Christopher Conrad

• Professor at Martin Luther University Halle-Wittenberg

West Africa’s vulnerability to climate change is influenced by a complex interplay of socio-economic and environmental factors, exacerbated by the region’s reliance on rain-fed agriculture. Climate variability, combined with rapid population growth, intensifies existing socio-economic challenges. Migration has become a key adaptive response to thes...

In the face of unabated urban expansion, understanding the intrinsic characteristics of landscape structure is pertinent to preserving ecological diversity and managing the supply of ecosystem services. This study integrates machine-learning-based geospatial and landscape ecological techniques to assess the dynamics of landscape structure in cities...

Random Forest (RF) is a widely used machine learning algorithm for crop type mapping. RF's variable importance aids in dimension reduction and identifying relevant multisource hyperspectral data. In this study, we examined spatial effects in a sequential backward feature elimination setting using RF variable importance in the example of a large-sca...

Additional water supply by irrigation is increasingly applied to high-value crops as potatoes in humid and temperate biomes to maximize yield and quality. In the light of increasing drought risks, innovative adjustments are required in irrigation scheduling to increase the efficiency and sustainability of supplemental irrigation. Hence, this study...

The importance of a safe food supply has increased due to climate change and its consequences. The number and severity of floods, droughts and plant diseases are rising which causes massive crop failures. Early and precise detection of plant diseases can lower crop failures as it enables early containment. Moreover, it promotes the targeted use of...

The African continent faces various challenges and numerous risks due to current and future climate change. To strengthen the resilience of West African societies in the sectors of agriculture, food security, water and risk management, adaptation measures need to be planned and implemented in time. Planning and implementing climate change adaptatio...

Migration-induced land degradation is a challenging environmental issue in Sub-Saharan Africa. The need for expansion due to urban development has raised the question of effective sustainable measures. Understanding migration and land degradation links is paramount for sustainable urban development and resource use. This is particularly true in Nig...

Plants need water to survive, but what about plants living in places where it does not rain much? Some of these special plants send their roots down into the Earth to find water deep underground, which is called groundwater. But there is a problem: we do not know exactly where these plants are growing. Our mission? To create a new map to find and p...

LANDSURF DSS (https://landsurf.geo.uni-halle.de/) NPM projects containing the websites that make up the DSS: - DSS main page - Documentation startpage English - Documentation startpage French - Documentation content English - Documentation content French - Docker container with the API

Root zone soil moisture (RZSM) is crucial for agricultural water management and land surface processes. The 1 km soil water index (SWI) dataset from Copernicus Global Land services, with eight fixed characteristic time lengths (T), requires root zone depth optimization (Topt) and is limited in use due to its low spatial resolution. To estimate RZSM...

Spatial information about plant health and productivity are essential when assessing the progress towards Sustainable Development Goals such as life on land and zero hunger. Plant health and productivity are strongly linked to a plant’s phenological progress. Remote sensing, and since the launch of Sentinel-1 (S1), specifically, radar-based framewo...

Climate change is affecting the snow cover conditions on a global scale, leading to changes in the extent and duration of snow cover as well as variations in the start and end of snow cover seasons. These changes can have a paramount impact on runoff and water availability, especially in catchments that are characterized by nival runoff regimes, e....

Rural communities in Ghana, dependent on agriculture and lacking resources and infrastructure, are highly vulnerable to climate and environmental change. Internal migration is often considered as a strategy to mitigate local livelihood constraints. Understanding the challenges of rural communities requires knowledge of local conditions. As only few...

This study harnesses Sentinel-1 time series of Alpha, Entropy, VV and VH backscatter intensities as well as their cross ratio to monitor phenological development in wheat, sugar beet, canola, and potatoes in Demmin (Germany) for the years 2017 to 2021 Overcoming challenges ranging from separate viewing geometries (incidence angles respectively) to...

Accurate estimations of crop water requirements accounting for spatial heterogeneous soil properties are recognized as a major contribution towards a sustainable agricultural irrigation management. Crop specific irrigation demand estimations may be improved by physics-based soil moisture models, although spatially distributed soil moisture simulati...

While scientific methods leveraging Earth Observation for agriculture are abundant, their actual application in Germany remains scarce. A key challenge in this context is to connect the end users to the data without the many technical obstacles. Therefore, we present a versatile platform that not only integrates and processes big geodata of highly...

The importance of a safe food supply has increased due to climate change and its consequences. The number and severity of floods, droughts and plant diseases are rising which causes massive crop failures. Early and precise detection of plant diseases can lower crop failures as it enables early containment. Moreover, it promotes the targeted use of...

Semi-arid regions of Central Asia suffer from wind erosion due to expanding steppe conversion and unsustainable farming practices. Empirical data from field observations are needed to support the implementation of adapted management. In this study, a mobile wind tunnel was used for the first time in Kazakhstan to assess the soil's erodibility under...

Food security in Burkina Faso is strongly linked to its agricultural sector and it is estimated by the United States Agency for International Development (USAID) that roughly 20 percent of Burkina Faso's population are considered to be food insecure. It is therefore important to develop land management strategies to increase the resilience of the a...

Many land-based ecosystems are dependent on groundwater and could be threatened by human groundwater abstraction. One key challenge for the description of associated impacts is the initial localisation of groundwater-dependent ecosystems (GDEs). This usually requires a mixture of extensive site-specific data collection and the use of geospatial dat...

Groundwater-dependent vegetation (GDV) is essential for maintaining ecosystem functions and services, providing critical habitat for species, and sustaining human livelihoods. However, climate and land-use change are threatening GDV, highlighting the need for harmonised, global mapping of the distribution and extent of GDV. This need is particularl...

The African continent faces various challenges and numerous risks due to current and future climate change. To strengthen the resilience of West African societies in the sectors of agriculture, food security, water and risk management, adaption measures need to be implemented in time. In the WASCAL-LANDSURF project, an earth system model for West A...

Effective monitoring of agricultural lands requires accurate spatial information about the locations and boundaries of agricultural fields. Through satellite imagery, such information can be mapped on a large scale at a high temporal frequency. Various methods exist in the literature for segmenting agricultural fields from satellite images. Edge-ba...

Satellite remote sensing is vital to monitoring, research, and policy addressing sustainability challenges from climate and ecosystem changes to food and water security. Here, Landsat satellite data play a crucial role, given their unique global and long-term historical coverage at high resolution. Yet, severe but mostly disregarded biases in the L...

Satellite remote sensing is vital to monitoring, research, and policy addressing sustainability challenges from climate and ecosystem changes to food and water security. Here, Landsat satellite data play a crucial role, thanks to their unique global, long-term, and high-resolution coverage. Yet, disregarded biases in the Landsat data archive threat...

The African continent faces various challenges and numerous risks due to current and future climate change. To strengthen the resilience of West African societies in the sectors of agriculture, food security, water and risk management, adaption measures need to be implemented in time. In the WASCAL-LANDSURF project, an earth system model for West A...

Groundwater dependent ecosystems (GDEs) are biodiversity hotspots and provide important ecosystem services. This study presents a novel multi-instrument concept for the local identification of groundwater dependent vegetation (GDV) in the Mediterranean. The concept integrates high-resolution Sentinel-2 remote sensing data with available geodata and...

The increasing demand for food, bioenergy and other agricultural products, as well as the intensification of climate change, pose special challenges for Central Asia’s agricultural sector in terms of implementing sustainable land management. Central Asia is a climate change hot spot. Adaptation measures of agricultural land use to climate change im...

In the view of increasing water demands in agriculture, efficient water use is a key factor in potato production. The aim of this study was to compare two deficit (80% and 90%) and one abundant (120%) gun sprinkler irrigation levels with the longtime used irrigation level of a farmer (100%). Irrigation was supplied during the 2021 growing season on...

Erosion is a severe threat to the sustainable use of agricultural soils. However, the structural resistance of soil against the disruptive forces steppe soils experience under field conditions has not been investigated. Therefore, 132 topsoils under grass‐ and cropland covering a large range of physico‐chemical soil properties (sand: 2–76%, silt: 1...

Migration in West Africa has been taking place for centuries for different reasons. Many dimensions of migration remain insufficiently documented and poorly understood. In particular, factors of migration in destination areas and areas of origin are still lacking comprehensive analysis. In this paper, we bring a new perspective to the model of push...

Large-scale crop type mapping often requires prediction beyond the environmental settings of the training sites. Shifts in crop phenology, field characteristics, or ecological site conditions in the previously unseen area, may reduce the classification performance of machine learning classifiers that often overfit to the training sites. This study...

Information provided by satellite data is becoming increasingly important in the field of agriculture. Estimating biomass, nitrogen content or crop yield can improve farm management and optimize precision agriculture applications. A vast amount of data is made available both as map material and from space. However, it is up to the user to select th...

Digital solutions in agricultural management promote food security and support the sustainable use of resources. As a result, remote sensing (RS) can be seen as an innovation for the fast generation of reliable information for agricultural management. Near real-time processed RS data can be used as a tool for decision making on multiple scales, fro...

In Germany, the agriculture produces by far the largest share of basic food and animal feed. In addition, raw materials such as construction and insulation materials and fuels are increasingly being produced for industrial use by the agricultural sector.Arable production systems thus represent an indispensable part of food security. At the same tim...

The local water regime of the small-scale Geisel catchment in Central Germany is vastly impacted by strong lignite-mining activities. Missing knowledge about hydrological regimes and low-flow discharges in this impacted region prevented integrated environmental flow assessments. As a consequence, targeted environmental flows of the lower Geisel usu...

The digitization of agriculture has been advancing for a number of years, but is not yet being implemented on a large scale in farms in Germany. In the area of spatial data use, the main challenges lie in the inadequate definition of interfaces and in a lack of data and knowledge transfer between science and practice. This is where the “AgriSens -...

The Group on Earth Observations Global Agricultural Monitoring Initiative (GEOGLAM) considers agricultural fields as one of the essential variables that can be derived from satellite data. We evaluated the accuracy at which agricultural fields can be delineated from Sentinel-1 (S1) and Sentinel-2 (S2) images in different agricultural landscapes thr...

The particle size distribution (PSD) of soil plays a vital role in wind erosion prediction. However, the impact of different pretreatments to remove binding agents for PSD and consequences for wind erosion modelling have not been tested. We collected 90 topsoil samples of Chernozems and Kastanozems from different test sites in Kazakhstan. Soil samp...

This study explores the potential of Sentinel-1 Synthetic Aperture Radar (SAR) to identify phenological phases of wheat, sugar beet, and canola. Breakpoint and extreme value analyses were applied to a dense time series of interferometric (InSAR) and polarimetric (PolSAR) features recorded during the growing season of 2017 at the JECAM site DEMMIN (...

Reliable near-surface soil moisture (θ) information is crucial for supporting risk assessment of future water usage, particularly considering the vulnerability of agroforestry systems of Mediterranean environments to climate change. We propose a simple empirical model by integrating dual-polarimetric Sentinel-1 (S1) Synthetic Aperture Radar (SAR) C...

Robust spatiotemporal estimation of the near-surface soil moisture (θ5cm) in a small-scale (~30 ha) Mediterranean agroforestry site (Southern Italy). Simulating θ5cm data for input into spatiotemporal modelling using two approaches at the point- and field-scale, and Sentinel-1 SAR data combined in a feasible. Limited availability of in situ θ5cm d...

The water cloud model (WCM) can be inverted to estimate leaf area index (LAI) using the intensity of backscatter from synthetic aperture radar (SAR) sensors. Published studies have demonstrated that the WCM can accurately estimate LAI if the model is effectively calibrated. However, calibration of this model requires access to field measures of LAI...

Die Digitalisierung der Landwirtschaft schreitet seit einigen Jahren immer weiter voran, wird aber in Deutschland noch nicht im großen Maßstab in landwirtschaftlichen Betrieben umgesetzt. Im Bereich der Geodatennutzung liegen die Herausforderungen vor allem bei der unzureichenden Definition von Schnittstellen sowie in einem mangelnden Daten- und Wi...

The precise estimation and mapping of the near-surface soil moisture (~5cm, SM5cm) is key to supporting sustainable water management plans in Mediterranean agroforestry environments. In the past few years, time series of Synthetic Aperture Radar (SAR) data retrieved from Sentinel-1 (S1) enable the estimation of SM5cm at relatively high spatial and...

Die Digitalisierung der Landwirtschaft schreitet seit einigen Jahren immer weiter voran, wird aber in Deutschland noch nicht im großen Maßstab in landwirtschaftlichen Betrieben umgesetzt. Im Bereich der Geodatennutzung liegen die Herausforderungen vor allem bei der unzureichenden Definition von Schnittstellen sowie in einem mangelnden Daten- und Wi...

Irrigated agriculture In the Aral Sea Basin (ASB) is commonly known for its high water consumption, inefficient water management, and dysfunctional irrigation and drainage infrastructure. Since 1991, six states have been engaged in intensive irrigated agriculture in the Aral Sea Basin (ASB), Afghanistan, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmeni...

Water crises are becoming severe in recent times, further fueled by population increase and climate change. They result in complex and unsustainable water management. Spatial estimation of consumptive water use is vital for performance assessment of the irrigation system using Remote Sensing (RS). For this study, its estimation is done using the So...

Accurate near-surface soil moisture (θ; ~ 5 cm) estimation is one of the most crucial challenges in agricultural management and hydrological studies. This study aims to map θ at high spatiotemporal resolution (17 m grid size, satellite overpass of 6 days) in a small-scale agroforestry experimental site (~ 30 ha) in southern Italy. The observation p...

Accurate near-surface soil moisture (θ; ~ 5 cm) estimation is one of the most crucial challenges in agricultural management and hydrological studies. This study aims to map θ at high spatiotemporal resolution (17 m grid size, satellite overpass of 6 days) in a small-scale agroforestry experimental site (~ 30 ha) in southern Italy. The observation p...

Accurate spatial information of agricultural parcels is fundamental to any system used in monitoring greenhouse gas emissions, biodiversity developments, and nutrient loading in agriculture. The inefficiency of the traditional methods used in obtaining this information is increasingly paving the way for Remote Sensing (RS). The Multiresolution Segm...

Image segmentation is a cost-effective way to obtain information about the sizes and structural composition of agricultural parcels in an area. To accurately obtain such information, the parameters of the segmentation algorithm ought to be optimized using supervised or unsupervised methods. The difficulty in obtaining reference data makes unsupervi...

Crop type classification using Earth Observation (EO) data is challenging, particularly for crop types with similar phenological growth stages. In this regard, the synergy of optical and Synthetic-Aperture Radar (SAR) data enables a broad representation of biophysical and structural information on target objects, enhancing crop type mapping. Howeve...

Land cover is a key variable in the context of climate change. In particular, crop type information is essential to understand the spatial distribution of water usage and anticipate the risk of water scarcity and the consequent danger of food insecurity. This applies to arid regions such as the Aral Sea Basin (ASB), Central Asia, where agriculture...

This study compares the performance of the five widely used crop growth models (CGMs): World Food Studies (WOFOST), Coalition for Environmentally Responsible Economies (CERES)-Wheat, AquaCrop, cropping systems simulation model (CropSyst), and the semi-empiric light use efficiency approach (LUE) for the prediction of winter wheat biomass on the Dura...

Accurate assessment of the soil salinization is an important step for mitigation of agricultural land degradation. Remote sensing (RS) is widely used for salinity assessment, but knowledge on prediction precision is lacking. A RS-based salinity assessment in Khorezm allows for modest reliable prediction with weak (R2=0.15–0.29) relationship of the...

Mapping near-surface soil moisture (θ) is of tremendous relevance for a broad range of environment-related disciplines and meteorological, ecological, hydrological and agricultural applications. Globally available products offer the opportunity to address θ in large-scale modelling with coarse spatial resolution such as at the landscape level. Howe...

Extensive over-exploitation of land and water resources is characterizing irrigated agriculture in the Aral Sea Basin (ASB). Over decades, inefficient and excessive water use had remarkable negative impacts on the groundwater and soil quality, hence on crop production. The countries sharing to the ASB look for opportunities to increase the sustaina...

Carbonate aquifers supply freshwater to about one-quarter of the world population. Their particular hydrodynamic behavior is a valuable property for groundwater extraction, on the downside, carbonate aquifers are vulnerable to overexploitation and pollution. Fractures, fissures, and typical karst features, such as conduits and vertical shafts, crea...

The shrinking groundwater resource is a major cause of ecosystem imbalance, which is further intensified by rapid changes in land use and land cover (LULC) and climate in the lower Chenab canal (LCC) of Pakistan. Present study aims to investigate groundwater dynamics using a novel approach by incorporating remote sensing data in combination with ac...

This study aims defining the best predictors of biophysical parameters and yield with vegetation indices derived from Landsat 8 OLI surface reflectance data. The study was conducted in 2015 at five crop fields in Kulavat canal irrigation system in Khorezm province, Uzbekistan. The Environment for Visualizing Images (ENVI) ver. 4.5 and R programming...

The video shows the pre-recorded video of the talk on building a science network for standardised and continuous in-situ data for crop monitoring on the DEMMIN experimental field. the presentation was given on the 1019 EuroGEOSS Workshop in Lisbon.

WUEMoCA is an operational scientific webmapping tool for the regional monitoring of land and water use efficiency in the irrigated croplands of the transboundary Aral Sea Basin that is shared by Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, Uzbekistan, and Afghanistan. Satellite data on land use, crop pro-duction and water consumption is integr...

Spatially explicit near-surface soil moisture (θ) patterns at high temporal resolution play a very important role in environmental modelling for improving risk assessment and for quantifying the effects of climatic seasonality and land use/land cover change on ecosystem services and functions in Mediterranean catchments. Remote sensing data from th...

Spatially explicit near-surface soil moisture (θ) patterns at high temporal resolution play a very important role in environmental modelling for improving risk assessment and for quantifying the effects of climatic seasonality and land use/land cover change on ecosystem services and functions in Mediterranean catchments. Remote sensing data from th...

The biomass of three agricultural crops, winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.), was studied using multi-temporal dual-polarimetric TerraSAR-X data. The radar backscattering coefficient sigma nought of the two polarization channels HH and VV was extracted from the satellite images. Subsequen...

This research has been conducted on a main agricultural production region of the NorthEast Germany over the time frame of 2015. Five widely used crop growth models, namely, WOFOST, Aqua Crop, Ceres Wheat, CropSyst and Light Use Efficiency (LUE), are compared to predict the biomass of winter wheat. To obtain the higher spatial and temporal coverage,...

The occurrence of species in rapidly changing environments, such as agricultural landscapes, is affected by their ability to recolonise habitats. Knowledge of the landscape scale affecting colonisation is essential for large‐scale pest management. Colonisation by insects can be affected on multiple landscape scales, as different morphs of a species...

In this study, we evaluate the suitability of interpolated time-series features for the classification of 19 crop types with optical Sentinel-2 , SAR Sentinel-1 and fusion of both data sources for a study area in Northern Germany (Brandenburg).

Spatially explicit soil moisture information in a high temporal resolution plays an essential role in environmental modeling for improving risk assessment, for quantifying the effects of rainfall seasonality and climatic variability, and for addressing ecosystem services. In this context, remote sensing data, particularly from the Copernicus missio...

Spatially explicit soil moisture (θ) information in a high temporal resolution plays an essential role in environmental modeling for improving risk assessment, for quantifying the effects of rainfall seasonality and climatic variability, and for addressing ecosystem services. Remote sensing data, particularly from the Copernicus mission is highly a...

Efficient irrigation agriculture is essential for the sustainable regional development and adaption to climate change in one of the largest drylands in Central Asia, the Aral Sea Basin (ASB). It requires reliable and accessible data on the water use efficiency (‘more crop per drop’) and irrigated land use. The online information tool WUEMoCA (Water...

InoCottonGROW aims at contributing to sustainable water use along the entire cotton-textile value chain "from cotton field to hanger". In case studies in Pakistan, a major supplier of German textile demand, our goal is to advance the water footprint (WF) concept to become a meaningful regional steering instrument for national decision makers in man...

Accurate information of soil salinity levels enables for remediation actions in long-term operating irrigation systems with malfunctioning drainage and shallow groundwater (GW), as they are widespread throughout the Aral Sea Basin (ASB). Multi-temporal Landsat 5 data combined with GW levels and potentials, elevation and relative topographic positio...

Reliable and accurate crop classification maps are an important data source for agricultural monitoring and food security assessment studies. For many years, crop type classification and monitoring were focused on single-source optical satellite data classification. With advancements in sensor technologies and processing capabilities, the potential...

Accurate crop type maps are vital for agricultural monitoring and sustainable land management. When derived from earth observation (EO) data, an accurate classification of crop type requires high spatial and temporal resolutions. In this study, we evaluate the suitability of interpolated time series features for the classification of 19 crop types...

The full potential of deriving information for phenological monitoring based on EO data has not been used so far. Reasons are lacking knowledge of remote sensing data and techniques of users with no remote sensing background, lacking knowledge of data portals and download opportunities for big datasats, lacking knowledge of data preparation, data f...

The Northeast German Lowland Observatory (TERENO-NE) was established to investigate the regional impact of climate and land use change. TERENO-NE focuses on the Northeast German lowlands, for which a high vulnerability has been determined due to increasing temperatures and decreasing amounts of precipitation projected for the coming decades. To fac...

The Northeast German Lowland Observatory (TERENO-NE) was established to investigate the regional impact of global change. TERENO-NE focuses on the Northeast German lowlands, for which a high vulnerability has been determined due to increasing temperatures and decreasing amounts of precipitation projected for the coming decades. In order to facilita...