4^th International Conference on GIS and Remote Sensing September 27-28, 2018 Berlin, Germany

Agustin Fernandez Eguiarte is responsible for the Informatics Unit for the Atmospheric and Environmental Sciences (UNIATMOS) of the Centro de Ciencias de la Atmósfera of UNAM and is a Geomatics Professor at the Facultad de Ingeniería of UNAM. In September 2014, he received the international Latin America Geospatial World Excellence Award granted by Geospatial Media and Communications. His research interests include, processing and quality control of continental and oceanic climatic-environmental data, GIS, marine and continental cartography, data bases, geospatial repositories and metadata, open data and interoperability and map servers on the internet.

The countries in the Intra-Americas Sea, particularly those located in the Gulf of Mexico and the Caribbean Sea, are exposed to the impacts of tropical cyclones that cause important human and economic losses to the region. The quantification of these impacts might be used as a preventive tool for risk reduction if it is used to evaluate the territory exposed to natural hazards and if it is made available in a friendly and simple way to concerned authorities and vulnerable people. Based on data of 2,117 tropical cyclones trajectories downloaded from the International Best Track Archive for Climate Stewardship for the period of June 1851 to November 2015 in the North Atlantic Basin, influence ratios were established for each trajectory: 150 km for wind and 350 km for rain, according to the publication by D.R. Chavas and K.A. Emanuel: “A QuikSCAT climatology of tropical cyclone size”. The number of strikes of the influence ratios overlapped on the coastline was counted. Maps were created with the total number of impacts of tropical cyclones on the coasts of countries located in the Gulf of Mexico and Western

Caribbean Sea. In the case of the 249,122 rural, 50,821 semi-urban and 4,562 urban localities of México, a similar process to that done for the coastline was completed. Maps were also created with the number of impacts of tropical cyclones on more than 3,000 localities.

Valentina Janev graduated in Electrical Engineering from the University of Ljubljana, Slovenia and received the PhD degree in the field of Semantic Web technologies from the University of Belgrade, School of Electrical Engineering and Computer Science. Recently, her research activity concerns Linked, Open and Big Data and implementation of EU policies in these domains. She serves as a reviewer of respectable international journals including International Journal on Semantic Web and Information Systems (IGI Global); International Journal of Digital Earth, Enterprise Information Systems, Knowledge Management Research and Practice, Information Systems Management (Taylor & Francis), Artificial Intelligence Review (Springer) and Data Mining and Knowledge Discovery (Wiley).

In the last few years, with the rise of the open data movement, a large and increasing number of governments and organizations have started to make information freely available and easily accessible online. In order to increase transparency, the information is also published as Linked Open Data. From the government systems perspective, the Linked Data approach can be observed as a technique for making the data interoperable and ready for consumption. In order to harmonize approaches used for describing the datasets, semantic services or repositories, the European Commission, in collaboration with the W3C consortium, has accepted a set of standard vocabularies that should be used to build public administration services. This presentation aims to discuss the challenges related to managing spatial and temporal information in Linked Data format and introduce the opportunities in terms of data aggregation/integration and creation of information mashups and decision-support tools on top of Linked Data. Being relatively a new field, currently there is a lack of tools that enable efficient exploration and analysis of linked geospatial statistical datasets. Therefore, ESTA-LD (Exploratory Spatio-Temporal Analysis) tool was developed to address some of the Linked statistical Data management issues, such as crossing the statistical and the geographical dimensions, producing statistical maps, visualizing different measures, and comparing statistical indicators of different regions through time. The modeling approach that was adopted so that the published data conform to the established standards for representing statistical, spatial and temporal data in Linked Data format will be also introduced. The main contribution of the research is related to the delivery of state-of-the-art open-source tools for retrieving, quality assessment, exploration and analysis of statistical Linked Data that is made available through a SPARQL endpoint.

Waqas Wajid is currently working in Landscape Architect firm L+P GmbH situated in Munich, he completed his masters from Anhalt university if applied sciences in landscape architect and done civil engineering from SSUET Karachi in 2010, he has ample work experience in construction industry. Also, he published an article and won a poster competition in DLA 2018

Background: Karachi is one of the biggest metropolitan cities of the world but lacks in basic urban infrastructure like mobility and recreational activities, etc. The author has tried to analyze the challenges and their coping strategies within constraints of its complications through ESRI ArcGIS by data available on the internet and open source platforms. The aim is to allocate and manage resources according to its urban districts. The criteria were urbanism, population, and recreational spaces. Methodology: The methods adopted to improve these urban complexities are Geo Design (Steinitz). GeoDesign applies system thinking to large problems of planning. Another approach was Spatial Planning through Remote Sensing: As the population is on a verge, so it requires a planning which helps the municipality to investigate and create an assessment out of it. For developing those spatial planning a platform of ESRI ArcGIS is widely used in a modern world. The city of Karachi has not yet adopted the same techniques yet. In this thesis form that particular platform shapefiles of each district will be created, by spotting out the best location which fulfills the practical engineering requirement specifically, topography of the region will determine the development and by just implementing a few changes in stereotype construction of the streets which is mainly its profile, the same area would act as reservoir during pluvial flooding. Which is a by-product of urbanization, drainage in terms of sewerage and stormwater will be compensated for this particular spatial planning. Conclusion: Cites are complex social engine where various ethnicities merge for gain economical and livable gains. The hypothesis of this research was: the developing cities could learn from developed ones and implement modern techniques in their developing phase. For Karachi in my thesis, I suggested strategies which could solve the various problem related to Urban infrastructure. Allocating the services in a district according to the demand which could perform multiple tasks simultaneously. interestingly while working professionally I found many of my results are standard planning practice in Munich. In a nutshell, these planning strategies could make Karachi a more livable city than before.

Peddada Jagadeeswara Rao is working as a Professor and Chairman, Board of Studies, Department of Geo-Engineering and Centre for Remote Sensing, College of Engineering (A), Andhra University. He has published research articles on groundwater resources, watershed management, solid waste management and HIV/AIDS in reputed national and international journals. He has guided 10 Research Scholars for their PhDs and he has been a consultant on water resources, remotesensing and GIS.

The present study is focused on spatio-temporal changes of land use/land cover and mangroves on identification of coastal erosion zones along the 339 km long coastline of the Krishna-Godavari (KG) delta region, Andhra Pradesh, India. This study analyzed multi-date satellite imagery of Landsat 4, 5, 7 and 8 TM and ETM sensors of 2002, 2011 and 2017 which reveals rapid changes in land use/land cover, deforestation of mangroves and coastal erosion. There is a decrease in area of about 28 km2 of mangroves and an increase in coastal erosion of 6.485 km2 is delineated from 2002 to 2011. Contrary to this, from the year 2011 to 2017 there is a considerable increase of 93 km2 in mangroves. During 2002 to 2017, severe beach erosion of 0.184 km2 and 0.418 km2 occurred at Uppada-Konapapapeta coast and Nilarevu river mouth, respectively. Similarly, an accretion of 0.526 km2 is observed at Vakalapudi in Godavari delta sea coast. In Krishna delta, the coast near Machilipatnam is getting eroded. No major coastal erosion is observed on the Krishna delta coast in comparison to Godavari delta coast. The results of this show that mangrove degradation and coastal erosion is taking place along the K-G delta region and suggests construction of sea walls, beach nourishment and prevention of the conversion of mangrove areas into aquacultural and agricultural land; these are the mostsuitable measures to arrest the coastal erosion.

Andrews Kwasi Afforo Odoom is a GIS specialist with over six years of working experience. He is an MSc GIS and Environmental Management Graduate from the

University of Brighton, UK. His working experiences includes GIS Teaching Assistant (University of Ghana), Mapping Engineer (Newmont Ghana Gold Limited) and GIS Technician (Ambiental Technical Solutions). He is currently the GIS Business Manager at Losamills Consult Limited, a leading mapping and engineering company in Ghana

Fly-tipping is one of the most devastating global hazards which offer significant threat to human health and environment. Hence, creating a readily read and accessible map for devising mitigation strategies at the local level is important. The study examined the integration of GIS to develop vulnerability map for aiding efficient surveillance of illegal dumping in Bassetlaw District, United Kingdom. The methodology involved three processes: (i) the integration of principal component analysis (PCA) and ordinary least square regression (OLS) to identify key geographical factors driving illegal dumping; (ii) developing criteria for ranking each factor and; (iii) building of geostatistical model into geographical information system to delineate the attractiveness of illegal dumping across the landscape. Using multiplicative index model, a composite vulnerability map was created from five key drivers for dumping in the district including population density, proximity to road, income, health and crime. The result revealed local disparities of illegal dumping due to varying geographical conditions. It also indicated that about 80% of incidences occurred within seven meters of road and that majority of waste type illegally dumped in the district was household waste (53%). Evaluation of the model was employed to examine and validate the effectiveness of the model output. By comparing the result with field incidence data, the map was successful in identifying districts with high-risk to illegal dumping. The result provides essential information for environmental managers to better understand and analyze illegal dumping and formulate remedial strategies.

Katerina Mekhlis has completed her PhD at the age of 26 from St. Petersburg State University, master degree at UAB (Barcelona), postmaster program Viadrina University (Germany). She is a CEO of NeoCityLab an IT GIS company specialised in data processing of laser scanning. She has an experience as a project leader for system implementation (incl. system design and implementation of ERP systems: SAP, Navision, Axapta etc.) in International Corporations such as Heineken, Henkel, Fraport, other companies.

This article is devoted to a new approach to the development of a system of 3D visualization of urban spaces and automated recognition of urban objects based on laser scanning data, photo panoramas and construction of three-dimensional models of cities (by identification of separate objects in city panoramas in automated mode and recovering from it 3D city models). The system may become an integrational platform for smart city, connecting all the data in one view point. It is also a useful tool for urban city management for city planning and maintenance. This kind of platform can be a very useful to perform urban city management, planning tasks as well as make a significant improvement in communication between citizens and institutions. To create this type of solution, the following problems were solved through automated data processing from mobile scanning equipment of standard type (for example Trimble, Topcon, etc.). Approaches for urban environment visualization were found to make it in the most perceivable way for different users and purposes (municipalities and citizen, games, education, augmented reality, etc.). Object recognition from point cloud in automated mode was developed to be used for a city modelling and other practical tasks (urban asset inventory, control and maintenance over the urban infrastructure objects and buildings, etc). Tools

to integrate data from all sources to create a “one window” solution – a Smart City platform. Several algorithms for analyzing the city environment are available and new can ones be developed by requirement (navigation, measurement of objects in panoramas, objects embedding for territory planning purposes; objects identification; objects comparison, data comparison, retrospective analysis to compare different time periods, etc.). The proposed solution is operative as an average European city can be scanned and processed within 2–3 weeks. This solution is very light to be used in mobile and web applications and will be appropriate for any user without the need of any special training to use the system.

Napoleon Kurantin is a Senior Lecturer and Head of Department of Development Policy in the GIMPA School of Public Service and Governance (GSPSG) at the Ghana Institute of Management and Public Administration. He was the Coordinator of the GIMPA–Ghana Armed Forces Command and Staff College (GAFCSC) Master’s Degree in Governance and Leadership; Coordinator of GIMPA–Kofi Annan International Peacekeeping Training Center (KAIPTC) Master of Arts Degree in Conflict, Peace and Security (MCPS) and was the Acting Director of GIMPA–HOTCATT. In his current position, he teaches courses in Research Methods (Advanced Quantitative Methods), Geo-spatial Statistics, Geospatial Governance Framework (Security and Good Governance), Natural Resources Management, Defence and Intelligence Management, Conflict and Crisis Management, Theories of Economic Development, Economic Science, Practice of Development Economics, Strategies and Management of Development, Environmental Economics and Management, Strategic Management and Leadership, Planning and Regional Economic Science. He has been with GIMPA, GAFCSC as Academic Directing Staff and KAIPTC as an Adjunct Lecturer for the past eight years

Poverty-alleviation programme is at the thrust of the agenda in the development strategies of the Government of Ghana. This study presents an integrated approach towards the development of a prototype of geo-spatial system (GIS) for the implementation of One District, One Factory (1D1F) in support of regional economic development and decision-making relative to poverty alleviation programmes. Based on the process of decentralization, poverty assessment is formulated at three administrative levels: district, regional and national (Central Government) to define and evaluate poor communities in the country. The main drawback to such a bottom-up approach is its emphasis mainly on socio-economic data-sets and manual techniques. GIS is hereby considered as a process and technique that strengthens the effectiveness of poverty assessment by changing bottom-up to a comprehensive integrated approach providing a stronger tool that enables the inclusion of spatial data-sets for the sitting of 1D1F, relative to regional economic development. To achieve the main goal of developing a prototype of GIS for the implementation of 1D1F policy in support of regional economic development and poverty alleviation programmes, this study adopts the Structured System of Development Methodology based on three phases namely: problem definition, system design and implementation. At the phase of problem definition, the proposal takes into consideration the problems of poverty assessment processes, the requirement of the users of such information to ensure an improved system; the outcome shows that in addition to socio-economic information, spatial data is included in poverty assessment and analysis that could be supported by GIS. At the second system design phase, the system design was undertaken on the basis of process modeling and data modeling using GIS. The integrated operation has at its thrust, the goal of overcoming the current lack of spatial data-sets. The last phase of data modeling is premised on the development of geo-database that integrates both socioeconomic and spatial data-sets in support of 1D1F. The prototype used Microsoft Access and ArcView software, respectively. Henceforth, a prototype of GIS is developed to investigate and examine the effectiveness of an integrated system geared towar the implementation of 1D1F in support of regional economic development and poverty alleviation programmes with Ghana as a laboratory.

Shogufa Popal has completed her Bachelor’s Degree from Kabul University in 2012 and her Master’s Degree from the University of Tokyo in 2018. Currently, she is a Lecturer in the Department of Forestry and Natural Resources, Faculty of Agriculture, Kabul University.

Deforestation and forest degradation are among significant environmental issues in Afghanistan but has not been studied intensively due to insecurity, confined budget, lack of expertise, and limited accessibility to new technology. In such a situation, remote sensing technology offers practical and economical means to acquire reliable, consistent, and up-to-date information for assessing forest cover and monitoring its spatial and temporal dynamics. Therefore, this study aims to detect forest cover change in six districts of Nuristan Province over the past three decades (1998–2016) using object-based classification of Landsat satellite imagery. The specific objectives to achieve the overall purpose of this study are: (i) ascertaining the current status of the forest cover, (ii) mapping forest cover in 1998, 2008, and 2016, and (iii) detecting forest cover change between 1988– 2008 and 2008–2016. The research methodology comprises of: (i) pre-processing of Landsat images using TNTmips (ii) objectbased image classification using eCognition Developer 9.0, (iii) mapping land and forest cover change, and (iv) quantifying land cover dynamics together with forest cover loss and gains. Overall, the results showed that although deforestation has not occurred on a large scale (7.26 km2) in the study area from 1998 to 2016, the forests have been continuously degraded during the study period, converting from dense broad-leaved forest to sparse as well as sparse to other vegetation areas, which can be  defined as “forest degradation”. Meanwhile, the overall accuracy for the maps were relatively high (>91 %).

Khalida Tadjer graduated Civil engineering at Mouloud Mammeri university (Tizi-ouzou, Algeria) then continued her studies (Master and Doctorate) in the Department of Civil Engineering, University of Blida, Algeria. At present, Khalida Tadjer is a assistant professor in the Department of Civil Engineering, University of Blida, Algeria. Her research activity concerns the assessment of seismic vulnerability of urabain area, the aim is to reduce the damage caused by the earthquake. She has several scientific papers and talks in different international conference.

The seismic vulnerability of an urban area is of a great deal for local authorities especially those facing earthquakes. So, it is important to have an efficient tool to assess the vulnerability of existing buildings. Blida is located in the north part of Algeria, an area prone to seismicity. It is classified zone III according to the Algerian Seismic Code (RPA99 version 2003). The town is among the oldest cities in the north. Build especially during the colonial period, Blida is characterized by vulnerable urban conditions with dense buildings and narrow roads. Using geographic information systems (GIS), the seismic vulnerability of Blida is assessed. First the vulnerability indexes of buildings are calculated, then making seismic scenarios. Damage rates are determined taking into account the seismotectonic aspect of the region and the vulnerability curves of structures commonly found in Blida. The rates of damage caused by the earthquake considered in the scenario highlighted the high vulnerability of Blida. These results can allow elaborating strategic countermeasure plans for the earthquake risk mitigation in the city.