Characterizing territory according to its relief using ArcGIS Desktop?

I want to characterize the territory according to its relief with ArcGis 10. I'm trying to define a wide territory by its relief, but I would like to do it in an automatic or semiautomatic form with the GIS.

I read on some webs that I can do it with the topographic position index, but I don't know how. Can somebody explain or give some references to learn how I can do this analysis?

Bioclimatic zonation and potential distribution of Spodoptera frugiperda (Lepidoptera: Noctuidae) in South Kivu Province, DR Congo

The fall Armyworm (FAW) Spodoptera frugiperda (JE Smith), is currently a devastating pest throughout the world due to its dispersal capacity and voracious feeding behaviour on several crops. A MaxEnt species distributions model (SDM) was developed based on collected FAW occurrence and environmental data’s. Bioclimatic zones were identified and the potential distribution of FAW in South Kivu, eastern DR Congo, was predicted.


Mean annual temperature (bio1), annual rainfall (bio12), temperature seasonality (bio4) and longest dry season duration (llds) mainly affected the FAW potential distribution. The average area under the curve value of the model was 0.827 demonstrating the model efficient accuracy. According to Jackknife test of variable importance, the annual rainfall was found to correspond to the highest gain when used in isolation. FAWs’ suitable areas where this pest is likely to be present in South Kivu province are divided into two corridors. The Eastern corridor covering the Eastern areas of Kalehe, Kabare, Walungu, Uvira and Fizi territories and the Western corridor covering the Western areas of Kalehe, Kabare, Walungu and Mwenga.


This research provides important information on the distribution of FAW and bioclimatic zones in South Kivu. Given the rapid spread of the insect and the climatic variability observed in the region that favor its development and dispersal, it would be planned in the future to develop a monitoring system and effective management strategies to limit it spread and crop damage.

Environmental fragility and land use capacity as instruments of environmental planning, Caratinga River basin, Brazil

The reconciliation between the environment and development of agricultural activities constitutes a serious challenge for the management of natural resources, considering that the inappropriate use of the land can trigger significant damages along the watersheds. Thus, this work aims to analyze the environmental fragility and the land use capacity as instruments of subsidy to the environmental planning of the Caratinga River basin, Brazil. The assessment of potential fragility was performed by multicriteria analysis of soil fragility factors, geology, relief dissection, and rainfall. To determine the real susceptibility to environmental degradation, land use and land cover variables were included in the analysis. The land was classified in the system of use capacity, verifying the existing conflicts with the current land use. Bivariate Moran's I index was used to evaluate spatial autocorrelation between the analysis. The results showed that the Caratinga River basin presents medium to high potential fragility, with over half of the area in the high environmental fragility class. Compared to the analysis of environmental fragility, the land classification methodology showed spatial autocorrelation significant and determined a similar area of the basin used above its capacity, making it possible to indicate pastures and areas of exposed soil as priorities for the application of restoration policies. Thus, it is concluded that the reconciliation of the two methodologies, including the analysis of environmental degradation factors together with the understanding of the maximum capacity for agricultural use, constitutes a fundamental action to subsidize the adequate planning of land use in watersheds.

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The exponential rise in the urban population of the developing countries in the past few decades and the resulting accelerated urbanization phenomenon has brought to the fore the necessity to develop environmentally sustainable and efficient waste management systems. Sanitary landfill constitutes one of the primary methods of municipal solid waste disposal. Optimized siting decisions have gained considerable importance in order to ensure minimum damage to the various environmental sub-components as well as reduce the stigma associated with the residents living in its vicinity, thereby enhancing the overall sustainability associated with the life cycle of a landfill.

This paper addresses the siting of a new landfill using a multi-criteria decision analysis (MCDA) and overlay analysis using a geographic information system (GIS). The proposed system can accommodate new information on the landfill site selection by updating its knowledge base. Several factors are considered in the siting process including geology, water supply resources, land use, sensitive sites, air quality and groundwater quality. Weightings were assigned to each criterion depending upon their relative importance and ratings in accordance with the relative magnitude of impact. The results from testing the system using different sites show the effectiveness of the system in the selection process.

Urban emergency management

This part covers a critical review on the use of spatial analysis in some urban emergency management situations. It provides an inside and out scope of the work cited in this regard to in such manner that it highlights the process of enhanced decision-making process. The extent of the scope will concentrate on the most important progressions in the utilization of spatial analysis methods for emergency management in urban situations.

Spatial analysis applications in natural hazards

Earthquakes and humanitarian coordination

The literature on GIS and humanitarian coordination has started by first looking at the different approaches in which GIS can be utilized for effective coordination. Regardless of the way that GIS has been predominately seen, within the disaster management community, as a cartographic tool, an approach to managing initial analysis and visualization, or an electronic navigational system, this does not attractively depict the best way of GIS utilization in humanitarian assistance (Currion 2006). There are numerous potential utilizations of GIS for humanitarian aid. For instance, the usage of enhancement, which is the use of cutting edge GIS calculations to take care of an outline issue, can be utilized to discover reasonable areas for clearing. For example, a support investigation, for analysis of spatial relationships using GIS as a tool, can be employed to gauge vulnerability to various hazards based on proximity.

In 2005, a Complex Humanitarian Emergencies Study by Verjee (2005) drew from contextual analyses and examples in innovative progression to format the potential GIS applications for humanitarian emergencies, which were:

Mapping and Cartography (Land use Mapping, Infrastructure Mapping, Demographic Mapping, Logistics, and Sustainability).

Outreach, Media and Communications (Public Access to Information, Reporting, Program Assessment, News Coverage).

Modeling and Simulation for Disaster Scenarios (Practice, drills, and exercises, Data information flow, planning for contingencies).

Environmental Management and Planning (Planning, Yield Cultivation, resources assessment).

Risk and Hazard Management (seismic analysis, site selection and planning, and water level estimation and mitigation).

Vulnerability Analysis and Assessment (Early Warning frameworks for the dry season, desertification and starvation, Epidemics modeling and Tsunami Planning).

Risk Reduction (‘problem areas’ distinguishing proof and relief programming).

Response Policies and Organizational Management (administration, planning, and training).

Table 1 is demonstrating the capabilities of GIS in this situation. In spite of the fact that there are various applications of spatial analysis as a GIS technique, they all share an ultimate target, which is to which is to exploit the situational the situational awareness to all areas taking an interest so fundamental concerns can be perceived and after that together achieved.

A late analysis by Eveleigh et al. (2007) and Al-Ahmadi et al. (2014) has utilized spatial analysis for earthquake disaster studies. The adopted approach recognizes that within the scope of humanitarian assistance “GIS innovation is battling with how to address complex issues that require the modeling of rapidly changing dynamic phenomena, feature, behavior, data and. They concluded that there is a high potential for GIS-based assessment models to give the leap forward expected to address the random way of humanitarian emergencies.

Bally et al. (2005) presented the use of remote sensing for Humanitarian Aid, showing that the utilization of remote detecting and GIS permitted 200,000 IDPS to be migrated to longer-term settlements that had a renewable water source and with improvement potential in regards to sanitation, farming, and even hydropower. Another powerful GIS application used to support humanitarian emergencies was The Global Connection Project, which included Carnegie Mellon University, NASA, Google and National Geographic, contributing to the relief planning for October 8, 2005, South Asian earthquake and tsunami. In this project, GIS was utilized to gain and convey high-resolution imagery from Digital Globe’s Quickbird.

Wild fire

ESRI (1999) has shown an approach to depicting a rapidly spreading fire event precisely spatial analysis can be utilized to recognize high-risk fire zones and set up buffer zones for evacuation. Notwithstanding the determination of high-risk regions, spatial analysis can be combined with statistical analysis as a verification method for the specifying areas of final damage assessment, in addition to deciding to provide visual models for highly impacted areas, according to Goodchild (2006). Lentile et al. (2006) gave direction by distinguishing potential layers that can be utilized for urban fire identification. The initial step was to employ scope and longitude directions to plot the different flames (based upon a decision of lightning or human-ignited fire) during a particular period. Fire information may seem, by all accounts, to be situated inside waterways. However, this is mainly a reason for adjusting buffer zones to give some slack to such errors. The process of connecting attributes information and present four analytical techniques for simulation and visualization out of control fire. In spite of the fact that their emphasis particularly on human-brought ablaze catastrophes, in proposing the four prescribed alternatives for finish urban fire examination:

The urban fire hazard is hard to avert. Notwithstanding, through the recognizable specification of the high-risk zones, the recurrence of flame can be minimized. Jaiswal et al. (2002) have demonstrated that GIS when joined with satellite imagery, can be useful in identifying high-hazard regions within given vicinity and restrict the fire spread and thus minimize the impact. Jaiswal et al. (2002) have also examined the utilization of ArcGIS for this idea, declaring that the mix of topographic foundation data and remote sensing for vegetation mapping can make a precise estimation of high-risk fire territories utilized for moderation and reaction purposes. In Jaiswal et al. (2002) different layers of vegetation, slope, proximity to settlements, and distance from roads were made to provide an indication about high-risk fire regions. After this data was plotted, buffer zones of 1000, 2000, 3000, and 4000 m surrounding the high-risk zones were plotted to extend the distinctive levels of danger. Although they have investigated a particular instance of India, the concept of using GIS spatial analysis consolidated with satellite imagery for distinguishing areas prone to high-risk of fire hazard has demonstrated the adequacy of GIS as a tool for urban disaster management. If GIS can be utilized to model and simulate high-risk fire zones with buffers, which gives benchmark understanding that GIS could likewise be used to show damage assessment models using different software and different data layers, regardless of the geographic location.

Pradhan et al. (2007) utilized GIS examination to decide fire susceptibility, using a “vector spatial database” with GIS and consolidated with topographic information, fuel information, base overview focuses, and maps. This took into account figuring variables, which were then changed over to a raster grid, recognizing 112 cells inside the fire events. A frequency-based proportion approach was used to characterize the “connections between hotspot areas and the components in the study area”. The challenges, notwithstanding, were in processing “a significant amount of data”. The conclusion is drawn from Pradhan et al. (2007) on the utilization of such projections for fire risk mapping and mitigation was quite compelling. In foreseeing fire susceptibility when utilizing frequency analysis, the prescribed results were recommended to be used with alert, according to Pradhan et al. (2007). It was suggested that the analysis approaches their examination is used fundamentally amid fire event, which proposes mapping fire-influenced zones instead of driving toward the relief bit of fire disaster management process.


Correia et al. (1998) demonstrated that GIS had been seen as a successful tool to organize and visualize data from different sources on far-reaching floodplain administration. As a part of this overall approach to manage floodplain management, it is crucial to have the ability to predict the aftereffects of different situations as to flooded regions and related regions at risk. Morrow (1999) discussed the hydrologic and water controlled zones accept a crucial part, and there is much to get in uniting these exhibiting capacities in a GIS system. The perspective of the using Intergraph GIS with IDRISI GIS provided an effective way in dealing with flood emergencies in both 2D and 3D. Using multidimensional modeling usually extended the flexibility of using GIS as an instrument for flood modeling. Gogoaşe Nistoran et al. (2016) have shown the effectiveness of spatial analysis using GIS for modeling flood inundation as a result of dam-break.

The role of GIS in Flood Disaster Management was analyzed by Cova (1999), through the perspective of Comprehensive Emergency Management (CEM) and its four phases: mitigation, preparedness, response and recovery. In the wake of a disaster, GIS is getting the chance to be vital in supporting damage assessment, evaluation, and cost estimation for development. In the aftermath of a catastrophe, GIS is a valuable tool in supporting cost evaluation and rebuilding. Abbas et al. (2009) proposed a GIS-based contemplate regarding the change of surge showing and representation for Allahabad Sadar Sub-District (India). This joins the framework, the methodology/approach that planned to research the degree for spatial analysis application for a rapid response. The flood affected zones have been recognized, and their positions are checked, where the GIS handiness has been manhandled to get the spatial information for the fruitful calamity organization for surge affected reaches. The adopted approach has helped in recognizing issues that may upgrade the present practices of emergency management organizations. The approach gives a suitable and quick fundamental authority instrument for snappy response to emergencies if used appropriately, which along these lines would help in minimizing loss of life and property. Al-Sabhan et al. (2003) proposed a GIS-construct study, in light of the change of flood levels and representation. This consolidates the arrangement, the investigated the present status of progressing hydrological models used for flood modeling and risk mitigation. It indicated how electronic systems could overcome a bit of the obstruction of existing structures. While hydrological GIS-based models are open, they are ineffectually suited to the consistent application and are frequently not primarily consolidated with spatial datasets.

Buchele et al. (2006) and Chen et al. (2009) discussed a modern approach for integrated flood risk assessment. In light of the setting of a more relative examination of different flood risk assessment models, for mapping, in the midst of extreme situations. The ampleness of synchronous and in-house proprietary methods using was analyzed by Chen and Zhan (2008). The study used an operator-based technique to model movement streams at the level of individual vehicles and examines the total practices of modeling and visualization of moving objects, during an emergency. De Silva (2000) presented a model Spatial Decision Support System (SDSS) which was normal for credibility making blueprints for emergency mapping, where response operations using spatial information dealing with and representation points of confinement in a GIS. It interfaces together with the geospatial part of the spatial analysis section is given by the GIS. The SDSS, so that gives a detailed spatial information of flood zone extension and involved layers.

Moreri et al. (2008) proposed an approach to manage making an internet-based Geographic Information Systems (WebGIS) application, which would reinforce people living in flood zones, which may at one point be unprotected in light of their closeness to the stream and the adequacy of the flooding. Zerger and Wealands (2004) showed that spatially quick hydrodynamic flood models could expect an essential part in average danger peril reducing. A key element of these models that make them suitable for risk exhibiting is the capacity to give time-blueprint immersion data about the onset, length, and embarking to an emergency situation. Such data can be the start for region utilize orchestrating, for mapping, for clearing directing, and for finding sensible crisis organization to give a couple of representations hazard responses. To address these confinements, a structure has been made that interfaces, with emergency response team with a GIS-based decision support system.

Dust storms

Dust Storms are otherwise called Sand Storms it represents one of the common hazards with a broad range of environmental impacts. During an event of a stand storm, it affects human health in various ways. Sandstorms are a critical reason for car crashes and cause air transportation delays. Goudie (2008a, b) discussed the products during the process of stand storm eruption. It presents fine particles, salts and chemicals (counting herbicides) into the environment, with a suite of health effects, including respiratory complaints as well as different serious illnesses. Dust storms can transport allergens including microscopic organisms and growths, in this manner affect human health. Spatial Analysis can be exceptionally successful in displaying and representation the degree and the effect of sandstorms. Specifically, we can utilize GIS to give the accompanying capacities in managing dust storms disaster management.

The recent developments in global warming and climate change have prompted increased activity of sand storms in various parts of the word. Numerous researchers including Goudie (2008a, b Xu et al. 2006) have dealt with the examination of sandstorms events and its impact on the land surface, utilizing GIS and Remote Sensing. Goudie (2009), discussed the first methodology relies upon the investigation of weather station information and representation of the spread of particulate matter in particular space in association with Dry Mid Temperature and Sub-Dry Temperature, particularly in the desert or semi-desert or zones. Measurable investigates exhibit that the event of sand–dust storms relate to a high degree of wind speed, which thus is firmly identified with land surface components then again, a significant relationship between rain event and other atmospheric elements, for example, precipitation and temperature were not watched. This is notwithstanding the part of vegetation cover, which has been unequivocally connected to dust storms.

Health hazards

According to Cioccio and Michael (2007) Emergency management of health impacts, specifically focus on the vulnerable population and access to medical services GIS technology is capable in extreme heat attacks, by providing the degree and application for spatially analyzing the distribution of services and its relation to the population at risk. Despite all that, the literature that covers the use of GIS for health impact is somewhat limited. Many requests for the use of GIS in health focuses on the methodology, and the practical applications to the domains of vulnerable population, health care facilities distribution, and emergency shelters distribution. These three themes could be linked to the census and traffic information to provide more detailed spatial models, when dealing with this hazard.

Sharma et al. (2008) pointed out that one of the key utilizations of GIS in pandemic modeling and simulation is to encourage access to health services by inhabitants who live in and around the security area of a mass gathering or a social event. This will be achieved by outlining an application GIS to help health authorities in the planning and implementation of emergency medical response, with an emphasis on improving support of vulnerable population, including:

Ensuring continuous routine for health services amid times of restricted access to a security area

Ensuring evacuation procedures for medical emergencies that are non-event related

Providing timely evacuation and health care in the event of mass causality incident.

This can be accomplished by outlining a mapping tool to locate vulnerable community members inside the affected zone, if there should arise an occurrence of a pending natural or technological disaster, for example, a heat wave or power outage. Becerra-Fernandez et al. (2008), explained that GIS could be used to for specifying access and evacuation routes, for approaching or in progress emergency or disaster management events. Goals may incorporate shelters, schools or other predefined destinations outside of the security zone Chandana et al. (2007). The key support of GIS in a pandemic episode can be through the utilization of GIS intending to general public health issues, particularly, to characterize its uses and restrictions in managing the inquiries of describing the vulnerable population. GIS supports advanced intervention operations, for example, Roland Daley et al. (2015) have highlighted some of these issues as following:

Choosing sites for community flu centers and vaccination stations.

Monitoring and assessing effect of vaccination centers and stations.

Canceling public events, and gatherings.

Closing schools, meetings and gatherings.

Restricting utilization of public transportation frameworks.

Identifying potential groups quarantine and isolation facilities.

Enforcing people to follow group or individual isolates.

Spatial analysis applications in technological hazards

Infrastructure disruption and malfunction

Cova and Church (1997) and Cimellaro (2016) discussed an approach for purposely recognizing neighborhoods that may go up against transportation challenges during an emergency evacuation. A description of this nature offers an interesting approach to manage assessing group of defenselessness in regions subject to advanced dynamic risks of uncertain spatial impact (e.g., hazardous spills on roadways). A heuristic estimation is delineated which can be usable for conveying useful, the excellent answer for this model in a GIS setting, as it was associated with a study region.

Camps (1993) presented a new computerized risk management framework for use by less experienced risk management personnel who to reduce the likelihood and seriousness of accidents. The framework, which was developed, is suitable for use in oil, gas, or chemical processing sites. It joins scientific models and calculation tools for accident simulation and building a database that incorporates accidents scenarios and response plans. It can likewise be utilized as a part of an emergency situation to decide favored approaches to find external assistance.

Spatial analysis applications in manmade hazards

Mass gathering and civil unrest

Numerous sorts of mass gathering and the concentration of population change participating in such events may vary, depends on the nature of the event, its location and the time and season of the event. For instance, civil demonstrations, outdoor rock concerts, and a football match are typical examples where there is clear variation in the density of population attending these events. According to McDonald (2008), these occasions regularly, don’t draw in one sort of participants. Therefore, risks might be connected with weather related sickness, harmful impacts of medications, or injury because of members attempting to draw near to the stage. Bradler et al. (2008), concluded that political events, for example, political parties conventions might have several risks, associated with. This incorporate trauma or toxic impacts of depression related to a political protest or terrorism-related incidents. Becerra-Fernandez et al. (2008) have indicated that GIS spatial analysis is valid in this applications, as it provides:

Specifying the dissemination of individuals around the event proximity.

Analyzing the scope and approach for mapping evacuation if there should be an occurrence of an emergency.

Determining the positions and movement of law enforcement in the field.

Analyzing the pattern of development of masses.

Supporting effective decision-making on evacuation and response to an emergency situation.


Kwan and Lee (2005) have shown that the terrorist attacks on the World Trade Center (WTC) in New York City and the Pentagon on September 11, 2001, has not quite recently impacted multi-level structures in an urban center. They have also influenced by their surroundings at the street level in ways that reduced the time limits for the speed of emergency response. The capacity of using progressing 3D GIS for the headway and execution of GIS-based intelligent emergency response systems. The fact was at urging a quick emergency response to terrorist attacks on multi-level structures (e.g., multi-story office structures). A system design and a framework data show that facilitates the ground transportation capabilities with the inside courses inside multi-level structures into a protected 3D GIS was examined. Issues of using adaptable representation stages were also discussed especially the prerequisite for the remote and versatile response plan. Critical decision support functionalities were moreover considered with particular reference to the utilization of framework based most restricted way computations. A test use of expected 3D structure data shows a GIS database for a nearby study area was demonstrated by Kwan and Lee (2005). The study indicates that reaction delay inside multi-level structures can be any longer than deferrals caused on the ground transportation framework, have the potential for impressively decreasing these postponements.

Johnson (2003) demonstrated that in times of crisis, the disaster managers have the necessary commitment in regards to quickly and adequately managing any situation that may happen. An adjusted GIS application was delivered engaging a brief based examination of a catastrophe occasion facilitated with the centralization of masses distinguished correctly to the room level. The GIS Emergency Management System (GEMS) application is an astute structure to be utilized as a part of the Emergency Operation Center (EOC) to help the heading of the response. On the off chance that a calamity needs to happen, the intervention and recovery attempts could be at initially focused on the most fundamental areas of the greatest convergence of people.

GIS Centre of PSNRU

Geographic Information Systems and Technology Center of Perm State National Research University (GIS Centre of PSNRU) was established in September 2000, on the scientific-research basis of Perm State University at the decision of the Coordination Council for the development of geographic information systems of public authorities (GIS PA) of Perm region. The creation of a network of GIS centers took place according to the Concept of GIS PA of Perm region for 1999-2001, approved by the governor of the region from 22.03.99 № 93, and GIS PA Program of Perm region for 2000-2001., approved by the governor of the region from31.12.1999 № 223.

From September 2000 to October 2005 the scientific adviser of the cetre was the first vice-rector of the University, doctor of technical sciences Vladimir M. Suslonov. Since February 2006 and by the present the scientific adviser isthe first vice-rector of PSNRU, PhD, associate professor Valery A. Sherstnev.
Sergey V. Pyankov, the candidate of technical science, associate professor, has been the head of the GIS center.

The GIS centre started to realize its scientific and practical activity in September, 2002, after the list of staff members and first contracts to perform research work appeared. The centre was licensed on October 15, 2002 by Roskardography RF № URG-00596 for the following activities:

  • creation and maintenance of geo-information systems for special purposes
  • making, updating, preparation for publication, edition, copy in graphic, digital (electronic) and other types of thematic maps, plans and atlases for special purposes
  • making, updating, preparation for publication, edition, copy in graphic, digital (electronic) and other types of calendars, guides and other promotional and informational publications on the cartographic basis or with its use
  • performance of research and experimental-design projects in the field of GIS technology.

Since that time the GIS Centre began its activity on the territory of Perm region. Environmental Protection Department of Perm region became the main customer of projects. Three works should be noted among the first research projects which later were developed and became the GIS Centre general response:

  • “Perm region zoning according to the ecological risks of natural and natural-technogenic emergency cases: territory zoning the creation of a data bank for the geographic information system of public authorities (GIS PA) “
  • “The creation of a digital model of the Kamskoye and Votkinskoye reservoirs relief bottom to conduct the monitoring subsystem of water biological resources within ecological monitoring framework.”
  • “The structuring and creation of thematic layers of the environmental section of GIS PAof Perm region: quarterly net,Goslesfond and Mezhhozles forestry borders”

The list of customers and activities has recently extended greatly. Currently the main customers are federal, regional, municipal and large business structures:

  • Central administrative board for Civil Defense and Emergencies of Perm Krai
  • FSU “The Kama Basin Water Management”
  • FGU “Kama-Ural basin management for protection and reproduction of fish inventory and the production regulation”
  • Natural Resources, Forestry and Ecology Ministry of Perm Krai
  • Security Ministry of Perm Krai
  • Agriculture and Food Ministry of Perm Krai
  • Management on Environmental Protection of Perm Krai Administration
  • Municipalities of Solikamsk, Berezniki, Krasnovishersk,Tchusovoy and many others.
  • Lt. “Lukoil-Permneft”
  • Lt. “Perm Motorostroitelnuy Zavod”
  • JSC “Institute of Information Systems”
  • PC “Solikamskbumprom”
  • PC “Mineral fertilizers”.

The worked out branches of activity “GIS and natural resources”, “GIS and Safety”, “GIS and Ecology” are confirmed byprofound research projects conducted by the GIS center according to the government order: “Scientific and technical substantiation and development of the program” Prevention of waters detrimental effects and hydrolic engineering construction safety in Perm Krai “(2006) (the regional target program was approved by the Perm krai legislative assembly in January 2007) “Creation of the space monitoring system for forest resources of Perm Krai” (2006-2007) “Creation and maintenance of the ” Forest resources database of Perm Krai ” GIS(2005-2007 )”Creation of the geoinfomation system called ” Forest Resources of PC “Solikamskbumprom” (2008-2009)”Elaboration of the insurance fund of Perm Krai documentation” (2006 – 2007) “Information support of state authorities, local government during the decision-making on public safety, prevention and elimination of natural, technogenic and bio-social emergency situations in Perm Krai municipalities ” (2007 – 2009)“Perm region zoning according to the ecological risks of natural and natural-technogenic emergency cases: territory zoning the creation of a data bank for the geographic information system of public authorities (GIS PA)” (2002-2004), Befor and after flood inspection of Perm Krai Territory (2007 – 2009).

It’s important to mention that a new branch of activity “GIS and agriculture” appeared in 2005. It has been developed in the ongoing project “Creationof space monitoring system based on the earth remote sensing data for the rational use of agricultural lands” (2005-2008).

The agreement to establish municipal geographic information system (MGIS) of Krasnovishersk was set up in 2003, the MGIS Conception of Berezniki was elaborated in 2005 and the tender for the establishment of municipal geographic information system (MGIS) of Solikamsk municipalitywas won in in 2007. Thus, there is another branch of development – the use of geographic information solutions for municipalities management where GIS is an integrating link for users on any possible space, scale or profile levels.

The resources development of the GIS centre of PSNRU in 2013 is as10 times high as in 2002 г.

Nowadays we have creative, professional and contractual relations with reliable partners. Among them are:

  • GIS Association of the Russian Federation (Moscow)
  • Data + (Moscow)
  • ITC “Scanex” (Moscow)
  • Institute of Water Environmental Problems (Barnaul)
  • Territorial Fund of Information on Natural Resources and Environment Ministry of Russia for Perm region (Perm) and many others.

Since the establishment and the choice of the development priorities we realized the need to create our own training department. In this regard, the Training Center onESRI software (Environmental Systems Research Institute, USA)- the first centre in the Western Urals- was certificated on November 3, 2003. S.V.Pyankov (“Introduction to ArcView», «Advanced Course of ArcView»), Y.N. Shavnina (“Introduction to ArcView», «Advanced Course of ArcView 3”) and A.V. Nekrasov (“Introduction to ArcGIS», Part 1, 2) became the first certified professors. Since that time, we have an opportunity not only to educate and increase the education level of customers in the use of GIS technology, but also the opportunity for our autonomous learning.More than 150 certificates of various courses have beencurrently issued, including the Perm State Universitystaff. Since February 2005 the ESRI Training Center has been a part of the Regional Institute for Continuing Education of Perm State National Research University.

Since 2014 the students are read the most modern courses: “ArcGIS Desktop I: Getting Started with GIS (Part 1)”, “ArcGIS Desktop II: Tools and Functionality (Part 2)”, “ArcGIS Desktop III: GIS Work processes and Analysis ( Part 3). ” Classes are carried on by a certified instructor, Ph.D. Cherepanova E.S.

Our own computer lab on ESRI software training and the use of modern GIS technologies in the substantiation and management decisions making was openedin December 2007 .

The staff of the GIS Center of PSU regularly participates in regional, federal and international conferences. Among them are GIS forums ofthe Russian Federation (Moscow, 1998 – 2010), GeoSibir (Novosibirsk, 2004-2014), Sustainable Development of Territories: GIS theory and practical experience (St. Petersburg, Russia – Helsinki, Finland (2001), Vladivostok, Russian Federation – Changchun (2005), China Khanty-Mansiysk – Yellowknife, Canada (2007), Rostov-na-Donu (2010), Belokuriha (2011), Belgrade (2014) and many others.

I Interregional Scientific and Practical Conference “Software of the spatial development of Perm region” was organized and held by the GIS center of PSU in autumn 2008.The aim of the conference was to develop a regional mechanism for the creation and development of spatial data infrastructure of Perm krai for the benefit of state and local authorities in their management decisions making. At the conference it was decided to make it traditional and annual. The series of the conferences have been held for over 5 years.

The Jubilee International Conference InterCarto-InterGIS – 15 “Perm” – “Gent” was held on the basis of the GIS center of PSU in summer 2009. More than 160 participants from Barnaul, Volgograd, Yekaterinburg, Izhevsk, Moscow, Nizhnevartovsk, Nizhny Novgorod, Novosibirsk, Perm, Petropavlovsk-Kamchatsky, Saransk, Tyumen, Khabarovsk and other Russian cities, as well as from Belgium, the UK, Germany, China, Netherlands, the Czech Republic, Estonia, South Korea took part in the conference. They represented organizations that specialize in the field of spatial planning, geoscience, geoinformatics, cartography, geology, mining and oil and gas transportation, higher education. By the beginning of the conference three volumes of its materials had been published, including more than 100 publications.

More than 200 articles, preceding papers and abstracts have been published by the GIS Center staff, 21 of them are included in the list of HAC. The main topics of publications are the creation and use of modern geoinformation methods in spatial tasks decisions.

Much work is done to improve the skills of the GIS center employees. Each of them takes at least 2 courses of ArcView 3.2a, ArcGIS 10.2 training. Besides key specialists are educated in organizations and companies that arethe leaders in the field of geoinformatics in the territory of the Russian Federation:

  • Certificate of participation in the International School of Young Scientists “Computational-informational technologies for environmental sciences: CITES-2007”, 14-25 July 2007 – Y.N. Shavnina (Tomsk State University)
  • Certificate of the course “Basics of ArcGIS Spatial Analyst», October 10, 2007 – Y.N. Shavnina (Moscow, Date +)
  • Certificate of the course “Introduction to ScanMagic», January 2011 – E.S. Cherepanova, A.N. Shikhov (Moscow, Scanex)
  • Certificate of the course “ArcGIS Desktop I, II, III”, April 2014 (Moscow, Date +)
  • Certificate of the course ” Geodatabase Construction”, 2014 – E.S. Cherepanova (Moscow Date +)

Hardware, software, information and technological equipment is purchesed, created and developed. Currently we have the most modern stock of computers and peripheral devices (including plotter, large format scanner, GPS-navigation).

The GIS center consistently, since its establishment, purcheses and develops software tools. We have a certified software of leading foreign and Russian companies-developers in geographic information systems and technologies: ArcView 3.2a (extensions Spatial Analyst 3D Analyst NetWork Analyst) («University set”) ArcGIS 9.2 (extensions Spatial Analyst GeoStatistical Analyst 3D Analyst NetWork Analyst) («University set”) ArcGIS 9.2 (extensions Spatial Analyst) (floating license) ArcEditor (floating license) EDN (floating license) (all software is the software product list of ESRI). ERDAS IMAGINE Professional (extensions: Vector Virtual GIS, OrthoBase, Radar Mapping System, MapSheets) (software products list of ERDAS) («University set”), as well as ScanMagic (Scanex) are licensed software products for data processing of remote sensing (satellite imagery) .

The first regional geoportal for the territory of Perm Krai has been created. We take actions to implement a single geodatabase as the topographic foundation for applied problems solutions at the regional level (modeling of snowmelt, the high waters and floods formation, droughts and flooding prediction and other natural and anthropogenic processes). Weprepare materials for the certification according to FSC standard.

To realize a number of projects in 2006 we purchasedsatellite images of the Perm Krai territory with a resolution of 6 m (2005-2007, IRS LISS), that allowed to identify spatial objects with generalization M 1:50000. In its turn, it extended a broad group of monitoring tasks associated with spatial modeling of changes in vegetation cover, rivers and reservoirs banks processing, illegal anthropogenic impact on the environment. Currently, the entire territory of Perm Krai is covered withimages with a resolution of 2.5 m (M 1:25000) with 1 mdetailed insets.

In 2009 PC “Scientific and Production Corporation” REKOD “and the State Educational Institution of Higher Professional Education” Perm State University “signed the agreement on cooperation in the field of space activity results use (RSA).

One of the main cooperation ares is the joint creation and development of “Space Services Center” on the basis of PSNRU. This decision has led to the creation of the innovationcompany Lt “MICspace technologies and services Center.”

In 2009,the scientific and educational center SEC “Mathematics and cartographic modeling of geosystems and complexes” was established on the basis of the GIS centre. The main goal of SEC is to develop a new scientific and educational structure, aimed at the development of basic research in mathematics and earth sciences, as well as the formation of new training schemes and the organization of education advanced scientific research and high technology.

In 2010, Perm State University received the status of National Research University (NRU) with the program “Efficient environmental management: forecasting technologies and management of natural and socio-economic systems.” Thus, a unique concentration of personnel, ideas, technology and finance appeared, which allowed for the first time in 9 years to conduct the first government funding of applied science and education activity of GIS center of PSNRU.

On February 14, 2011 Interregional Center of Space Monitoring (ICSM)of Perm region was established on the basis of the GIS center of Perm State National Research University. The centreincluded two satellite receiving stations: “Alisa – CK” and “UniScan – 24.” The first station now allows to receive data from two types of satellites: NOAA (POES), MetOp, and the second one- from Modis (Terra / qua), Spot-4-5, and EROS A / B. Thus optical survey has completely covered a number of large-scale remote sensing data as well as a wide range of current thematic tasks.

Currently the received satellite monitoring system is widely used in the investigation of natural-territorial complexes of different hierachical level and territorial coverage. The main advantage of ICSM is information efficiency that can not be obtained when ordering data through INTERNET. Furthermore, it should be noted that the remote sensing methods are significantly more economical ways in comparicon with the traditional spatial data gathering.

TheCenter of Space Monitoring is installed on an “open architecture” principle, that allows,if necessary, to add blocks and modules. The centre configuration on the reciving principles can vary, thatallows to develop the ICSM in time, extending the range of tasks solved by it. The dynamics and the direction of the development is determined by, first, the acute needs of practical problems in the region, secondly, by the existing technical opportunities, and thirdly, by the considerations of economic expediency.

Comprehencive processing of space information and ground-based measurements results is the basis for the target data organisation necessary for decoding and case studies held for the objective information about the current state of the region. The results of processing are integrated into the thematic GIS to conduct a comprehensive analysis and information about the dynamics of positive and negative territorial and object processes. Such information makes it possible to make deliberate decisions that greatly improve the efficiency of regional and local governments in various functioning areas of the entities.

In September 2011, the first base reference station in Perm was put into test operation. It was based on the specialized GNSS-receiver AshTech ProFlex500 (France). This is the first step in the creation and development of a network of base stations in Perm region.

Functioning network of such stations in future will allow tomake engineering and survey works, the imposition of points in nature and field inventory works with centimeter accuracy having only a GNSS-receiver. It will be poccible toreceive coordinates correctionshaving satellite equipment of AshTech brand, as well as the equipment of third-party manufacturers. Due to the integral RTDS-server, it is possible to operate simultaneously with 90 rovers of all brands and broadcast corrections in any existing formats.

Basic reference station is operating in the test mode now, an evaluation of the quality of positioning on the real terrain is done by the rover AshTech ProMark200 in various modes – Static, Stop-n-Go, RTK. The planned accuracy is 10 mm in RTK within the boundaries of Perm and up to 10 cm in most parts of Perm region. The functioning of the basic reference station provides new opportunities for surveyors using satellite GNSS-receivers. First, it is the cost optimization of engineering research – it eliminates the need to purchase expencive private basic station. Second, it improves the quality of field and office works – high precision characteristics of the equipment and powerful but easy to use software of GNSS Solution will quickly and easily handle the materials of field surveys. The third opportunity concernsthe significant time savings for field work – there’s no need to justify the image development, visibility between points: the basic reference station is tied to the local coordinate system once and for the whole period of its operation.

Professionalism, the dynamics of sustainable development, the experience are the main features of the Geographic Information Systems and Technology Centerof Perm State University.


River classification is one of the recommendations of the European Water Framework Directive 2000/60/EC, which establishes that classifications should be carried out according to different variables hierarchically organized from a smaller to a larger scale. We suggest incorporating into the Directive’s hierarchical system a geoecological unit (lithotopo unit) that discriminates rivers with similar geomorphological features and ecological funtionality. The lithotopo units are not an alternative to the Directive typology, they are a complement intended to improve it.

Our method is divided into two stages, the first focused on the development of LTUs and the second on their validation. We applied the concept of lithotopo units to a 30,000 km 2 region in the NW of the Iberian Peninsula (Spain) using a Geographic Information System and field work. Seven kinds of lithotopo units were identified for the study area, each with its own geomorphological processes and dynamics, and, as a consequence, particular associated habitats. Cartographic validation was done through the analysis of 122 sample sites distributed in eight basins. Of the five validation variables originally employed, specific stream power and median grain size are the two that yielded the best results. Each kind of lithotopo unit displays a range of values of specific stream power and median grain size that is internally homogeneous but different from that of the other units. The methodology thus produced, which can be applied to other regions, is transparent, objective and quantitative.


This project aims to collect, analyse, digitise and reproduce dispersed laboratory data on physical properties of rocks of Switzerland and surrounding regions that carry geological relevance. The final aim is to provide an organized and controlled collection of data, including estimates of uncertainties and links to original data sources, representative of all the main rocks types of a continental crust. The collection should be able to represent a useful data base for academic studies but also for applicative purposes. It should be open to the wide public and should be able to benefit from input from new data collections.

The SAPHYR dbase centralises, homogenises and sustains otherwise widespread, differentiated and inaccessible laboratory and literature data, and information stored in master theses, and reports issued by Swiss scientific committees, or semi-private data collection. Data are carefully checked for consistency and completeness of information that allows to attribute each data to a geographic location and a specific rock type. The dbase is used to calculate physical properties maps, upon statistical treatment of each data group.

Here we describe as example of presentation of the data, the bulk density and Vp0 maps of Switzerland, as well as the used statistical method to construct these maps from sample data and the methodology behind this approach.

The data collection has been transferred to the Federal Office of Topography swisstopo, with the intent to make the dbase open and accessible online by the swisstopo webpage. In the swisstopo dbase tool there will be physical properties distributions for each lithology group.

The GIS based SAPHYR library should be continuously updated by including new laboratory and literature data and by re-assessing sample characteristics. The more data points included in the database, the more specific lithology groups will form, resulting in an optimised map resolution.

Exploring urban morphology through crowd sourced geographic information

The articles discussed yet another interesting theme of understanding the urban morphology through the prism of crowd sourced geographic information. This topic kindles a great interest because the rapid urbanization and globalization calls for deeper understanding of the patterns interwoven in the urban landscape. Moving beyond understanding the preliminary research along the lines of traffic management and understanding the source of data generation, the articles discuss a wider variety of applications that carried more appeal and charm.

While Crooks et al. Frias-Martinez et al. Liu et al. aim to study the urban form and function, they all differ in their approach and content. Crooks et al.’s article serves as an introduction and sets the stage for understanding the research framework and provides a novel ‘bottom approach’ for studying urban activity. However the only concern that I had was the fact that although crowd sourced GIS can serve as an important tool for gaining understanding urbanism. They come with their own set of difficulties when it comes to understanding subjectivities. In a similar vein, in their study, food, sport and entertainment can be categorically classified but not sentiment which is subject to one’s subjectivity. It is never possible to completely comprehend peculiarities and singularities. The authors mention that it had been difficult to obtain individual connotations. My argument is that it is difficult to obtain that even with the advent of modern technology. Their approach of using Flickr to study subjectivity can be called into question and needs further research. In addition, their sample is not representative of the entire civilian community across the world. Also much depends on the attitude of the people participating. VGI is complementing the process, nevertheless helping us make meaningful interpretations and conclusions about our study, but the process is slow and is only in its nascent stages. We still have a long way to go in terms of configuring a way to somehow decipher VGIS data to make authoritative.

Frias-Martinez et al. also study the characteristics of urban landscapes using geolocated tweets. They also allude to the complementary nature of crowd sources geographic data in the research frontier. Their article is very similar to the article by Crooks et al. in the fact that urban landscapes is very similar to urban form and function. One of the issues I that came to my mind was when the authors mentioned that the categories predefined in social networking websites did not allow for explicit classification was of the system’s design structure feeding into the loop of the research work. The design of the system invariably factor into the system a bias because the motive of the designer will be called into question. However, their research work is still worthwhile because their method can be formulated to incorporate other user generated datasets as well.

Liu et al.’s research article in their exploration of the urban land-use pattern and traffic ‘source-sink areas’ modelled along the lines of an ecological study by looking at the balance between drop-off and pick-ups balance vector (DPBV), although very technical presents an interesting alternative to study urban morphology through the lens of implicitly collected geographic information. I found the idea of using geo-information obtained from GPS enabled taxis in Shanghai in China very fascinating. Their reasoning for using GPS data from taxis because of the need to accommodate the peculiar feature attributed to their study area is very convincing. Their study is very significant because most of crowd-sourced study only caters to the developed countries. There have been very few studies designed to study developing economies from the eyes of VGI and making an effort to bridge the digital divide. Hence, their extensive research is commendable not only for their exhaustiveness but also for their study of the implications of the digital and social divide on VGI.

All three articles deserve commendation and merit not only for their informative and educative purpose but also for opening up a plethora of options in the research frontier with regard to VGIS.

Crooks, Andrew, Dieter Pfoser, Andrew Jenkins, Arie Croitoru, Anthony Stefanidis, Duncan Smith, Sophia Karagiorgou, Alexandros Efentakis, and George Lamprianidis. 2014. “Crowdsourcing Urban Form and Function.” International Journal of Geographical Information Science (ahead-of-print): 1-22.

Frias-Martinez, Vanessa, Victor Soto, Heath Hohwald, and Enrique Frias-Martinez. 2012. “Characterizing Urban Landscapes using Geolocated Tweets.”IEEE, .

Liu, Yu, Fahui Wang, Yu Xiao, and Song Gao. 2012. “Urban Land Uses and Traffic ‘source-Sink Areas’: Evidence from GPS-Enabled Taxi Data in Shanghai.” Landscape and Urban Planning 106 (1): 73-87.

Geoambiente Sensoriamento Remoto Ltda.

GEOAMBIENTE, is a Consulting Engineering Company which aggregates knowledge and value to the business of its clients using GEOTECHNOLOGIES. With a solid experience of many years in the market and professionals with multi-disciplinary background, GEOAMBIENTE always aims to innovation, and it is known as one of the main geotechnology companies in Brazil.

The Company's GIS-IT team develops complete Information Technology Solutions focused on a geographic view. GEOAMBIENTE is a partner of the main market players, such as ESRI and GOOGLE, accumulating in its portfolio several success cases on the conception, development, integration and implementation of corporative GIS systems.

The Company's specialists in Remote Sensing, Cartography and Environmental Analysis developed intelligent solutions for thematic and plani-altimetric mapping, data integration, analysis of multi-varied information and environmental management. The Company applies its knowledge from Geosciences, acting on several market segments, always aiming to create innovative responses and optimized solutions for the needs of its clients. The success of its partnerships with the image distributors Space Imaging, DigitalGlobe and RapidEye, as well as the supply of TeleAtlas databases, guarantee the efficiency of its business model.

GEOAMBIENTE is committed to the excellence of business processes of its clients, with both social-environmental sustainability and the best practices for the development of complete solutions in geotechnologies. GEOAMBIENTE is continually performing significant and growing investments on the development of its System for Quality Management. It is a set of activities and corporative procedures which ensure that GEOAMBIENTE fully complies with the requirements of its clients, of the regulating agencies and of the society, on a structured and monitored way, aligned with the best market practices.

The Company is continuously improving its corporative processes, such as the introduction of strategic planning, using the Balanced Scorecard Pattern, the good practices of Capability Maturity Model Integration (CMMI) for the development of systems, an efficient project management based on the PMBOK, besides the quality control by sampling selection, directed by ABNT (Brazilian Association for Technical Standards), among other actions.

The good performance and quality actions extrapolate the technical area and attain all sectors of the company. Since GEOAMBIENTE exerts an efficient and responsible financial management, it is registered and certified at the database of D&B (Dun & Bradstreet), which is one of the most respected entities for the financial qualification of companies worldwide.

In practice, the excellence at Service Quality is a commitment from GEOAMBIENTE

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