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REMOTE SENSING IN PRECISION AGRICULTURE

Transforming Scientific Advancement intoInnovation

Remote Sensing in Precision Agriculture: Transforming Scientific Advancement into Innovation compiles the latest applications of remote sensing in agriculture using spaceborne, airborne and drones’ geospatial data. The book presents case studies, new algorithms and the latest methods surrounding crop sown area estimation, determining crop health status, assessment of vegetation dynamics, crop diseases identification, crop yield estimation, soil properties, drone image analysis for crop damage assessment, and other issues in precision agriculture. This book is ideal for those seeking to explore and implement remote sensing in an effective and efficient manner with its compendium of scientifically and technologically sound information.

Paperback ISBN: 9 7 8 - 0 - 3 2 3 - 9 1 0 6 8 - 2
eBook ISBN: 

Application of Remote Sensing abd GIS in Natural Resources and Built Infrastructure Management

ISSN 0921-092X ISSN 1872-4663 (electronic)
Water Science and Technology Library
ISBN 978-3-031-14095-2 ISBN 978-3-031-14096-9 (eBook)
https://doi.org/10.1007/978-3-031-14096-9

Ashish Kumar Ph.D. student in our Hydroinformatics and Integrated Hydroclimate Lab and in the Civil Engineering Department at the Indian Institute of Technology Bombay successfuly defend his doctoral degree

Ashish – Ph.D. student in the Civil Engineering Department at the Indian Institute of Technology Bombay-- presented his dissertation "Machine Learning Approach for Improving Near-Real-Time Satellite Rainfall Estimates and Streamflow Simulations." Ashish was co-advised by Professor RAAJ Ramsankaran and Francisco Munoz-Arriola. Ashish published two articles. In the first article "Machine learning approach for improving near-real-time satellite-based rainfall estimates by integrating soil moistureKumar et al., Remote Sensing  (2019), Ashis merges rainfall and soil moisture data from remote sensing, improving rainfall estimates during the monsoon season in Central India. In his second paper "A simple machine learning approach to model real-time streamflow using satellite inputs: Demonstration in a data scarce catchmentKumar et al. Journal of Hydrology (2021), Ashish used a machine learning technique to improve the estimations of streamflow. Ashish will join the Indian Institute of Technology Delhi, where he will continue his work integrating remote sensing data and data-driven models.

For more information contact Francisco Muñoz-Arriola (fmunoz@unl.edu).

Francisco and the Hydroinformatics and Integrated Hydroclimate Lab delivered a lecture to the University of Zululand and Chang’An University's Earth and Environmental Sciences International Webinar Conference 2021

Francisco – fellow of the Daugherty Water for Food Global Institute, the Policy Center, and the Nebraska Governance and Technology Center-- delivered the lecture Climate-resilient water infrastructure in a non-stationary world. This is the third lecture explaining the foundation and practical experiences toward building climate-resilient infrastructure. This time, Francisco's lecture was part of a virtual seminar series organized by the University of Zululand and Chang’An University. The Conference on Earth and Environmental Sciences 2021 brought together more than five hundred scientists, practitioners, and students from around the worls. Francisco's lecture central thesis states that "Socioenvironmental variables and processes integrate complexities capturing systems and infrastructure’s  responses to change". This presentation integrates Alessandro Amaranto (2020)Munoz-Arriola et al. (submitted), Kumar et al., (2021), Sarzaeim, Ou, Alves de Oliveira and Munoz-Arriola (accepted), Werner et al., (submitted).
For more information contact Francisco Muñoz-Arriola (fmunoz@unl.edu).

Francisco and the Hydroinformatics and Integrated Hydroclimate Lab delivered a lecture to the Escuela Colombiana de Ingeniería Julio Garavito's Seminario Abierto Hidroinformática Para La Sostenibilidad De Los Recursos Hídricos

Francisco – fellow of the Daugherty Water for Food Global Institute, the Policy Center, and the Nebraska Governance and Technology Center-- delivered the lecture Complejidades en la construcción de infraestructura hídrica y agrícola resiliente al Cambio Climático. The lecture was part of a virtual seminar series organized by the Escuela Colombiana de Ingeniería Julio Garavito, Ministry of Foreign Affairs of the Netherlands, and the Delft Institute for Water Education (IHE Delft). The Open Seminar on Hydroinformatics afor the Sustainability of Water Resources brought together more than five hundred scientists, practitioners, and students from around the Americas. Francisco's lecture central thesis states that "El monitoreo de sistemas geofísicos y humanos contribuye al entendimiento y predicción de la resiliencia de los paisajes complejos a políticas y eventos hidrometeorológicos y del clima". This presentation integrates Alessandro Amaranto (2019)Munoz-Arriola et al. (submitted), Werner et al., (submitted), and Jain, Khare, and Munoz-Arriola (2021).
For more information contact Francisco Muñoz-Arriola (fmunoz@unl.edu).

Francisco and the Hydroinformatics and Integrated Hydroclimate Lab delivered a keynote lecture to the IAWEES and IHE Delft's International workshop "Application of remote Sensing and GIS: Water, Environment, Land and Society"

Francisco – fellow of the Daugherty Water for Food Global Institute, the Policy Center, and the Nebraska Governance and Technology Center-- delivered the keynote lecture Climate-Resilient Water Infrastructure in Complex Agricultural landscapes: Integration of Data, Management, and Policy. The lecture was part of the International Association for Water, Environment, Energy, and Society (IAWEES) and the Delft Institute for Water Education (IHE Delft) International Workshop: Application of Remote Sensing and GIS: Water, Environment, Land and Society. More than two thousand scientists, practitioners, and students from around the world attended IWAEES-IHE Delft workshop. Francisco's lecture central thesis states that "Integrated remote sensing, in situ, and modeling-based products by artificial intelligence can predict aquifer resilience to policy implementation and climate/weather events." This presentation integrates Alessandro Amaranto (2018, 2019, and 2020) and Munoz-Arriola et al. (submitted).
For more information contact Francisco Muñoz-Arriola (fmunoz@unl.edu).

University of Nebraska-Lincoln and the Universidade do Sao Paulo joint a virtual classroom to learn about Attribution, Decision Making, and Socio(agro)ecological systems

A group of scientists and engineers from around the world foresee to integrate worldwide Climate Change-Environment attributions due to COVID-19 lockdowns

The team formed by six institutions around the world expects that scientific, engineering, and innovation will be advanced by transforming observations and cumulative knowledge into conceptualizations and assessments of resilience in all the continents. The book Scenarios of environmental resilience and transformation in times of Climate Change: effects and lessons from the COVID-19 will represent an intellectual collective that evidence how the natural and the built environments have been relieved from the consistent acceleration of the human enterprise. This relief is an unprecedented opportunity to test and (re)evaluate climate change mitigation and adaptation plans. More than 40 groups around the world have shown interest in sharing their experiences in fields as broad as urban water supply and wastewater, energy generation and tradeoffs, atmospheric dynamics and air quality, ecosystem and infrastructure functionality, contaminant loadings and human health, financial recession and poverty, and tourism and the environment.