Every Utility Network’s Conflation process has intricate business rules. Assets / structures always have a geometric and spatial relationship with their respective linear network. In the real world scenario, we will have instances where the network alignment and relative spatial positions will be different at different locations. Shift between linear network and the assets / structures are not uniform and heterogeneous. There is an industry challenge to incorporate relational assets conflation into the architecture of custom conflation. This plays a key role in providing business solutions across the enterprise.

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Cities are complicated places. Navigating any major city is challenging, be it large centers like New York, London or Moscow or smaller cities such as Missoula, MT or Truckee, CA. While what we see of a city appears complicated, it is nothing compared to what we can’t see; all of what lies below our feet. While infrastructure is mostly invisible, it is vital; critical to our existence. It supplies the water we drink, the power we use, the fuel for heat, our communication and entertainment channels and the waste we generate. Without it, life as we know it, would grind to a halt!

Smart City is no longer a new term; there are extensive number of publications, many of us have read about the funding of smart city projects such as the one in Columbus, OH, and maybe a few of you have been involved in the implementation of smart infrastructure like public Wifi, smart meters or even bus tracking. While these transformational projects are changing the world we live in, most of us reside in places still lacking the basic information required to make a smart city work; location.

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Every Utility constantly strives for ‘operational excellence’ with the aspiration to transform entire business performance directly impacting their operational costs, growth, and revenues. In order to achieve this objective, companies must take relevant action to safeguard their GIS and Asset management data. Many utilities go through multiple checks at each stage of the process to ensure that they meet the predefined business rules and comply with the industry’s regulatory requirements. In fact, data needs to go through hundreds of checks for various parameters and it is not feasible to do this manually.
In such a scenario, data validation is of crucial importance and can be achieved by using efficient tools and methods. This approach helps utilities ensure that their systems function the way you expect them, in order to meet business objectives.

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Normally, organizations planning a data migration consider the style that’s most suited to their needs. While you can choose from several strategies, depending on the project requirements and available processing windows, it often boils down to two fundamental types: big bang migrations or trickle migrations. Unfortunately, a UN migration isn’t suited to either on its own.

So, what does this mean? You need flexibility. You need a current GN database capable of facilitating operations which also allows business processes to migrate at their own pace. You need a long migration period, so that you can minimize program costs through existing enterprise upgrade and enhancement plans. Lastly, you need to ensure that there is no disruption to operations. Does this sound like I want to have my cake and eat it too? Nope, que the UN’s best friend “The Twin”.

While the Utility Network (UN) is a significant enhancement in the utility landscape (one that many have waited years for), it also entails a substantial investment. The UN has deviations from the Geometric Network (GN) in both model structure as well as content. This makes it hard for one to view the transition process as a simple migration. It requires preparation and planning to ensure this is a positive experience for your organization. These activities will also enable you to have control over the costs associated with the work.

To help our clients make the move, RMSI has developed a Program called the Utility Network Digital Transformation (UNDT). This Program has three distinct stages: Assessing your readiness for the UN, the initial migration followed by the “Twin”. Today let’s talk about how to start your work with a Readiness Assessment.

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In India, power failure, low voltage, high voltage etc. are very frequent and normal incidents. How can such problems be resolved or minimized?

“With the exponentially increasing power demand, the supply and generation of power has become the center of focus for the entire ecosystem. The most important area for DISCOMS and power generating companies, where they are bleeding money today, is transmission and theft (tampering). And the answer to these is Smart Meters and Smart Street lights.”

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Smart grid could be the possible answer to address the above challenges of the power sector. The Electric grid is made up of architectures, in which, power is generated at site, and is capable of delivering large quantities of energy, which then carry to the last mile along power lines to homes and commercial sites.

Smart grids are modern intelligent electric power grid system for enhanced efficiency and reliability that integrates the technology of automated control, high-power converters, sensing and smart metering and modern communications infrastructure for energy management techniques based on the optimization of demand, energy and network availability. IOT and GIS are the key components of Smart grid.

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The Sana’a city (Capital of Yemen) has been experiencing increase in flood risk due to modifications of existing land use and increased urban activities particularly in flood prone areas. In view of this, municipality of Sana’a decided to prepare a long-term City Development Strategy (CDS) including an urban upgrading strategy, land use planning, capital investment and prioritized action plan. Towards this, RMSI has conducted a study to assess the exisitng and planned storm water networks and their impact on the overflow of main drainage of Saylah. The end objective was to prepare an Integrated Storm Management plan for Sana’a city to overcome losses due to overflowing of Saylah.

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RMSI’s GIS (Geographical Information System) based Decision Support Sysyem (DSS) has emerged as an effective tool for disaster management – for the purpose of preparedness, mitigation and response and recovery operations. This GIS based DSS has the capability of organizing, storing, analyzing, building scenarios, performing what-if-analysis, and presenting final results in the form of maps, analytical tables and comprehesive reports. This paper presents two decision support systems developed by RMSI – ‘Puducherry Decision Support System for Multi Hazard Risk Assessment’ and ‘Flood Risk Modeler for Ganges’.

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Today one of the major global challenges is the hunger faced by a significant percentage of the population. Agriculture is the industry that is most likely to alleviate hunger. Yet due to land degradation and lack of arable land, it is extremely difficult for farmers to produce enough food to meet the demand. Sustainable agriculture development offers solutions for finding suitable land for agriculture expansion and also to grow more crops in the same land with fewer inputs. This paper defines the concept of food security, causative factors of food security and highlights the importance of integrated use of geospatial approach to food security scenarios and its associated benefits. It also explains the role of remote sensing and GIS in the areas of sustainable agricultural development/ management include cropping system analysis; agro-ecological zonation; quantitative assessment of soil quality and land productivity; soil erosion inventory; integrated agricultural drought assessment and management. This paper discusses the holistic approach of database creation, planning, monitoring and evaluation using geospatial technology for maximizing economic returns with minimal costs and inpu

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This paper presents the integrated use of geospatial technology in several areas of food security viz., agriculture intelligence data creation, crop suitability modeling & analysis, rangeland demarcation & management and community forest development, with the help of various project case study examples.

The first case study explains the satellite image classification based crop mapping, NDVI based crop condition assessment and NDVI vs yield regression model based crop production estimation as part of agriculture intelligence to soybean agribusiness community in India. The second case study is on remote sensing based land use land cover mapping, soil survey and mapping, topography and climatic parameters based integrated GIS analysis for crop suitability zonation in Mozambique. The third project case highlights rangeland demarcation in desserts and uplands of Saudi Arabia using spectral unmixing technique of satellite image processing. The fourth project case is on satellite image and field survey based forest type mapping & biomass estimation as part of community forest development in Cambodia.

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The presentation highlighted the state of catastrophic modeling capabilities in India for various natural hazards such as earthquake, cyclone, flood, drought, and climate change. The speaker initiated his discussion with catastrophe modeling concepts and methodology for catastrophe modeling of earthquake, cyclone, and flood. By way of socio-economic loss numbers he emphasized that the need of catastrophe modeling for various natural hazards is unquestionable for Indian Insurance Industry,

Further on, he showcased RMSI’s in-house capability for developing state-of-art catastrophe risk models for various hazards such as earthquake, cyclone, and flood through its models/products developed for India. He presented modeled impact of climate change in India and how to manage climatic (hydro-met) risks, and three pronged approach of managing NatCat risk through exposure management, scenario loss modeling, and probabilistic loss modeling.He emphasized that the predictability of loss models can be improved to a great extent if systematic insured loss data is gathered by the insurance industry for calibration of risk models, and the need for concentrated efforts by Insurance Industry to collate such data.

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In the present study, the groundwater prospect of Sinnar area has been delineated using remotely sensing data, base map of Geological Survey of India(GSI), ground truth data, and geographic information system. Based on these integrated studies, it has been noticed that the lithology of the area mainly consist vesicular/weathered basalt, massive and hard compact basalt belonging to cretaceous to early Eocene period. Based on hydro-geomorphological, geological and lineament mapping the Sinnar area can be qualitatively categorized into three groundwater potential units, viz. good, moderate and poor . The high prospect zones are alluvial plains and valley fills mainly influenced by quaternary formations with yield expectation between 15 to 180 lpm. The moderate zone is mainly consisting of weathered and fractured aquifer material with expected yield of water between 30 to180 lpm. The low potential zones mainly comprises of massive and hard rocky surface with expected discharge below 50 lpm.

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Land use/land cover mapping plays an important role for surface water conservation management plan. The study land use/land cover mapping prioritizes locations for suggesting appropriate recharge structures and effects of land use/land cover(LU/LC) changes on surface water storage. Main objective of the study is surface water conservation and management via multi-spectral information resulting from remotely sensed data to increase the irrigation. With the use of remote sensing/GIS data and techniques in the current study, catchment area, gross command area, minimum draw down level, full reservoir level, length of dam and height of the dam have been delineated. These parameters are required for feasibility study and detailed project report preparation for dam construction. The land use/land cover statistics of submerged area help to identify the cultivated land, fallow land, open/waste land, forest, settlement and surface water bodies of study area. Identification of fracture/lineaments, creation of digital elevation model, digital terrain model and 1 meter interval contours are prerequisites for undertaking surface water conservation and management in basaltic terrain. Command area of the proposed scheme lies in Beda Sub-basin which is a tributary of the Narmada river. This study proves that the implementation of Nimkheda scheme will increase the cultivated area under irrigation, facilitate the farmers for multi season cropping and help in improving their economic condition.

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Spatial databases have wide and high importance in both developing/developed nations because of their requirement in multiple fields. For example – Natural Resources Management, Disaster Management and public utility systems. Governmental and Non-governmental organizations and MNCs dealing in above mentioned geospatial application domains utilize these spatial databases as an integral component of their businesses. The biggest challenge in front of these organizations is to maintain a track of available spatial data for a particular geography. The manual check to track the spatial data requires more resources and enormous time. To overcome this challenge an automated tool which provides the platform to explore the spatial data in a short time has a great significance.

“FIND MAP” tool is based on ArcObjects and VBA on ArcGIS platform. This tool helps in data mining based on the location attribute of spatial data from huge repository of databases. The salient features of this tool include production of Thumbnails of feature classes, search through query builder and manual spatial search over a geographic world map. This automated tool was implemented to search the available geological source maps located on different server within an organization with significant reduction in search time.

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Geographical Information Systems (GIS) have evolved from paper maps to high end softwares that are capable of delivering desired datasets. To use this technology to the best of its capabilities with higher efficiency is however the real challenge. This effort aims in deploying a customized tool for Geographical Information System (GIS) editing and analysis, when integrated into a work-flow management system, which will greatly benefit large scale development projects.

Integrated watershed derivation application plays a significant role in achieving high efficiency on watershed derivation and editing process. Visual Studio .NET based on ArcObject technology developed by Environmental Systems Research Institute (ESRI) was used to develop an interface within ArcGIS for Watershed derivation application. Watershed derivation application allows the user to derive the watershed and river with the desired range of user specified watershed area using the Flow Accumulation and Flow Direction input raster grids. The process uses Stream linking through given accumulation threshold, stream to feature and watershed hydrological functions to derive the Watershed and rivers. The use of powerful robust functionality of ArcObjects in customizing the Watershed derivation application greatly reduces the time and iterative process that is handled while deriving watershed and rivers manually through the functions available in ArcGIS.

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Advancements in geospatial and remote sensing technology is increasingly being adopted and used by the mining industry for exploration and identification of prospective locations. In conventional methods of field survey, geologist looks for surface manifestations that are often not perceivable through naked eye due to regional extensions. Similarly, structural features are also not identifiable in the field traverses. Remote sensing images helps to decipher these information’s on regional extents in lesser time frame. A host of earth observation satellite images like IRS LISS 3, LISS 4, ASTER, SPOT, ALOS are available providing detail information on the land resources at various resolution and sizes.

ASTER images in association with limited field inputs can be used for mapping potential anomaly regions. It is observed that using advanced images like Hyperspectral remote sensing technology can further help in delineating the different minerals. The latest in the trend is aerial hyperspectral which provides hyperspectral images at very high resolution (~3 meters), making it possible to delineate the ore bodies on the ground.

RMSI has successfully tested and has delivered niche business solution for many mining giants in various part of the world. Some notable case studies include mapping base metals in Madhya Pradesh in India, Iron in Central in India, Limestone and Chromite in Middle East and also in parts of Africa. This time tested outputs have helped the clients optimizing the field and preliminary investment cost by upto 40 per cent.

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Agriculture plays a dominant role in India’s economic development, employment, food security, national self reliance and the overall general well being. The responsiveness of the farmers to economic incentives directly determines the extent of the contribution of the agriculture industry to the development of the economy.

Many countries use the conventional technique of data collection for crop monitoring and yield estimation based on ground surveys, and scatter available reports.

With advancements in technology, remote sensing and GIS based approaches have proven to be a cost and time effective solution in providing near real time information for estimating acreage coupled with monitoring the health of crops.

This paper highlights a study undertaken by RMSI to map and estimate acreage, yield, and production of sugarcane crop in the pre-identified districts of the Indian states of Maharashtra and Uttar Pradesh.

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Automated extraction of hydrological features from DTM is gaining significant importance because of the availability of high resolution data. The derived hydrological features are not only spatially accurate, but they also significantly enhance the overall quality of modeling projects such as water resource management and flood risk modeling.

However, processing high resolution DTMs also has some serious issues such as handling artifacts and depressions, and these issues compound as the resolution of DTM increases. Furthermore, processing high resolution DTM is extremely time consuming particularly when dealing with artifacts (man-made constructions across the rivers) and depressions.

Natural depressions like pot-holes and sinks-holes play an important role, especially in the derivation of hydrological features like river network and watersheds. Moreover, the presence of artifacts also creates secondary sinks.

This paper demonstrates the best possible ways of handling artifacts and depressions while deriving hydrological features from high resolution DTMs.

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Landslides are not uncommon in the Himalayan foothills of Bhutan. The geo-environment comprises a fragile and highly pulverized lithology. It is embedded in the Himalayan Main Boundary Thrust fault and is seismically active. The area also experiences intensive rainfall which increases pore water pressure and makes it favourable to landslide occurrences.

However, the landslides have significantly increased in the past few decades mainly due the rapid developmental activities taking place in the area.

Phuentsholing is a major industrial and business hub in Bhutan. A couple of mega hydro-electric projects and few industrial development projects have come up there in the recent past. Such rapid urban expansion and human intervention has negatively impacted the entire landscape of the city. The frequency and occurrence of landslides has increased and this has in-turn effected people, transport, property and cultural monuments. The best known examples are, landslides hampering the supply of vital goods to the capital (Thimphu) and other places, threatening the cultural monument Gumpha

(A Buddhist temple), crop loss, and flash floods.

This paper attempts to highlight how urban development and human intervention is threatening the basic geo-environment around Phuentsholing city in Bhutan.

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While the reliability and accuracy of remote sensing data is routinely checked through systematic sampling and ground verification, there has never been a large scale accuracy check that was commodity-based via the supply chain. In this paper the authors have made an attempt to scientifically compare remote sensing-based data with supply chain sources such as millers, exporters and wholesale commodities markets. This first-of-its-kind study was undertaken to assess the accuracy of remote sensing-based production estimations of Basmati rice for the 2005 growing season against the actual arrivals at various grain depots as well as other related sources. The survey was conducted through export, wholesale and marketing boards of Basmati in four leading rice-producing states in India: Uttar Pradesh, Uttaranchal, Punjab and Haryana.

Based on a comparative analysis between Kharif (monsoon growing season) 2005 estimates derived using remote sensing, versus the actual arrives at market, a March 2006 conclusion, based on certain calculated and logical assumptions and limitations found that the remote sensing-based estimated results for Kharif 2005 harvest provided an accuracy of 90% to 94% in the study areas. As anticipated, remote sensing based data as expressed in estimates is higher in a predictable manner than total supply chain sources, thus confirming the reliability of this project’s data.

The authors consider this to be a cautious, well calculated and mathematical analyses-based study done for the first time in India. Results are re-defining certain usage of remote sensing techniques in agriculture market research and supply chain study. This study may also have an application in calibrating demand forecasting as well.

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The information in any database is as good as the data that resides within it. Data quality is crucial to efficient Data Management (DM), Business Intelligence (BI) initiatives and value of information. A consultative approach is intrinsic to improving information value. Automating quality improvements to increase accuracy, currency and credibility help reduce manual activities, rework and stabilization of the system than on business. Three aspects of improving data quality via a consultative approach are discussed.

Understanding Inputs: it is critical to understand context of inbound / input data with respect to business needs, transformation processes and required quality of output data. The solution must include tools, techniques, processes and frameworks.

Workflow Management: the entire process of data quality management hinges on efficient workflow management. Such a system provides flexibility to build and manage quality improvement rules, create exception and manage flow of data volume.

Statistical Analysis: Use of statistical means is important to monitor quality of data and establish trigger points. Using the premise that “Quality is fitness for purpose”, multiple checkpoints for data quality verification are needed be established in the entire lifecycle.

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Mongolia, with an area of 1,565,000 square kilometers and population of 2,700,000 has one of the lowest population densities in the world. Around 1.7 million of its population lives in towns of which the capital, Ulaanbaatar, is by far the largest. Population is largely concentrated in the urban areas. Unplanned residential development (the Ger Areas) is a particular feature of the outskirts of Ulaanbaatar. Rural life is dominated by nomadic livestock rearing on the open range and the rural infrastructure is not well developed. The government of Mongolia commissioned RMSI to develop a National Land Information System (NLIS) to support its overall land reform policy. The key objectives were to ensure the efficient use of land resources, development of a functional property market, provision of secure and transparent titles to property, raising land revenues, and making land related information readily available to all citizens, commercial enterprises and Government Agencies. Mongolia National Land Information System (MoNLIS) being a centralized system across the country, the centralized database at ALAGAC is now storing the entire country data. This data are being analyzed and a national level. This system automates Land Fee/ Land tax collection, land value estimation, land use and infrastructure planning and archiving all information and documents

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The objective of this paper is to explain the European contribution to SDIs in view of the goals of the Indian NSDI. It is argued that these SDI entities will become increasingly important in resource allocation strategies in the next decade. By resource allocation we mean all aspects of the built environment including both disaster management responses and efficient consumption of resources in building infrastructure. We address these matters by reviewing the following topics:

• An overview of the consensus approach used in INSPIRE
• The ESDIN project, which is building a candidate INSPIRE infrastructure
• The Network Services architecture.

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Governments are increasingly harnessing the benefits of technology to counter the looming threat of urbanization such as destruction of nature, increasing pollution, and reduction of resources to sustain the growing number of population. Rajasthan, which is known for its marvel in town planning since 1727 is the first state to implement a Decision Support System for Urban Information for multiple sectors and departments.

This project is unique in itself, and has the following key features 1) Scientific collection, organization and management of data 2) Data usage by multiple business/across various departments 3) Edit and update of data by 18 departments through a centralized database over the web, 4) Access to the system by a wide range of people starting from citizens to almost all the ministries of state government 5) Citizens direct access to a grievance management system over the web for urban assets, 6) Routing application for citizens, tourists, hospitals, and different department

This paper will discuss how this system is catering to the needs of the citizens & different departments in their daily spatial analysis along with providing the required information for preparing master development and zonal development plans, and town planning schemes.

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Due to the increasing availability of information systems and 3D data, planners and municipalities are focusing on modeling the urban space in 3D. A particular focus is given to the effectiveness of GIS and its related methods for their capacity to accommodate the demands of visual representation of urban environment as well as the basis for analysis and simulation.

In this paper the authors present a framework for 3D urban GIS and the concept of digital cities as a social information infrastructure for urban life (including shopping, business, transportation, and education). The proposed architecture for digital cities includes:

• City mapping (integrates both data archives and real-time sensory information)
• Digital City Model (DCM)
• Value added services
• Surveying
• Integration of field updates.

These 3D models deliver a true picture of the ground and enable the users to view the location of services and real places in an intuitive and user-friendly way. These models are useful for multifarious applications such as transportation management and planning, disaster management and micro telecommunication network planning.

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Geographical Information Systems provides the civil engineer today with tools for creating, managing, analyzing, and visualizing all types of geographic information. This information can be related to both the project and its broader geographic context. GIS is thus playing an increasingly important role in civil engineering projects, supporting all phases of the design cycle.

In India too, Government and non-government organizations such as municipalities, planning and architectural firms, and real-estate organizations, are increasingly realizing the power of using such technologies to make their systems more efficient.

This paper presents a practical usage of a variety of geospatial tools that can be of significance to the community working on ‘built form’.

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Seismic risk in Yemen is associated with the rifts of the Red Sea and the Gulf of Aden along the southern boundary of the Arabian plate. In general, the seismic activity in Yemen is most pronounced along the regional basement tectonics of the spreading ridges, but a low level of seismicity, characterized by small to moderate-size events, occurs within the Arabian plate. The seismic hazard model is created by modeling seismicity and ground motion using standard published and modified weighted attenuation equations to calculate peak ground acceleration at 10% and 50% probability of exceedance in 50 years under local soil site conditions. This study will be used in preparing the countrywide seismic risk profile and financial response capacity for Yemen, under the initiative of the World Bank.

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Spatially explicit hydrodynamic flood models can play an important role in natural hazard risk reduction. A key element of these models that make them suitable for risk reduction is the ability to provide inundation information of a hazard event. Such information can be critical for land use planning, for mapping evacuation routes, and for locating suitable emergency.

A flood risk model was developed for Lower Shire basin of Malawi for damage assessment due to floods. In this study, flow frequencies were developed using regional flow frequency analysis based on L-moments. Daily flow discharges for 13 stations over the period 1949-50 to 2005-06 were used for frequency analysis. Regional probability distributions were identified by means of L-moment ratio diagram. Extreme Value type 1 Distribution has been identified as suitable distribution for the region. Regional homogeneity was tested by the Hosking-Wallis (1993) criteria. Suitability of the distributions was tested by means of the Chi-Square test and the Kolmogorov-Smirnov test.

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Geographical Information Systems (GIS) have evolved from paper maps to high end softwares that are capable of delivering desired datasets. To use this technology to the best of its capabilities with higher efficiency is however the real challenge. This effort aims in deploying a customized tool for Geographical Information System (GIS) editing and analysis, when integrated into a work-flow management system, which will greatly benefit large scale development projects.

Integrated watershed derivation application plays a significant role in achieving high efficiency on watershed derivation and editing process. Visual Studio .NET based on ArcObject technology developed by Environmental Systems Research Institute (ESRI) was used to develop an interface within ArcGIS for Watershed derivation application. Watershed derivation application allows the user to derive the watershed and river with the desired range of user specified watershed area using the Flow Accumulation and Flow Direction input raster grids. The process uses Stream linking through given accumulation threshold, stream to feature and watershed hydrological functions to derive the Watershed and rivers. The use of powerful robust functionality of ArcObjects in customizing the Watershed derivation application greatly reduces the time and iterative process that is handled while deriving watershed and rivers manually through the functions available in ArcGIS.

For the full paper, write in to us at info@rmsi.com

Hurricanes normally result in tree fall hazard. In fact tree fall hazard is one of the major concerns for building owners because sometimes the damage from tree fall outscores that of the wind. To assess the risk from tree fall, it is important to get the information on the tree coverage within the residential areas and mapping this kind of data from the conventional methods is an expensive exercise.

Through a project case study, this paper highlights an innovative yet cost effective solution to assess the loss to a given property occurring as a result of tree fall.

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Poor people in developing countries are particularly vulnerable to disasters mainly because of where they live. Published research shows that they are more likely to occupy dangerous locations, such as flood plains, river banks, steep slopes, reclaimed land, and highly populated settlements of badly constructed shanty homes.

The earthquake that devastated Bam in Iran in December of 2003 killed more than 40,000 people primarily because their housing was not designed to handle a major tremor. The availability of a probabilistic risk assessment tool may have better prepared the government to handle the situation.

The paper describes how the use of geospatial technologies coupled with accurate data and probabilistic risk assessment can help local authorities and international agencies better prepare for coping with natural disasters in general and earthquakes in particular.

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LiDAR is a relatively new technology that can be used to accurately geo-reference terrain features. Higher accuracy, less time for data collection and processing, least human intervention, and weather and light independence are some of the key advantages offered by this technology, over other conventional methods of topographic data collection.

LiDAR technology provides very high resolution data through which important parameters for flood dynamics and flood propagation such as dykes, constructed river banks, and roads can easily be identified.

This paper highlights the use of LiDAR technology to extract high resolution DEMs and its associated benefits.

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Automated extraction of hydrological features from DTM is gaining significant importance because of the availability of high resolution data. The derived hydrological features are not only spatially accurate, but they also significantly enhance the overall quality of modeling projects such as water resource management and flood risk modeling.

However, processing high resolution DTMs also has some serious issues such as handling artifacts and depressions, and these issues compound as the resolution of DTM increases. Furthermore, processing high resolution DTM is extremely time consuming particularly when dealing with artifacts (man-made constructions across the rivers) and depressions.

Natural depressions like pot-holes and sinks-holes play an important role, especially in the derivation of hydrological features like river network and watersheds. Moreover, the presence of artifacts also creates secondary sinks.

This paper demonstrates the best possible ways of handling artifacts and depressions while deriving hydrological features from high resolution DTMs.

For the full paper, write in to us at info@rmsi.com