Sameer Saran

Multicriteria Spatial Decision Analysis in Web GIS Environment

Internet, a client/server system, is a perfect means of GIS data accessing, analyzing and transmission. The World Wide Web, FTP (file transfer protocol) and HTTP programs make it convenient to access and transfer data files across the Internet. Using Internet for GIS makes it easy access to acquire GIS data from diverse data sources in the distributed environment. The geospatial multicriteria decision analysis in a client/server environment is an important and challenging task for the GIS community because of narrow Internet bandwidth for large geospatial data sets. In the present paper, we are developing a multicriteria decision analysis tool for spatial decision making in the web GIS environment. The developed system has been demonstrated for biodiversity conservation and priorities. An attempt has been made to generate the alternative decisions based on priority vectors. The multicriteria technique of Analytic Hierarchy Process (AHP) is used to derive the eigen vectors with the given multiple constraints of conflicting criteria and aims at selecting optimal alternative from the available sets. However, the evaluation recognizes the importance of expert knowledge when assigning the weights for the best spatial priorities. Comparing within classes and alternatives using judgment and decision matrix is based on Saaty’s Pairwise Comparison. The Multicriteria Spatial Decision Support System (MC-SDSS) software development uses ASP, ArcIMS 9.0, ArcSDE9.0 and Oracle 9i data server in the web GIS environment. The database organization of spatial and non-spatial data is done in the RDBMS environment using ArcSDE and Oracle 9i data server.

Evaluation of digital elevation models for delineation of hydrological response units in a Himalayan watershed

This study reports results from evaluation of the quality of digital elevation model (DEM) from four sources viz. topographic map (1:50,000), Shuttle Radar Topographic Mission (SRTM) (90 m), optical stereo pair from ASTER (15 m) and CARTOSAT (2.5 m) and their use in derivation of hydrological response units (HRUs) in Sitla Rao watershed (North India). The HRUs were derived using water storage capacity and slope to produce surface runoff zones. The DEMs were evaluated on elevation accuracy and representation of morphometric features. The DEM derived from optical stereo pairs (ASTER and CARTOSAT) provided higher vertical accuracies than the SRTM and topographic map-based DEM. The SRTM with a coarse resolution of 90 m provided vertical accuracy but better morphometry compared to topographic map. The HRU maps derived from the fine resolution DEM (ASTER and CARTOSAT) were more detailed but did not provide much advantage for hydrological studies at the scale of Sitla Rao watershed (5800 ha).

Forest Canopy Density Stratification: How Relevant is Biophysical Spectral Response Modelling Approach?

Abstract Monitoring of forest cover is an essential tool for sustainable management of natural resources. Woody green cover can better maintained and managed by identification of forest gaps and their subsequent refilling. Forest canopy density mapping is one of the tools used to identify such canopy openings and most useful parameter to consider in the planning and implementation of afforestation and reforestation program. The present study demonstrate the test‐assessment and practicability of forest canopy density mapping using satellite remote sensing data and biophysical spectral response modelling. Forest canopy density stratification through object oriented image analysis and conventional method of visual interpretation also have been compared with the Forest Canopy Density (FCD) Mapper semi expert system. In this study, forest canopy density is effectively stratified through linear multi‐parametric approach by utilizing advanced vegetation index, bare soil index, shadow index and thermal index. Isadata cluster analysis of forest canopy density map derived from FCD Mapper and conventional methods were shown similar results with respect to percent area of forest and non‐forest. The high percentage (10-30%) occurrence of bushy vegetation like Lantana Camera in ground canopy poses challenge in delineation of forest canopy density as its spectral reflectance is similar to that of the forest.

CityGML at semantic level for urban energy conservation strategies

The exponential growth of cities in India due to urbanization resulted in increased use of non-renewable energy resources to meet the essential power requirements of urban built environment. It is essential for urban planners to provide innovative solutions in context of urban energy simulation based on virtual 3D city models. The recent 3D geoinformation science studies are insufficient in providing optimal solutions because of lack of emerging concepts and integrated softwares. Presently 3D GIS data can be generated into various LODs (Levels of Detail) depending upon the application requirement and input data used. There are various 3D GIS softwares like Google SketchUp, ESRI CityEngine etc., which are being used mostly for data creation especially for boundary representation for geometry abstraction without semantic information. The 3D GIS data conversion from native format into City Geography Markup Language (CityGML) enhances it by providing information both at geometric and at semantic level in interoperable format. A building information model of Geoinformatics department building in IIRS campus is created using Google SketchUp and exported to energy modelling program in gbXML schema. The present investigation explores the semantic characteristics of developed CityGML model for solar thermal and photovoltaic energy production potential assessment based on building semantic components. The amount of solar irradiation incident on bounding features and also illumination obtained through openings of building is quantized using SunCast and RadianceIES application of IESVE Software, respectively. The simulated energy data are integrated with building semantic features and stored in open-source PostGIS RDBMS to address basic semantic queries.

Formulation of hierarchical framework for 3D-GIS data acquisition techniques in context of Level-of-Detail (LoD)

Two-Dimensional Geographic Information Science (2D GIS) development has reached its highest level in terms of acquisition, processing, analysis and presentation techniques. Further development in 2D GIS is restricted due to its 2D abstraction of real world objects which are having third dimension (3D) in practical world. The abstraction of 3D real world objects is of extreme importance for user applications to address issues related to infrastructure development, entertainment, tourism, sustainable management of cultural sites and to tackle effects of various social and environmental factors. Hence, formulation of mechanism to model 3D real world objects and its phenomena especially related to urban segment from data acquisition and analysis perspective is essential. The 3D GIS data acquisition techniques such as Satellite Photogrammetry, LIDAR data processing, Building structure extraction algorithms, Close-Range Photogrammetry and total station survey contribute significantly towards generation of 3D digital models. Most of 3D GIS analysis largely depends upon 3D data structure and on data acquisition mechanism in particular. The structured way of data acquisition facilitates encoding of same into common information model which further aids in complex GIS analysis. Therefore, this paper proposes a structured mechanism for data acquisition in context of hierarchical framework of Level-of-Detail (LoD).

Implementation of CityGML energy application domain extension (ADE) for integration of urban solar potential indicators using object-oriented modelling approach

With the advent of energy rating systems and increased energy efficiency requirements for built environment, the assessment of energy performance of new buildings and refurbishment rates of existing buildings have become an important compliance in the building design process. In order to analyse and simulate the effects of energy-efficient measures for buildings, it is essential to establish spatio-semantic information interoperability between the building design and energy modelling softwares. Data interoperability facilitates different domains to interact with the single building model. The geometrical properties of building semantics such as effective areas exposed to total incident radiation were used as indicators for assessment of seasonal solar potential of buildings. The key urban solar potential indicators were identified based on the semantic components of buildings. The CityGML instance document derived from a proposed energy application domain extension (ADE) conceptual schema could be used as common interoperable model for both the design and energy simulation systems.

Markov random field-based method for super-resolution mapping of forest encroachment from remotely sensed ASTER image

Forest encroachment (FE) is a problem in Andaman and Nicobar Islands (ANI) in India for environment and planning. Small gaps created in the forest slowly expand its periphery disturbing the biodiversity. Therefore, intrusion of poachers, slash and burn and other factors causing FE must be carefully detected and monitored. Remote sensing offers a great opportunity to accomplish this task because of its synoptic view. Conventional classification methods with remotely sensed images are problematic because of small size of FE and mixed landcover composition. This study presents an application of super-resolution mapping (SRM) based on Markov random field for detection of FE using ASTER (15 m) images. The SRM results were validated using multispectral IRS LISS-IV (5.8 m) image. Non-contiguous FE patches of various sizes and shapes are characterized using the spatial contextual information. The novelty of this approach lies in the identification and separability of small FE pockets which could not be achieved with pixel-based maximum likelihood classifier (MLC). The SRM parameters were optimized and found comparable to previous studies. Classification accuracy obtained with SRM at scale factor 3 is κ = 0.62 that is superior to accuracy of MLC (κ = 0.51). SRM is a promising tool for detection and monitoring of FE at Rutland Island in ANI, India.

A geo-information system approach for forest fire likelihood based on causative and anti-causative factors

Innumerable forest fire spread models exist for taking a decision, but far less focus is on the real causative factors which initiate/ignite fire in an area. It has been observed that the majority of the forest fires in India are initiated due to anthropogenic factors. In this study, we develop a geo-information system approach for management of forest fire in Mudumalai Wildlife Sanctuary, Tamil Nadu, India, with the objective to develop a forest fire likelihood model, integrating GIS and knowledge-based approach for predicting fire-sensitive initiation areas considering major causative and anti-causative factors. Amongst the various causative factors investigated, it was found that wildlife-dependent factor (antler collection and poaching) contributed significantly to fire occurrence followed by management-dependent factors (uncontrolled tourism and grazing), with much less influence of demographic factors. Similarly, anti-causative factor (stationing of anti-poaching/ fire camps) was considered as quite significant. The likelihood model so developed, envisaging various factors and flammability, accounted for different scenarios as a result of pair-wise comparison on an ordinal scale in a knowledge matrix. The inferential statistics computed indicated the robustness of the model and its insensitivity to moderate changes. It makes it possible for this forest fire likelihood model to predict and prevent a forest fire in an effective and scientific manner because it can assume forest fire likelihood in real time and present in proper time.

Development of CityGML Application Domain Extension for Indoor Routing and Positioning

CityGML is an open data model for storage and exchange of 3D city models. It is categorised into thirteen thematic classes, i.e., buildings, tunnels, bridges, etc., lacking the other themes such as indoor routing and positioning. With the amplified use of indoor routing and positioning, the need for prerequisite notion of detailed semantic, as well as geometric information of the 3D building data has grown. We intend to extend the CityGML schema to add attributes of indoor features using the facility of Application Domain Extension (ADE) provided by the OGC CityGML 2.0. In this study, we aim to showcase the formation of Indoor Routing and Positioning ADE along with the process concerning its development, such as the 3D model design, network dataset creation, routing, positioning and Unified Modeling Language based ADE application schema generation. This research would help the users to easily store and exchange 3D city data on which they can perform routing and positioning inside the buildings with enhanced semantic and geometric properties.

Comprehensive study on AOD trends over the Indian subcontinent: a statistical approach

ABSTRACT Aerosol optical depth (AOD) trend analysis has been carried out using various statistical techniques over Indian sub-regions. AOD data acquired from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites from January 2003 to December 2015 have been utilized in the present study. Mann–Kendall test, Spearman partial rank correlation (SPRC) test, Pearson test, t-test, linear regression analysis, and Sen’s slope estimate are performed on 13 years of AOD data to observe the trend over different Indian sub-regions. AOD trend is found to be positive (0.0035–0.0154 per year) over different Indian sub-regions indicating the enhanced level of suspended particles over the Indian subcontinent. All six methods are evaluated for trend detection using both satellite data. Linear regression and Sen’s slope test provide good estimate of slope values to observe the magnitude of AOD change per year. Mann–Kendall test, SPRC test, and Pearson test support the trends results obtained from linear regression and Sen’s slope estimate. So, these tests are preferable for the trend analyses.