Gurwinder Singh – författare

Invest in Artificial Intelligence in Remote Sensing for Disaster Management to gain invaluable insights into cutting-edge AI technologies and their transformative role in effectively monitoring and managing natural disasters.

Artificial Intelligence in Remote Sensing for Disaster Management examines the involvement of advanced tools and technologies such as Artificial Intelligence in disaster management with remote sensing. Remote sensing offers cost-effective, quick assessments and responses to natural disasters. In the past few years, many advances have been made in the monitoring and mapping of natural disasters with the integration of AI in remote sensing. This volume focuses on AI-driven observations of various natural disasters including landslides, snow avalanches, flash floods, glacial lake outburst floods, and earthquakes. There is currently a need for sustainable development, near real-time monitoring, forecasting, prediction, and management of natural resources, flash floods, sea-ice melt, cyclones, forestry, and climate changes. This book will provide essential guidance regarding AI-driven algorithms specifically developed for disaster management to meet the requirements of emerging applications.

Invest in Artificial Intelligence in Remote Sensing for Disaster Management to gain invaluable insights into cutting-edge AI technologies and their transformative role in effectively monitoring and managing natural disasters.

Artificial Intelligence in Remote Sensing for Disaster Management examines the involvement of advanced tools and technologies such as Artificial Intelligence in disaster management with remote sensing. Remote sensing offers cost-effective, quick assessments and responses to natural disasters. In the past few years, many advances have been made in the monitoring and mapping of natural disasters with the integration of AI in remote sensing. This volume focuses on AI-driven observations of various natural disasters including landslides, snow avalanches, flash floods, glacial lake outburst floods, and earthquakes. There is currently a need for sustainable development, near real-time monitoring, forecasting, prediction, and management of natural resources, flash floods, sea-ice melt, cyclones, forestry, and climate changes. This book will provide essential guidance regarding AI-driven algorithms specifically developed for disaster management to meet the requirements of emerging applications.

This book analyses subsidies from various perspectives and creates a model that determines whether or not their use is justified. Further, it analyses the various causes of trade distortion, trade-discriminatory practices, and other issues associated with unregulated subsidies. In addition, the book considers how these issues fall within the scope of subsidies described under the SCM Agreement.

The primary discussion from the perspective of WTO objective concerns the trade practice of awarding subsidies, for exports and also for protectionist purposes. Here, the terms justifiable and non-justifiable are used as hypothetical parameters to determine the extent of state support, considering the country classification based on economic and technological criteria, and their objectives for development. These parameters are distinct from Prohibited, Actionable, and Non-Actionable subsidies, as classified under the SCM Agreement.

Subsidies awarded for the purposesof development and for welfare are considered as justifiable, whereas subsidies for the promotion of exports or state measures adopted for protectionist purposes are non-justifiable.  Lastly, the book addresses the implications of such subsidies on the core objectives of the WTO and in connection with fair trade values.