DeepCount: In-Field Automatic Quantification of Wheat Spikes Using Simple Linear Iterative Clustering and Deep Convolutional Neural Networks

Crop yield is an essential measure for breeders, researchers and farmers and is comprised of and may be calculated by the number of ears/m2, grains per ear and thousand grain weight. Manual wheat ear counting, required in breeding programmes to evaluate crop yield potential, is labour intensive and expensive; thus, the development of a real-time wheat head counting system would be a significant advancement. In this paper, we propose a computationally efficient system called DeepCount to automatically identify and count the number of wheat spikes in digital images taken under the natural fields conditions. The proposed method tackles wheat spike quantification by segmenting an image into superpixels using Simple Linear Iterative Clustering (SLIC), deriving canopy relevant features, and then constructing a rational feature model fed into the deep Convolutional Neural Network (CNN) classification for semantic segmentation of wheat spikes. As the method is based on a deep learning model, it replaces hand-engineered features required for traditional machine learning methods with more efficient algorithms. The method is tested on digital images taken directly in the field at different stages of ear emergence/maturity (using visually different wheat varieties), with different canopy complexities (achieved through varying nitrogen inputs), and different heights above the canopy under varying environmental conditions. In addition, the proposed technique is compared with a wheat ear counting method based on a previously developed edge detection technique and morphological analysis. The proposed approach is validated with image-based ear counting and ground-based measurements. The results demonstrate that the DeepCount technique has a high level of robustness regardless of variables such as growth stage and weather conditions, hence demonstrating the feasibility of the approach in real scenarios. The system is a leap towards a portable and smartphone assisted wheat ear counting systems, results in reducing the labour involved and is suitable for high-throughput analysis. It may also be adapted to work on RGB images acquired from UAVs

Geochemical modeling of magmatic gas scrubbing

The EQ3/6 software package, version 7.2 was successfully used to model scrubbing of magmatic gas by pure water at 0.1 MPa, in the liquid and liquid-plus-gas regions. Some post-calculations were necessary to account for gas separation effects. In these post-calculations, redox potential was considered to be fixed by precipitation of crystalline a-sulfur, a ubiquitous and precocious process. As geochemical modeling is constrained by conservation of enthalpy upon water-gas mixing, the enthalpies of the gas species of interest were reviewed, adopting as reference state the liquid phase at the triple point. Our results confirm that significant emissions of highly acidic gas species (SO2(g), HCl(g), and HF(g)) are prevented by scrubbing, until dry conditions are established, at least locally. Nevertheless important outgassing of HCl(g) can take place from acid, HCl-rich brines. Moreover, these findings support the rule of thumb which is generally used to distinguish SO2-, HCl-, and HF-bearing magmatic gases from SO2-, HCl-, and HF-free hydrothermal gases

A GIS for flood risk management in Flanders

In the past decades, Flanders, a region of north Belgium that extends from the coastline inland (in northwest Europe), has suffered several serious riverine floods that caused substantial property damage. As Flanders is one of the most densely populated regions in the world, a solid water management policy is needed in order to mitigate the effects of this type of calamity. In the past, Flemish water managers chose to drain off river water as quickly as possible by heightening the dikes along the rivers. However, this method leads to a higher flood probability further downstream. Moreover, water defence infrastructure can always suffer from technical failures (e.g., breaching) creating even more damage than would have occurred if no defences were in place. In a search for a better solution to this recurring problem, the Flemish administration proposed a new approach in the 1990 s. This approach focuses on minimizing the consequences of flooding instead of attempting to prevent floods. To implement this approach, large amounts of data were gathered for the Flemish Region. Using a Geographic Information System (GIS), a risk-based methodology was created to quantitatively assess flood risk based on hydrologic models, land use information and socio-economic data. Recently, this methodology was implemented in a specifically designed GIS-based flood risk assessment tool called LATIS. By estimating the potential damage and number of casualties during a flood event, LATIS offers the possibility to perform risk analysis quickly and effectively. This chapter presents a concise overview of LATIS’ methodology and its implementation for flood risk management in Flanders

Assessing the storm vulnerability of the Belgian coastline

Climate change is likely to induce increased sea level and storm frequency. As such, assessing the strength of the Belgian coastal defence infrastructure against natural hazards is of primordial importance to reduce inundation consequences to properties and nature. This study presents an integrated methodology to estimate damage risks from a hypothetical storm with a surge level of +8m TAW and a duration of 45 hours along the entire coastline. After translation of deep water hydrometeorological conditions to the nearshore, several failure modes of the defence infrastructure are modelled: beach and dune erasion, collapse of dikes due to wave impact and overtopping, and subsequent breach forming and flooding of the low-lying coastal plain. Attention was paid to the various model uncertainties. Damage of infrastructure, properties and human casualties are calculated using a raster-based GIS model. Multiplication of the results with a rate factor based on prognoses of the evolution of socio-economic parameters allows projection of the results to 2050. All this, in combination with a social cost benefit analysis, will provide a tool for supporting coastal zone management in Belgium in a quantitative way

SAFECoast: Comparison between different flood risk methodologies. Action 3B report - SAFECOAST Interreg IIIb North Sea Project

The Interreg IIIB project SAFECoast considers the question “How to manage our North Sea coasts in 2050?’ and focuses on the consequences of climate change and spatial developments with respect to safety from coastal flooding. Therefore, a team of coastal managers from the Netherlands, Germany, Belgium, Denmark and the UK are continuing their cooperation in SAFECoast which aims to build on each other’s experiences in, and understanding of coastal risk management. Flanders Hydraulics Research (FHR, located in Borgerhout, Belgium) has proposed a flood risk methodology in the past which makes it possible to compare different areas and different situations with a view to damage and risk calculations. In the past years, the methodology has been extended and improved, and meanwhile it is used in several studies in Flanders. This report is the contribution of Flanders Hydraulics Research to the SAFECoast project (action 3b). The goal is to compare basic parameters of the existing coastal risk methodologies and make an inventory of the strong and weak points of the different approaches. It is neither possible nor desirable to make a ranking of them. Because of data availability and case specific parameters and constraints, each methodology generally fits the best for the area they are made for. However we want to learn from them and incorporate good ideas to improve the existing methodologies. To improve coastal risk methodology means to make its results less uncertain, or more complete. In this study all the different sources of uncertainty are analysed and compared so it becomes possible to identify the weak links in the calculation chain

Coastal flooding risk calculations for the Belgian coast

Coastal flooding risk calculations are carried out for the entire Belgian coastal zone to support the management ofthe coastal defence system. The floodprone low-lying coastal area has an average width of 20 km and is locatedon average 2 m below the surge level of an annual storm. The natural sea defences are sandy beaches anddunes, which have been strengthened by revetments in the coastal towns. The Belgian standard of coastalprotection is to be safe against a surge level with a return period of 1000 years, but at present it is investigated if and how this standard could be redefined based on risk analysis

Non-destructive Assessment of Quality and Yield for Grass-Breeding

Selection of cultivars has, until now, been based mainly on dry matter (DM) yields because of the high costs of sampling and chemical analysis. Imaging spectroscopy could reduce costs by limiting sampling and harvesting of individual plots to reference samples (Schut et al., accepted). In this study, the prediction accuracy of DM yields and chemical composition with imaging spectroscopy is evaluated for cultivar selection purposes