Develop a solution that addresses one of the hackathon challenges. Developed solutions must take advantage of Copernicus data and/or services. You will get access to Copernicus data via the ONDA DIAS or OpenDataCube. Note that the challenge you choose will determine which platform you work with. Participants are encouraged to use the guidance of our coaches when developing your solutions.
The COVID-19 virus is testing countries all around the globe. It has disrupted daily life as we know it and has become one of the biggest crises of our lifetime. The world is facing many challenges as various countries strive to regain a level of normalcy.From societal problems to the impact on the economy, even when the spread of this infectious disease has been halted, the crisis is far from over.
There is no better time than now to focus our efforts on addressing the inevitable changes that will lead us into a post-pandemic world!Your mission should you choose to accept it, is to create an application that can help monitor or alleviate the changes caused by the global pandemic.
👉Find the entire challenge here!
💻ONDA DIAS platform.
📷 Photo by CDC on Unsplash
The issue of global water scarcity is largely tied to the timely utilization and distribution of water to the human masses, agriculture and industries. Therefore, monitoring the availability of water resources and their sources and sinks are very essential for an efficient water management. The strategies applied for water management also affects the urban planning as a whole and hence careful consideration and inputs about water delivery, usage, and recycling plays a key role.
Satellite image data can also be used to classify different surface water sources and sinks to manage water resources for various purposes.
👉Find the entire challenge here!
💻ONDA DIAS platform.
📷 Photo by redcharlie on Unsplash
In Sweden there is about 96 000 lake ranging from lake Vänern the largest in the Europeanunion to small size lakes than are two acres. The scale of economic dependency on lakes and water bodies gives an indicator of the extent of the ecological damage that can be caused byhuman activities. A comprehensive water quality monitoring system is essential to guarantee sustainable use of water resources. Water quality monitoring for large scale water bodies is a challenging operation that can be expensive and time consuming.
The goal of this challenge is to utilize satellite data to develop solutions to help various stakeholders to better monitor water quality.
👉Find the entire challenge here!
💻ONDA DIAS platform.
📷 Photo by Curioso Photography on Unsplash
Agriculture plays a vital role in food security and economic growth of most of the countries in the world. Precision Agriculture is one of the modern and efficient agricultural practices. It manages variations in the field accurately to improve agricultural yield by reducing fertilizer and production costs. It also reduces pollution through less use of chemicals.
One of the main tasks in precision agriculture is field delineation as it provides a valuable input for agricultural applications such as yield estimations, monitoring of the crop.
👉Find the entire challenge here!
💻ONDA DIAS platform.
📷 Photo by Bence Balla-Schottner on Unsplash
There are dozens of anomalies in a field that farmers cannot detect until the later stages of an anomaly by then significant damage has been done to the crop in these cases there is a need for early anomaly detection systems which can monitor the crop growth cycles and provide the early warnings if there is an anomaly. In general, the anomaly may be due to variability in physical and chemical soil properties, the presence of pathogens like nematodes, or an insect propagation. It can also result from faults in fertilizer application and water irrigation system design.
Monitoring plant growth status and irrigation needs require extensive high-quality checks and monitoring from remote sensing data. Usually, the process of monitoring agriculture farmlands using satellite imagery requires a lot of time and patience since to detect changes in field conditions, one should continuously compare the images and mull through the data for differences, which can be quite subtle.
👉Find the entire challenge here!
💻ONDA DIAS platform.
📷 Photo by Adele Payman on Unsplash
The availability of large amounts of satellite imagery data through the European Copernicus project and open source platforms like the OpenDataCube (ODC) greatly bolsters the opportunities to apply classical machine learning and deep learning algorithms. These models can be employed to meet many challenges. One challenge that is particularly relevant in our time is that of climate change and global warming. An important aspect of this challenge is monitoring the effects of climate change using the aforementioned satellite data. Thus change of snow cover in itself is already an interesting phenomenon to follow and report as a complement to other measurements which allow us to monitor the indicators of climate, such as surface temperature, ocean heat, or sea levels. More importantly, however, it has been widely researched how the change in snow cover influences surface energy level, water balance, thermal regimes, and vegetation and thus plays a major role in the ecological, and hydrological systems, as well as the climate of Arctic and other regions. Moreover, the extent of snow cover, has more direct economic effects too. For example in road cleaning costs, and in architecture. In order to accurately track the changes in snow cover, it is an important step to be able to identify snow in satellite images, and also to distinguish between a snow-covered area and an area occluded by clouds. This inspired the launch of this challenge.
👉Find the entire challenge here!
💻OpenDataCube platform.
📷 Photo by Alberto Restifo on Unsplash
The availability of large amounts of satellite imagery data through the European Copernicus project and open source platforms like the OpenDataCube (ODC) greatly bolsters the opportunities to apply classical machine learning and deep learning algorithms. These machine learning models can be employed to meet many challenges. One challenge that is particularly relevant in our time is that of the global Covid-19 pandemic. An important aspect of this challenge is monitoring human activity in different types of areas, as well as traffic between different areas. On one hand, increased activity in areas corresponding to hospitals and health care institutes, for example, in the right circumstances can forecast a new wave of viral infection. On the other hand, monitoring human activity in areas associated with commerce and entertainment can be used as an approximation of how strictly certain lockdown measures are observed. Monitoring activity in residential areas can also provide important insights related to the ongoing global pandemic.
👉Find the entire challenge here!
💻OpenDataCube platform.
📷 Photo by Fusion Medical Animation on Unsplash
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