This document provides information on the GEOG2750 module on Earth Observation and GIS of the Physical Environment. It is a 20-credit module split into two semesters, with the first focusing on Earth Observation and the second on GIS. The GIS portion aims to teach students how to use GIS software like ArcGIS for applications in physical geography, interpret spatial environmental data, and address issues like data quality. It involves lectures, practical sessions, and assessments including practical worksheets and an exam. The syllabus covers topics like spatial data variability, interpolation, terrain modeling, and hydrological modeling over 10 weeks.
Satellite Image Based Mapping of Wetland Tundra Landscapes Using ILWIS GISUniversität Salzburg
This document describes a study that used ILWIS GIS and Landsat TM satellite images from 1988 and 2011 to map and monitor changes in wetland tundra landscapes on the Yamal Peninsula over a 23-year period. The author processed the satellite images using techniques like georeferencing, spectral reflectance analysis, image clustering, and classification. The results identified 13 land cover types for 1988 and 2011, showing changes like an increase in willow shrub coverage over time. The mapping aims to understand landscape dynamics in this Arctic tundra region.
Glacier area evolution of Nevados Caullaraju/Pastoruri in the last decadesInfoAndina CONDESAN
This document describes a study analyzing glacier area changes in the Nevados Caullaraju and Pastoruri regions of Peru between 1984-2011 using Landsat imagery and ancillary data. Historical Landsat 5 TM images from the dry season were processed to estimate clean and debris-covered glacier areas over time. Normalized difference snow index (NDSI) thresholding was used to delineate clean glaciers, but debris-covered areas were difficult to identify. The results found a significant decrease in glaciated area of 3.3 km2 per decade, consistent with ground-based data. However, errors in estimating total area were around 30% due to challenges in identifying debris-covered glaciers with optical remote sensing alone.
DSD-INT 2018 Application of XBeach to a Low-elevation Dune System with Hurric...Deltares
This document summarizes a study that used the XBeach model to simulate the morphological changes to a low-elevation dune system in Louisiana from Hurricane Gustav in 2008. The objectives were to model the erosion processes during the hurricane and establish a modeling framework to forecast future hurricane impacts. A tiered modeling approach was used with the XBeach model nested within larger scale Delft3D models. The results showed the model captured the general erosion patterns but overpredicted erosion in some areas. Future work involves coupling the models and examining the effect of barrier island disintegration on wave fields.
From global to regional scale: Remote sensing-based concepts and methods for ...Repository Ipb
The document discusses land cover mapping and change detection in tropical regions using remote sensing. It provides an overview of existing land cover classification systems and global and regional satellite-based mapping products. The paper compares different land cover maps for a test region in Central Sulawesi, Indonesia, finding inconsistencies between products and uncertainty in estimates of land cover classes and changes between years. Future work on operational land cover mapping in the tropics needs further harmonization of definitions and products, regional validation, and a standardized multi-level classification workflow.
Mineral potential projects in the Southern New England Orogen: a pilot study conducted by the Geological Survey of NSW and Kenex to provide a comprehensive account of the mineral resource potential of the region
Glaciers and ice caps (GICs), excluding those in Greenland and Antarctica, lost mass at a rate of 148 +/- 30 Gt yr-1 from 2003 to 2010 according to a study using GRACE satellite gravity measurements. This contributed 0.41 +/- 0.08 mm yr-1 to global sea level rise. The GIC loss rate was about 30% lower than previous estimates. Additionally, Greenland and Antarctic ice sheets, including peripheral GICs, contributed 1.06 +/- 0.19 mm yr-1 to sea level rise. In total, all ice-covered regions contributed 1.48 +/- 0.26 mm yr-1 to sea level rise over this period according to the study.
geog2750_15.ppt principles of grid based modellingsuerie2
This document discusses linking models to GIS and principles of grid-based modeling. It describes how GIS provides tools for environmental data management but limited spatial analysis, which can be addressed by linking models. Grid-based or "cartographic" modeling involves applying mathematics to raster maps using spatial operators and functions. The document outlines different types of modeling functions in ArcGIS including local, focal, zonal, and global functions. It provides examples of using these functions to perform tasks like slope modeling, soil modeling, and land capability mapping.
This document summarizes three case studies that used remote sensing and GIS techniques to analyze land use and land cover change over time. The first case study analyzed changes from 1990-2010 in Hawalbagh, India using Landsat imagery. It found increases in built-up land and decreases in barren land. The second studied coastal Egypt from 1987-2001 using Landsat, identifying 8 land cover classes. The third examined Simly watershed, Pakistan from 1992-2012 using Landsat and SPOT data, finding increases in agriculture and decreases in vegetation. All three used supervised classification and post-classification comparison to analyze land use/cover changes.
Satellite Image Based Mapping of Wetland Tundra Landscapes Using ILWIS GISUniversität Salzburg
This document describes a study that used ILWIS GIS and Landsat TM satellite images from 1988 and 2011 to map and monitor changes in wetland tundra landscapes on the Yamal Peninsula over a 23-year period. The author processed the satellite images using techniques like georeferencing, spectral reflectance analysis, image clustering, and classification. The results identified 13 land cover types for 1988 and 2011, showing changes like an increase in willow shrub coverage over time. The mapping aims to understand landscape dynamics in this Arctic tundra region.
Glacier area evolution of Nevados Caullaraju/Pastoruri in the last decadesInfoAndina CONDESAN
This document describes a study analyzing glacier area changes in the Nevados Caullaraju and Pastoruri regions of Peru between 1984-2011 using Landsat imagery and ancillary data. Historical Landsat 5 TM images from the dry season were processed to estimate clean and debris-covered glacier areas over time. Normalized difference snow index (NDSI) thresholding was used to delineate clean glaciers, but debris-covered areas were difficult to identify. The results found a significant decrease in glaciated area of 3.3 km2 per decade, consistent with ground-based data. However, errors in estimating total area were around 30% due to challenges in identifying debris-covered glaciers with optical remote sensing alone.
DSD-INT 2018 Application of XBeach to a Low-elevation Dune System with Hurric...Deltares
This document summarizes a study that used the XBeach model to simulate the morphological changes to a low-elevation dune system in Louisiana from Hurricane Gustav in 2008. The objectives were to model the erosion processes during the hurricane and establish a modeling framework to forecast future hurricane impacts. A tiered modeling approach was used with the XBeach model nested within larger scale Delft3D models. The results showed the model captured the general erosion patterns but overpredicted erosion in some areas. Future work involves coupling the models and examining the effect of barrier island disintegration on wave fields.
From global to regional scale: Remote sensing-based concepts and methods for ...Repository Ipb
The document discusses land cover mapping and change detection in tropical regions using remote sensing. It provides an overview of existing land cover classification systems and global and regional satellite-based mapping products. The paper compares different land cover maps for a test region in Central Sulawesi, Indonesia, finding inconsistencies between products and uncertainty in estimates of land cover classes and changes between years. Future work on operational land cover mapping in the tropics needs further harmonization of definitions and products, regional validation, and a standardized multi-level classification workflow.
Mineral potential projects in the Southern New England Orogen: a pilot study conducted by the Geological Survey of NSW and Kenex to provide a comprehensive account of the mineral resource potential of the region
Glaciers and ice caps (GICs), excluding those in Greenland and Antarctica, lost mass at a rate of 148 +/- 30 Gt yr-1 from 2003 to 2010 according to a study using GRACE satellite gravity measurements. This contributed 0.41 +/- 0.08 mm yr-1 to global sea level rise. The GIC loss rate was about 30% lower than previous estimates. Additionally, Greenland and Antarctic ice sheets, including peripheral GICs, contributed 1.06 +/- 0.19 mm yr-1 to sea level rise. In total, all ice-covered regions contributed 1.48 +/- 0.26 mm yr-1 to sea level rise over this period according to the study.
geog2750_15.ppt principles of grid based modellingsuerie2
This document discusses linking models to GIS and principles of grid-based modeling. It describes how GIS provides tools for environmental data management but limited spatial analysis, which can be addressed by linking models. Grid-based or "cartographic" modeling involves applying mathematics to raster maps using spatial operators and functions. The document outlines different types of modeling functions in ArcGIS including local, focal, zonal, and global functions. It provides examples of using these functions to perform tasks like slope modeling, soil modeling, and land capability mapping.
This document summarizes three case studies that used remote sensing and GIS techniques to analyze land use and land cover change over time. The first case study analyzed changes from 1990-2010 in Hawalbagh, India using Landsat imagery. It found increases in built-up land and decreases in barren land. The second studied coastal Egypt from 1987-2001 using Landsat, identifying 8 land cover classes. The third examined Simly watershed, Pakistan from 1992-2012 using Landsat and SPOT data, finding increases in agriculture and decreases in vegetation. All three used supervised classification and post-classification comparison to analyze land use/cover changes.
Soil Organic Carbon mapping by geo- and class- matchingExternalEvents
The presentation was given by Mr. Bas Kempen & Ms. V.L. Mulder, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
This document provides information about the Environmental Remote Sensing course GEOG 2021. It introduces the structure and content of the course, including lectures, practical sessions, assessment, and reading materials. The course is split into two halves, with the first introducing remote sensing concepts and the second focusing on a practical example. Lectures are on Mondays and practical sessions on Thursdays. Assessment consists of an exam and a coursework write-up. Relevant reading materials and online resources are also listed.
The document outlines an introductory training program on practical geosciences. It includes an opening speech, discussion, and coffee break on the first day. The program then covers sessions on carbonate rocks, clastic rocks, exercises using interactive workshops and games, movies on geological processes, explanatory software on plate tectonics and earthquakes, and a potential field trip to the Dammam Dome. A variety of topics are listed like carbonate and clastic facies mapping, seismic stratigraphy, and reservoir characterization. The goal is to provide background and hands-on learning to help understand key geological concepts and their application in Saudi Aramco's work.
GIS Training Objectives and Schedule_v2.docxAriful Islam
The document describes a 4-week training course on fundamentals of Geographic Information Systems (GIS). The objectives of the course are to build participants' capacity to use GIS data in their work, train personnel in open source and commercial GIS software, analyze geo-information problems, and establish referral networks. The course outline includes 12 modules that cover topics such as GIS history, platforms and software, database formats, map projections, digitization, attribute data, geoprocessing, spatial analysis, data visualization, and a case study. The training methods include lectures, software demonstrations, exercises and field work using GPS devices.
Advances in Agricultural remote sensingsAyanDas644783
This document summarizes a 3-part training program on crop mapping using synthetic aperture radar (SAR) and optical remote sensing. The training will cover crop classification using time series of polarimetric SAR data, monitoring crop growth through SAR-derived crop structural parameters, and classifying crop types using time series optical and radar data. Attendees will learn how to analyze satellite image time series from sensors like Sentinel-1 and Sentinel-2 for applications like crop monitoring. The training objectives are to understand polarimetric SAR for crop assessment and using multitemporal SAR and optical data for crop monitoring and classification.
This document discusses embedding GIS in undergraduate learning at Newcastle University. It provides an overview of the Geomatics group, which includes 11 academics and 10 researchers. The group teaches GIS to around 200 undergraduate students from various programs, as well as 100 postgraduate students and 20 PhD students.
GIS is taught throughout the undergraduate curriculum, from basic concepts in stage 1 to advanced techniques like spatial statistics and Python scripting in stage 3. Practical field courses apply GIS skills. Challenges include keeping up with changing technology and ensuring value for high tuition costs. The group seeks better integration with open source tools and industry to provide work opportunities for graduates.
The presentation was given by Mr. Bas Kempen & Ms. V.L. Mulder, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
This document discusses using the Trends.Earth tool to calculate land degradation, with a focus on experiences in Latin America and the Dominican Republic. It provides background on how land degradation was previously calculated through extensive spatial analysis. Trends.Earth allows countries to calculate the three indicators of land degradation - land cover, land productivity, and soil organic carbon - more easily. The document shares an example of calculating land degradation in the Dominican Republic and promoting Trends.Earth for national reporting in Latin America.
This document provides information about an advanced surveying course. It outlines the course outcomes, which include applying geometric principles to solve surveying problems, using modern instruments to obtain and analyze geo-spatial data, and analyzing geodetic data to perform survey analysis. It also maps the course outcomes to various program outcomes related to engineering knowledge, problem analysis, design/development, investigations, tool usage, and more. Finally, it provides details about the course specification, textbook, assessment structure, units to be covered, and mapping of course to program outcomes.
This document describes European community research projects funded by the European Commission that contribute to building GEOSS. The projects deliver systems, tools, and protocols to enhance interoperability between geospatial information systems and improve collection, integration, and access to harmonized environmental data. This supports the design and implementation of GEOSS by developing smart monitoring networks and open service-oriented architectures. The projects are funded through the EU Framework Programmes for research and are informed of GEO priorities so they can voluntarily contribute to GEO tasks.
This document provides information about an advanced surveying course. The course aims to teach students to apply geometric principles to solve surveying problems, use modern instruments to obtain and analyze geospatial data, analyze geodetic data to solve survey problems, integrate surveying with geospatial tools, and evaluate different land and satellite survey methods. The course outcomes and program outcomes are also listed, covering topics like engineering knowledge, problem analysis, design skills, investigation skills, tool usage, societal and environmental awareness, ethics, teamwork, communication, project management, and lifelong learning.
Maria Antonia Brovelli, Carolina Arias Muñoz, Marco Minghini, Giorgio Zamboni.
https://drive.google.com/file/d/0B3xWOhmJOx-_am5Ld3c4dnFPUUE/view
https://www.youtube.com/watch?v=dQ-EdwoPMVQ&feature=youtu.be
The document describes a term project applying GIS techniques to study glacial retreat in the Buni Zum area of Chitral, Pakistan. A group of 5 students will use Landsat imagery from 2006 and 2013 to identify changes in snow cover, vegetation cover, and water in the study area over this period. They will use various image processing techniques like thresholding, classification, band ratios, and indices to analyze changes. Preliminary results found around a 6% decrease in glacier area, indicating rapid glacial depletion. The results were overlaid on a DEM contour map to analyze melting patterns across elevation ranges.
1) The study tested how expert users interact with animated versus non-animated maps to understand the narrative of floods impacting a railway network.
2) The results found no significant difference in efficiency between map types, but animated maps influenced user confidence and hesitation. Information retrieval tasks were easier than analyzing causality.
3) Two questions had ambiguous wording, influencing the results. Additionally, question complexity likely had a greater impact than map type.
4) Future work could involve controlling task types by using standardized sets from other domains to improve reproducibility and comparison across studies.
Open Data Day 2024 - Mapping Climate Change in 4D: Belvedere Glacier’s Open G...Federica Gaspari
Presentation material for the webinar organised by LabMGF at Department of Civil and Environmental Engineering of Politecnico di Milano on the occasion of Open Data Day 2024. The webinar held on March 5th, was organised in 2 modules. The first one was dedicated to the monitoring activity of the Belvedere glacier (Italy) as part of a research project started in 2015. The main focus is the adoption of geomatics techniques (mostly photogrammetry) for the 3D reconstruction of the surface area of the glacier, tracking in time, through periodic in-situ surveys, its evolution. The obtained 3D and 2D geodata (point clouds, orthophotos and digital surface models) are publicly available as open data on a dedicated Zenodo repository.
In the second module of the webinar, two practical sessions are provided with guided tutorial on how to process Belvedere open data with popular open source software like QGIS and CloudCompare.
Objectives:
Develop a replicable integrated model (methodology) for evaluating the extent and development potential of renewable (non-renewable) groundwater resources in arid lands, with the Eastern Desert of Egypt as a pilot site.
The model will be replicable for similar arid areas; North of Sudan, Tibesty, Yemen, and Saudi Arabia.
Building national capacities.
This document provides an update on Solargis' uncertainty map for its solar radiation database. It summarizes Solargis' methodology for developing the map, which considers various uncertainty drivers like clouds, aerosols, water vapor, terrain variability and more. Preliminary results estimate the total GHI uncertainty to be within ±4% to ±8% for a long-term yearly value, representing an 80% probability of occurrence. Next steps include further refining the uncertainty model with new empirical evidence and developing an uncertainty map for DNI values.
This document summarizes work from an optimization subgroup in remote sensing. It discusses three main topics: 1) defining optimization problems and algorithms in remote sensing, 2) the role of optimization in remote sensing retrievals, and 3) potential projects focused on improving temperature and humidity profile retrievals from satellite data and intersatellite calibration. The subgroup explored using neural networks and Gaussian processes to develop atmospheric temperature and humidity profiles from HIRS satellite data.
This document presents a novel approach for classifying groundwater systems using time series data from monitoring wells. The approach uses principal component analysis and clustering algorithms to group similar groundwater hydrographs based on features like mean, standard deviation, and maximum levels. This produces a more systematic and data-driven classification than previous subjective expert methods. The goal is to predict groundwater behavior at unmonitored locations and improve groundwater modeling and assessment of climate change impacts. The developed groupings could also provide clearer definitions of classifications like "slow and fast responding" groundwater systems.
How To Cultivate Community Affinity Throughout The Generosity JourneyAggregage
This session will dive into how to create rich generosity experiences that foster long-lasting relationships. You’ll walk away with actionable insights to redefine how you engage with your supporters — emphasizing trust, engagement, and community!
Soil Organic Carbon mapping by geo- and class- matchingExternalEvents
The presentation was given by Mr. Bas Kempen & Ms. V.L. Mulder, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
This document provides information about the Environmental Remote Sensing course GEOG 2021. It introduces the structure and content of the course, including lectures, practical sessions, assessment, and reading materials. The course is split into two halves, with the first introducing remote sensing concepts and the second focusing on a practical example. Lectures are on Mondays and practical sessions on Thursdays. Assessment consists of an exam and a coursework write-up. Relevant reading materials and online resources are also listed.
The document outlines an introductory training program on practical geosciences. It includes an opening speech, discussion, and coffee break on the first day. The program then covers sessions on carbonate rocks, clastic rocks, exercises using interactive workshops and games, movies on geological processes, explanatory software on plate tectonics and earthquakes, and a potential field trip to the Dammam Dome. A variety of topics are listed like carbonate and clastic facies mapping, seismic stratigraphy, and reservoir characterization. The goal is to provide background and hands-on learning to help understand key geological concepts and their application in Saudi Aramco's work.
GIS Training Objectives and Schedule_v2.docxAriful Islam
The document describes a 4-week training course on fundamentals of Geographic Information Systems (GIS). The objectives of the course are to build participants' capacity to use GIS data in their work, train personnel in open source and commercial GIS software, analyze geo-information problems, and establish referral networks. The course outline includes 12 modules that cover topics such as GIS history, platforms and software, database formats, map projections, digitization, attribute data, geoprocessing, spatial analysis, data visualization, and a case study. The training methods include lectures, software demonstrations, exercises and field work using GPS devices.
Advances in Agricultural remote sensingsAyanDas644783
This document summarizes a 3-part training program on crop mapping using synthetic aperture radar (SAR) and optical remote sensing. The training will cover crop classification using time series of polarimetric SAR data, monitoring crop growth through SAR-derived crop structural parameters, and classifying crop types using time series optical and radar data. Attendees will learn how to analyze satellite image time series from sensors like Sentinel-1 and Sentinel-2 for applications like crop monitoring. The training objectives are to understand polarimetric SAR for crop assessment and using multitemporal SAR and optical data for crop monitoring and classification.
This document discusses embedding GIS in undergraduate learning at Newcastle University. It provides an overview of the Geomatics group, which includes 11 academics and 10 researchers. The group teaches GIS to around 200 undergraduate students from various programs, as well as 100 postgraduate students and 20 PhD students.
GIS is taught throughout the undergraduate curriculum, from basic concepts in stage 1 to advanced techniques like spatial statistics and Python scripting in stage 3. Practical field courses apply GIS skills. Challenges include keeping up with changing technology and ensuring value for high tuition costs. The group seeks better integration with open source tools and industry to provide work opportunities for graduates.
The presentation was given by Mr. Bas Kempen & Ms. V.L. Mulder, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
This document discusses using the Trends.Earth tool to calculate land degradation, with a focus on experiences in Latin America and the Dominican Republic. It provides background on how land degradation was previously calculated through extensive spatial analysis. Trends.Earth allows countries to calculate the three indicators of land degradation - land cover, land productivity, and soil organic carbon - more easily. The document shares an example of calculating land degradation in the Dominican Republic and promoting Trends.Earth for national reporting in Latin America.
This document provides information about an advanced surveying course. It outlines the course outcomes, which include applying geometric principles to solve surveying problems, using modern instruments to obtain and analyze geo-spatial data, and analyzing geodetic data to perform survey analysis. It also maps the course outcomes to various program outcomes related to engineering knowledge, problem analysis, design/development, investigations, tool usage, and more. Finally, it provides details about the course specification, textbook, assessment structure, units to be covered, and mapping of course to program outcomes.
This document describes European community research projects funded by the European Commission that contribute to building GEOSS. The projects deliver systems, tools, and protocols to enhance interoperability between geospatial information systems and improve collection, integration, and access to harmonized environmental data. This supports the design and implementation of GEOSS by developing smart monitoring networks and open service-oriented architectures. The projects are funded through the EU Framework Programmes for research and are informed of GEO priorities so they can voluntarily contribute to GEO tasks.
This document provides information about an advanced surveying course. The course aims to teach students to apply geometric principles to solve surveying problems, use modern instruments to obtain and analyze geospatial data, analyze geodetic data to solve survey problems, integrate surveying with geospatial tools, and evaluate different land and satellite survey methods. The course outcomes and program outcomes are also listed, covering topics like engineering knowledge, problem analysis, design skills, investigation skills, tool usage, societal and environmental awareness, ethics, teamwork, communication, project management, and lifelong learning.
Maria Antonia Brovelli, Carolina Arias Muñoz, Marco Minghini, Giorgio Zamboni.
https://drive.google.com/file/d/0B3xWOhmJOx-_am5Ld3c4dnFPUUE/view
https://www.youtube.com/watch?v=dQ-EdwoPMVQ&feature=youtu.be
The document describes a term project applying GIS techniques to study glacial retreat in the Buni Zum area of Chitral, Pakistan. A group of 5 students will use Landsat imagery from 2006 and 2013 to identify changes in snow cover, vegetation cover, and water in the study area over this period. They will use various image processing techniques like thresholding, classification, band ratios, and indices to analyze changes. Preliminary results found around a 6% decrease in glacier area, indicating rapid glacial depletion. The results were overlaid on a DEM contour map to analyze melting patterns across elevation ranges.
1) The study tested how expert users interact with animated versus non-animated maps to understand the narrative of floods impacting a railway network.
2) The results found no significant difference in efficiency between map types, but animated maps influenced user confidence and hesitation. Information retrieval tasks were easier than analyzing causality.
3) Two questions had ambiguous wording, influencing the results. Additionally, question complexity likely had a greater impact than map type.
4) Future work could involve controlling task types by using standardized sets from other domains to improve reproducibility and comparison across studies.
Open Data Day 2024 - Mapping Climate Change in 4D: Belvedere Glacier’s Open G...Federica Gaspari
Presentation material for the webinar organised by LabMGF at Department of Civil and Environmental Engineering of Politecnico di Milano on the occasion of Open Data Day 2024. The webinar held on March 5th, was organised in 2 modules. The first one was dedicated to the monitoring activity of the Belvedere glacier (Italy) as part of a research project started in 2015. The main focus is the adoption of geomatics techniques (mostly photogrammetry) for the 3D reconstruction of the surface area of the glacier, tracking in time, through periodic in-situ surveys, its evolution. The obtained 3D and 2D geodata (point clouds, orthophotos and digital surface models) are publicly available as open data on a dedicated Zenodo repository.
In the second module of the webinar, two practical sessions are provided with guided tutorial on how to process Belvedere open data with popular open source software like QGIS and CloudCompare.
Objectives:
Develop a replicable integrated model (methodology) for evaluating the extent and development potential of renewable (non-renewable) groundwater resources in arid lands, with the Eastern Desert of Egypt as a pilot site.
The model will be replicable for similar arid areas; North of Sudan, Tibesty, Yemen, and Saudi Arabia.
Building national capacities.
This document provides an update on Solargis' uncertainty map for its solar radiation database. It summarizes Solargis' methodology for developing the map, which considers various uncertainty drivers like clouds, aerosols, water vapor, terrain variability and more. Preliminary results estimate the total GHI uncertainty to be within ±4% to ±8% for a long-term yearly value, representing an 80% probability of occurrence. Next steps include further refining the uncertainty model with new empirical evidence and developing an uncertainty map for DNI values.
This document summarizes work from an optimization subgroup in remote sensing. It discusses three main topics: 1) defining optimization problems and algorithms in remote sensing, 2) the role of optimization in remote sensing retrievals, and 3) potential projects focused on improving temperature and humidity profile retrievals from satellite data and intersatellite calibration. The subgroup explored using neural networks and Gaussian processes to develop atmospheric temperature and humidity profiles from HIRS satellite data.
This document presents a novel approach for classifying groundwater systems using time series data from monitoring wells. The approach uses principal component analysis and clustering algorithms to group similar groundwater hydrographs based on features like mean, standard deviation, and maximum levels. This produces a more systematic and data-driven classification than previous subjective expert methods. The goal is to predict groundwater behavior at unmonitored locations and improve groundwater modeling and assessment of climate change impacts. The developed groupings could also provide clearer definitions of classifications like "slow and fast responding" groundwater systems.
How To Cultivate Community Affinity Throughout The Generosity JourneyAggregage
This session will dive into how to create rich generosity experiences that foster long-lasting relationships. You’ll walk away with actionable insights to redefine how you engage with your supporters — emphasizing trust, engagement, and community!
Presentation by Julie Topoleski, CBO’s Director of Labor, Income Security, and Long-Term Analysis, at the 16th Annual Meeting of the OECD Working Party of Parliamentary Budget Officials and Independent Fiscal Institutions.
The Power of Community Newsletters: A Case Study from Wolverton and Greenleys...Scribe
YOU WILL DISCOVER:
The engaging history and evolution of Wolverton and Greenleys Town Council's newsletter
Strategies for producing a successful community newsletter and generating income through advertising
The decision-making process behind moving newsletter design from in-house to outsourcing and its impacts
Dive into the success story of Wolverton and Greenleys Town Council's newsletter in this insightful webinar. Hear from Mandy Shipp and Jemma English about the newsletter's journey from its inception to becoming a vital part of their community's communication, including its history, production process, and revenue generation through advertising. Discover the reasons behind outsourcing its design and the benefits this brought. Ideal for anyone involved in community engagement or interested in starting their own newsletter.
FT author
Amanda Chu
US Energy Reporter
PREMIUM
June 20 2024
Good morning and welcome back to Energy Source, coming to you from New York, where the city swelters in its first heatwave of the season.
Nearly 80 million people were under alerts in the US north-east and midwest yesterday as temperatures in some municipalities reached record highs in a test to the country’s rickety power grid.
In other news, the Financial Times has a new Big Read this morning on Russia’s grip on nuclear power. Despite sanctions on its economy, the Kremlin continues to be an unrivalled exporter of nuclear power plants, building more than half of all reactors under construction globally. Read how Moscow is using these projects to wield global influence.
Today’s Energy Source dives into the latest Statistical Review of World Energy, the industry’s annual stocktake of global energy consumption. The report was published for more than 70 years by BP before it was passed over to the Energy Institute last year. The oil major remains a contributor.
Data Drill looks at a new analysis from the World Bank showing gas flaring is at a four-year high.
Thanks for reading,
Amanda
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New report offers sobering view of the energy transition
Every year the Statistical Review of World Energy offers a behemoth of data on the state of the global energy market. This year’s findings highlight the world’s insatiable demand for energy and the need to speed up the pace of decarbonisation.
Here are our four main takeaways from this year’s report:
Fossil fuel consumption — and emissions — are at record highs
Countries burnt record amounts of oil and coal last year, sending global fossil fuel consumption and emissions to all-time highs, the Energy Institute reported. Oil demand grew 2.6 per cent, surpassing 100mn barrels per day for the first time.
Meanwhile, the share of fossil fuels in the energy mix declined slightly by half a percentage point, but still made up more than 81 per cent of consumption.
Causes Supporting Charity for Elderly PeopleSERUDS INDIA
Around 52% of the elder populations in India are living in poverty and poor health problems. In this technological world, they became very backward without having any knowledge about technology. So they’re dependent on working hard for their daily earnings, they’re physically very weak. Thus charity organizations are made to help and raise them and also to give them hope to live.
Donate Us:
https://serudsindia.org/supporting-charity-for-elderly-people-india/
#oldagehome, #donateforeldersinkurnool, #donateforelders, #donationforelders, #donateforoldpeople, #donationforoldpeople, #sponsorforelders, #sponsorforoldpeople, #donationforcharity, #charity, #seruds, #kurnool, #donateforoldagehome, #oldagehomedonation
Presentation by Rebecca Sachs and Joshua Varcie, analysts in CBO’s Health Analysis Division, at the 13th Annual Conference of the American Society of Health Economists.
1. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 1
GEOG2750
Earth Observation & GIS of the Physical
Environment
20 Credit Level 2 Module
Louise Mackay & Steve Carver
Module Information
See also
http://www.geog.leeds.ac.uk/courses/level2/geog2750/index.html
2. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 2
Module Outline
• Runs Semester 1 & 2.
• Semester 1: Earth Observation of the Physical
Environment – Louise Mackay
• Semester 2: GIS of the Physical Environment –
Steve Carver
• Two complimentary technologies for monitoring
& understanding the Earths physical environment
3. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 3
GIS Aims
On completion of semester 2 students should have:
1. Knowledge of the use of GIS across a range of
applications in physical geography including
terrain analysis, hydrology, landscape evaluation
and environmental assessment;
2. Familiarity with the use and application of the
ArcGIS package; and
3. Knowledge of environmental data sources, skills
in the interpretation of spatial environmental data
and an awareness of specific problems and issues
relating to data quality, spatial data models and
methods of interpolation.
4. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 4
GIS Objectives
1. Identify principles and functional issues
pertaining to physical geography applications of
GIS;
2. Examine and review specific application areas
where GIS is a useful tool;
3. Investigate techniques provided by GIS which
have particular relevance to physical geography
applications and problem solving; and
4. Identify and address problem areas such as data
sources, modelling, error and uncertainty.
5. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 5
Overall Learning Outcomes
• On completion of this module students should be
able to:
– Demonstrate a clear knowledge and understanding of
the key concepts concerning the application of Earth
observation and GIS to problems in physical
geography;
– Critique and evaluate the applicability of Earth
observation and GIS in relation to physical geography
applications; and
– Demonstrate a high level of skill in the application of
Earth observation & GIS software to the solving of
environmental problems.
6. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 6
Dates & Times
• GIS – Semester 2:
– 10 x 1hr lectures, Monday 10-11am, Geography Lecture
Theatre
– 10 x 2hr practicals, Tuesday 3-5pm or Friday 9am-1pm,
Textiles G34 Computer Lab
7. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 7
Module Assessment
Semester 2 - GIS
• 5 practical worksheets contributing 5% each to the final
module mark
• 1 x 1hr exam (short answer) at the end of the semester (2
questions from 5) contributing 25% of module mark
Overall assessment based on:
• 10 Practicals = 50% of final module mark (5 x Earth
Observation = 25% done already last semester)
• 2 exams = 50% of final module mark (Earth Observation
= 25% done already last semester)
8. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 8
GIS Syllabus – Semester 2
(Weeks)
14. Introduction to GIS for environmental applications
15. Spatial & Temporal variability and environmental data
16. Error & Uncertainty
17. Interpolation of environmental data
18. Principles of grid-based modelling
19. Terrain modelling: the basics
20. Reading week
21. Terrain modelling: applications
22. Hydrological modelling
23. Environmental assessment
24. Making Decisions
9. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 9
Lecture 11
Introduction to GIS for
environmental applications
• Outline
– what makes physical geography applications of
GIS different?
– environmental science and management
– the role of GIS?
10. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 10
What makes physical geography
applications of GIS different?
• The natural environment is…
– extremely complex
– highly variable (space and time)
– complicated further by human action
• Understanding of natural systems
– very basic
– multiple approaches to natural science
11. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 11
From this…
…to this
12. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 12
Spatio-temporal variation
• Range of variability over a range of spatial
and temporal scales
– variation depends on the scale of observation
e.g. vegetation (species, community, ecosystem)
– sliding scale to represent both spatial and
temporal variability
i.e. space from infinitesimal (zero) to infinite
i.e. time from the instantaneous to ‘for ever’
13. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 13
Spatio-temporal scales of
operation
• Variety of spatial and temporal scales:
– micro scale - meso scale - macro scale
– e.g. Hydrology
Micro : runoff plots, infiltrometer, hillslope
Meso: sub-catchment, headwaters, reach
Macro: whole catchment, region, watershed
– now - sec - min - day - year - century - etc.
– e.g. Climatology
Seconds: Wind speeds
Minutes: Incoming solar radiation
Day: Anabatic/katabatic winds
Year: Annual temperature variation
Millennium: Glacial/interglacial periodicity
14. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 14
Complexity
• Complex nature of environmental systems
makes possibility of realistic modelling
seem remote
• Frustrated by lack of understanding
– e.g. influence of human activity
• Variations in complexity:
– most GIS applications model only 1 or 2
processes with assumptions/simplification
15. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 15
Question…
• How can sampling strategies be matched to
spatio-temporal scales?
16. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 16
Sampling theory
• Sampling spatial processes:
– the sampling frequency needs to be small enough to
record local variations without undue generalisation of
spatial pattern but coarse enough so as to avoid data
redundancy
• Sampling temporal processes:
– in order to record variations in temporal processes
sampling frequency needs to be about half the
wavelength of the process to avoid measurement bias
and too much detail
• Sampling dependent on process(es) operating
17. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 17
Sampling theory
DEM Cell size 1 Cell size 2
Time
Rate
1 wavelength
amplitude
18. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 18
Question…
• How do we choose appropriate sampling
frequencies?
19. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 19
Advantages of GIS
• GIS is good at…
– handling spatial data
– visualisation of spatial
data
– integrating spatial data
– framework for:
analysis and modelling
decision support
20. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 20
(dis)Advantages of GIS
• GIS is not so good at…
– handling temporal data
– visualisation of temporal data
– integrating spatial and temporal data
– framework for:
analysis and modelling of time dependent data
volumetric analysis
uncertainty
21. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 21
GIS alone is not enough
• Integrated systems:
– limited ‘off-the-shelf’ spatial analysis and modelling
– framework for developing better integrated systems
GIS - image processing systems
GIS - modelling systems
GIS - statistical software
– facilitated through
specialist programming languages (e.g. AML and Avenue)
universal programming languages (e.g. Java and Visual Basic)
access to source code (e.g. GRASS)
22. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 22
Integrated systems
• Combined (symbiotic) systems
• Example:
– NERC/ESRC Land Use Programme (NELUP):
decision support for land use change in UK
GRASS GIS
models: hydrological (SHE), agricultural economics
and ecological
Graphic User Interface (GUI)
Spatial Decision Support System (SDSS)
23. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 23
NELUP
24. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 24
Conclusions
• The physical world is complex and our
understanding simple
– environmental data is highly variable
– implications for GIS applications
• GIS has important role to play in
environmental science and management
– handling and analysing spatial data
– problems with temporal data
25. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 25
Practical
• Spatial variability in environmental data
• Task: Investigate the spatial variability in terrain
datasets and determine the effects of a) sampling
strategy, and b) resolution on the data.
• Data: The following datasets are provided for the
Leeds area
– 10m resolution DEM (1:10,000 OS Profile data)
– 50m resolution DEM (1:50,000 OS Panorama data)
– 10m interval contour data (1:10,000 OS Profile data)
26. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 26
Practical
• Steps:
1. Display both elevation datasets in ArcMap and look for
visible differences - do these result from differences in
sampling strategy or resolution or both? Use the
IDENTIFY tool to interrogate the images.
2. Calculate the slope (gradient) from both the 10m and
50m data – is there any ‘striping’ in the slope data and
what might this be due to? (use the slope tool in
ArcMap or ArcGRID to calculate slope)
27. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 27
Learning outcomes
• Familiarity with scale issues especially
resolution and sampling in relation to
spatial variation in environmental data
• Experience/practice in use of analysis and
display functions in ArcMap
• Familiarity with OS terrain model products
28. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 28
Useful web links
• NELUP web site
– http://www.ncl.ac.uk/wrgi/wrsrl/projects/nelup/nelup.
29. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 29
Next week…
• Spatial and temporal variability and
environmental data
– general characteristics of environmental data
– environmental data sources
– toward integrated databases
• Practical: Using Digimap to access OS data
products