Poster Presentation : GIS Using Slope Analysis of Landslides in Centraal Japan

(Takashi Fujita),(Venkatesh Raghavan),(Shinji Masumoto) 한국지형학회 1999 SYMPOSIUM PROGRAM Vol.- No.-

Exploration of expansion patterns and prediction of urban growth for Colombo City, Sri Lanka

Jayasinghe Pavithra,Raghavan Venkatesh,Yonezawa Go 대한공간정보학회 2021 Spatial Information Research Vol.29 No.4

This study attempts to analyze and simulate urban growth pattern of Colombo city in Sri Lanka which is a dynamic and rapid urbanizing region. The spatiotemporal urban growth patterns during 1997–2019 were first analyzed by comparing Land Cover (LC) maps for time intervals between 1997–2008 and 2008–2019 using intensity and growth pattern analysis. Urban lands in Colombo have grown in a faster rate during 1997–2008 as compared to 2008–2019 period. The prominent spatial expansion pattern during 1997–2008 is outlying, as opposed to edge expansion which is predominant during 2008–2019. These major urban expansion patterns were modeled to predict the future urban structure of Colombo in 2030 using FUTURES (FUTure Urban-Regional Environment Simulation) model. FUTURES is a patch-based, multilevel modeling framework for simulating the emergence of landscape spatial structure in urbanizing regions. Simulated result generated from the model reveals substantial agreement with real ground urban changes showing a kappa value of 0.78. The model allows to predict three different scenarios, namely Business as Usual, Infill Growth and Sprawl showing over 100 km2 increase in urban lands by 2030. Predicted urban structure was then compared with proposed development plan. With certain limitations arising from available data, the model is effective in predicting possible urban scenarios and providing valuable inputs to support better decision making for sustainable development of Colombo city. The results demonstrated in this study would be useful in modelling urban growth in other cities and further validate the efficacy of the proposed workflow.

GIS using slope analysis of landslides in central Japan

Takashi,Fujita,Venkatesh,Raghavan,Shinji,Masumoto 한국지형학회 1999 한국지형학회지 Vol.6 No.2

Development of optimal routing service for emergency scenarios using pgRouting and FOSS4G

Sittichai Choosumrong,Chingchai Humhong,Venkatesh Raghavan,Ge´rald Fenoy 대한공간정보학회 2019 Spatial Information Research Vol.27 No.4

This study aims to implement a system for Emergency Routing Decision Planning (ERDP) based on Service Oriented Architecture. A Web-based system is implemented to facilitate ubiquitous dynamic routing services on up-to-date road network data. Integration of Dijkstra’s shortest path and Analytic Hierarchy Process (AHP) algorithms has facilitated improved weighted travel- time computation. Route computations are done considering situation at source, transit and destinations. The AHP is used to prioritize amongst possible destinations considering impedance factors affecting travel time. The routing algorithm is deployed as Web Processing Service (WPS) using the ZOO-Project Platform. Two scenarios for application of the ERDP Web services are demonstrated. In the first scenario of medical emergency, the ERDP computes routes between patient’s location, emergency car to hospital in proximity of accident site considering dynamic factors such as conditions of road network, the patient’s state and availability of medical facilities and expertise in the target hospital. In the second scenario of a disaster situation, the GRASS GIS r.sim.water simulation model for overland flow under excess rainfall conditions was integrated into the ERDP system as a WPS. The result of the simulation is used to automatically update the road network database and new routes are computed based on existing conditions. The system is developed using Free and Open Source Software for Geoinformatics (FOSS4G) stack and is amenable to customization to support other emergencies such as fire, debris flow and tsunami. Integration with Sensor Observation Services for automatic data updates from CCTV camera and weather stations could further improve utility as a real-time ERDP system.

Multi-scale object-based fuzzy classification for LULC mapping from optical satellite images

Hang T. Do,Venkatesh Raghavan,Luan Xuan Truong,Go Yonezawa 대한공간정보학회 2019 Spatial Information Research Vol.27 No.2

In this paper, a multi-scale object-based fuzzy approach is demonstrated for land use/land cover (LULC) classification using high-resolution multi-spectral optical RapidEye and IKONOS images of Lao Cai and Can Tho areas in Vietnam respectively. Optimal threshold for segmentation procedure is selected from rate of change-local variance graph. Object-based fuzzy approach is implemented to identify LULC classes and LULC initial sets, and then the initial sets are classified to final LULC classes. In case of Lao Cai area, normalized difference vegetation index (NDVI), normalized difference water index (NDWI), water index (WI) in object-based are used to generated water, terrace field classes, and built-up and vegetation sets. NDVI, soil index (SI) and red band are used to distinguish built-up set to building, bare land and road classes. NDVI and RedEgde band are inputs to classify rice field and forest classes from vegetation set. In case of Can Tho area, NDWI and WI are generated to water, vegetation, paddy field classes and built-up set, and then built-up set is classified to building, bare land, road, and paddy field classes. The technique is able to create LULC maps of Lao Cai and Can Tho areas with (90.8%, 0.84), and (92.3%, 0.90) classification accuracy and kappa coefficient, correspondingly.

Development of open source Web-GIS platform for threedimensional geologic modeling and visualization

Nemoto Tatsuya,Masumoto Shinji,Raghavan Venkatesh,Nonogaki Susumu,Nakada Fumio 대한공간정보학회 2020 Spatial Information Research Vol.28 No.6

An Open Source Web-GIS platform for Geologic Voxel (Geo-Vox) modeling and visualization, has been developed. Geo-Vox provides a comprehensive framework by integrating GIS, relational database, open geospatial standards-compliant web mapping engine, 2-D and 3-D rendering libraries for geologic modeling. Free and Open Source Software for Geoinformatics (FOSS4G) stack comprising of GRASS GIS, PostgreSQL, MapServer, OpenLayers and three.js JavaScript 3-D library have been used to implement the system. Geo-Vox overcomes several limitations of solid modeling by construction of model based on an intuitive logical relation between geologic units and boundary surfaces. Two-dimensional visualization allows rendering of horizontal and vertical sections at user-defined planes. The voxel model can also be exported in a format amenable for rendering as 3-D solid model. Geo-Vox is unique, in that, (a) logics used to create the model are easily comprehensible to geologist (b) offers high degree of interoperability (c) leverages FOSS4G stack to implement a comprehensive geologic modeling tool that is hitherto unavailable. The functionality of Geo-Vox is demonstrated using data derived from published geologic map. The results confirm the potential of Geo-Vox to provide an interoperable and scalable framework for delivery of value-added geological information for a variety technical and societal needs.

Soil moisture retrieval in farmland using C-band SAR and optical data

Xin Zhao,Ni Huang,Zheng Niu,Venkatesh Raghavan,Xianfeng Song 대한공간정보학회 2017 Spatial Information Research Vol.25 No.3

Soil moisture retrieval in vegetation-covered area with space borne synthetic aperture radar is a challenging process due to the impact of vegetation on the multiple scattering of electromagnetic wave. In this paper, a semi-empirical method is proposed to estimate farmland soil moisture by active microwave remote sensing and optical remote sensing. By integrating the vegetation water content estimated from optical data and thermal infrared data into a coupling model based on a water–cloud model, the influence of vegetation on microwave backscattering coefficient was eliminated and thus soil moisture in vegetation-covered area was accurately retrieved. The experiment of soil moisture retrieval was carried out using Radarsat-2 and Landsat 8 datasets in western Great Khingan Mountains, Inner Mongolia, China. The research showed that the accuracy of the coupling model is high and the R2 is up to 0.69 using HH polarization. Moreover, the effects of crop types on soil moisture retrieval, particularly barley, could also be distinguished using the coupling model.

Bananas diseases and insect infestations monitoring using multi-spectral camera RTK UAV images

Sittichai Choosumrong,Rhutairat Hataitara,Kawee Sujipuli,Monthana Weerawatanakorn,Amonlak Preechaharn,Duangporn Premjet,Srisangwan Laywisadkul,Venkatesh Raghavan,Gitsada Panumonwatee 대한공간정보학회 2023 Spatial Information Research Vol.31 No.4

Recent advances in multi-spectral imagery generated using Unmanned Aerial Vehicles (UAVs) have opened new possibilities for agricultural crop monitoring and management, even in small-holder farms. In this study, Vegetation Indices (VIs) derived from UAV-captured multi-spectral images with Real-time kinematic positioning were applied to assess the health and growth of banana plants and fruits. Multi-spectral images consisting of Red, Green, Blue, Red-EDGE, and Near-Infrared were collected using quadcopter UAV flown at a height of 80 m. Several VIs was examined with ground truth from 67 sampling sites for healthy and stressed banana plants. The results indicate that Triangular Vegetation Index (TVI), Normalized Difference Red Edge Index (NDRE) and Normalized Difference Vegetation Index (NDVI) provide valuable information for crop monitoring in a timely and quantifiable manner. Kappa coefficients comparing plant health with TVI (0.85), NRDE (0.83) and NDVI (0.75) provide excellent result with overall accuracy being 92.48%, 89.66% and 88.95%, respectively. The data preparation workflow was implemented using Free and Open-Source Software. The datasets generated and the procedures described are not only useful to local farmers for mitigating loss in yield in banana plantations but can also offer a generic solution in promoting smart farming.