Land & Natural Resources Management ABSTRACTS & BIOGRAPHIES

DEIMOS IMAGING: UTILISATION OF DEIMOS DATA IN LAND AND RESOURCE MANAGEMENT

Abstract:

Developing and newly industrialized countries in any part of the world are experiencing a rapid expansion in economic growth mirrored by the expansion of the cities, urban development, infrastructure and industry. Geospatial Technology and Satellite Data play a major role in Urban and Rural Planning which involve determining appropriate future decisions and actions through a series of choices. Making choices requires, in addition to thorough planning knowledge, comprehensive (geo)data about the past, present and future.
Asian countries Like Indonesia, India Malaysia, Thailand etc. have shown that tremendous growth in engineering, architecture and urban planning sectors are key to foster development in Smart / Safe city and Sustainable Rural Growth.

Maps are an essential tool, not only in our everyday lives, but also to foster sustainable growth through urban planning. As cities continue to expand, even the most accurate maps will be quickly outdated. Thus, a challenge arose: to develop an easy-to use and cost-effective solution to map new infrastructures and urban growth.

Deimos Imaging, a subsidiary of UrtheCast Corp., has played a key role in the design, implementation and operational consolidation of highly relevant services in Land and Natural Resources Management in different parts of the world. The Deimos-2 and Deimos-1 satellites are a combination of High Resolution and High Repetitive solution which provide a cost-effective and highly responsive service to cope with the increasing need of fast access to very-high demanding Satellite imagery. This data can be effectively utilized in application areas like:

• Land Use Monitoring
• Sustainable Agriculture
• Urban Growth Monitoring
• Soil Mapping
• Land Movement Monitoring
• Geological Mapping
• Forest Management

Biography:

Mr. Krishanu Acharya, is currently working as Regional Sales Manager, Middle East, Africa and South Asia for Deimos Imaging, a subsidiary of the Canadian UrtheCast Corp. He holds a decade of experience in Remote Sensing and various application areas of Earth Observation Industry. He has worked with numerous private Organisation and achieved unparalleled experience in field of Geospatial Technology. For the last five years he is instrumental in promoting sustainable and time proven EO Solutions in various Asian Countries.

Identification of Driving Factors Causing Land Cover Change in Bandung Area Using Binary Logistic Regression Based On Geospatial Data

Abstract:

Land is a fundamental factor in production activity and is closely related to economic growth that supports the needs of human life. In many cases, human activities related to land use are often uncontrollable and have negative impacts on the environment, both locally and globally. In an effort to understand the phenomenon of land cover changes, land cover change modeling can be used. One model that can be used to identify factors causing land cover change is the Binary Logistic Regression (BLR). Based on this ability, this model can simulate the prediction of land cover changes that occur in a region by considering the parameters that represent the characteristics of the studied area, in this case physical and social economic conditions. In this study, Bandung area is selected as the study area. Bandung area has a fairly high economic activity which will have direct impact on many things, including land use changes, and eventually lead to land cover changes. The results show that physical condition represent by elevation, curvature, and road have more influence to cause land cover changes in Bandung area. However social economic condition represent by population and central business district has low impact.

Biography:

Dr Riantini Virtriana is currently a lecturer and a researcher in Remote Sensing and Geographic Information Science, Department of Geodesy and Geomatics Engineering, Institute of Technology, Bandung (ITB). She received the B.Eng, M.Sc., and Ph.D. degrees from Institute of Technology, Bandung, Indonesia, in 2004, 2007, and 2016, respectively. Most of her works are focused on understanding land use/land cover change and BIG data.

Geospatial feature class integration for urban information system with latent semantic analysis

Abstract:

Data integration of different geographic information systems is necessary to set up spatial data infrastructures for collecting and disseminating geographic datasets. However, syntactic, structural, semantic and geometric heterogeneities present many troubles for automated processes. Among them, the semantic one is finding corresponding feature types between systems which represent the same real world entities or phenomena. An instance-based automated method is proposed in this research based on a simple assumption that the more corresponding objects between two feature types from each systems exist, the more both the feature types are semantically related. We applied a well-known information retrieval method, latent semantic analysis, to find overall semantic relation between feature types of two different geospatial datasets, cadastral land category map and POI field investigation dataset. With more than 800,000 corresponding instance pairs between the above dataset, not only corresponding feature types but also a hierarchical relations could be obtained and a new analysis perspective could be derived.

Biography:

Yong Huh was born in Rep. of Korea in 1978. He received the B.E.(Civil Engineering) and Ph.D.(Surveying and Spatial Information) degrees from Seoul National University, Seoul, Rep. of Korea, in 2001 and 2011, respectively. He joined Spatial Information Research Institute, Korea Land and Geospatial Informatrix Corp. in 2014 and now is a principal researcher. His main areas of research interest are high resolution remote sensing, cadastral surveying and feature matching for spatial data integration.

Incorporating Land Use Change Analysis and High Conservation Value Area Identification to Assess Possibility of Land Swap and Better Spatial Planning

Abstract:

Indonesia has been experiencing massive land use change since 1990s. Data issued by Indonesia Ministry of Environment and Forestry (MoEF) shows that forest areas across Indonesia had been shrinking around 22.9 million ha during 1990-2015. This area covers dry land forest, mangrove forest, and peat land forest, which are considered to have High Conservation Value (HCV).
This study aims to investigate whether during period 1990-2015 the areas experiencing land use change also contain areas with HCV. The study areas will cover two provinces that experienced major land use change and deforestation, namely Riau and South Sumatera province. To answers the research question, this study will incorporate time series land use maps and map of HCV area distribution. Identification of HCV areas refer to HCV-Toolkit Indonesia. Land use maps and HCV map will be used to identify areas that contain HCV and experience land use change through GIS analysis in ArcGIS. Expected result of the study is: areas with no HCV and did not experience land use change can also be identified. These areas will be potentially proposed for land swap for the future spatial planning, while areas containing HCV and experiencing land use change will be proposed for restoration.

Biography:

Zuraidah Said is a Forest and Climate Research Analyst at WRI Indonesia office. She is responsible for research on issues of Indonesia climate, forest, and land use, as well as working on spatial data and analysis.