Satellite Communications

This study is motivated by the need to give the reader a broad view of the developments, key concepts, and technologies related to information society evolution, with a focus on the wireless communications and geoinformation technologies and their role in the environment. Giving perspective, it aims at assisting people active in the industry, the public sector, and Earth science fields as well, by providing a base for their continued work and thinking

An AI approach to operationalise global daily PlanetScope satellite imagery for river water masking

Monitoring rivers is vital to manage the invaluable ecosystem services they provide, and also to mitigate the risks they pose to property and life through flooding and drought. Due to the vast extent and dynamic nature of river systems, Earth Observation (EO) is one of the best ways to measure river characteristics. As a first step, EO-based river monitoring often requires extraction of accurate pixel-level water masks, but satellite images traditionally used for this purpose suffer from limited spatial and/or temporal resolution. We address this problem by applying a novel Convolutional Neural Network (CNN)-based model to automate water mask extraction from daily 3 m resolution PlanetScope satellite imagery. Notably, this approach overcomes radiometric issues that frequently present limitations when working with CubeSat data. We test our classification model on 36 rivers across 12 global terrestrial biomes (as proxies for the environmental and physical characteristics that lead to the variability in catchments around the globe). Using a relatively shallow CNN classification model, our approach produced a median F1 accuracy score of 0.93, suggesting that a compact and efficient CNN-based model can work as well as, if not better than, the very deep neural networks conventionally used in similar studies, whilst requiring less training data and computational power. We further show that our model, specialised to the task at hand, performs better than a state-of-the-art Fully Convolutional Neural Network (FCN) that struggles with the highly variable image quality from PlanetScope. Although classifying rivers that were narrower than 60 m, anastomosed or highly urbanised was slightly less successful than our other test images, we showed that fine tuning could circumvent these limitations to some degree. Indeed, fine tuning carried out on the Ottawa River, Canada, by including just 5 additional site-specific training images significantly improved classification accuracy (F1 increased from 0.81 to 0.90, p < 0.01). Overall, our results show that CNN-based classification applied to PlanetScope imagery is a viable tool for producing accurate, temporally dynamic river water masks, opening up possibilities for river monitoring investigations where high temporal variability data is essential

Book of short Abstracts of the 11th International Symposium on Digital Earth

The Booklet is a collection of accepted short abstracts of the ISDE11 Symposium

Spatial modelling and GIS-based decision support tools to evaluate the suitability of sustainable aquaculture development in large catchments

Land, water and natural resources are under increasing pressure due to rising demands for food and energy from the rapidly growing global population. Across a catchment there can be multiple stakeholders with conflicting opinions over how space and resources should be used and managed. Consequently, it is important to consider the suitability of a catchment for a particular purpose to optimise use of the area and minimise potential conflicts and impacts on the wider environment. Aquaculture is a significant contributor to world food supply and as fisheries are unlikely to increase it is expected that the industry will continue to grow and expand in the future to help meet food security requirements. As a result, it is essential that the sector aims for sustainable development within the most suitable locations. However, it can be difficult to assess the suitability of multiple large catchments and some issues may not be immediately apparent. This project aimed to show how spatial models could be used as decision support tools to evaluate the suitability of large catchments for sustainable aquaculture. Four large areas of importance to aquaculture were selected; covering 10,148km2, 26,225km2, 48,319km2 and 66,283km2 in Bangladesh, China, Thailand and Vietnam respectively. Asia is by far the most dominant aquaculture region in the world and each of the four study areas contribute to local, regional and global food supplies. The study area in Bangladesh was located in Khulna region in the south west of the country and the main species of focus were prawn and shrimp. The Chinese study area was located in the south eastern province of Guangdong and the main species covered were tilapia and shrimp. Similarly, in Thailand, the main species evaluated were tilapia and shrimp whilst the study area extended across the Central region. Finally, the largest study area was the Mekong Delta in Vietnam and the main species of focus in this area were pangasius catfish and shrimp. One of the challenges in modelling large catchments is model applicability and data availability. Often, the required data are not available (or accessible) and it would be difficult, time consuming and expensive to collect new information. Furthermore, when assessing multiple areas is it vital that a representative and unbiased approach is used where no one catchment is favoured over the other due to higher quality data. Therefore, this study used data that are available for almost any area in the world; allowing future application of the models and enabling effective and unbiased decision support. Four modelling stages were employed in this study to evaluate the suitability of large catchments for sustainable aquaculture development. The first stage was the classification of seasonal land use models from satellite imagery. This provides information on what the land is used for and how aquaculture could impact or be impacted by the wider environment. The second step was the development of seasonal models of site suitability using optimal values within a GIS-based multi-stage framework. These models identify which locations are best for culture and can also be used to estimate the availability of areas for food production. The next stage investigated the use of Maxent as a novel approach in site suitability modelling to evaluate the conditions experienced by existing farms. The information from Maxent can be used to identify trends, opportunities and concerns related to sustainable management and farm locations. Finally, qualitative models of non-point source pollution (NPSP) were developed which assess the risk of NPSP within a catchment. NPSP is an issue which can impact both aquaculture and the wider environment. Thus, it is important to understand the areas within a catchment where NPSP risk is higher enabling the establishment of monitoring and/or mitigation procedures. The models support the ecosystem approach to aquaculture (EAA) and enable objective planning and management strategies to enhance productivity across large catchments without negatively impacting the environment. In order to meet growing food requirements, large areas will need to be used for agriculture and aquaculture; therefore, analysis at a wider catchment level, which complements assessment at a local scale, is required as it allows a holistic view of the situation. The work presented here illustrates the potential use of spatial models across large catchments and considers the suitability of the areas for aquaculture development

Advances in Remote Sensing-based Disaster Monitoring and Assessment

Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones

Science-based restoration monitoring of coastal habitats, Volume Two: Tools for monitoring coastal habitats

Healthy coastal habitats are not only important ecologically; they also support healthy coastal communities and improve the quality of people’s lives. Despite their many benefits and values, coastal habitats have been systematically modified, degraded, and destroyed throughout the United States and its protectorates beginning with European colonization in the 1600’s (Dahl 1990). As a result, many coastal habitats around the United States are in desperate need of restoration. The monitoring of restoration projects, the focus of this document, is necessary to ensure that restoration efforts are successful, to further the science, and to increase the efficiency of future restoration efforts

Forest landscapes and global change. New frontiers in management, conservation and restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference

This volume contains the contributions of numerous participants at the IUFRO Landscape Ecology Working Group International Conference, which took place in Bragança, Portugal, from 21 to 24 of September 2010. The conference was dedicated to the theme Forest Landscapes and Global Change - New Frontiers in Management, Conservation and Restoration. The 128 papers included in this book follow the structure and topics of the conference. Sections 1 to 8 include papers relative to presentations in 18 thematic oral and two poster sessions. Section 9 is devoted to a wide-range of landscape ecology fields covered in the 12 symposia of the conference. The Proceedings of the IUFRO Landscape Ecology Working Group International Conference register the growth of scientific interest in forest landscape patterns and processes, and the recognition of the role of landscape ecology in the advancement of science and management, particularly within the context of emerging physical, social and political drivers of change, which influence forest systems and the services they provide. We believe that these papers, together with the presentations and debate which took place during the IUFRO Landscape Ecology Working Group International Conference – Bragança 2010, will definitively contribute to the advancement of landscape ecology and science in general. For their additional effort and commitment, we thank all the participants in the conference for leaving this record of their work, thoughts and science