Day 2 :
- Remote Sensing.
Session Introduction
Benjamin K. Malphrus
Morehead State University, USA
Title: Lunar IceCube: Ushering in a new era of planetary remote sensing using small satellite platforms
Time : 09:50-10:50
Biography:
Dr. Benjamin K. Malphrus is Professor of Space Science at Morehead State University where he also directs the University’s Space Science Center and serves as the Director of Space Operations for the Kentucky Space program. He has served as Principal Investigator on several nanosatellite missions including KySat-1, CXBN 1 and 2, and TechSat-1. He and his team recently received an $8M contract from NASA to design a small space probe to fly to the Moon to prospect for water ice. In the late 1990s, he developed a theory of galaxy formation that has gained wide acceptance among the astronomical community.
Abstract:
Lunar IceCube, a 6U CubeSat designed to prospect for water in solid (ice), liquid, and vapor forms and other lunar volatiles from a low-perigee, highly inclined lunar orbit, has been selected by NASA for a flight opportunity on Exploration Mission-1 (EM-1). The mission is a partnership between Morehead State University, NASA Goddard Spaceflight Center (GSFC), JPL, the Busek Company, Vermont Tech, and Kentucky Space LLC. Lunar IceCube will be deployed during lunar trajectory by the Space Launch System (SLS) and use an innovative RF Ion engine to achieve lunar capture and a science orbit (inertially locked, highly elliptical, 100 km periapsis) to investigate the distribution of water (ice, vapor, water components), as a function of time of day, latitude, and regolith composition in the context of mineralogy. IceCube will include the Broadband InfraRed Compact High Resolution Exploration Spectrometer (BIRCHES)- a compact version of the successful volatile-seeking New Horizons Ralph instrument. BIRCHES has the high spectral resolution (5 nm) and wavelength range (1 to 4 μm) needed to distinguish phase states of water. The mission addresses NASA Strategic Knowledge Gaps related to lunar volatile distribution, and will complement the work of Lunar Flashlight and LunaH-Map by focusing on the distribution and transportation physics of water ice at a variety of latitudes, thus not restricted to permanently shadowed regions. The 13 secondary payload CubeSats that will be included on EM-1, including Lunar IceCube, will usher in a new era of solar system exploration with CubeSats and other small satellite platforms.
Xuelian Meng
Louisiana State University, USA
Title: New era of 3D coastal morphology mapping using LiDAR and unmanned aerial vehicle
Time : 11:10 -12:10
Biography:
Xuelian Meng is an Assistant Professor at Louisiana State University and Fellow of the Coastal Studies Institute. Her research interest is to apply geospatial technologies to investigate fragile ecosystems that are sensitive to human activities. Specific topics of her research include LiDAR, unmanned aerial vehicle (UAV), 3D modeling of coastal morphology, image processing, feature extraction and land cover and land use analysis. Her recent studies focus on applying terrestrial LiDAR and UAV for coastal morphological mapping under dense vegetation and fine scale sediment change analysis. She is a life-time Member of the International Association of Chinese Professionals in Geographic Information Sciences (CPGIS), Member of Association of American Geographers (AAG) and American Society of Photogrammetry and Remote Sensing (ASPRS).
Abstract:
Coastal morphology addresses the evolution of coastal features such as sediment, vegetation and their interaction with hydrodynamics, which is an important subject in coastal studies. Previous researches mainly used historical data from satellite or airborne sensors to map coastal morphology in land cover and 3D structure, which are limited by the availability in time, location, cost and resolution of existing data. Other commonly used approaches are field data collection through RTK (Real Time Kinematic) GPS, total station, leveling sensor and manual survey of vegetation plots. Although elevation profiles and vegetation plots provide insight into terrain morphology and sediment dynamics, these discrete survey methods faces major challenges in coastal environments with spatial heterogeneity and unpredictable locations with severe morphological changes. In recent years, the development of high-resolution and portable survey instruments of terrestrial light detection and ranging (LiDAR) and unmanned aerial vehicle (UAV) provide flexible field mapping tools to fill in the gap between the existing imagery and discrete field elevation survey, which have gained popularity in morphological mapping. This presented study focuses on our recent applications of terrestrial LiDAR and UAV on coastal morphological mapping by addressing the following questions: How effective and accurate are terrestrial LiDAR and UAV for coastal terrain mapping? What are the uncertainties and causes in areas with low accuracy? What are the main challenges to map densely vegetated coastal environment and how to correct elevation under dense vegetation? In the end, this study applies recently developed coastal morphology analyst (CMA) for sediment change and evolution analysis.
Jennifer L Summers
Tulane University, USA
Title: Schoenoplectus americanus clones and genetic heat map across kirkpatrick marsh, edgwater, MD
Time : 12:10-12:40
Biography:
Jennifer L Summers completed her Bachelor of Arts degree at Furman University in Greenville, SC in 2013. She has worked with Jenks Farmer, a sustainable garden designer, in SC as well as working with partners in agriculture in Haiti. She is currently a PhD student in Michael J Blum’s Molecular Ecology Lab.
Abstract:
Salt marshes are increasingly important for coastal ecosystems around the world in the face of climate change. Ecosystem services provided by salt marshes include wildlife habitat, water filtration, fishery nurseries, storm buffers, AND land-building. The plants that compose salt marshes include sedges like Schoenoplectus americanus. S. americanus is foundational sedge found throughout North America and contributes majorly to marsh accretion (land-building) through its rhizomal growth. Understanding the genetic landscape or variation in genomes of individuals across different spatial scales, of salt marsh sedges like S. americanus helps climate change scientists better estimate salt marsh species’ capacity to adapt to major climatic change going forward. S americanus is a clonal plant whose reproduction and dispersal are poorly understood. Recent studies suggest it exhibits surprisingly substantial genetic variation across short distances. Mapping the genetic landscape of S. americanus builds on basic biological understanding of clonal plant spread and the dynamics of salt marsh plant reproduction. Using GIS technology (ESRI ArcMap 10.3), I built maps of the clonal ranges of S. americanus sampled from across Kirkpatrick Marsh in Edgewater Maryland, the site of decades-long studies on salt marshes and climate change implemented by collaborators at the Smithsonian Environmental Research Center. In addition to mapping individual genotypes that appear multiple types across the marsh, I mapped out different microclimate associated with the plots we sampled. Finally, I took the results of our comparison of genetic similarity across all individuals into 2-5 clusters and interpolated them to illustrate genetic grouping of samples across Kirkpatrick Marsh.
Wilbert A.McClay
Northeastern University, USA
Title: Mobile data and individual client diagnostic acquisition from pgws call analysis utilizing spark and the hadoop ecosystem
Time : 12:40-13:10
Biography:
Wilbert A McClay has served as Managing Technical Scientist at Aerospace Corporation and is a Principal Investigator, Visiting Scientist and Signal Processing Engineer at Lawrence Livermore National Laboratory. At Southern University he taught courses in Electrical Engineering and currently at Northeastern University serves as Cyber Security, Brain Computer Interface and Big Data (Hadoop, MapReduce and NoSql databases) researcher. Additionally while acquiring his 2nd Master’s in Information Assurance at Northeastern University in Boston, Massachusetts, he has worked extensively as a Big Data Hadoop Architect/Developer Contractor for top Fortune 500 media corporations such as NBC Universal and DirecTV.
Abstract:
Individual Client Diagnostics, is an account specific event log to diagnose customer experience from PGWS call analysis. The meaning of a PGW call is to perform policy enforcement, packet filtering for each DirecTV user, charging support, lawful interception and packet screening. Another key role of the PGW is to act as the anchor for mobility between 3GPP and non-3GPP technologies such as WiMAX and 3GPP2 (CDMA 1X and EvDO). Thus, the acquisition of the PGW calls within the Kafka API demonstrates the objective of the DirecTV Mobile Diagnostics project. The Spark Dstream is connected to a HBase/Websocket to IMAP with a projection into HBase. The big data analytics and diagnostics component will rely heavily upon the aggregation windows return, which prescribes how IMAP wants the PGWS call data lucidly defined. The Spark analytics machine learning analysis post Kafka API inspection of key-value pair analysis from IMAP PGWS Request and Response Data demonstrate the following statistical results utilizing Spark machine learning library (MLlib), SparkR and SparkSQL, projected into HBase as a column family architecture.
Iqra Ashraf
National University of Science and Technology (NUST), Islamabad.
Title: Spatio-temporal analysis of tuberculosis in relation to socio-economic and environmental factors
Time : 14:10-14:40
Biography:
Iqra Ashraf, has completed my MS in geographic information system and Remote sensing in 2015 from school of Geographical Information systems, National university of science and technology, Islamabad, Pakistan. I have combined GIS/RS field with epidemiology making use of new ArcGIS tools and have my two research papers submitted in peer-reviewed journals of epidemiology.
Abstract:
Tuberculosis (TB) is a debilitating infectious disease affecting more than one third of the global population. Pakistan is among the top most affected and vulnerable countries of TB. A study was designed (1) to conduct a field survey of the TB patients in the study area of Ravi town, Lahore and develop a Geodatabase (2) hotspot analysis and spatial regression analysis of TB patient’s data with socio-economic & environmental factors data and (3) to investigate population at risk of TB using Standard Morbidity Ratio (SMR) statistics. The patient’s data showed an increasing trend of TB cases from 2011 to 2013 with the spatial spread from North-East to South-West direction in the study area. The hotspot analysis indicated two major clusters (90 & >95% confidence level) in Faisal park. A combination of four socioeconomics variables (low income, overcrowding, low literacy and malnourishment) were found to be the best subset of predictors in applying the ordinary least square (OLS) and geographically weighted regression (GWR) spatial statistical techniques. Multiple environmental and host-related socio-economic factors were presented in the mapping of pulmonary TB cases of Ravi town, Lahore. The spatial and temporal analysis of TB patient’s data along with the socio economic, and environmental factors data may be useful for assessing disease risk and formulating intervention and control strategies for resources allocation and appropriate management of TB.
Makario Sylvia Bosibori
Geowiz Services Limited, Kenya
Title: MWRMM - T: Mobile Water Resource Mapping and Management Tool
Time : 14:40-15:10
Biography:
Makario Sylvia Bosibori’s experience spans the fields of geospatial engineering and space technology. She holds a Bsc in Geospatial Engineering and Space Technology from the University of Nairobi, Kenya and is now pursuing Master’s of Science in Information Technology. She has worked with the United Nations and other organizations. She is co-founder and management executive of a startup company Geowiz Services, which she founded in 2013. Her main focus is on business development and fostering partnerships to enable the company deliver services to both the public and private sectors with special emphasis on those that need systems and applications that need integration of Space/Spatial data. She is currently taking a Professional Practicum at Ramani Geosystems, a geospatial and space technology engineering firm in Kenya. She also curates information and writes about emerging technologies in her blog where her major focus is on geospatial technologies and earth observations for development in a wide range of Areas. Her other interests are on design thinking and how creating tools and strategies around design thinking can enable provide solutions to problems centered around the user.
Abstract:
Mobile water resource mapping and management tool (MWRMM-T) is a mobile application coded on the android platform to help combat water scarcity problems while promoting sustainability of the existing water resources in Machakos County, Kenya with plans of rolling out the tool to the whole country of Kenya and other African Counties. The tool integrates both the mobile application with the location element (GPS Tracking) that enables the registering of the mapped water resources with their specific location. The MWRMM-T is a very simple tool that meets the needs of even those with low literacy level in the community who have shown interest in being part of the mapping party due to its visualization power, as it can be displayed in the back-end database, the mapped information is sent instantly through real time mapping. All the existing data archived in the back-end database was collected in Machakos County in collaboration with the county government individuals and civic leaders with the need to test the tool. Information can be visualized by clicking on any water resource mapped to get the particular details, including any kind of action required for making better informed decisions. The back-end database is a web application that is hosted on our own server spaces. Searching/querying the database is by location name, sub-county or feature format. Keen selections of spatial analysis methods for water resources analysis or regular quality control are also possible with MWRMM-T. MWRMM-T was hence built understanding the needs of the grassroot level individuals in the rural and peri-urban setting in Kenya, working on promoting sustainability on their water resources.
Ichio ASANUMA
Tokyo University of Information Sciences, Japan
Title: Possibility of detection and identification of boats and vessels detected by Day-Night-Band of VIIRS and synthetic aparture radar on RADARSAT
Biography:
Ichio Asanuma has received Doctor of Engineering from the Chiba University in 1999. He has been working on the satellite oceanography, especially on the primary productivity of the ocean using the visible and infrared bands. His main source of data are received by the receiving stations operated at the Tokyo University of Information Sciences, which receive data from the VIIRS on the Suomi-NPP, which covers the western boundary region of the Asia.
Abstract:
The day-night-band (DNB) of the visible infrared and imaging radiometer suite (VIIRS) on the Suomi-NPP detects light of the fishery boats on the open water at night, although the presence of clouds exhibits a limitation of detection. In contrast, the synthetic aperture radar (SAR) on the RADARSAT detects the boats and vessels on the water even through the clouds, although the observations are difficult in the midnight because of power consumption by SAR. The locations of vessels weighing greater than 300 tons are reported by the automatic identification system (AIS) with the maritime mobile service identity (MMSI) and are available to the public, although the locations of smaller fishery boats are not included. In this study, the locations of boats and vessels detected by DNB, SAR and reported by the AIS are plotted on the geophysical information system (GIS) so as to discuss the inconsistencies of locations introduced by the difference of observation time. Although the ship identifications are difficult for the data observed by the DNB and the SAR by itself, the MMSI data reported by the AIS with the interpolation methods exhibited the possibility to identify the large vessels from the data observed by DNB and SAR on the GIS analysis.
Farai Dondofema
University of Venda, South Africa.
Title: Determining the relationship between gully characteristics and environmental factors at sub catchment level using GIS and remote sensing in Zimbabwe
Biography:
F Dondofema is currently a Chief Technician in the School of Environmental Sciences at the University of Venda, South Africa. He has completed his BSc in Agriculture specializing in Animal Science in 2000 from the University of Zimbabwe, BSc in Applied remote sensing and GIS from the University of Fort Hare in 2004, MSc in Pasture Ecology from the University of Fort Hare in 2004 and MSc in Integrated Water Resource Management (IWRM) from the University of Zimbabwe in the year 2007. He has published several articles in agriculture, ecology, GIS, remote sensing and water management. He is registered as a Professional Natural Scientist with the South African Council for Natural Scientific Professions.
Abstract:
GIS and remote sensing techniques were used to identify and monitor gully erosion, and its relationship with selected environmental factors in Zhulube in Zimbabwe. The results showed that gully characteristics are significantly explained by soil characteristics, environmental factors, slope gradient, sediment loadings and the erosive power of streams. There was an evident, significant (p<0.05) relationship between gully depth and bulk density at r2=0.873. The soil clay content was another soil property that showed a significant relationship with gully development with its related minerals, indicating a decline in erosion with an increase in proportions. A significant relationship between gully depths and slope gradient showed a resultant increase of r2= 0.62. There was a significant relationship between gully development and the erosive power of stream while sediment loadings of the streams indicated a non-significant effect on the gully depth with an r2=0.02. The susceptibility of soils to detachment and transport by various erosive agents was a function of soil properties including, among others, physical and chemical soil properties. The effects of each soil property were different between sites, thereby influencing the degree of vulnerability of any given soil to destructive erosion forces. The interactive effects of the topography, vegetation cover and rainfall factors greatly influenced erosive agents. Soil erodibility assessment using simulated stream erosive forces and sediment loadings revealed that sediment yield or the erosive power of the streams in the study area increased with increasing slope gradient depending on the clay content of the soil.
Volodymyr Hnatushenko
Oles Honchar Dnipropetrovsk National University, Ukraine
Title: Urban change detection method of multitemporal remote sensing images
Biography:
In 1994 V.Hnatushenko graduated from the Dnipropetrovsk college of automation and telemechanics in Machine with CNC and robotic systems. In 1999, he received a M.S. degree in Technology and Telecommunications from Dnipropetrovsk National University, Ukraine. Volodymyr Hnatushenko has completed his PhD in 2003 and postdoctoral studies from Dnipropetrovsk National University. In 2006 - docent, 2009 - Doctor of Sciences, 2011 – Full Professor. He is the head of the automated data processing systems department at the Oles Honchar Dnepropetrovsk National University, Ukraine. He has supervised to completion 7 research PhD. He has published more than 200 papers in reputed journals
Abstract:
Change detection analyses describe and quantify differences between images of the same scene at different times. Change detection is a complex phenomenon which includes different procedures such as identifying the specific change detection problem, image preprocessing and variables and algorithm selection for the computations. The widely used methods for high-resolution image change detection rely on textural/structural features. However, these spatial features always produce high-dimensional data space since they are related to a series of parameters. Moreover, the current urban change detection methods are totally reliant on visual interpretation. This article presents a new automatic change detection method of multitemporal remote sensing high-resolution images and visual interpretation of results. To detect change we apply a series of algorithms, which are independent of each other: subpixel registration of multitemporal images, spectral classification (building masks), singling-out of the most informative stripes and threshold segmenting, morphological filtering and object classification, vectorization and calculation of parameters, visualization of the changes on the map. The candidate changed areas are obtained base on spatial mask filtering, then the spectral difference, searching for spectral-temporal anomalies, morphological technique and a shadow detection method to identify the real changes. Experiments were conducted on the multitemporal Pléiades images. Experimental results show that the proposed method can effectively and quickly extract the changing urban area between the two temporal optical remote sensing images of high spatial resolution. Compared with other change detection methods, the proposed method reduces the effects of classification and segmentation on the change detection accuracy
Makario Sylvia Bosibori
Geowiz Services Limited, Kenya
Title: MWRMM-T -Mobile water Resource Mapping and Management Tool
Time : 14:40-15:10
Biography:
Makario Sylvia Bosibori’s experience spans the fields of geospatial engineering and space technology. She holds a Bsc in Geospatial Engineering and Space Technology from the University of Nairobi, Kenya and is now pursuing Master’s of Science in Information Technology. She has worked with the United Nations and other organizations. She is co-founder and management executive of a startup company Geowiz Services, which she founded in 2013. Her main focus is on business development and fostering partnerships to enable the company deliver services to both the public and private sectors with special emphasis on those that need systems and applications that need integration of Space/Spatial data. She is currently taking a Professional Practicum at Ramani Geosystems, a geospatial and space technology engineering firm in Kenya. She also curates information and writes about emerging technologies in her blog where her major focus is on geospatial technologies and earth observations for development in a wide range of Areas. Her other interests are on design thinking and how creating tools and strategies around design thinking can enable provide solutions to problems centered around the user.
Abstract:
Mobile water resource mapping and management tool (MWRMM-T) is a mobile application coded on the android platform to help combat water scarcity problems while promoting sustainability of the existing water resources in Machakos County, Kenya with plans of rolling out the tool to the whole country of Kenya and other African Counties. The tool integrates both the mobile application with the location element (GPS Tracking) that enables the registering of the mapped water resources with their specific location. The MWRMM-T is a very simple tool that meets the needs of even those with low literacy level in the community who have shown interest in being part of the mapping party due to its visualization power, as it can be displayed in the back-end database, the mapped information is sent instantly through real time mapping. All the existing data archived in the back-end database was collected in Machakos County in collaboration with the county government individuals and civic leaders with the need to test the tool. Information can be visualized by clicking on any water resource mapped to get the particular details, including any kind of action required for making better informed decisions. The back-end database is a web application that is hosted on our own server spaces. Searching/querying the database is by location name, sub-county or feature format. Keen selections of spatial analysis methods for water resources analysis or regular quality control are also possible with MWRMM-T. MWRMM-T was hence built understanding the needs of the grassroot level individuals in the rural and peri-urban setting in Kenya, working on promoting sustainability on their water resources
Laurent Thum
Geologist, Lausanne, Switzerland
Title: 2D and 3D GIS-based geological modeling – application for geotechnical investigations, tunneling and mining
Biography:
Laurent Thum completed his master’s degree at Lausanne University in 2008. He was awarded the prize of the Swiss Geological Society for his work on Alpine Geology. He is the co-founder of D&T Geodata Management and operates as a senior engineering geologist for one of the leading Swiss engineering companies, Edy Toscano. A member of the Swiss Tunneling Society, he recently published, together with Geol. Reto De Paoli, an innovative GIS-based methodology for the digital mapping and 3D modeling of geological features during the excavation of a tunnel
Abstract:
Knowledge of sub-surface characteristics in the context of a civil engineering project is essential to reduce the risks related to geological uncertainties. In the quest to improve geological models, modern GIS tools facilitate the acquisition, management and interpretation of data. It was in parallel with the Ceneri base tunnel project, one of the longest tunnels in Switzerland, that 3D digital mapping and modeling tools were developed in ESRI’s ArcGIS Desktop. The geological and geotechnical monitoring during the excavation of the tunnel has been optimized with digital tablet mapping and automated 3D modeling of geological elements. The discontinuities (faults, joints, strata interfaces) as well as a certain number of specific points of information (water ingress points, samples, etc. ...) are drawn on a model of the tunnel walls, and are then georeferenced and modeled in 3D using geoprocessing tools. These objects can then be viewed in their actual geographical position on a geological map of the project (horizontal cross-section halfway up the tunnel), as well as in a 3D model. A graphic parallel to the tunnel axis automatically displays all the numerical data related to the progress. The adaptation of the technique for monitoring underground mining is underway. Since exploratory drillings have a decisive role in this type of project, a tool to model them in 3D, based on their geometrical characteristics (coordinates, azimuth, dip), has been developed; it is used to represent data such as stratigraphic layers, the level of the water table, water inflows, in situ and laboratory tests values. The developed GIS tools allow rapid and accurate modeling and synthesis of a large quantity of data and helps improve the safety and performance of the works
Volodymyr Vasiliev
CTO EOS Data Analytics, Ukraine
Title: Urban change detection method of multitemporal remote sensing images
Biography:
Volodymyr Vasiliev is a graduate of Dnipropetrovsk National University. He is the CTO EOS Data Analytics Ukraine and PhD student of the Faculty of Physics, Electronics and Computer Systems, Oles Honchar Dnepropetrovsk National University. His main research interests include remotely sensed data processing, real scene image retrieval, cloud computing and GIS methods
Abstract:
Change detection analyses describe and quantify differences between images of the same scene at different times. Change detection is a complex phenomenon which includes different procedures such as identifying the specific change detection problem, image preprocessing and variables and algorithm selection for the computations. The widely used methods for high-resolution image change detection rely on textural/structural features. However, these spatial features always produce high-dimensional data space since they are related to a series of parameters. Moreover, the current urban change detection methods are totally reliant on visual interpretation. This article presents a new automatic change detection method of multitemporal remote sensing high-resolution images and visual interpretation of results. To detect change we apply a series of algorithms, which are independent of each other: subpixel registration of multitemporal images, spectral classification (building masks), singling-out of the most informative stripes and threshold segmenting, morphological filtering and object classification, vectorization and calculation of parameters, visualization of the changes on the map. The candidate changed areas are obtained base on spatial mask filtering, then the spectral difference, searching for spectral-temporal anomalies, morphological technique and a shadow detection method to identify the real changes. Experiments were conducted on the multitemporal Pléiades images. Experimental results show that the proposed method can effectively and quickly extract the changing urban area between the two temporal optical remote sensing images of high spatial resolution. Compared with other change detection methods, the proposed method reduces the effects of classification and segmentation on the change detection accuracy