Devanjan Bhattacharya

Opening up Smart Cities: Citizen-Centric Challenges and Opportunities from GIScience

The holy grail of smart cities is an integrated, sustainable approach to improve the efficiency of the city’s operations and the quality of life of citizens. At the heart of this vision is the citizen, who is the primary beneficiary of smart city initiatives, either directly or indirectly. Despite the recent surge of research and smart cities initiatives in practice, there are still a number of challenges to overcome in realizing this vision. This position paper points out six citizen-related challenges: the engagement of citizens, the improvement of citizens’ data literacy, the pairing of quantitative and qualitative data, the need for open standards, the development of personal services, and the development of persuasive interfaces. The article furthermore advocates the use of methods and techniques from GIScience to tackle these challenges, and presents the concept of an Open City Toolkit as a way of transferring insights and solutions from GIScience to smart cities.

Knowledge-Based Landslide Susceptibility Zonation System

The landslide susceptibility of a region is important for socioeconomic considerations and engineering applications. Thus, an automated system for mapping of landslide susceptibility could be of significant benefit for society. In this paper, a knowledge-based landslide susceptibility zonation (LSZ) system has been proposed. The system consists of input, understanding, expert, and output modules. The input module accepts thematic images of contributing factors for landslides. The understanding module interprets input images to extract relevant information as required by the expert module. The expert module consists of knowledge base and inference strategy to categorize a region into different landslide intensities. Finally the output module provides a LSZ map. It is a pixel-based system and provides output having the scale same as that of the input maps. The system has been tested to prepare a landslide susceptibility map for the Tehri-Garhwal region in Indias lower Himalayas, and further validated with studies for two other different regions. The proposed system provides output commensurate with that provided by experts. The categories of hazard zones have a discrepancy as little as 6.2% in high hazard zones and near to 1.5% and 4% in moderate and low hazard zones, respectively. The high hazard zones in the LSZ maps from the proposed system are supersets of that obtained by experts (i.e., the proposed system provides safer LSZ map). Thus, it can be concluded that the proposed system can be used for preparation of LSZ maps. In the future, the methodology may be extended for real time assessment and prediction of landslide hazards.

Automated Geo-Spatial System for Generalized Assessment of Socio-Economic Vulnerability due to Landslide in a Region

Abstract The paper explains a system to assess automatically vulnerability due to landslide on socio-economy of a region by categorizing landslide hazard using spatial as well as temporal causative factors. The expert system has input, understanding, expert & output modules & uses digital spatial data of causative factors of landslide. Input accepts thematic images of contributing factors for landslides, Understanding module interprets to extract relevant information as required by expert module consisting of a Knowledge Base & Inference strategy categorizing region into different susceptibilities of landslide. Overlaid on socioeconomic parameters in output module for vulnerability maps of landslide on population, forestry, urban, rural, agriculture separately to ascertain the impact of landslide on socio-economy of the Tehri-Garhwal region lower Himalayas, India.

Automated Geo-Spatial Hazard Warning System GEOWARNS: Italian Case Study

AbstractHazard warning is an area of research that requires both hazard evaluation and warning dissemination. At present, no such system carrying out both hazard evaluation and warning communication directly to the user community exists. Thus, there has been a need to develop an automated integrated system to categorize hazard and issue warning that reaches users directly. The objective of this paper is to develop an integrated, independent, generalized, and automated geo-hazard warning system, making use of geo-spatial data under popular usage platform. Thus, in this paper, development of GEOWARNS, an automated geo-spatial hazard warning system, has been elaborated. Testing and validation of the developed system has been carried out for landslide hazard evaluation and its warning dissemination pertaining to a comprehensive case study in Italy. The functionality of GEOWARNS is modular in architecture, having input, understanding, rainfall prediction, expert, output, and warning modules. The categories of ...

Toolkits for Smarter Cities: A Brief Assessment

The literature has offered a number of surveys regarding the concept of smart city, but few assessments of toolkits. This paper presents a short analysis of existing smart city toolkits. The analysis yields some general observations about existing toolkits. The article closes with a brief introduction of the Open City Toolkit, a toolkit currently under development which aims at addressing some of the gaps of existing toolkits.

Location Intelligence for Augmented Smart Cities Integrating Sensor Web and Spatial Data Infrastructure (SmaCiSENS).

Bhattacharya, D., & Painho, M. (2018). Location intelligence for augmented smart cities integrating sensor web and spatial data infrastructure (SmaCiSENS). In GISTAM 2018 - Proceedings of the 4th International Conference on Geographical Information Systems Theory, Applications and Management (Vol. 2018-March, pp. 282-289). SciTePress.

Selected Indicators and Methods for Evaluation of E-Participation

All democratic governments try to involve the citizens into the public deals. So, they support development of information society in many ways including high investments into increasing utilization of information and communication technologies in public administration. But it is still very difficult to measure successfulness of this support and compare countries between themselves. A possible way how to assess development of E-Participation is proposed.

Interlinking Opensource Geo-Spatial Datasets for Optimal Utility in Ranking

The joining of geospatial datasets is required to utilize the complete set of information available in each of them. There are many open source geospatial datasets available such as GeoNames, Open Street Map, Natural Earth and to get a comprehensive dataset with the union of all available information it is important that such datasets are linked optimally without redundancy or loss of information. Many of the geolocations on digital maps are not classified for importance because of the lack of additional information such as population or administrative level. A way to give an importance scale to the names is by linking the GeoNames to other datasets (OSM, natural earth). OpenStreetMap data provides a limited number of place classifications (such as city, town, village). For the best cartographic results we need classes that are a little more comprehensive about how they rank cities. The challenges faced include geometry searching, matching, buffer determination, local regional naming text inclusion and accuracy. This has been achieved by the current research work where presently GeoNames, Natural Earth and Open Street Map data tables have been merged with the union of all their attribute columns resulting in a complete geospatial dataset with place accuracy of atleast 95 % for any given country dataset. The data tables at global level consist of hundreds of thousands of rows with each row depicting a geolocation. The geometry, name and geo-id complete and fuzzy searching and matching around a buffer of 50 km took a minimum of 30 s to maximum 1 min in a commodity computer with 2 GHz, 2 GB memory, according to size and complexity of the query run for a country which could have a list of points ranging from a dozen to several hundreds. The future aim is to ultimately do this for global datasets to create an all-encompassing geodata bank having such information as administrative, political, ecological details from important databases as GAUL, SALB, GADM etc.

Distributed GIS for automated natural hazard zonation mapping Internet-SMS warning towards sustainable society

Abstract Today, open systems are needed for real time analysis and warnings on geo-hazards and over time can be achieved using Open Source Geographical Information System (GIS)-based platform such as GeoNode which is being contributed to by developers around the world. To develop on an open source platform is a very vital component for better disaster information management as far as spatial data infrastructures are concerned and this would be extremely vital when huge databases are to be created and consulted regularly for city planning at different scales, particularly satellite images and maps of locations. There is a big need for spatially referenced data creation, analysis, and management. Some of the salient points that this research would be able to definitely contribute with GeoNode, being an open source platform, are facilitating the creation, sharing, and collaborative use of geospatial data. The objective is development of an automated natural hazard zonation system with Internet-short message service (SMS) warning utilizing geomatics for sustainable societies. A concept of developing an internet-resident geospatial geohazard warning system has been put forward in this research, which can communicate alerts via SMS. There has been a need to develop an automated integrated system to categorize hazard and issue warning that reaches users directly. At present, no web-enabled warning system exists which can disseminate warning after hazard evaluation at one go and in real time. The objective of this research work has been to formalize a notion of an integrated, independent, generalized, and automated geo-hazard warning system making use of geo-spatial data under popular usage platform. In this paper, a model of an automated geo-spatial hazard warning system has been elaborated. The functionality is to be modular in architecture having GIS-graphical user interface (GUI), input, understanding, rainfall prediction, expert, output, and warning modules. A simplified but working prototype of the system without the GIS-GUI module has been already tested, validated, and reported. Through this paper, a significantly enhanced system integrated with web-enabled-geospatial information has been proposed, and it can be concluded that an automated hazard warning system has been conceptualized and researched. However, now the scope is to develop it further.