ESGRS

Multisource Remote Sensing-based Precipitation Estimation over the UAE
2022-09-07 10:00 - 11:00 (Asia/Dubai)
Given its predominantly arid climate, the Arabian Peninsula (AP) is considered a regional water stress hotspot, amplified by the rising demands associated with its rapid urbanization and population growth. The scarcity of renewable water resources across the AP requires improved monitoring of available precipitation and terrestrial water storage to quantify water budget deficits and implement targeted water resource management strategies. However, accurate and timely monitoring of precipitation remains a challenge, particularly in arid regions such as the AP, characterized by sparse ground-based observational networks and complex land-atmosphere dynamics. This webinar will present an overview on remote sensing-based monitoring of precipitation, challenges and targeted solutions for improved monitoring over the UAE and the larger AP region.

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DR. YOUSSEF WEHBEPROGRAM OFFICER – UAEREP AT NATIONAL CENTER OF METEOROLOGY (NCM)Dr. Youssef Wehbe is a Project Officer for the UAE Research Program for Rain Enhancement Science. His expertise includes water resource management, coupled land-atmosphere modeling, cloud microphysics, and weather modification technology. His ongoing research addresses next-generation water resource monitoring by integrating satellite and radar remote sensing, hydro-meteorological modeling, and relevant applications of AI/machine learning tools. He was a crew member in a flight campaign under the NASA Airborne Science Program to gather aerosol and cloud microphysical measurements over the eastern UAE. Youssef led several studies on water resources in MENA region, including developing machine learning-based calibrations for satellite-inferred rainfall estimates, coupling land and atmospheric prediction models, and mapping groundwater recharge and migration paths.

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Earth and Planetary Science Remote Sensing Projects in Zayed University
2022-08-24 10:00 - 11:00
This session will discuss in detail about the Earth, Moon, and Mars projects like- 1) Impact of Prosopis Juliflora on depletion of groundwater in UAE using remote sensing and GIS, 2) Introduction to UAE’s first hyperspectral library website, 3) Terrestrial analog studies to show the intensity to unclog the forthcoming activities for the future perspective aspects on the lunar and other planetary surfaces., 4) Examining the potential of liquid water on the surface of mars, and many other interesting projects.

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MR. MANISH SHARMAREMOTE SENSING AND ENVIRONMENT SPECIALIST AT THE COLLEGE OF NATURAL AND HEALTH SCIENCES (CNHS) AT ZAYED UNIVERSITYMr. Manish serves as a Remote Sensing and Environment Specialist at the College of Natural and Health Sciences (CNHS) at Zayed University. His research interest includes exploring mineralogy, geology, geomorphology, and atmospheric parameters of Mars, Moon, Earth, and other extra-terrestrial planets using Remote Sensing satellite images and Geographic Information System (GIS) tools. Previously, He was a Research Assistant at The Hong Kong Polytechnic University (PolyU), working for China lunar exploration mission, where he assisted on Chang E 5 and Chang E 4 lunar missions by delivering useful scientific outputs like regolith thickness mapping, mineralogical mapping, geomorphological mapping, geological mapping, etc. of Landing and Backup Landing sites.

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SAR Interferometry for Monitoring of Land Surface Deformations
2022-08-10 10:00 - 11:00
Remote sensing datasets and techniques have proved their capability to monitor the Earth’s surface by providing invaluable information about natural phenomena and anthropogenic activities. Radar remote sensing has a privilege over optical remote sensing by it is the independency of illumination source and weather. SAR Interferometry techniques are the most valuable tools for land surface deformations. The development of these tools has increased along with enormous SAR satellite missions launched in the last two decades, such as Sentinel-1, TerraSAR-X, ALOS-1/-2, Radarsat-1/2, etc. SAR Interferometry techniques measure the land surface movement in millimetric resolution. These techniques have been developed in order to monitor land surface subsidence, landslides, earthquakes, moving objects like cars and ships, and sea ice drift and glacier flow.

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DR. MUHAGIR ELKAMALIDEPARTMENT OF GEOGRAPHY & URBAN SUSTAINABILITY, UAEUDr. Muhagir Elkamali received his Bachelor and Master degrees from the University of Khartoum in 2012 and 2016. He earned his Ph.D. degree from the United Araba Emirates Univesity in 2022. His research concentrated on the Earth surface monitoring such as urban expansion, LULC changes, geothermal exploration, and land surface subsidence. He published his research in international journals such as the Science of The Total Environment (STOTEN) as well as he presented his work at international conferences including the international conference on Water Resources Management and Sustainability and EAGE Middle East Geomechanics Workshop.

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Potential Applications of Geoinformatics in Assessing the Impacts of Climate Change
2022-07-27 10:00 - 11:00
Several countries around the world suffers from limited natural and water resources and the high rate of population increase over the last few decades, this resulted in widening the gap between water demand and supply. Furthermore, the impacts of climate change are anticipated to worsen this situation by jeopardizing existing water resources. Strategic vision to ensure an adequate, safe, and secure drinking water supply presents a challenge, particularly for such countries, faced with a critical supply-demand imbalance and a high risk of water quality deterioration. To provide sustainable and equitable long-term water management plans, current and future demands, along with available adaptation options should be assessed through community engagement.Recently, Geoinformatics were used efficiently for several climate change studies, this includes the use of the state-of-art technology for investigating, monitoring, documenting, and understanding the impacts of climate change and its consequences. Geoinformatics is the science and the technology which develops and uses information science infrastructure to address the problems of geography, cartography, geosciences and related branches of science and engineering. This includes the use of earth observation satellites (EOS), Global Navigation Satellite Systems (GNSS), Geographic Information Systems (GIS), and other related technologies.
In this webinar, the speaker will focus the shed on the current of future trend of geoinformatics and its applications in assessing the impacts of climate change.

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PROF. NEZAR ATALLA HAMMOURIPROFESSOR OF GIS AND REMOTE SENSING DEPARTMENT OF APPLIED PHYSICS AND ASTRONOMY UNIVERSITY OF SHARJAH

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Remote sensing for disaster response
2022-07-13 10:00 - 11:00
Remote sensing data is an invaluable resource in providing critical insights before and after natural and human-made disasters. Prior to disasters, “primary” remote sensing data in the forms of optical imagery and SAR data can be used measure potential various hazards (e.g. floods, droughts) and “secondary” remote sensing data, such as gridded population datasets, can be used to measure exposure to such hazards. Post disaster situations, satellite data can be used to generate rapid insights that could help guide efforts of first responders. In this talk, in depth examples will be shared of how remote sensing data has been used both prior and post disaster situations. The focus will be on the Beirut 2020 Explosion and how a collaboration between local stakeholders and NASA JPL led to one of the most data rich disasters recorded in modern history. Key projects: SAR data was initially used to generate a damage proxy map, a social media campaign to collect geo-located photos created a rich database used for ground truthing to further improve the assessment models, and finally a drone mapping project using advanced photogrammetry resulted in a very high resolution 3D model and point cloud of the entire impacted area.

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MS. MELDA SALHABCO-FOUNDER OF OPEN MAP, LEBANONMelda is the co-founder of Open Map Lebanon and a doctoral researcher at the Centre for Advanced Spatial Analysis, UCL, London, UK. Her doctoral research is focused on extracting economic insights from remote sensing datasets, at the country and sub-country scale, but with global coverage. Through Open Map Lebanon, she supported disaster recovery post the Beirut 2020 explosion, by leveraging remote sensing and crowdsourced data. Previously, Melda was a consultant at the World Bank where she assessed global population exposed to multiple types of flood risk using satellite data. Previously, she was a management consultant at Monitor Deloitte Middle East. Melda has a BA in Economics, an MSc in Urban Economic Development, and an MRes in Spatial Data Science and Visualization.

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Drone Surveys & Mapping: Innovation through the years and future trends
2022-06-29 10:00 - 11:00
An overview of the evolution of drone technology in the industry through the years followed by where Rabih thinks the industry and drone technology as a whole is headed. This presentation aims to provide insights on where drones started, current industry trends, and what to keep an eye out for in the future.

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RABIH BOU RACHEDFOUNDER & CEO OF FEDS- DRONE POWERED SOLUTIONSRabih Bou Rached takes a vision and makes it a reality through methodical planning and execution, he is both a pioneering entrepreneur and leader who intuitively identifies opportunities and inspires action. He leads mainly by example, constantly striving for excellence and encourages others to do the same. He is recognized for his ability to balance grand design with financial information while making decisions. Rabih is a leader and an educator who inspires others to reach their full potential. For over 7 years, Rabih Bou Rached has been a noteworthy leader in the Commercial Drone space. The Founder and CEO of FEDS- Drone Powered Solutions, Rabih has guided his company from its humble beginnings in the middle east to serving over 35 countries at the global stage. Being highly knowledgeable on drone rules and regulations, Rabih is part of the community for the betterment of these regulations. Rabih is a strong believer in the power of education and uses his knowledge to train the next generation of industry professionals on platforms like gisworx, The Big 5, JUIDA(Japan UAS Industrial Development Association), YPS(Young Professionals in Space) and many more. Rabih believes that in the near future, drones will play a major role in our daily lives and will be as indispensable as the phone is today.

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GIS and Remote Sensing for Environmental Studies/ Technologies and Challenges
2022-06-15 10:00 - 11:00
Satellite imagery is a sphere with vast data perfect for machine and deep learning. With significant earth observation and rapid advances in machine learning, increasing prospects for innovative analysis have emerged to aid earth environmental monitoring. This presentation will overview various challenges related to environmental earth observation data capturing, integration, fusion, and validation. Several examples that summarize the available satellite data sources and trends will be presented. This includes LULC mapping from the integration of SAR and optical Sentinel images; Image Segmentation Parameter Selection and Ant Colony Optimization for Date Palm Tree Detection; Digital Mapping of Groundwater Potential Zones Using Remote Sensing; Assessment of Temporal Growth of Sharjah City; Spatial-Temporal Analysis of Urban Growth and its Impact on Surface Runoff; COVID-19 Lockdown and the Impact on Mobility, Air Quality, and Utility Consumption; Spatial and Temporal Inversion of Land Surface Temperature in arid regions.

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PROF. RAMI AL-RUZOUQ PROFESSOR OF GEOMATICS ENGINEERING  UNIVERSITY OF SHARJAH  DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING AT THE  COORDINATOR OF THE MASTER PROGRAM IN GIS AND REMOTE SENSINGEducation • Ph.D.: geomatics engineering from the University of Calgary in Canada, (2004). • M.Sc.: Geodetic science from Ohio State University in the US, (2002). • M.Sc.: Civil Engineering from Jordan University of Science and Technology, (1996). • B.Sc.: Civil Engineering from the Jordan University of Science and Technology, (1993). Research • Environmental Remote Sensing/GIS Applications; UAV/ Digital Photogrammetry; Land-Use Land-Cover Classification; Spatial Statistics and Analysis; Satellite Image Processing and Change Detection; Urbanization and Smart Cities. • Published more than 75 scientific journals and conference publications. • Citation more than 1000 with h-index=17. (Google Scholar). Teaching • Twenty years of teaching experience at undergraduate and postgraduate levels. Teaching and developing several graduate and undergraduate courses in Geomatics Engineering • Chair of accreditation committee (Commission for Academic Accreditation, CAA) of the M.Sc. in GIS and Remote Sensing Program (2016-2020). contribute to the preparation of ABET application for the Civil Engineering program. Professional • Academic and administrative positions in the US, Canada, Jordan, and the UAE. Member of many local and international scientific societies, including the American Society of Photogrammetry and Remote Sensing (ASPRS), Mapping Sciences Institute in Australia, Jordan Engineers Association, and the Institution of Geospatial and Remote Sensing Malaysia. Email: ralruzouq@sharjah.ac.ae alruzouq@gmail.com

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GAIAS – Geospatial Artificial Intelligence Addressable Systems. An emerging combinator for future growth
2022-06-01 10:00 - 11:00
To provide an overview of key concepts encompassing the growing field of GAIAS including machine learning, deep learning, data mining and spatial data science; recent applications and potential future directions in GAIAS by Falcon Robotics.

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AHMAD ALDARWISHCEO FALCON ROBOTICSAhmad is an Engineer, Entrepreneur, and Inventor dedicated to building cutting-edge AI technology that delivers practical value. He started his career as an Aircraft Broker at ACS, UK and then as a Flight Operations Engineer at Emirates Airlines, where he successfully led parts of the digital transformation of Emirates’ Fleet, saved millions in fuel costs and lowered carbon emissions by millions of tons. In 2018 he founded Falcon Robotics and currently serves as the CEO. His career thus far has seen him earn prestigious entrepreneurship awards, recently recognized as CEO of the Year 2021 for UAE by CEO Review Magazine UK. Ahmad has an educational background in Aerospace Engineering from ERAU, Florida. He is an active member of the Royal Aeronautical Society (MRAeS) and currently serves as the regional chairperson for MENA airlines at Airbus Fuel Efficiency group.

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Remote Sensing – Data & Technology A Walk through from Past to Present
2022-04-20 10:00 - 11:00
Remote sensing is defined as the science of acquiring of information from a distance. Remote sensors collect data by detecting the energy that is reflected from Earth. These sensors can be on satellites or mounted on aircraft. Remote Sensing has a growing relevance in the modern information society. It has become a key service that is used widely in many civil applications such as agriculture, forestry, mining (and prospecting for many types of resources), map making, research in geosciences, urban planning, disaster management and even land speculation. Remote sensing, Earth observation, related Geographical Information Systems (GIS), plus the interpretation and use of this type of data are today often referred to today as Geomatics. In this session let us walk through, from the past to present on the growth & development in the Remote sensing domain from data and technology perspective.

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MR. KANNAN JAYARAMANSR. REMOTE SENSING & GIS DATA ANALYST AT GISTECA veteran GIS professional with about 18 years of experience in GIS & Remote Sensing data and in its’s various interrelated domains. Expert in Analyze, Design, Development and Deployment of Desktop and Web applications (2D & 3D). Having excellent knowledge in Workflows/process design, automation techniques of the COTS products.

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Recent Advances in Spectral Unmixing for Hyperspectral Imagery
2022-04-06 10:00 - 11:00
Hyperspectral imaging (HSI) systems collect image data simultaneously in hundreds of narrow, adjacent spectral bands. Hyperspectral remote sensing is used in a wide array of applications such as agriculture, mineralogy, surveillance, etc.In HSI, the observed radiation represented from a single pixel rarely comes from a pure material. However, the high spectral resolution of the HSI spectrometer enables the detection, identification and classification of subpixel objects and their contribution to the measured spectra. The distinct materials associated with the surface are called endmembers, and the fractions in which they appear in a pixel are called abundances. The unmixing problem refers to finding the number of endmembers, their spectral signatures, and their abundances from a given hyperspectral image.

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DR. MOHAMMED Q. ALKHATIBASSISTANT PROFESSOR, COLLEGE OF ENGINEERING & IT, UNIVERSITY OF DUBAIDr. Mohammed Alkhatib earned his Bachelor in Telecommunications Engineering from Yarmouk University in 2008. He received his Masters’ and PhD degrees in Electrical and Computer Engineering from The University of Texas at El Paso in 2011 and 2018, consecutively. In 2021, Dr. Alkhatib joined the College of Engineering and IT (CEIT) in University of Dubai as an Assistant professor. Prior to CEIT, he served as an instructor in the Academic Support Department in Abu Dhabi Polytechnic. Dr. Alkhatib research interests are spectral unmixing for hyperspectral images, HSI classification, and HSI super-resolution. He presented his research at international Journals and conference meetings including the 2019 Multidisciplinary Digital Publishing Institute (MDPI), Proceedings of the IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) and the Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

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Observing Earth Climate and Weather from Space
2022-03-16 10:00 - 11:00
Earth observations are nowadays key tools for a better understanding of the climate and weather patterns in different regions around the globe. In this webinar, I will discuss the significant contribution of Earth Observations from space towards unravelling several phenomena and allow scientists to gain knowledge on how they occur and what are their characteristics and impacts.Curious to learn more about polynyas in Polar Regions, dust storms in the tropics, rainfall and temperature trends over the UAE, snow and ice darkening in the Arctic and the Alps, etc…?

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DR. DIANA FRANCISHEAD OF THE ENVIRONMENTAL AND GEOPHYSICAL SCIENCE (ENGEOS) LAB AT KHALIFA UNIVERSITY, UAEDr. Francis is an atmospheric scientist with a Ph.D. in Atmospheric and Environmental Sciences from Sorbonne University, Paris. She is an internationally renowned scientist with more than 10 years in Academia and scientific research. Beside her role at Khalifa University as Head of ENGEOS lab, she is currently the lead of the Climate Data & Modelling cluster of the UAE Climate Change Research Network of the Ministry of Climate Change and the Environment (MOCCAE) and she is the principal investigator of several projects related to Climate and Earth observations at Khalifa University. You can learn more about her team’s work by visiting ENGEOS lab webpage: https://earth.masdar.ac.ae/index.html

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Uncertainties of Satellite-Derived Coastal Water Quality Products
2022-03-02 10:00 - 11:00
Monitoring coastal water quality is important and the sea surface temperature is one of the key parameters of water quality. It plays a significant role in studying climate change and oceanic environmental processes. SST has always been measured with buoys and thermometers in the field and by remote sensing. The use of remotely sensed SST is significantly more common for mapping SST with a wider area and at high temporal resolution. Remotely sensed SST, however, may reveal uncertainties due to factors such as water depth and turbidity. This is in addition to the atmospheric effects, such as dust, fog, wind, solar angles, and humidity. Thus, remote sensing SST estimation is compared to the measured in-situ SST for the Arabian Gulf waters, and the critical atmospheric and oceanic variables contributing to the errors are identified

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DR MARYAM R. AL SHEHHIASSISTANT PROFESSOR AT CIVIL, INFRASTRUCTURE, AND ENVIRONMENTAL ENGINEERING AT KHALIFA UNIVERSITY, UAEDr Maryam R. Al Shehhi is an Assistant Professor in the Department of Civil, Infrastructure, and Environmental Engineering at Khalifa University and a member of the Khalifa University Space Technology and Innovation Center (KUSTIC). Before joining Khalifa University, she has worked as a postdoctoral researcher at the world leading university, Massachusetts Institute of Technology (MIT). Dr. Al Shehhi has been working in several projects with international and local environmental agencies. One of the recent projects she works on is utilizing satellite-derived IOPs to model water quality in the Arabian Gulf. Her scientific findings have been published in more than 20 research articles in reputable journals.

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The Digital Twin Project
2022-02-23 10:00 - 11:00
The GIS center at Dubai municipality aims to provide a digital twin of Dubai, which is a digital replica of the city of Dubai in the form of two-dimensional and three-dimensional maps containing all assets, structures and features, starting from the macro level of the land master plans and reaching down to the micro level of building’s unit level details

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NOORA BIN HAIDERGEOGRAPHIC INFORMATION SYSTEM CENTER, DUBAI MUNICIPALITYNoora Bin Haider holds a Bachelor Degree in Architectural Engineering and a professional diploma in Future Government Leaders. She works at the GIS center in Dubai municipality on the Dubai BIM Roadmap project. This strategic project aims to establish a BIM road map and BIM e-Submission platform and standards for all Dubai building permitting authorities.

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Spatio-temporal Forest fire monitoring using spatial-statistical and Geo-spatial analysis of factors determining forest fire in Margalla Hills, Islamabad, Pakistan
2021-11-30 10:00 - 11:00
The spatio-temporal changes in burnt area were identified using Landsat satellite data and modeling was used to predict the fire ignition and size distribution daily and yearly. Forest fire ignition models are effective ways to predict and classify drivers for ignition probability across broad areas. The aim was therefore to compare the predictive output and significance of predictable ignition and spatial patterns of three inflammation-distribution model types; one parametric, a statistical model and two machine-learning algorithms: Maximum entropy (Maxent) and Random Forests (RF). We parameterized the models for Margalla Hills, the National Park, Islamabad, Pakistan using 30 years of ignition, socio-economic, and environmental data. The best predictors of forest fire sites in all models were human population and development variables (although variable rankings were slightly differentiated), as well as elevation. However, despite similar model performance and variables, the map of ignition probabilities generated by Maxent was markedly different from those of the two other models.
Related Published papers:

Tariq, A.; Shu, H.; Siddiqui, S.; Munir, I.; Sharifi, A.; Li, Q.; Lu, L. Spatio-temporal analysis of forest fire events in the Margalla Hills, Islamabad, Pakistan using socio-economic and environmental variable data with machine learning methods. For. Res. 2021, 13, 12, doi: https://doi.org/10.1007/s11676-021-01354-4 (Journal of Forestry Research)
Tariq, A*.; Shu, H.; Saddiqui, S.; Mousa, B.G.; Munir, I.; Nasri, A.; Waqas, H.; Baqa, M.F.; Lu, L. Forest fire Monitoring using spatial-statistical and Geo-spatial analysis of factors determining Forest fire in Margalla Hills, Islamabad, Pakistan. Geomatics, Nat. Hazards Risk 2021, 12, 1212–1233, doi: https://doi.org/10.1080/19475705.2021.1920477 (Geomatics, Natural Hazards and Risks).

DR. AQIL TARIQKEY POSTDOCTORAL FELLOW STATE KEY LABORATORY OF INFORMATION ENGINEERING IN SURVEYING, MAPPING AND REMOTE SENSING (LIESMARS), WUHAN UNIVERSITY, WUHAN CHINA. (PHOTOGRAMMETRY, REMOTE SENSING, GIS, GEOMATICS, SPATIAL ANALYSIS AND GEOINFORMATION)Dr. Aqil Tariq was born in Rawalpindi, Punjab, Pakistan. Currently, he is working as postdoctoral fellow in the State key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan China. He did one Master of Science in Geography and second Master of Science in Remote Sensing and GIS. Dr. Aqil Tariq has completed his Ph.D. (Photogrammetry and Remote sensing) within a span of three years i.e. from.2018-2021. He published 17 papers during Ph.D. tenure. He has very good scientific research writing abilities. Now, he is author of more than twenty four (24) SCI/SSCI peer reviewed journal papers. He has abilities to conduct research individually. His research interest areas are 3D Geoinformation, Urban analytics, spatial analysis to examine land use/land cover, Geospatial data science, Agriculture monitoring, Forest Fire, Forest monitoring, forest cover dynamics, spatial statistics, multi-criteria algorithms, ecosystem sustainability, hazards risk reduction, statistical analysis and modelling using Python, R and MATLAB. He is also working as reviewers in high SCI/SSCI impact factor Journals. He is also member of different international science communities’ i.e. ISPRS, International Water Resources Association, International Association of Geodesy, Surveying & Spatial Sciences Institute (SSSI) and Emirati Society of GIS and Remote Sensing.

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Earth Observation Products and Services: From Concepts to Applications and Beyond
2021-11-16 10:00 - 11:00
The Mohammed Bin Rashid Space Centre (MBRSC) is integral to the strategic initiative put in place by the Dubai government to inspire scientific innovation, technological advancement, and to advance sustainable development in the United Arab Emirates. Products and services offered by the MBRSC include high-resolution earth satellite imagery, satellite image analysis, ground station service, antenna hosting service, environmental monitoring services, and global disaster management support. It provides a vital source of instant information and reference for a variety of projects. From analysis, forecasting and monitoring, to managing resources and activities globally, MBRSC products are an integral component in a range of applications, including disaster management, civil management, civil engineering, land planning, natural resources exploration, geographical information studies, and environmental projects. Throughout this webinar, you will get an insight of MBRSC vision, mission, projects and initiatives, EO products and services, etc…

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ENG. DIENA AL-DOGOMRESEARCH ASSISTANT AT MOHAMMED BIN RASHID SPACE CENTRE (MBRSC)Diena Aldogom is a research assistant at Mohammed Bin Rashid Space Centre (MBRSC). She holds M.Sc. in Geographic Information System from Pennsylvania State University (PSU) in the US (2016). B.Sc. in Geomatics and Surveying Engineering (2008) from BAU, Jordan. Diena Served in several academic and industrial positions related to GIS and Remote Sensing. Before joining the MBRSC lab team, she worked at the Royal Jordanian Geographic Center and Thomson Reuters. Diena is an active researcher with many international journal and conference publications. Her research domain expands to cover spatial and statistical analysis, GIS and Remote sensing analysis, data management, Environmental studies, and hazard assessments.

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Exploring Land use/land cover change and Flooding Risks using Remote Sensing and GIS Techniques
2021-11-02 10:00 - 11:00
This study was conducted to investigate the spatiotemporal changes of land use/land cover (LULC) along the eastern coast of the United Arab Emirates (UAE) over a 20-year period using an integration of remote sensing and Geographic Information Systems techniques. The impact of land use change on flooding potential was also investigated through hydrologic model simulations. Landsat images of the years 1996, 2006 and 2016 were processed and analyzed. Change detection was carried out to assess changes in the built-up areas. Furthermore, the impact of urbanization on flooding was assessed using a hydrologic model in two major watersheds of Fujairah Emirate. It was observed that for the period 1996–2006 the vegetation and the built-up areas had increased at a rate of 11.23% and 24.56%, respectively. For the period 2006–2016, this expansion more than doubled in terms of the vegetation class (27.51%) and slightly increased for the built-up class (28.98%). The change detection analysis revealed that urbanization has mostly occurred along the coastal boundary. Hydrologic model simulations quantified the role of urbanization in increasing the flooding potential. The increase depends on watershed characteristics and the rate of change in urbanization and the magnitude of the rainfall event.

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DR. KHAULA ALKAABIChief Innovation Officer, and an Associate Professor at the Geography and Urban Sustainability Department at UAEUDr. Khaula Alkaabi is the Chief Innovation Officer, and an Associate Professor at the Geography and Urban Sustainability Department at the United Arab Emirates University (UAEU). She holds a BA degree (Hons) in Geography from UAEU, a MA (Hons) and a PhD (Hons) in Geography from UNCG, USA. Her research interests include air transportation, land use planning, spatial analysis, GIS applications, unmanned aircraft applications, tourism, urban development, economic geography, entrepreneurship and innovation, and the surface of Mars. She has published several academic articles in various international academic journals, as well as reviewed several government reports and academic international journal publications.

DR. KHALID HUSSEINDepartment of Geography and Urban Sustainability, College of Humanities and Social Studies (CHSS), UAEUDr. Khalid Hussein joined the Department of Geography and Urban Sustainability, College of Humanities and Social Studies (CHSS), UAEU in 2015. Prior to that Khalid taught and conducted research at the University of Colorado, Boulder. Khalid competed his graduate and postgraduate studies at the University of Georgia Augusta, Goettingen, Germany, and the University of Colorado, Boulder, USA. Khalid research interests are in the use of geographic information systems (GIS) and satellite and airborne remote sensing techniques, integrated with in situ observations and modeling, to understand how and why the Earth cover is changing, and what those changes mean for life on Earth. Khalid research focuses on three areas. The first is the use of remote sensing techniques integrated with GIS, and in situ data to understand how and why land cover and land use are changing; and what those changes mean for sustainability of natural resources. The second research area focuses on the understanding of the effects of climate change on the Earth’s surfaces using remotely sensed data and field measurements. Finally, he is also interested on the application of thermal remote sensing in identifying and delineating areas of geothermal activities as a potential source of energy.

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Geospatial Multicriteria Analysis for Earthquake Risk Assessment: Case Study over Fujairah, UAE
2021-10-19 10:00 - 11:00
A clear understanding of the spatial distribution of earthquake events facilitates the prediction of seismicity and vulnerability amongst researchers in the social, physical, environmental, and demographic aspects. Generally, there are few studies on seismic risk assessment in UAE within the geographic information system (GIS) platform. Former researches and recent news events have demonstrated that the eastern part of the country experiences jolts of 3-5 magnitude, specifically near Fujairah city and surrounding towns. This study builds on previous research on the seismic hazard that extracted the eastern part of the UAE as the most hazard-prone zone. Therefore, this study develops an integrated analytical hierarchical process (AHP) and machine learning (ML) for risk mapping considering eight geospatial parameters- distance from shoreline, schools, hospitals, roads, residences, streams, confined area, and confined area slope. Experts’ opinions and literature reviews were the basis of the AHP ranking and weighting system. To validate the AHP system, support vector machine (SVM), decision tree (DT) and random forest (RF) classifiers were applied to the datasets. The datasets were split into 60:40 ratio for training and testing. Results show that SVM has the highest accuracy of 79.6% compared to DT and RF with a ‘predicted high’ precision of 87.5% attained from the model. Risk maps from both AHP and ML approaches were developed and compared. Risk analysis was categorized into 5 classes ‘very high’, ‘high’, ‘moderate’, ‘low’, and ‘very low. Both approaches modelled relatable spatial patterns as risk prone zones. AHP approach concluded 3.6% as ‘very high’ risk zone, whereas only 0.3% of total area was identified from ML. The total area for the ‘very high’ (20 km2) and ‘high’ (114 km2) risk were estimated from ML approach.

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SAEED AL MANSOORIHEAD OF THE APPLICATIONS DEVELOPMENT AND ANALYSIS SECTION (ADAS) AT MOHAMMED BIN RASHID SPACE CENTRE (MBRSC)Saeed Al Mansoori is the head of the Applications Development and Analysis Section (ADAS) at Mohammed Bin Rashid Space Centre (MBRSC). He has received B.Sc. degree in Communication Engineering from Khalifa University of Science, Technology and Research (KUSTAR), Sharjah, UAE in 2010 and the M.Sc. degree in Electrical Engineering from American University of Sharjah (AUS) in 2016. Saeed’s research interests are in the area of image processing (super-resolution, watermarking, object detection and image classification). He is the member of the international society of optics and photonics and one of the program committee in High-Performance Computing in Remote Sensing since 2012.

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Applications of Remote Sensing to Air Quality Monitoring
2021-10-05 10:00 - 11:00
Air pollution has always been considered a major problem worldwide. The formation of air pollutants depends upon the sources of their precursors whether natural or anthropogenic. The level of air pollution, and therefore a measure of air quality, is derived from measurement of concentrations of pollutants such as O3, NO2 and particulate matter (PM). These measurements are usually collected at a limited number of ground-based monitoring stations and may not convey a full characterization of their spatial distribution. This presentation discusses the potential of various remote sensing systems to estimate such measurements and consider their limitations. As an example, an approach to estimate PM10 from MODIS aerosol optical depth over Al Ain region will be detailed and its results discussed.

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DR. NAZMI SALEOUSASSOCIATE PROFESSOR OF REMOTE SENSING AND GIS DEPARTMENT OF GEOGRAPHY AND URBAN SUSTAINABILITY, UAEUDr. Nazmi Saleous holds a computer engineering degree (1987) and a Ph.D. in Electronics (1990) from the University of Science and Technology of Lille (France). He joined the United Arab Emirates University (UAEU) in August 2006 where he currently holds a position of Associate Professor of Remote Sensing and GIS in the Department of Geography and Urban Sustainability. He serves as the coordinator of UAEU’s Master of Science in Remote Sensing and GIS program. Dr. Saleous is involved in multiple research projects including the use of Geospatial technology in estimating carbon sequestration, and monitoring and modeling urban growth. Prior to joining UAEU, Dr. Saleous spent 14 years at NASA Goddard Space Flight Center where he conducted research on satellite data processing and the development of long-term remote sensing data sets for use in land and environmental applications. Dr. Saleous’ research interests are in the application of remote sensing and GIS for solving environmental and urban problems. They include remote sensing data processing, creation of data time series, land use and land cover change, carbon sequestration in plantations, desertification, and modeling of environmental processes using geospatial technology.

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Application of Remote Sensing and GIS to Flood and Rainwater Harvesting
2021-09-21 10:00 - 11:00
The construction of the Grand Ethiopian Renaissance Dam (GERD) will have positive and negative impacts on the people living downstream. Among possible impacts is the probability of flooding of human settlements along the Blue Nile. Reduction of water level is also a possible adverse effect on the agricultural schemes along the Blue Nile; the Gezira scheme, one of the largest irrigation projects in the world. The objective of this study is two-fold. The first objective is to identify cities and villages near the Sennar Dam (in Sudan) that may be affected by potential fluvial (river) floods. The second objective is to select rainwater-harvesting (RWH) sites that can be used for water-supply backup while minimizing possible water-level reduction. RWH is in line with UN Global Sustainable Development Goals (UN-SDG). The use of remote-sensing techniques has enabled access to unique sources of information (satellite images and DEM) to better characterize hazards and risks, and a GIS was used as an effective modeling and visualization tool.Keywords: Fluvial flood, Rainwater harvesting, Sennar Dam, Sudan, Remote sensing, GIS

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DR. MOHAMED YAGOUBDEPARTMENT OF GEOGRAPHY AND URBAN SUSTAINABILITY, UAEUProf. Yagoub led Graduate Studies at the Department (20016-2020), chaired the Department between 2005 and 2007, and directed the Master Program of Remote Sensing and GIS at the UAE University between 2002 and 2005. His scholarship is indexed in Google Scholar, Scopus, Web of Science, and Research Gate. Dr. Yagoub teaches various courses related to Geoinformatics such Remote Sensing, Geographic Information System (GIS), and Global Navigation Satellite Systems (GNSS). Dr. Yagoub is a referee to many organizations/journals. He participated in organization of national and international conferences and co-chaired the 5th International Conference on Earth Observation for Global Changes (EOGC), 2015. He received Abu Dhabi -Spatial Data Infrastructure (AD-SDI) Distinguished Award for contribution to GIS/Remote Sensing academic programs (2018). He also received the Teaching Faculty Recognition Award on August 28, 2007 bestowed by H.H. Sheik Nahayan Mabarak Al Nahayan, former Minister of Higher Education and Scientific Research.

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Remote Sensing of Soil Salinity in the United Arab Emirates
2021-09-07 10:00 - 11:00
Soil salinity, whether natural or human induced, is a major geo-hazard in arid and semi-arid landscapes. In agricultural lands, it negatively affects plant growth, crop yields, whereas in semi-arid and arid non-agricultural areas it affects urban structures due to subsidence, corrosion and ground water quality, leading to further soil erosion and land degradation. Accurately mapping soil salinity through remote sensing techniques has been an active area of research in the past few decades particularly for agricultural lands. Most of this research has focused on the utilization and development of salinity indices for properly mapping and identifying saline agricultural soils. This research develops a soil salinity index and model using Landsat 8 OLI image data from the near infra-red and shortwave infra-red spectral information with emphasis on soil salinity mapping and assessment in non-agricultural desert arid and semi-arid surfaces. The developed index when integrated into a semi-empirical model outperformed in its soil salinity mapping overall accuracy (60%) in comparison to other salinity indices (~50%). The newly developed index further outperformed other indices in its accuracy in mapping and identifying high saline soils (67%) and excessively high saline soils (90%).

DR. NAEEMA AL HOSANIChair, Department of Geography and Urban Sustainability, UAEUDr. Naeema Alhosani, obtained her Ph. D. (2009), and her M.A. (2005) in Geography “Cartography” from the University of Kansas, USA. Currently, she is department chair since Aug. 2017, as well as she was an assistant dean for student affairs in CHSS from 2013-2017. She has many awards. Her research interests are: Cartography, Maps & Mapping, Map Conception & Development, Map scale, Cartographic Design, Information Design, Practicum in Cartography, Problems in Production map, Cartography and Environment, GIS, Remote Sensing, and Education. Dr. Naeema has participated in many conferences (both regional and international) and research projects as well as maps publications, besides being a member of many professional committees. Also she is affiliated to many professional associations. She has various contributions at the departmental, College, University and Community levels.

DR. ABDELGADIR ABUELGASIMAssociate Professor, Department of Geography and Urban Sustainability, UAEUDr. Abuelgasim received both his masters and PhD degrees from Boston University in 1996. He later joined the NASA Goddard Space Flight Center in Maryland, USA in 1998 as a visiting scientist where he worked in a research program exploiting multi-angle remote sensing observations. In 2000 he relocated to Canada where he has been with the Canada Centre for Remote Sensing and the Canadian Space Agency as a research scientist. Dr Abuelgasim also served as the international geospatial data consultant during 2012 for the Nile Basin Initiative. Dr Abuelgasim research and teaching interests are focused on the analysis of geospatial data for information products generation, physical and human geography and on the effects of human induced environmental and ecological changes. He is currently an associate professor of geography at UAEU.

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Spatial Enhancement of Hyperspectral Satellite Imagery
2021-07-13 10:00 - 11:00
Remote sensing technology has undeniable importance in various industrial applications. Some of which include mineral exploration, plant detection, defect detection in aerospace and shipbuilding, and optical gas imaging, to name a few. Remote sensing technology has been continuously evolving, offering a range of image types that can facilitate the aforementioned applications. One such type is Hyperspectral Images (HSIs). Unlike multispectral and natural images, HSIs consist of hundreds of bands, which makes it easier to identify objects through their spectral reflectance signals. Despite its high spectral resolution, HSIs suffer from low spatial resolution. This is a natural tradeoff that occurs due to cameras attempting to capture 3D images using 2D sensors. In order to implement remote sensing applications effectively with satisfying accuracy, HSIs need to have high spectral resolution as well as high spatial resolution. This webinar discusses the several advances in the field of HSI spatial enhancement, highlights and assesses the most recent state-of-the-art approaches, and draws the future direction of this research field.

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ENG. NOUR ABURAEDRESEARCH ASSISTANT @MBRSC LAB - UNIVERSITY OF DUBAINour Aburaed is a holder of BSc degree in Electrical and Computer Engineering and MSc degree in Electrical and Computer Engineering from Khalifa University of Science and Technology in Abu Dhabi – UAE. Her MSc is specialized in High-ISO Image De-noising and Quantum Image Processing. Nour was a Teaching Assistant for various math, physics, and programming courses at Khalifa University for two years. She has been working as a Research Assistant at Mohammed Bin Rashid Space Centre Laboratory based at the University of Dubai since 2018, where she specializes in applications of Image Processing and Artificial Intelligence within the context of remote sensing imagery. Nour is also currently a PhD student at the University of Strathclyde, where she studies the enhancement of Hyperspectral Satellite Imagery. Her research and study activities resulted in various publications in notable conferences and journals. Her current interests include object detection, semantic segmentation, single image super resolution, hyperspectral images, convolutional/complex/quantum neural networks, and data analytics and visualization.

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Automated Surveying Using AI & Google Maps Satellite Imagery
2021-06-29 10:00 - 11:00
In this session, InfraLytiks will present some very interesting capabilities and case studies for automation and Artificial Intelligence (AI) case studies for Satellite Data based automated surveying. The focus will be on a case study have been successfully developed and completed by InfraLytiks for engineering surveying & planning. AI has been used to automatically identify and generate shapefiles for objects of interest for surveying such as road attribute detection, tress cover, water body & structure types identification from Google Maps API. A live demo will also be performed to showcase the AI algorithm in actions along with additional software features. InfraLytiks is a complex data analytics and automation company based in the USA & UAE that specializes in engineering-based data analytics and development of custom software products.

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AKASH VIDYADHARANCHIEF TECHNOLOGY OFFICERFounder & CTO of InfraLytiks · 4+ years of successful company operations in USA · Experience in leading ML, AI, Automation & Software Development · Experience in Robotics & Drone Development & Automation · BS Aerospace Engineering · MS Aerospace Engineering · M.Eng. Systems Engineering · Iowa State University, USA

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Earth Observation in the New Space Age
2021-06-15 10:00 - 11:00
The “NewSpace” age has been a great disruptor of the earth observation industry ecosystem over the last few years, more so in the last three years with several new startups announcing plans to develop constellations of microsatellites with the ability to provide very high spatial resolution data. This competition is significantly accelerating innovation in both hardware and software, thereby contributing to the enhancement of the quality of data. The amount of high-resolution data is significantly increasing both from optical and radar satellites. Along with the spatial resolution, the concept of constellations has greatly improved the temporal resolution of the data and this is expected to get better with the launch of new constellations and adding more satellites to the existing constellations such as Planet, ICEYE, Satellogic, etc. In parallel to the data explosion, the field of machine learning has gone through a significant disruption due to the improving hardware capabilities and the exponential growth of deep learning architectures. This is greatly supporting the processing of the large amount of data becoming available from the satellites. In line with these developments, this talk explores how data and the corresponding processing architectures are expected to be handled in the future with an outlook on opportunities that can be created.

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DR. PRASHANTH MARPUTECH LEAD OF SPACE PROGRAM AT GROUP 42Dr. Prashanth Marpu is the Tech Lead of Space Program at Group 42, Abu Dhabi, United Arab Emirates. Prior to joining G42, he was an Associate Professor in the Department of Electrical Engineering and Computer Science and Manager of YahSat Space Lab at Khalifa University of Science and Technology, Abu Dhabi, UAE. His specialization is in small satellites, image processing, machine learning, remote sensing and internet of things. Before coming to the UAE, Dr. Marpu worked as a researcher at the University of Iceland and at the University of Pavia, Italy, where he was a Marie Curie Fellow working on developing advanced methods for earth observation data analysis. He holds a PhD in Remote Sensing from TU Freiberg, Germany, and MSc in Wireless Engineering from the Technical University of Denmark. He was involved in designing and building small satellites as a project manager of four satellite programs MYSat-1, DhabiSat, MeznSat and Light-1 while participating as an advisor and reviewer for several other satellite programs. He has also actively contributed to the development of novel approaches for processing remote sensing data for a wide range of applications. Dr. Marpu has been a Council member of the International Society of Digital Earth since 2020 and has been part of several international committees related to Earth Observation technologies. He has contributed to more than 150 publications in various journals and conferences and has been actively involved in the space and remote sensing educational activities.

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Contribution of GIS and remote sensing technologies to an integrated coastal and marine environmental management framework
2021-06-01 10:00 - 11:00
The coasts and islands that flank the United Arab Emirates (UAE), host an important number of benthic habitats; seagrass beds and coral reefs that should be the focus of conservation actions. Well-designed conservation and management plans require efficient monitoring systems that include mapping the extent and location of the major habitats and also understanding their status and trends over time. The coastal waters of the UAE are optically complex and heterogeneous, thus providing a challenging environment for mapping and monitoring seagrass beds and coral reefs. This is due to the similarity in reflectance characteristics of benthic features such as seagrass, corals and macroalgae. The mapping limitations are mainly faced by broadband multispectral sensors usually advantageous for their affordability. These challenges are taken on by providing more accurate knowledge on the UAE benthic habitats’ spatial distribution and more insights into their temporal variations. Advances in GIS, remote sensing instrumentation, data availability, and processing methods are presented and discussed. Additional tools to better evaluate and monitor the conditions of the UAE’s marine environment are presented. An integrated framework for future investigations that are at the forefront of contemporary marine environment science and management issues is suggested.

DR. HAIFA BEN-ROMDHANEVISITING ASSISTANT PROFESSORHaïfa Ben-Romdhane is presently a visiting assistant professor to the department of Geography and Planning, and the Environment: Dynamics of Territories and Societies programme at the Paris Sorbonne University Abu Dhabi. Dr. Ben-Romdhane received her PhD in Interdisciplinary Engineering (2016) from the Masdar Institute of Science and Technology in collaboration with Massachusetts Institute of Technology. She conducted her master’s studies at the Atmosphere and Ocean Research Institute of the University of Tokyo, Japan, and received her MSc degree in Aquatic Biosciences – Ecology, Behaviour and Observation Systems (2009). Before that, she received her BEng degree in Marine Environmental Engineering (2005) from the National Agronomic Institute of Tunisia. Before joining Sorbonne University, she was a researcher at the Research Centre for Renewable Energy Mapping and Assessment (ReCREMA), Khalifa University, Masdar Campus. Before joining Khalifa University, she worked as a project manager, data processing and data quality specialist at the Military Survey Department – Bayanat for Mapping and Surveying Services, Abu Dhabi, UAE. Her expertise falls in the fields of statistical methods and image processing with applications in the general fields of environmental data analysis, land use, land cover, change detection and analysis, time series analysis of environmental and climatic variables, water resources monitoring, etc. Her aspirations are to help protect the ocean and marine environments through the establishment of adaptive management plans, highlighting the role of science to provide a basis for robust decision-making against urgent problems and long-term management outcomes.

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Protecting Satellite Images Against Attacks using AI and Image Processing Techniques
2021-05-20 10:00 - 11:00
Satellite imagery is a pivotal source of valuable information for monitoring our planet along with natural resources. However, these images have an extreme acquisition cost. Nowadays, with the widespread of the advanced technology, unauthorized ordinary people can access these data, modify their content and utilize them illegally. Therefore, there is a massive demand for providing secure storage and transmission of such data. Hence, digital watermarking has been introduced for overcoming this illegitimate practice.

DR. ALAVIKUNHU PANTHAKKANASSISTANT PROFESSORDr. Alavikunhu Panthakkan is a dynamic research scientist in electronics engineering and image signal processing. His research interests are in the areas of engineering education, copyright protection, authentication, medical image processing, video signal processing and artificial neural network. He received bachelor degree (B.Tech) in electronics and communication engineering, master degree (M.Tech) in electronics engineering and Ph.D. in electronics engineering. He has 4 years industrial experience and 7 years of teaching/research experience. He has published 20 papers in international conferences and journals. He is a member of Institute of Electrical and Electronic Engineers (IEEE), member of Institution of Engineers (India) (MIE), member of International Association of Engineers (IAENG), member of International Association of Computer and Information Technology (IACSIT) and member of Institute of Research Engineers and Doctors (IRED).

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Semantic Segmentation of Roads in Satellite Imagery
2021-05-04 10:00 - 11:00
Remote sensing is a field that is constantly growing due to its importance in applications related to urban planning, risk assessment, resource exploration, and disaster management. Some of the most highly researched topics in the area of remote sensing include Land Cover Land Use (LCLU), object detection, scene classification, and semantic segmentation. Nowadays, researchers are looking into automating these tasks, as performing them manually is time and cost inefficient. Therefore, Deep Learning (DL) algorithms have been utilized for remote sensing and image processing tasks in the recent years. Many studies proved efficiency of DL algorithms, however, several challenges remain unsolved. In particular, semantic segmentation is one of the challenging tasks that is under heavy demand in the field of remote sensing. For this research study, semantic segmentation is applied to extract roads from satellite images. Road mapping is an essential first step in several applications that include transportation, traffic management, and city planning. Extracting roads efficiently and accurately will in turn boost the overall outcome of the aforementioned applications. U-Net is the state-of-the-art Convolutional Neural Networks (CNN) that perform semantic segmentation. This network will be trained using publically available Massachusetts dataset. The accuracy and loss of all experiments will be reported and sample results from the dataset will be demonstrated.

ENG. MINA AL-SAADRESEARCH ASSISTANT @MBRSC LAB - UNIVERSITY OF DUBAIMina Al-Saad is a Research Assistant at Mohammed Bin Rashid Space Center (MBRSC) Lab at university of Dubai. She received her BSc in Laser and Optoelectronics Engineering from Al-Nahrain University, Iraq in 2009 and received her MSc in Laser and Optoelectronics Engineering from Al-Nahrain University, Iraq (2012). Her research interests include: Geographic information system (GIS) and remote sensing, Autonomous Object Detection, Semantic Segmentation, and Satellite Calibration and Validation.

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Satellite Remote Sensing for Maritime, Urban Planning and Agricultural Applications
2021-04-20 10:00 - 11:00
Satellite remote sensing has emerged as a transformative technology with diverse applications, notably in maritime monitoring, urban planning, and agriculture. In the maritime domain, satellites with advanced sensors can track vessel movements, detect oil spills, and monitor ocean health, bolstering maritime security and environmental conservation efforts. In urban planning, satellite data aids in mapping urban growth, infrastructure development, and land-use patterns, enabling informed decision-making for sustainable city planning. Furthermore, satellites provide invaluable insights into crop health, yield prediction, and soil moisture levels in agriculture, empowering farmers to optimize their practices and enhance food security. With its far-reaching capabilities, satellite remote sensing continues revolutionizing these critical sectors, offering a bird’s-eye view of our ever-changing world.

DR. ALI AL HAMMADICO-FOUNDER OF FARMINDr. Ali Al Hammadi received his BSc in Chemical Engineering (CE) from the Petroleum Institute, Abu Dhabi (honors with distinction, 2011) and received his PhD from the Department of Chemical and Biomolecular Engineering (CHBE) at Rice University, Houston, TX, USA (2016). His research is focused mainly on the challenges facing the oil industry as more heavy crude oils are produced; in particular, the clogging of wellbores, chocks, pumps, and reservoirs caused by the presence of asphaltene. The effect of asphaltene is an example of how both thermodynamics and kinetics can contribute to a problem. On the thermodynamic part, it mainly concerns with how asphaltene presence in a mixture or crude oil can affect the phase behavior and PVT properties. On the kinetics part, it mainly emphasizes the precipitation, aggregation, and deposition interactions and the prediction of the extent of such deposit. Another main research of Dr. Al Hammadi are nanotubes and fiber-reinforced composites. Experiments are being established to purify nanotubes by removing byproducts that hinder the full capabilities of nanotubes and study their scalability. Such nanotubes composites can be used for better electrical efficiency, lower densities, and extreme temperature applications.

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Use Cases of GIS and Remote Sensing Projects: from Concepts to Applications
2021-04-06 10:00 - 11:00
GIS (Geographic Information Systems) and remote sensing technology use various applications, from conceptualization to practical implementation. These powerful tools have revolutionized the way we interact with spatial data. Starting with concepts, GIS aids in spatial data collection, analysis, and visualization, facilitating decision-making processes in fields as diverse as urban planning, natural resource management, and disaster response. Remote sensing complements GIS by providing real-time and historical Earth observation data, enabling applications like environmental monitoring, crop yield prediction, and disaster risk assessment. Together, GIS and remote sensing create a dynamic synergy, transforming abstract ideas into tangible solutions that address complex challenges in our ever-evolving world.
