Day 3 :
- Geodynamics | GIS software | Digital Earth
Session Introduction
Xuelian Meng
Louisiana State University, USA
Title: New era of 3D coastal morphology mapping using LiDAR and unmanned aerial vehicle
Biography:
Dr. Xuelian Meng is an assistant professor at Louisiana State University and fellow of the Coastal Studies Institute (SCI). Her research interests are to apply geospatial technologies to investigate fragile ecosystems that are sensitive to human activities. Specific topics of 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), and 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 research mainly use 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 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 developments of high-resolution and protable 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 descrete field elevation survey, which have gained popularity in morphological mapping. This presented studies focus 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.
Barbara Bollard Breen
Auckland University of Technology, New Zealand.
Title: Remote sensing in conservation and ecological research
Biography:
Dr Barbara Bollard Breen is a senior lecturer in the School of Applied Sciences at AUT. Her research interests are in GIS applications, ecosystem management, cultural landscapes and spatial ecology. She has over 20 years’ experience working in government and NGO’s in both Australia and New Zealand. Her research focus has been the identification and selection of Protected Areas, using remote sensing technology, such as UAV, to map habitats and landscapes for conservation planning and integrating social data with environmental and biological information using decision support systems, multivariate statistics and GIS
Abstract:
The Auckland University of Technology unmanned aerial vehicle (UAV) research team are leaders in the application of UAV technology and remote sensing in conservation and ecological research. The team works in partnership with industry to customise and develop unmanned systems for use in New Zealand and extreme environments such as Antarctica, desert systems and offshore islands. Low flying unmanned aerial vehicles (UAV) offer ecologists new opportunities to collect scale appropriate data at high spatial and temporal resolution. The presentation will showcase the use of UAVs in spatial ecology and demonstrate existing post processing tools for UAV imagery. The talk will explore opportunities for use of computer vision techniques for analysis of high resolution video imagery in a variety of environments and ecological studies.
Yafra Khan
Universiti Malaysia Sarawak, Malaysia
Title: E-BABE-Encyclopedia of bioanalytical methods for bioavailability and bioequivalence studies of pharmaceuticals
Biography:
Yafra Khan pursuing Masters of Computer Science(Research) degree from Universiti Malaysia Sarawak, Faculty of Computer Science and Information Technology. The topic of my research is Water Quality Analysis and Prediction. Before this, I did my Bachelors of Software Engineering from Pakistan. I have previously done two internships in reputable organizations in Pakistan, mainly related to Web Development. I am also doing a freelance job of Software content writing and Web Development. Under this job, I have written wide ranging content including software proposals and other documents. I am interested in the fields of Machine Learning and GIS.
Abstract:
The lack of clean water resources is one of the direst issues faced by humanity, especially in the developing countries. Therefore, management of water resources to optimize the quality is very crucial. There has been a lot of research in past few years to find ways of using technology for efficient water quality management and solving issues surrounding this. In more recent years, some work has been done to improve the prediction accuracy of water quality using Artificial Intelligence algorithms like Artificial Neural Networks (ANN), Bayesian Networks (BN) etc. However, more work needs to be done in terms of reliability, accuracy and usability of these water quality management tools. The goal of this research is to develop a methodology using a hybrid of ANN and fuzzy inference, known as Adaptive Neuro- Fuzzy Inference System (ANFIS) as well as using GIS tools to improve the prediction accuracy. The data for this research has been taken from United States Geographical Survey (USGS), with Time-Series data for six months (January-June) each of the year 2014 and 2015. The data includes 17 quality parameters. The integration of Artificial Intelligence and GIS techniques intends to provide a comprehensive methodology for effective analysis and prediction of future trends of water quality. This research intends to utilize both these tools by interactive display and graphical manipulation of the results produced. This research also studies different aspects of the methodologies used in past, reflects upon current and future challenges as well as provides insight into further improvements.
Rakshan Roohi
La Trobe University, Australia
Title: Assessment of wateruse of different landcovers using Surface Energy Balance Algorithms for Rainfed Agriculture (SEBARA) in western Victoria, South Australia
Biography:
Rakhshan has completed her first PhD at the age of 33 years from Colorado State University, USA. She stayed involved in research, research management and education for more than more than 30 years in different capacities at Pakistan Agricultural Research Council. She took an early retirement and moved to Australia and is currently working as a causal staff/Associate Research Fellow at LaTrobe University besides perusing her second PhD at LaTrobe University, Australia. She has participated in more than 20 international trainings/conferences/workshops mostly related to remote sensing and GIS and has more than 30 publications including journal articles and book chapter.
Abstract:
Evaporation and transpiration components of the energy balance are influenced by many factors especially in water-limited ecosystems: surface temperature, soil moisture, vegetation type and growth stage, and atmospheric advection and therefore are the most difficult ones to estimate. Any shift in landuse/Landcover (LULC) can disturb the hydrological balance and thus put stress on the water resources. Following the principals of energy balance equation, Surface Energy Balance Algorithm for Rainfed Agriculture (SEBARA) has been devised to estimate the evapotranspiration (ET) of different LULCs in western Victoria using medium spatial resolution Landsat data. ET estimates of four LULCs: crops, plantations, natural vegetation and pastures revealed that generally the crops and plantations have 12-20% higher evapotranspirtation rate than the natural vegetation and pasture which is due to lower surface albedo and emissivity, resulting in lower outgoing longwave radiation. As a consequence, the higher available net radiation and lower soil heat flux in crops and plantations result in higher ET rate. It is observed that the tree roots can reach extend down to 12m to access groundwater which is deeper than the 6-8m previouly measured. The younger plantation with an open canopy has lower ET than the older plantation, but similar to the pastures and natural vegetation. The cultivated oats have similar evapotranspiration rate as that of old plantation. Overall the ET from pastures is lowest however, the rate depends upon the pasture species. The estimated ET compares well with ET measured using flux tower and adjusted sapflow readings (accuracy > 95%).
Munkhnasan Lamchin
Korea University, Korea
Title: Assessment of land cover change and desertification using remote sensing technology in a local region of Mongolia
Biography:
I am Mongolian now studying at the Ph.D. course of Environmental GIS-RS lab of Korea University. My research is an assessment of desertification by remote sensing and GIS method and classifies land cover of Mongolia. So far my two papers have published at the international journal a title is “Monitoring of Vegetation Dynamics in the Mongolia Using MODIS NDVIs and their Relationship to Rainfall by Natural Zone”. The second one is “Assessment of land cover change and desertification using remote sensing technology in a local region of Mongolia”.
Abstract:
Desertification is a serious ecological, environmental, and socio-economic threat to the world, and there is a pressing need to develop a reasonable and reproducible method to assess it at different scales.The Hugnu Khaan region lies in the semiarid regions of center, Mongolia. Remote sensing and GIS are being used to study desertification in this region. In this paper, we used Landsat TM and ETM data between July and September first week in 1990, 2002, and 2011 to analyze the spatial and temporal patterns of the desertification using three indices: the Normalized Difference Vegetation index (NDVI), Topsoil Grain Size index (TGSI), the Land Surface albedo. We normalized the indicators, determined their weights, and defined five grades of desertification: non, low, medium, high, and severe. The times of image acquisition on the assessment indicators, sets of assessing rules were built, and a Decision Tree approaches were used to assess the desertification and we computed Compound Topographic index (CTI), Land Surface Temperature (LST) and Perpendicular Drought index (PDI). Then tested the correlation between the level of desertification and the six variables and compared with each other, checked by field data. We found that desertification in the Hugnu Khaan covered severe desertification more than 15 % of the total land area, the total area of severely desertified land was 7% in 1990. The desertification of the study area is increasing each year; in the desertification map for 1990–2002, there is a decrease in areas of non and low desertification, and an increase in areas of high and severe desertification. From 2002 to 2011, areas of non desertification increased significantly, with areas of severe desertification also exhibiting increase, while areas of medium and high desertification demonstrated little change.
Thomas MacMullen
Eastern Illinois University, USA
Title: Implementing GIS Laboratory Practices: Migration to a distance learning based Instruction
Biography:
Eastern Illinois University,
Abstract:
Traditional learning environment laboratory practices related to GIS is aimed towards learning to use the software in a dedicated lab located in a room on campus. The need to be physically present at pre-scheduled hours, often with an instructor limits the possibilities of many non-traditional students wanting to take GIS courses. The need to design viable alternatives that allow students to access laboratory facilities remotely without losing most of the educational objectives, typically achieved in a face-to-face environment, is increasing by the day. This paper proposes a solution already implemented and tested in order to move a traditionally taught GIS course, to an ONLINE based instruction. The design requires remote access authentication via the VMWare View system which is composed of three servers: The secure server, the composer server and the administrative server. The seservers have been virtualized and reside on the hardware allocated for the project. The VMWare View system is housed on a cluster of two Dell Poweredge R720 blades with Teradici graphics accelerators. Each blade serves as a VMWare ESX 6.0 host. Within the administrative server, a pool of virtual computers is created. Any student with internet access enrolled in the course can authenticate to the VMWare View secure server which checks them for password validity and for access authorization. Once access is granted, the user is assigned to a random virtual computer in the pool. Upon logging off, the virtual computer that the user was logged into will be deleted and re-copied from the snapshot so that the next user who logs in to it will get a clean copy and will not be able to access the previous user’s data. Once student is granted access to a virtual machine they can first perform GIS mapping within the virtual server environment using the ArcGIS or qGIS. Once thes tudents gets proficient with a simulated laboratory environment, which mimics the real set-up of the laboratory facilities, a specially created secure proxy-firewalled network allows then to take control of the laboratory real GIS server facilities, which are prewired for the specific practice in place. Students then are allowed to manage and program real GIS mapping and perform laboratory practices as if they were inside the laboratory. In case they need assistance, instructors with remote access to the facilities can be reached online within the laboratory hours.
Biography:
Student
Abstract:
Web Processing Services (WPS) have upgrowing concern in geoinformation research. However, teaching about them is difficult because of the generally complex circumstances of their use. They limit the possibilities for hands- on- exercises on Web Processing Services. To support understanding however a Training Tools Collection was brought on the way at University of Applied Sciences Stuttgart (HFT). It is limited to the scope of Geostatistical Interpolation of sample point data where different algorithms can be used like IDW, Nearest Neighbor etc. The Tools Collection aims to support understanding of the scope, definition and deployment of Web Processing Services. For example it is necessary to characterize the input of Interpolation by the data set, the parameters for the algorithm and the interpolation results (here a grid of interpolated values is assumed). This paper reports on first experiences using a pilot installation. This was intended to find suitable software interfaces for later full implementations and conclude on potential user interface characteristics. Experiences were made with Deegree software, one of several Services Suites (Collections). Being strictly programmed in Java, Deegree offers several OGC compliant Service Implementations that also promise to be of benefit for the project. The mentioned parameters for a WPS were formalized following the paradigm that any meaningful component will be defined in terms of suitable standards. E.g. the data output can be defined as a GML file. But, the choice of meaningful information pieces and user interactions is not free but partially determined by the selected WPS Processing Suite
Shashi Bhushan
Jawaharlal Nehru University School of Social Science, India
Title: Assessing change of forest cover and their socio-economic impact through LULC and NDVI in Kaimur, Bihar, India: 1977-2014.
Biography:
Shashi Bhushan is continuing PhD from Jawaharlal Nehru University from Center for the Study of Regional Development, School of Social Science and about to submit their thesis by July 2016. Currently He is working on various aspect of forestry along with socio-economic perspective and of livelihood as well as climatic impact in tropical forestry region of India. He has published two papers in international journal including FAO (Food and Agricultural Organisation, UNO) and many papers are waiting for publication, which focussing on the several perspectives of forestry in India.
Abstract:
The Study attemts to identify the ulitisation of land use pattern and status of forest area in kaimur region of Bhabua, Bihar, India using LULC(Land use Land Cover) classification and normalized difference vegetation index (NDVI)-based land-cover change detection method based on harmonic analysis. Apart from this, the study also tried to discover the regions of forest scarcity through checking the quality of forest nearest to settlement and visual interpretation.The main focus is the forested areas of kaimur district of bihar, boardered with Sonabhadra districts of Uttar Pradesh prioritized in changing socio-economic structure of surrounding livelihood and contemperary conservation with livelihood initiatives. GIS (Geographical Information System) and Remote sensing applied to landsat images of the pleateau a region in 1977 and 2014 indicates a 17% decline in overall forest for the study area. Nearly 50% of the area is covered with forest area, out of which 36% are open and 14% are dense forest cover, where most of the open forest are were degraded for different purpose of activities. There was 16% increase in agricultural area and 3% in built up area, which shows that most of the forest area has been shifted into agricultural land and settlement expansion due to population pressure on local natural resources. The remote-sensing analysis, complemented by fieldwork in the region, attributes the negative trends to the livelihood demand for firewood, animal grazing and NTFP. The study proposes the application of satellite remote sensing and geospatial techniques for future environmental monitoring and forest dynamics studies.
Obinna Anejionu
Imperial College London, London
Title: multi-tier accounting of ghg emissions and removals associated with bioenergy-induced land use changes using GIS and Remote sensing
Biography:
Dr Obinna C.D Anejionu is a Research Associate at Imperial College London, where he is developing an Earth Observation Laboratory as part of a UK Space Agency / Biz sponsored project on ‘Advancing Earth Observation Applications in Forests. His expertise covers Geomatics, Geography, Remote Sensing and GIS, with field experience in land surveying in Nigeria. He has worked as a lecturer in the Department of Geoinformatics and Surveying, University of Nigeria Nsukka. His research interests span applied Environmental Remote Sensing and Spatial Analysis in environmental monitoring and management
Abstract:
Current global momentum urging the use of non-fossil-based energy as a viable means of curbing global climate change is prompting increasing interests in the use of bioenergy. However, increasing bioenergy generation activities are mounting pressure on land resources, leading to land use changes, which impact on global greenhouse gas emission and removal, as a result of its influence on ecosystem processes such as photosynthesis, respiration, decomposition and combustion. Land use land use change and forestry (LULCF) is included as one of the 6 key sectors of the Intergovernmental Panel on Climate Change (IPCC) global GHG inventory. The IPCC guidelines outlined generic methods for the country-based accounting of GHG emissions and removals at three different tiers (levels of details). However, such national or regional accounting of the GHG emissions, where results are presented as national aggregates has limited application to related studies such as understanding the impacts of bioenergy industry-driven land use changes on GHG emission for specific areas or at sub-national and/or sub-regional levels. For such studies, a spatially disaggregated method for LULUCF accounting will be required. This study aims at using GIS and remotely-sensed techniques and data to establish the basis for the accounting of carbon stock, emissions and removals associated with LULUCF activities at varying spatial scales, based on IPCC-recommended methods. Spatially explicit land use areas will be used to develop nested multi-resolution techniques for the three different tiers based on remotely-sensed images of varying spatial resolutions, integrated with appropriate IPCC default values. This research is expected to establish robust platform for understanding how bioenergy activities may drive future global climate change.
Wael EL ZEREY
Associate Professor, Djillali Liabes University, Algeria
Title: The use of remote sensing and GIS for monitoring and analysis of desertification in Algerian territory
Biography:
Wael El Zerey is an Associate Professor at the department of environment in Djillali Liabes University. He obtained his engineering degree (2002) in ecology and his M.S. (2004) and Ph.D. (2010) in Environmental Sciences from Djillai Liabes University in Algeria. His research focuses on the monitoring and understanding of land cover change and desertification by the use of remote sensing, and GIS technology
Abstract:
The desertification results from an imbalance in the dynamic interactions between the four elements of the ecosystem (climate, soil, vegetation, human beings). It is then a state which settles under the combined effects of the climatic modifications and the human activities applied to fragile soil and vegetation. The current vegetation all over the world is the complex result of interactions between flora, climate, and soil conditions. According to the different studies of desertification phenomena in North Africa, the most significant indicators are the biophysical ones like the state of vegetation cover and the state of landscape Combating desertification gives a priority to the execution of preventive measures in favour of the not yet degraded regions. This step remains however dependent on precise and reliable information in the time and space on the situation and the evolution of desertification. remote sensing technology and geographical information systems can play a great role in land desertification investigation, monitoring land changes, and as a tool for regional planning. If the multi-temporal remote sensing data at optimum season are acquired, it is possible to establish a desertification analysis model to study the cause of land desertification and predict the tendency of its expansion quantitatively. The remote sensing is also a powerful tool to follow the state of landscape and its the relationship with the distribution of the water resources. The synthesis of the totality of results under a geographical information system GIS as well as their confrontation with others types of data can allow the mapping of the desertification risk
Elvis Obeng Boateng
Czech University Of Life Sciences, Czech Republic
Title: GIS In natural resources
Biography:
Elvis Obeng Boateng is a graduate student of Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. I completed in 2010 with second class upper in Natural Resource Management. I am 30 years of age. Currently I am offering my masters in Nature conservation in Czech University of Life Sciences, Prague, Czech Republic. I work with University of Energy and Natural Resources, Sunyani, Ghana as assistance teacher. I have did some field studies in illegal mining in Ghana and the impart it have on nature in 2011.
Abstract:
A geographic information system (GIS) lets us visualize, question, analyze, and interpret data to understand relationships, patterns, and trends.GIS benefits organizations of all sizes and in almost every industry. There is a growing interest in and awareness of the economic and strategic value of GIS. GIS analysis and processing uses specialized applied geometric, mathematical, and relational operators on the basic features/records in the reource of countries. Nearly all resource management problems are spatial in nature or have a strong spatial component in the resource. The challenges that exist for organizations thinking of distributing GIS capabilities to field offices, a move becoming more prevalent as recent natural resource graduates likely will have GIS experience in coursework, and exposure or training in the field. Some federal agencies make significant amounts of natural resource GIS data available to the public. Recognize that there are factors that hinder an organization’s willingness to share a database. This is the first step to successfully negotiate getting the data. Reluctance to share data may arise in Sensitive inter formation such as endangered species or archeological sites, ownership holdings or management practices and scientific interest. GIS used in natural resource uses basic ecological research in identification of landscape areas meeting particular complex criteria and project objectives, rather than other measures, should be emphasized and can keep personnel focused when setbacks occur.