or derived vegetation indices are great potentials for the data quality management of remote sensing products.
Biodiversity includes multiscalar and multitemporal structures and processes, with different leve... more Biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organization, from genetic to ecosystemic levels. One of the mostly used methods to infer bio- diversity is based on taxonomic approaches and community ecology theories. However, gathering extensive data in the field is difficult due to logistic problems, especially when aiming at modelling biodiversity changes in space and time, which assumes statistically sound sampling schemes. In this context, airborne or satellite remote sensing allow information to be gathered over wide areas in a reasonable time. Most of the biodiversity maps obtained from remote sensing have been based on the inference of species richness by regression analysis. On the contrary, estimating compositional turnover (β-diversity) might add crucial information related to relative abundance of dif- ferent species instead of just richness. Presently, few studies have addressed the measurement of species compositional turnover from space. Extending on previous work, in this manuscript we propose novel techniques to measure β-diversity from airborne or satellite remote sensing, mainly based on: i) multivariate statistical analysis, ii) the spectral species concept, iii) self-organizing feature maps, iv) multi- dimensional distance matrices, and the v) Rao’s Q diversity. Each of these measures addresses one or several issues related to turnover measurement. This manuscript is the first methodological example encompassing (and enhancing) most of the available methods for estimating β-diversity from remotely sensed imagery and potentially relating them to species diversity in the field
While held to be a means for climate change adaptation and mitigation, nature-based solutions (Nb... more While held to be a means for climate change adaptation and mitigation, nature-based solutions (NbS) themselves are vulnerable to climate change. To find ways of compensating for this vulnerability we combine a focused literature review on how information technology has been used to strengthen positive social–ecological–technological feedback, with the development of a prototype decision-support tool. Guided by the literature review, the tool integrates recent advances in using globally available remote sensing data to elicit information on functional diversity and ecosystem service provisioning with information on human service demand and population vulnerability. When combined, these variables can inform climate change adaptation strategies grounded in local social–ecological realities. This type of integrated monitoring and packaging information to be actionable have potential to support NbS management and local knowledge building for context-tailored solutions to societal challen...
The heat waves and droughts of 2018 / 2019 and in 2020 have had a devastating impact on the funct... more The heat waves and droughts of 2018 / 2019 and in 2020 have had a devastating impact on the functioning of ecosystems and have led to an increasing vulnerability beyond the duration of heat waves (e.g. degradation and increased erosion, reduced carbon uptake by vegetation, modulated energy balance). Such impacts also include loss of agricultural production. A better understanding of the progression and the consequences of heatwaves and droughts is essential for the development and improvement of adaptation and protection measures. The airborne remote sensing event campaign performed in the agricultural area of the 'Magdeburger Boerde' in Central Germany aimed at providing remote sensing data sets from different platforms to derive high quality data for improving the understanding of influences and lag effects on hydrologic, biological/biogeochemical and atmospheric processes induced by the summer drought 2020. Multiple recurrences of drought periods in previous years may hav...
The identification of spatial and temporal patterns of soil properties and moisture structures is... more The identification of spatial and temporal patterns of soil properties and moisture structures is an important challenge in environmental and soil monitoring as well as for soil landscape model approaches. This work examines the use of hyperspectral remote sensing techniques for quantifying geophysical parameters from the hyperspectral reflectance of the vegetation canopy. These can be used as proxies of the underlying soil and soil water conditions. Different spectral index derivatives, single band reflectance, and spectral indices from the airborne hyperspectral sensor AISA were quantified and tested in univariate and multivariate regression models for their correlation with geophysical measurements with electromagnetic induction (EMI) and gamma-ray spectrometry. The best univariate models for predicting electrical conductivity based on spectral information were based on the vertical dipole of an EM38DD with an R2 = 0.54 with the spectral index Normalized Pigments Reflectance Inde...
Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring o... more Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. To implement and better understand RS techniques and the spectral indicators derived from them in the monitoring of geomorphology, this paper presents a new perspective for the definition and recording of five characteristics of geomorphodiversity with RS, namely: geomorphic genesis diversity, geomorphic trait diversity, geomorphic structural diversity, geomorphic taxonomic diversity, and geomorphic functional diversity. In this respect, geomorphic trait diversity is the cornerstone and is essential for recording the other four characteristics using RS technologies. All five characteristics are discussed in detail in this paper and reinforced with numerous examples from various RS technologies. Methods for classifying the five characteristics of geomorphodiversity using RS, as well ...
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Birds strongly respond to vegetation structure and composition, yet typical habitat models based ... more Birds strongly respond to vegetation structure and composition, yet typical habitat models based on earth observation (EO) data use pre-classified data such as land use state classes for the habitat modelling. Since this neglects factors of internal spatial composition of the land use classes, we propose a new scheme of deriving multiple continuous indicators of urban vegetation heterogeneity using high-resolution earth observation datasets. The deployed concepts encompass spectral trait variations for the quantification of vegetation heterogeneity as well as subpixel vegetation fractions for the determination of the density of vegetation. Both indicators are derived from RapidEye data, thus featuring a continuous resolution of 5 meters. Using these indicators of plant heterogeneity and quantity as predictors, we can model the breeding bird habitats with a random forest machine learning classifier for our case study Leipzig while exclusively using one input dataset. Separate models ...
Vegetation diversity and health is multidimensional and only partially understood due to its comp... more Vegetation diversity and health is multidimensional and only partially understood due to its complexity. So far there is no single monitoring approach that can sufficiently assess and predict vegetation health and resilience. To gain a better understanding of the different remote sensing (RS) approaches that are available, this chapter reviews the range of Earth observation (EO) platforms, sensors, and techniques for assessing vegetation diversity. Platforms include close-range EO platforms, spectral laboratories, plant phenomics facilities, ecotrons, wireless sensor networks (WSNs), towers, air- and spaceborne EO platforms, and unmanned aerial systems (UAS). Sensors include spectrometers, optical imaging systems, Light Detection and Ranging (LiDAR), and radar. Applications and approaches to vegetation diversity modeling and mapping with air- and spaceborne EO data are also presented. The chapter concludes with recommendations for the future direction of monitoring vegetation divers...
Modelling dataset and fractional vegetation cover dataset used in the study "Earth observati... more Modelling dataset and fractional vegetation cover dataset used in the study "Earth observation based indication for avian species distribution models using the spectral trait concept and machine learning in an urban setting" Wellmann et al. 2020.
Presentations of the Scientific Colloquium 'Perspectives on the Use of Remote Sensing in Plan... more Presentations of the Scientific Colloquium 'Perspectives on the Use of Remote Sensing in Plant Health' organised by the European and Mediterranean Plant Protection Organization and the Euphresco network for phytosanitary research coordination and funding. Presentation Brown: Remote Sensing, an overview Presentation Lausch: Understanding forest health by remote sensing Presentation Beck: Early detection of diseases in forests and agricultural crops using advanced aircraft-based imaging Presentation D'Onghia: The application of remote sensing in the official monitoring of Citrus tristeza virus and Xylella fastidiosa Presentation Nelson: Developments in remote sensing platforms, data and services Presentation Christiaens: The use of remote sensing:complex regulation and economic feasibility Presentation Skoneczny: Life+ HESOFF Presentation D'Onghia and Brown: The applications of remote sensing in plant health
Hyperspektraldaten stellen für die Forschung eine sehr bedeutsame Auswertegrundlage dar, da sie a... more Hyperspektraldaten stellen für die Forschung eine sehr bedeutsame Auswertegrundlage dar, da sie aufgrund ihrer geometrischen als auch spektralen Eigenschaften eine Vielzahl unterschiedlicher Anwendungsgebiete (z.B. Gewässerzustandserfassung, Vegetationsklassifizierungen, Charakterisierung physikalisch-biochemischer Vegetationsparameter, Strukturierung und Zusammensetzung des Bodens, Erfassung von großflächigen Bodenkontaminationen) eröffnen. Es besteht somit ein sehr hoher Bedarf an Hyperspektralinformationen. Der Einsatz von kommerziellen Hyperspektraldaten ist jedoch mit einer Vielzahl von Problemen verbunden. So sind Forschungen hinsichtlich unterschiedlichen räumlich/hierarchischer als auch zeitlichen Skalen mit Hyperspektraldaten nur sehr schwer möglich, andererseits existieren keine Untersuchungen zu kausalen Zusammenhängen zwischen abbildenden Hyperspektralsignalen und interessierenden Zielgrößen. Am HELMHOLTZ Zentrum für Umweltforschung UFZ Leipzig wurde eine skalenspezifisc...
Heterogeneity of agricultural landscapes is supposed to be of significant importance for species ... more Heterogeneity of agricultural landscapes is supposed to be of significant importance for species diversity in agroecosystems (Weibull et al. 2003). Thus it is necessary to account for structural aspects of landscapes in land management decision processes. Spatial optimization models of land use can serve as tools for decision support. These models can aim at various landscape functions like nutrient leaching and economical aspects (Seppelt and Voinov 2002), water quality (Randhir et al. 2000) or habitat suitability (Nevo and Garcia 1996). However neighbourhood effects stay unconsidered in these approaches. In this paper we present an optimization model concept that aims at maximizing habitat suitability of selected species by identifying optimum spatial configurations of agricultural land use patterns. Bird species with diverging habitat requirements were chosen as target species. Habitat suitability models for these species are used to set up the performance criterion. Landscape st...
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