Clement Atzberger

• PhD
• Head of Research at Mantle Labs Ltd

Monitoring soil moisture (SM) on individual crop fields is of great interest for agricultural applications. Synthetic aperture radar (SAR) systems such as Sentinel-1 provide sensitivity to surface SM at a spatial resolution compatible with crop-field monitoring. Different algorithms have been proposed to relate SAR backscattering to SM, yet most ov...

Remote sensing (RS) spectral time series provide a substantial source of information for the regular and cost-efficient monitoring of the Earth’s surface. Important monitoring tasks include land use and land cover classification, change detection, forest monitoring and crop type identification, among others. To develop accurate solutions for RS-bas...

The detection of grassland cuts is relevant for modelling grassland yield and quality because information on cut dates and cut intensity aids in the modelling of the nutrient biomass ratio of fodder. This research improves an existing grassland cut detection methodology developed for Austria based on Sentinel-2 (S2) optical time series. To further...

If you are interested in learning more on the use of EO for agriculture, you will find a number of interesting thoughts here ...

Mangroves play pivotal roles in ecosystem services, but anthropogenic pressures contribute to their alarming degradation. Precise quantification of vital vegetation characteristics, particularly leaf area index (LAI), is crucial for effective monitoring. LAI serves as a key biophysical parameter in assessing vegetation structure, ecophysiological p...

Scientists often model physical processes to understand the natural world and uncover the causation behind observations. Due to unavoidable simplification, discrepancies often arise between model predictions and actual observations, in the form of systematic biases, whose impact varies with model completeness. Classical model inversion methods such...

Timely and accurate crop acreage information is essential for food security and the informed decision-making by governmental bodies and stakeholders in the agro-economic system. Surveys and fieldwork are expensive and time consuming, and the information is usually only released after the cropping season. Remote sensing technology is inexpensive, sc...

Soil organic carbon (SOC) measurements are an indicator of soil health and an important parameter for the study of land-atmosphere carbon fluxes. Field sampling provides precise measurements at the sample location but entails high costs and cannot provide detailed maps unless the sampling density is very high. Remote sensing offers the possibility...

The start of the growing season (SOS) in grasslands is a critical factor that significantly affectsgrassland dynamics, production and quality. In the context of grassland fodder production, theexact detection of the start of the growing season allows farmers and land managers toprecisely plan harvest schedules for hay production or silage making. H...

Timely and accurate estimates of sugarcane yield provide valuable information for food management, bio-energy production, (inter)national trade, industry planning and government policy. Remote sensing and machine learning approaches can improve sugarcane yield estimation. Previous attempts have however often suffered from too few training samples d...

Vegetation productivity is a critical indicator of global ecosystem health and is impacted by human activities and climate change. A wide range of optical sensing platforms, from ground-based to airborne and satellite, provide spatially continuous information on terrestrial vegetation status and functioning. As optical Earth observation (EO) data a...

Satellite-based monitoring is a key tool for supporting global food security and natural resource management but is challenged by cloud corruption and lack of labelled training data. To address these issues, self-supervised learning (SSL) techniques have been developed that first learn representations from almost limitless available unlabeled data,...

The Remote Sensing (RS) field continuously grapples with the challenge of transforming satellite data into actionable information. This ongoing issue results in an ever-growing accumulation of unlabeled data, complicating interpretation efforts. The situation becomes even more challenging when satellite data must be used immediately to identify the...

Non-photosynthetic vegetation (NPV) is considered a key quantifiable variable in the context of new spaceborne imaging spectroscopy missions. Knowledge of NPV is essential for all terrestrial ecosystems, and its mapping is beneficial for agriculture and forestry. In agriculture, crop residues (CR) play an important role in tillage, erosion control...

The problem of estimating earthquake risk is one of the primary themes for researchers and investigators in the field of geosciences. The combined assessment of spatial probability and the determination of earthquake risk at large scales is challenging. To the best of the authors’ knowledge, there no updated earthquake-hazard-and-risk assessments f...

The special issue “Tree species diversity mapping” presents research focused on the remote assessment of tree species diversity, using different sensor modalities and platforms. The special issue thereby recognizes that the continued loss of biodiversity poses a great challenge to humanity. Precise and regularly updated baseline information is urge...

The relationship between yield and quality of grassland fodder is an important factor for livestock farmers to consider when deciding the timing of grassland cuts. Even for experienced farmers, estimating this relationship is difficult because external factors such as weather can affect the growth rate of plants. Satellite remote sensing techniques...

Afforestation, reforestation and revegetation (ARR) projects, such as converting degraded pasture into agroforestry systems (AFSs), are among the most promising strategies for atmospheric CO2 removal (CDR). As project-related climate change mitigation only exists if CO2 removal would not have occurred in the absence of the project implementation, t...

Vegetation phenology reflects the temporal dynamics of vegetation growth and is an important indicator of climate change. However, differences consistently exist in land surface phenology derived at different spatial scales, which hinders the understanding of phenological events and integration of land surface phenology products from different scal...

The main objective of this study is to investigate land degradation and environmental change in Mongolia using time series of multi-sources remotely sensed data and advanced approaches. As the data analysis techniques, the Random Forest (RF) classifier, Ordinary Least Square (OLS), and Partial Least Square (PLS) regressions, Break for Additive Seas...

Understanding how biophysical and biochemical variables contribute to the spectral characteristics of vegetation canopies is critical for their monitoring. Quantifying these contributions, however, remains difficult due to extraneous factors such as the spectral variability of canopy background materials, including soil/crop-residue moisture, soil-...

This investigation evaluates the potential of combining Copernicus Sentinel-1 (S1) and Sentinel-2 (S2) satellite data in producing a detailed Land Use and Land Cover (LULC) map with 19 crop type classes and 2 broader categories containing Woodland/Shrubland and Grassland over 28 Member States of Europe (EU-28). The Eurostat Land Use and Coverage Ar...

Quantum yield of fluorescence (φF) is key to interpret remote measurements of sun-induced fluorescence (SIF), and whether the SIF signal is governed by photochemical quenching (PQ) or non-photochemical quenching (NPQ). Disentangling PQ from NPQ allows using SIF estimates in various applications in aquatic optics. However, obtaining φF is challengin...

The accurate and timely prediction of crop yield at a large scale is important for food security and the development of agricultural policy. An adaptable and robust method for estimating maize yield for the entire territory of China, however, is currently not available. The inherent trade-off between early estimates of yield and the accuracy of yie...

Crop production and productivity monitoring play a crucial role for food security and livelihoods, international trade and sustainable agricultural practices. Earth Observation (EO) data provides high spectral, spatial and temporal data for various agricultural applications. However, mapping and monitoring small crop fields and complex landscapes a...

Microwave and optical imaging methods react differently to different land surface parameters and, thus, provide highly complementary information. However, the contribution of individual features from these two domains of the electromagnetic spectrum for tree species classification is still unclear. For large-scale forest assessments, it is moreover...

Grasslands are an important part of pre-Alpine and Alpine landscapes. Despite the economic value and the significant role of grasslands in carbon and nitrogen (N) cycling, spatially explicit information on grassland biomass and quality is rarely available. Remotely sensed data from unmanned aircraft systems (UASs) and satellites might be an option...

East Africa has experienced a number of devastating droughts in recent decades, including the 2010/2011 drought. The National Drought Management Authority in Kenya relies on real-time information from MODIS satellites to monitor and respond to emerging drought conditions in the arid and semi-arid lands of Kenya. Providing accurate and timely inform...

One of the most challenging aspects of obtaining detailed and accurate land-use and land-cover (LULC) maps is the availability of representative field data for training and validation. In this manuscript, we evaluate the use of the Eurostat Land Use and Coverage Area frame Survey (LUCAS) 2018 data to generate a detailed LULC map with 19 crop type c...

Vitality loss of trees caused by extreme weather conditions, drought stress or insect infestations, are expected to increase with ongoing climate change. The detection of vitality loss at an early stage is thus of vital importance for forestry and forest management to minimize ecological and economical damage. Remote sensing instruments are able to...

Earth observation data play a vital role for efficient modeling of invasive species. Particularly, optical Sentinel-2 (S2) data with its capability of providing high spatial, spectral and temporal resolutions creates ample opportunities. However, few studies so far evaluated the combined use of S2 derived variables and environmental variables for m...

Despite the low area coverage, riparian vegetation presents several ecosystem services. But there is no precise spatial information on these ecosystems in Iran. Considering the lack of such information, mapping and providing a spatial database is essential. Due to the mixture of these vegetation types and other land covers, the detection of these t...

Accurate modeling of invasive species in areas of limited distribution of meteorological stations is challenging. In this regard, climate records from satellites are good alternatives. However, the accuracy of these datasets needs to be validated and their performance should be evaluated. Hence, this study aimed at evaluating the performance of fou...

Grasslands are an important part of pre-Alpine and Alpine landscapes. Despite the economic value and the significant role of grasslands in carbon and nitrogen (N) cycling, spatially explicit information on grassland biomass and quality is rarely available. Remotely sensed data from unmanned aircraft systems (UAS) and satellites might be an option t...

A large number of studies have been published addressing sugarcane management and monitoring to increase productivity and production as well as to better understand landscape dynamics and environmental threats. Building on existing reviews which mainly focused on the crop’s spectral behavior, a comprehensive review is provided which considers the p...

Zusammenfassung Im Forschungsprojekt FATIMA (FArming Tools for external nutrient Inputs and water MAnagement) wurde ein integrierter Ansatz für die Optimierung des Stickstoffmanagements in der Landwirtschaft gewählt. Neben der technischen Komponente, die die Verarbeitung von Sentinel-2-Satellitendaten umfasste, wurden auch die sozio-ökonomischen As...

Grasslands in their various forms of appearance characterize the pre-Alpine landscape. Despite the economic value and significant role of plants in grassland carbon and nitrogen cycling, spatially explicit information on grassland biomass are rarely available. This study aims to develop routines to monitor grassland traits at different spatial scal...

Zanthoxylum bungeanum Maxim (ZBM) is an important woody species in large parts of Asia, which provides oils and medicinal materials. Timely and accurate mapping of its spatial distribution and planting area is of great significance to local economy and ecology. As a special tree species planted in the Grain for Green Program of China, Linxia Hui Au...

Global maps of bioclimatic variables currently exist only at very coarse spatial resolution (e.g. World-Clim). For ecological studies requiring higher resolved information, this spatial resolution is often insufficient. The aim of this study is to estimate important bioclimatic variables of Mongolia from Earth Observation (EO) data at a higher spat...

Background Species Distribution Modelling (SDM) coupled with freely available multispectral imagery from Sentinel-2 (S2) satellite provides an immense contribution in monitoring invasive species. However, attempts to evaluate the performances of SDMs using S2 spectral bands and S2 Radiometric Indices (S2-RIs) and biophysical variables, in particula...

Prediction and modeling using integrated datasets and expertise from various disciplines greatly improve the management of invasive species. So far several attempts have been made to predict, handle, and mitigate invasive alien species impacts using specific efforts from various disciplines. Yet, the most persuasive approach is to better control it...

Economic theory notes tenure security is a critical factor in agricultural investment and productivity. Therefore, several African countries' development initiatives enabled land titling to enhance tenure security. This paper examines the effect of land certification on tenure security, land investment, crop productivity and land dispute in Gozamin...

The use of deep learning (DL) approaches for the analysis of remote sensing (RS) data is rapidly increasing. DL techniques have provided excellent results in applications ranging from parameter estimation to image classification and anomaly detection. Although the vast majority of studies report precision indicators, there is a lack of studies deal...

Sparse vegetation such as riparian forests and trees outside forests (TOF) cover only small areas but present various ecological advantages. The detection of these vegetation types in semi-arid mountainous areas is challenging as trees are heavily mixed with other land cover types. Their mapping requires therefore high-resolution imagery. We propos...

If you want to learn more on the use of Earth Observation (EO) data for forestry, you will find some good ideas here ...

Land cover patterns in sub-Saharan Africa are rapidly changing. This study aims to quantify the land cover change and to identify its major determinants by using the Drivers, Pressures, State, Impact, Responses (DPSIR) framework in the Ethiopian Gozamin District over a period of 32 years (1986 to 2018). Satellite images of Landsat 5 (1986), Landsat...

Wildfires are becoming an increasing threat to human health, infrastructure, forestry, agriculture and biodiversity. In Alpine regions, fires are often at the start of cascading risks including avalanches, mudslides or rock fall due to the loss of forest and vegetation layers. Additionally, wildfires are expected to occur more frequently in the fut...

High-throughput crop phenotyping is harnessing the potential of genomic resources for the genetic improvement of crop production under changing climate conditions. As global food security is not yet assured, crop phenotyping has received increased attention during the past decade. This spectral issue (SI) collects 30 papers reporting research on es...

This work aims at addressing two issues simultaneously: data compression at input space and semantic segmentation. Semantic segmentation of remotely sensed multi- or hyperspectral images through deep learning (DL) artificial neural networks (ANN) delivers as output the corresponding matrix of pixels classified elementwise, achieving competitive per...

Qinghai Province is one of the four largest pastoral regions in China. Timely monitoring of grass growth and accurate estimation of grass yields are essential for its ecological protection and sustainable development. To estimate grass yields in Qinghai, we used the normalized difference vegetation index (NDVI) time-series data derived from the Mod...

In diesem Beitrag werden die Bereiche Umweltdatenmanagement und Umweltstatistik vorgestellt und ihre Anwendung in der Umweltökonomie beispielhaft gezeigt. Dafür sind Kenntnisse und Fertigkeiten zu Management, Modellierung und Bewertung von Umweltdaten mit Raum- und Zeitbezug wichtig. Im Bachelorstudium UBRM werden dazu Grundlagen vermittelt, die im...

For improved drought planning and response, there is an increasing need for highly predictive and stable drought prediction models. This paper presents the performance of both homogeneous and heterogeneous model ensembles in the satellite-based prediction of drought severity using artificial neural networks (ANN) and support vector regression (SVR)...

Crop phenology is an important parameter for crop growth monitoring, yield prediction, and growth simulation. The dynamic threshold method is widely used to retrieve vegetation phenology from remotely sensed vegetation index time series. However, crop growth is not only driven by natural conditions, but also modified through field management activi...

Detailed knowledge about tree species composition is of great importance for forest management. The two identical European Space Agency (ESA) Sentinel-2 (S2) satellites provide data with unprecedented spectral, spatial and temporal resolution. Here, we investigated the potential benefits of using high temporal resolution data for classification of...

The objective of this research was to develop a robust statistical model to estimate climatologies (2002-2017) of monthly average near-surface air temperature (Ta) over Mongolia using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) time series products and terrain parameters. Two regression models were analyzed...

In many African countries and especially in the highlands of Ethiopia—the investigation site of this paper—agricultural land is highly fragmented. Small and scattered parcels impede a necessary increase in agricultural efficiency. Land consolidation is a proper tool to solve inefficiencies in agricultural production, as it enables consolidating plo...

There is increasing need for highly predictive and stable models for the prediction of drought as an aid to better planning for drought response. This paper presents the performance of both homogenous and heterogenous model ensembles in the prediction of drought severity using the study case techniques of artificial neural networks (ANN) and suppor...

For those developing satellite-based insurance products, there is no consensus in the scientific community on which of the many available indices most accurately track agro-ecological shocks as experienced by farmers and pastoralists. Furthermore, metrics commonly used by the remote sensing community for assessing the accuracy of indices in retriev...

Droughts, with their increasing frequency of occurrence, especially in the Greater Horn of Africa (GHA), continue to negatively affect lives and livelihoods. For example, the 2011 drought in East Africa caused massive losses, documented to have cost the Kenyan economy over 12 billion US dollars. Consequently, the demand is ever-increasing for ex-an...

Model-based Selection of hyperspectral EnMAP Channels for optimal Inversion of Radiation Transfer Models in Agriculture. Satellite-based hyperspectral Earth observation data combined with physically based radiative transfer models have the strong potential to support sustainable agriculture by providing accurate spatial and temporal information of...

For food crises early warning purposes, coarse spatial resolution NDVI data are widely used to monitor vegetation conditions in near real-time (NRT). Different types of NDVI anomalies are typically employed to assess the current state of crops and rangelands as compared to previous years. Timeliness and accuracy of such anomalies are critical facto...

Droughts, with their increasing frequency of occurrence, continue to negatively affect livelihoods and elements at risk. For example, the 2011 in drought in east Africa has caused massive losses document to have cost the Kenyan economy over $12bn. With the foregoing, the demand for ex-ante drought monitoring systems is ever-increasing. The study us...

Satellite hyperspectral Earth observation missions have strong potential to support sustainable agriculture by providing accurate spatial and temporal information of important vegetation biophysical and biochemical variables. To meet this goal, possible error sources in the modelling approaches should be minimized. Thus, first of all, the capabilit...

Derivation of main land cover classes and a detailed tree species distribution map from Copernicus datasets in UNESCO’s Biosphere Reserve Wienerwald.

Aim Prosopis spp. are an invasive alien plant species native to the Americas and well adapted to thrive in arid environments. In Kenya, several remote‐sensing studies conclude that the genus is well established throughout the country and is rapidly invading new areas. This research aims to model the potential habitat of Prosopis spp. by using an en...

The aim of this study was to develop a robust methodology to estimate pasture biomass across the huge land surface of Mongolia (1.56 × 10⁶ km²) using high-resolution Landsat 8 satellite data calibrated against field-measured biomass samples. Two widely used regression models were compared and adopted for this study: Partial Least Squares (PLS) and...

The aim of this study was to develop a robust methodology to estimate pasture biomass across the huge land surface of Mongolia (1.56 × 106 km2) using high-resolution Landsat 8 satellite data calibrated against field-measured biomass samples. Two widely used regression models were compared and adopted for this study: Partial Least Squares (PLS) and...

The Sentinel-2 mission of the ESA’s Copernicus programme is generating unprecedented volumes of data at high spatial, spectral and temporal resolutions. The objective of this short communication is to assess the value of multi-temporal information for crop type classification using Sentinel-2 data. The analysis is carried out in an agricultural reg...

Die Vitalität vieler Baumarten ist durch den Klimawandel und die damit einhergehenden Wetteränderungen stark gefährdet. Der Bedarf an kostengünstigen Methoden zum großfl ächigen Monitoring von Waldfl ächen ist deshalb von großer Bedeutung. Im Projekt VitTree der Bayerischen Forstverwaltung wurde von einem Projektteam aus BOKU Wien, DLR, BaySF, ÖBf...

Knowledge of the distribution of tree species within a forest is key for multiple economic and ecological applications. This information is traditionally acquired through time-consuming and thereby expensive field work. Our study evaluates the suitability of a visible to near-infrared (VNIR) hyperspectral dataset with a spatial resolution of 0.4 m...

Agricultural land use and cropping patterns are closely related to food production, soil degradation, water resource management, greenhouse gas emission, and regional climate alterations. Methods for reliable and cost-efficient mapping of cropping pattern, as well as their changes over space and time, are therefore urgently needed. To cope with thi...

This study aims to explain effects of soil textural class, topography, land-use and land-use history on soil GHG fluxes in the Lake Victoria region. We measured GHG fluxes from intact soil cores collected in Rakai, Uganda, an area characterized by low-input smallholder (<2 ha) farming systems, typical for the East African highlands. The soil cores...

Upcoming satellite hyperspectral sensors require powerful and robust methodologies for making optimum use of the rich spectral data. This paper reviews the widely applied coupled PROSPECT and SAIL radiative transfer models (PROSAIL), regarding their suitability for the retrieval of biophysical and biochemical variables in the context of agricultura...

Klimawandelbedingte Wetteränderungen führen oftmals zur Verringerung der Vitalität von Bäumen. Mehrere Hauptbaumarten haben deshalb ein gesteigertes Gefährdungspotenzial. Dadurch steigt der Bedarf an kostengünstigen, rasch durchführbaren Methoden zum großflächigen Monitoring von Waldflächen. Das Projekt »VitTree« untersucht, in welchem Ausmaß und a...