GIS Database Research Articles

Penetration Resistance of Laacher See-tephra Andosols—Evaluating Rooting Conditions of Undisturbed and Excavated Forest Soils in SW-Germany

This study discusses penetration resistance (PR) of forested Pumice-Andosol sites. PR, a key soil property influencing root growth and elongation, exerts a substantial influence on ecological site quality and tree growth. Andosols were expected to show low PR because of their unique characteristics (low bulk density, loose soil matrix). Five sites, two undisturbed and three backfilled, were sampled. The latter result from pumice excavation and were examined to quantify potential PR alterations in the aftermath of backfilling and pumice removal. Penetrologger sampling on undisturbed sites showed mean PR not exceeding 3 MPa, a literature-based, critical threshold restricting root growth, in the upper 0.80 m, indicating conditions fostering tree rooting. Backfilled sites mostly exhibited increased (> 3 MPa) PR, leading to rooting restrictions even beginning at −0.21 m. Deviations from undisturbed soils range from −15.6 to +109.3% depending on depth and age of the backfilled site. Furthermore, GIS-based data interpolation helped to identify spatial PR patterns and allowed a direct comparison before/after backfilling at one site. Statistical analysis revealed significantly altered PR after backfilling, while a concluding ANOVA provided at least significant governing factors (depth, area, clay + silt content, soil organic matter), albeit with only small effect sizes.

Prediction the Locations of Future Earthquakes in Eastern Part of Iraq Using GIS Techniques

An earthquake is a natural phenomenon and natural catastrophe. It can cause massive damage and losses of life. Future prediction of natural catastrophes such as earthquakes can minimize their risks and save people lives and properties. GIS can be very essential for predicting and estimating a future earthquake. Thus, this study is dedicated to predict the locations of future earthquakes in the eastern part of Iraq using GIS techniques. The study involves establishing a GIS database (DB) of the previous earthquake in the period (1985 - 2015), identifying the parameters that a map layers of all parameters (factors) which are responsible on occurring earthquakes, and using GIS techniques to identify and predict the locations of the future earthquakes.This research is accomplished through a number of essential stages. These are data gathering, data processing and data analyzing. The gathered data among the period of the study (from 1985 to 2015) was classified into three stages ((1985-1995), (1996-2005), and (2006 to 2015) to distinguish a fine details of past earthquakes easily and precisely. The results show that GIS is a powerful tool that can provide an accurate prediction of upcoming natural phenomena such as earthquakes. This can evaluate earthquake hazards and raise the awareness of the government to save people’s lives, properties and infrastructures against the possible future earthquakes and the accuracy assessment processes reveals that about 80% of coming quakes happened where they expected (very close to the prediction seismic line).

Gis-based Analysis of Water Quality Parameters of Groundwater with Proximity to Onsite Wastes Pits in Vom Community of Jos South, Nigeria

Water quality assessment is an important part of environmental quality management especially in groundwater resources located close to sources of contamination. This study involved the assessment of groundwater quality for hand dug wells at locations with proximity to pit latrines in Vom community, Plateau State, Nigeria and the use of GIS for data analysis. Water samples were collected from six (6) locations in a small area to assume possible interaction between the water in the sampling wells, the maximum distance between any two points being 100 m and the minimum distance being 22 m. Eleven (11) physical, bacteriological and chemical parameters were analyzed for the water samples. The results were compared with World Health Organization and Nigerian Standard for Drinking Water Quality standards. The chemical parameters in the samples tested met the WHO and NSDWQ limits with the exception of pH which was slightly acidic for four samples. The results also showed that E. coli was found in all the samples tested. This may be attributed to the proximity of the wells to pit latrines. The results obtained from laboratory analyses were inputted into a GIS database in ILWIS 3.8 where the variation maps were developed and also classified maps for each of the parameters based on whether they meet WHO standards or not. The classified maps were all overlaid in GIS to develop the groundwater quality information map where any point highlighted gives information on the parameters for that point. This makes the retrieval of water quality parameters easy and also the comparison of the parameters with respect to location. Treatment of the groundwater with chemicals like soda ash and chlorine are recommended before consumption. It is generally recommended that wells should not be located in close proximity to onsite underground wastes disposal pits. Government should provide sufficient potable water for the Vom Community.

Mapping the Villagescape: An Archaeological Approach to Political Ecology Along the Falemme River, AD 1000–1900

Historical narratives in Upper Senegal largely center on precolonial statecraft, long-distance trade, and ethno-religious mobilization. Drawing on the perspective of political ecology, we examine how these regional processes intersected with village life through local relations to land. Specifically, we chart the long-term dynamics of settlements and their catchments along the Falemme River between the states Gajaaga and Bundu, centered on the Senegal confluence, and a shifting frontier with the non-state societies of Bambuk to the south. This involves first integrating site data from our independent archaeological surveys of the Lower and Middle Falemme study areas into a GIS database for regional analysis of settlements patterns during the second millennium AD. We then compare these patterns with site catchments for surface soils classified from multispectral satellite imagery (Landsat 8 OLI-TIRS) to model everyday access to cultivable land. Our results challenge state-centric narratives of Upper Senegal by suggesting that everyday experiences of village life along the Falemme River were more firmly grounded in local concerns for land and subsistence production than in regional politics of statecraft and frontier.

Agricultural permanence in large Asian cities: a case study of Nanjing, China

ABSTRACT Nanjing, the capital of China's Jiangsu Province, has grown rapidly during the post-reform era and the pace of change placed tremendous pressure on the city's arable land resources. This case study of land use/land cover change (LU/LC) in Nanjing's Jiangning district assesses changes in agricultural land, production, and labor within the ten 2016-era jiedao (sub-district political units) of Jiangning from 2000 to 2015. This case study provides an opportunity to assess an important component of the Ginsburg-McGee desakota hypothesis predicting that Asian extended metropolis regions, unlike similar large cities in Western nations, will consistently maintain agricultural land and labor supplies within metropolitan boundaries. The study is based on field visits combined with time-series LU/LC analyses of a GIS database joining archived agricultural and agro-economic data with additional LU/LC data layers derived from satellite imagery including Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM) imagery. Results show Jiangning continues to retain high, if decreasing, proportions of agricultural land and employment. After significant decreases for all ten jiedao from 2000 to 2010, government policies appear to have helped stabilize arable land losses from 2010 to 2015. Jiedao in the closest proximity to Nanjing's central business districts lost arable land at greater rates than those in the periphery. OLS linear multiple regression analyses identified factors that are the most effective predictors of arable land persistence including lower mean annual income, higher percentage of men in the farm workforce, higher reliance on traditional double-cropped rice-wheat, and less vegetable production.

A pseudo time‐series reveals the rapid recovery and high variability of benthic macroinvertebrate populations following catchment wildfire

Abstract The increasing risk of wildfire has focused attention on the timescale of the impact and recovery of river ecosystems and methods for their bioassessment. An 18‐year pseudo time‐series was exploited to document patterns in benthic macroinvertebrate impact and recovery and evaluate the efficacy of alternative metrics to assess fire damage. Macroinvertebrates were surveyed by kick‐sampling and data were collected on river habitats. Details of river catchments and wildfire were collated as a GIS database. Macroinvertebrate richness and abundance recovered rapidly, marked by a phase of dynamic increase, followed by relative stability (0–2 years and 3–18 years, respectively). Across sites, richness and abundance were best explained by time since fire. A biotic index of general river quality was ineffective as an indicator of fire damage. While a metric of K‐selected taxa (Odonata richness) was generally indicative of fire‐affected assemblages, a contrasting metric of r‐selected taxa (percentage of chironomids, baetids, and simuliids) was not. Ordination analysis revealed time as a significant determinant of community structure across sites; however, its overall statistical importance was eclipsed by habitat characteristics (water quality, shade, altitude, and latitude) that were associated with ecological variation across both recently affected sites and the putatively recovered communities. These results highlight the stochastic processes – environmental and ecological – that frame the macroinvertebrate response to wildfire. This probabilistic context emphasizes the difficulties of developing indicator taxa for wildfire bioassessment and reinforces the importance of standardized survey protocols and the use of contrasting metrics in the assessment of wildfire impact on the ecological quality of rivers.

An evaluation of different forest cover geospatial data for riparian shading and river temperature modelling

AbstractRiparian tree planting is increasingly being used as a strategy to shade river corridors and offset the impact of climate change on river temperature. Because the circumstances under which tree planting generates the greatest impact are still largely unknown, researchers are increasingly using process‐based models to simulate the impacts of tree planting (or felling) on river temperature. However, the high‐resolution data on existing riparian tree cover needed to parameterise these models can be difficult to obtain, especially in data‐sparse areas. In this paper, we compare the performance of a river temperature model parameterised with a range of different tree cover datasets, to assess whether tree cover data extracted from readily available GIS databases or coarser (i.e., 2–5 m) digital elevation products are able to generate river temperature simulations approaching the accuracy of higher resolution structure from motion (SfM) or LiDAR. Our results show that model performance for simulations incorporating these data is generally degraded in relation to LiDAR/SfM inputs and that tree cover data from “alternative” sources can lead to unexpected temperature model outcomes. We subsequently use our model to simulate the addition/removal of riparian tree cover from alongside the river channel. Simulations indicate that the vast majority of the “shading effect” is generated by tree cover within the 5‐m zone immediately adjacent to the river channel, a key finding with regards to developing efficient riparian tree planting strategies. These results further emphasise the importance of incorporating the highest possible resolution tree cover data when running tree planting/clearcutting scenario simulations.

Integrated Geospatial Database and Web Based Tools for Land Management and Administrative Planning (ILMAP) for Imphal East and Thoubal Districts, Manipur State, India

Manipur, as most of the north eastern area, come under hilly and difficult area, economically and infrastructurally underdeveloped area category. Manipur is facing the unenviable situation of being a resource starved State coupled with decades old insurgency widespread across the State, desperately crying out for a major thrust in inclusive development. As part of the initiative by the Govt. of India for the development of the north-eastern India, an Integrated Land Management and Administrative Planning (ILMAP) was taken up in Manipur State with the state-of-the-art technology. In the present work Imphal East and Thoubal Districts are selected. The objective of the study is to generate GIS database on drainage, water bodies, administrative boundaries, and other utility maps. The methodology involves geo-referencing of Quick Bird (QB) data with the help of DGPS survey. Drainage and surface water bodies, base map and land use/land cover maps are generated with the help of QB data. Point of Interest is mapped in all urban areas covering important landmarks such as Govt. offices, post offices, banks, religious places, and places of tourist interest etc., along with photographs and geographical coordinates. Using the soil maps generated by AISLUS and NBSS and LUP as a base, soil maps are prepared. All these maps are geo-referenced to QB satellite data. Using this database, a customized GIS application is developed for e-governance which can be accessed by authorized beneficiaries through State Wide Area Network (SWAN). The application was deployed in the State Data Centre (SDC) and training was provided to all the department officials for effective use in all developmental projects.

Mapping groundwater suitability for irrigation using GIS: A Case study of Ilorin, Kwara State, Southwestern Nigeria

Agricultural water in the right quantity and desired quality is needed to drive agrarian revolution in Nigeria. Groundwater, among the forms of water in nature is strategic for Nigeria has it is easy to exploit, readily available not affected by seasonality and the largest natural storage of available freshwater on the planet. The study was aimed at evaluating and mapping irrigation water quality of groundwater system within Ilorin metropolis. Forty-four well samples were collected in triplicates over the dry and wet seasons with their locations georeferenced. The water samples were sent to the laboratory and the results were incorporated into a GIS database in the development of a water map. Six indices, Sodium Adsorption Ratio (SAR), Magnesium Adsorption Ratio (MAR), Permeability Index (PI), Residual Sodium Carbonate (RSC), Kelly’s Ratio (KR) and Soluble Sodium Percentage (SSP), were used to evaluate suitability for irrigation. The geo-spatial representation is displayed using Surfer 9 and ARC Map software. The sampling points were concentrated in the southern portion of the study area, with dense settlements and expected anthropogenic activities. The western portion of the study area within the vicinity of Moro river basin reflected general good irrigation water quality and low settlement is prime for irrigated agriculture. The geospatial representations of irrigation water quality developed guides decision makers on the use of various ground water sources within the area. In the same light, it demonstrates high efficiency of GIS in elucidating complex geospatial data through the development of quality maps.

Brightness Transformation and CNN-MRF Model for Road Network Extraction using RSI

For effective urban planning and GIS database, it is necessary to extract effectively the network of road from remote sensing images. The very high spatial resolution images (VHR) taken by space and space probes are the main source of an accurate extraction of the route. Manual techniques disappear because they take time and are expensive. As a result, the much more automated route extraction method has become a research tool in the processing of remote sensing information. The extraction of road networks in remote urban areas of images plays an important role in many urban applications (eg. Road traffic, geometric correction of remote sensing images in cities, updating geographical information, etc.). Because of the complex geometry of buildings and the geometry of sensor detection, it is generally difficult to distinguish the road from its background. In this paper, a hybrid method is proposed for the extraction of paths from high resolution images based on the segmentation using sigmoid CNN-MRF model. The proposed method includes noise removal and enhancement using brightness transformation function then segmentation of road and non-road pixels using CNN and edges are joined using CNN model also. And lastly the markov random field is used connecting edges with similar end points. Simulation will be conducted on remote sensing images in urban, suburban and rural areas to demonstrate the proposed method and compare it with other similar approaches. The results show better performance of proposed road network extraction method as compared to existing technique.

A modified motion planning algorithm for horizontal highway alignment development

AbstractA horizontal alignment can be represented by three key factors: number of horizontal points of intersection (HPIs), their locations, and corresponding horizontal curve radii. Deciding all the three factors simultaneously requires extensive effort, which is not practically feasible in the manual alignment development process. Most available computer‐aided methods prioritize some or all the three factors in the automated alignment development processes. However, approximation in HPI location or pre‐selection of HPI number and curve radius are the few limitations of these methods. This study presents a modified motion‐planning based algorithm for developing new horizontal alignments with optimized costs and impacts. It simultaneously uses a low‐discrepancy sampling technique to develop increasingly dense potential HPIs, rapidly exploring random trees to find a suitable number of intermediate HPIs at appropriate locations and sequential quadratic algorithm to select optimally fitted curve radii. The proposed algorithm is integrated with the GIS database for realistic location‐dependent cost and environmental impact assessment. Two real‐world study areas were selected to compare the results with the one reported in the literature and to evaluate backtracking capability. Results indicated the proficiency of the proposed algorithm in developing new alignments. The sensitivity analyses revealed the effect of design speed and right‐of‐way width on the alignment generation. The proposed algorithm can automate the new horizontal highway alignment development process and support highway engineers in planning and development.

GIS Based Index Overlay Method in Targeting Heavy Mineral Deposits, Southern Kerala Coast, India

Owing to the strategic importance in defence and the other industrial applications, the heavy minerals have attracted the attention of the geoscientists since long time. But they have been using mostly the traditional techniques for a long time for targeting the heavy mineral deposits. Later, the scientists have started employing modern techniques like scintillometer based field surveys, remote sensing and the laboratory based sedimentological and heavy mineral studies. But since the traditional techniques are more cumbersome and would be very difficult to cover the vast length of the Indian coasts of over 7500 km, faster and effective techniques are necessary. So, the information value method was accomplished in the present study to demonstrate the targeting of heavy minerals in parts of Kerala extending from 76° 41' - 08° 53' in NNW and 77° 13' - 08° 17' in SSE (1,811sqkm). In this study five geosystem maps, viz; Lithology, Lineament Frequency, Lineament Density, Lineament Intersection density and Geomorphology were prepared using the raw and digitally processed LANDSAT ETM 7 and IRS LISS IV FCC data sets. These geosystem maps were firstly prepared as vector GIS layers and then converted into raster maps using ARC GIS software with the pixel size of 100sq.m and the total pixels of 1,64,358. On the basis of the contribution of the above five main geosystem variables towards the heavy mineral potentials, weightages were assigned (Wi) to each of them. Similarly, depending upon the heavy mineral possibilities of the sub variables of the above five main geosystem variables, scores were assigned (Si) to each sub variables of the 5 main geosystem variables. Then, the Wi values were multiplied with the corresponding Si values of each of the sub variables of the 5 main geosystem variables and those were considered as final weightages (HMP-Heavy Mineral potentials) and assigned the same to the corresponding pixels of each sub variables of the five main variables. Followingly, the each WiSi weighted values of the 1,64,358 pixels of the lithology main geosystem variable were added with corresponding pixels of the remaining 4 main geosystem variables using ADD function menu of ARC GIS and integrated raster GIS database was generated with all the 1,64,358pixels having the cumulative WiSi values (ΣWiSi). Then, on the dynamic range of the ΣWiSi values, these pixels were classified into Very High, High, Moderate, Low and Very Low zones of heavy mineral concentrations. This was validated with heavy mineral weight percentage data derived from the field samples collected from the study area during survey. This study was basically undertaken to replicate it for the rapid appraisals of the probable heavy mineral target areas along the Indian coasts. However this can be replicated anywhere.

A Framework Proposal for Regional-Scale Flood-Risk Assessment of Cultural Heritage Sites and Application to the Castile and León Region (Central Spain)

Floods, at present, may constitute the natural phenomenon with the greatest impact on the deterioration of cultural heritage, which is the reason why the study of flood risk becomes essential in any attempt to manage cultural heritage (archaeological sites, historic buildings, artworks, etc.) This management of cultural heritage is complicated when it is distributed over a wide territory. This is precisely the situation in the region of Castile and León (Spain), in which 2155 cultural heritage elements are registered in the Catalog of Cultural Heritage Sites of Castile and León, and these are distributed along the 94,226 km2 of this region. Given this scenario, the present study proposes a methodological framework of flood risk analysis for these cultural heritage sites and elements. This assessment is based on two main processing tools to be developed in addition: on the one hand, the creation of a GIS database in which to establish the spatial relationship between the cultural heritage elements and the flow-prone areas for different flood return periods and, on the other hand, the creation of a risk matrix in which different variables are regarded as associated both to flood hazard (return period, flow depth, and river flooding typology) and to flood vulnerability (construction typology, and construction structural relationship with the hydraulic environment). The combination of both tools has allowed us to establish each cultural heritage flood risk level, making its categorization of risk possible. Of all the cultural heritage sites considered, 18 of them are categorized under an Extreme flood risk level; and another 24 show a High potential flood risk level. Therefore, these are about 25% to 30% of all cultural heritage sites in Castile and León. This flood risk categorization, with a scientific basis of the cultural heritage sites at risk, makes it possible to define territories of high flood risk clustering; where local scale analyses for mitigation measures against flood risk are necessary.

Neighbourhood drivability: environmental and individual characteristics associated with car use across Europe

BackgroundCar driving is a form of passive transportation associated with higher sedentary behaviour, which is associated with morbidity. The decision to drive a car is likely to be influenced by the ‘drivability’ of the built environment, but there is lack of scientific evidence regarding the relative contribution of environmental characteristics of car driving in Europe, compared to individual characteristics. This study aimed to determine which neighbourhood- and individual-level characteristics were associated with car driving in adults of five urban areas across Europe. Second, the study aimed to determine the percentage of variance in car driving explained by individual- and neighbourhood-level characteristics.MethodsNeighbourhood environment characteristics potentially related to car use were identified from the literature. These characteristics were subsequently assessed using a Google Street View audit and available GIS databases, in 59 administrative residential neighbourhoods in five European urban areas. Car driving (min/week) and individual level characteristics were self-reported by study participants (analytic sample n = 4258). We used linear multilevel regression analyses to assess cross-sectional associations of individual and neighbourhood-level characteristics with weekly minutes of car driving, and assessed explained variance at each level and for the total model.ResultsHigher residential density (β:-2.61, 95%CI: − 4.99; -0.22) and higher land-use mix (β:-3.73, 95%CI: − 5.61; -1.86) were significantly associated with fewer weekly minutes of car driving. At the individual level, higher age (β: 1.47, 95%CI: 0.60; 2.33), male sex (β: 43.2, 95%CI:24.7; 61.7), being employed (β:80.1, 95%CI: 53.6; 106.5) and ≥ 3 person household composition (β: 47.4, 95%CI: 20.6; 74.2) were associated with higher weekly minutes of car driving. Individual and neighbourhood characteristics contributed about equally to explained variance in minutes of weekly car driving, with 2 and 3% respectively, but total explained variance remained low.ConclusionsResidential density and land-use mix were neighbourhood characteristics consistently associated with minutes of weekly car driving, besides age, sex, employment and household composition. Although total explained variance was low, both individual- and neighbourhood-level characteristics were similarly important in their associations with car use in five European urban areas. This study suggests that more, higher quality, and longitudinal data are needed to increase our understanding of car use and its effects on determinants of health.

Water Resource Assessment of a Complex Volcanic System Under Semi-Arid Climate Using Numerical Modeling: The Borena Basin in Southern Ethiopia

The Borena basin is located in southern Ethiopia, in a semi-arid climate, on the eastern shoulder of the south Main Ethiopian Rift (MER). The study area covers 18,000 km2 and is characterized by a lack of perennial surface waters that can be used for domestic and agricultural purpose. As a result, groundwater, which occurs in complex volcanic settings, is the only source for water supply in the study area. This work is focused on the basaltic aquifers, which are intensely fractured, resulting in strong connectivity within the system. All available data (geology, hydraulic head, hydraulic parameters, well inventory and discharge, etc.) were compiled in a GIS database. The overall objective of this work is the assessment of groundwater potential, its spatial distribution and factors controlling its movement using numerical groundwater modeling to enhance groundwater management and use in the Borena basin. The modeling task was conducted at two scales: (i) regional scale; (ii) wellfields scale. The regional steady state model was calibrated using the Pilot points approach, highlighting a strongly heterogeneous system. A significant result of the regional model consisted of estimating the water balance of the whole system. The total inflow to the basin amounts to 542 × 106 m3/year, of which 367 × 106 m3/year are provided by superficial recharge. Groundwater resources are exploited with 7 wellfields. Exploitation of the wellfields was optimized based on the Sustainable Yield concept, which reserves a fraction of natural recharge for the benefit of the environment (surface waters, ecosystems). Each wellfield was extracted from the regional model, refined and used to simulate and optimize pumping scenarios, with the objective of maximizing discharge rates and avoiding over-exploitation of the groundwater. The optimized abstraction at all wellfields amounts to 121 × 106 m3/year, which represents 33% of the natural recharge and fully agrees with the sustainable yield concept.

Generating Substantially Complete Landslide Inventory using Multiple Data Sources: A Case Study in Northwest Himalayas, India

Abstract Landslide inventory contains basic information about landslides such as location, classification, morphometry, volume, run-out distance, activity, date of occurrence, damages caused etc. In most landslide inventory maps only spatio-temporal distribution of slope failures is shown. A complete portrayal of landslide inventory, both in number of landslides mapped and associated attributes such as morphometry, classification etc. is a must as it has bearing on the estimation of landslide susceptibility, hazard and risk. Despite of its enormous importance, landslide inventory is rarely found to be complete. This can be attributed to limited availability of requisite data and the inherent uncertainties in landslide inventory mapping from different sources and importantly the insufficient field inputs. In the present work in the Mandakini valley of Uttarakhand Himalayas attempts have been made to prepare a substantially complete landslide inventory, both in terms of number of landslides and attributes, using multifarious data sources substantiated with thorough field checks. Supplementary historical data sources along with the conventional data sources have been used to prepare the inventory. The approach followed includes pre-field mapping of landslides from different Earth Observation (EO) data followed by interpretation of archival records and detailed field surveys. The data available for the period 1962 to 2013 were used to build up the inventory database in GIS. A total of 644 landslides have been mapped and attributed using conventional EO data and also the different supplementary data sources for an area covering 400 sq. km. An inventory of 151 landslides prepared from EO data have been confirmed and updated during the field study. Finally, the detailed landslide inventory prepared during the course of this study was analysed to understand the behaviour of landslides and role of triggering factors in susceptibility mapping and the geo-environmental conditions governing the magnitude of the event.

Integration of Digital Technologies into Underground Utility Asset Management

Installation, detection, maintenance, mapping, and management of underground utility assets present challenges to owners, engineers and contractors. Industry-wide practices include the use of geophysical and similar technologies to determine depth and location, and 2D as-built plans integrated with GIS databases for information management. The feasibility of incorporating 3D BIM models of the subsurface to replace the 2D plans to improve visualization and data management is examined in this paper. Obtaining an accurate image of the underground infrastructure would help minimize excavation accidents due to equipment-utility collisions and prevent property damage. Further, the inclusion of automated data collection and sharing features realized through BIM technology can enhance operations of smart cities. The research methodology consists of a state-of-the-art review of the current underground utility management systems, combined with statistical analysis of survey responses received from utility providers and one-call centers in the U.S. Three categories of utility practices are identified based on the level of digital technology integration. It is found that a vast majority of utility firms have adopted GIS databases with 2D plans, depth and other asset information, while a smaller percentage of providers have achieved full GIS-BIM integration, incorporating a wide range of asset data. Future progress on broader implementation appears to be constrained by the digital literacy of personnel and high costs of technology acquisition and application. A three-step framework for converting 2D plans to 3D BIM models is also presented and discussed. The process model proposed for this purpose allows the utilization of commercially available software with minimal need for additional coding.

On Statistical Measures for Data Quality Evaluation

Most GIS databases contain data errors. The quality of the data sources such as traditional paper maps or more recent remote sensing data determines spatial data quality. In the past several decades, different statistical measures have been developed to evaluate data quality for different types of data, such as nominal categorical data, ordinal categorical data and numerical data. Although these methods were originally proposed for medical research or psychological research, they have been widely used to evaluate spatial data quality. In this paper, we first review statistical methods for evaluating data quality, discuss under what conditions we should use them and how to interpret the results, followed by a brief discussion of statistical software and packages that can be used to compute these data quality measures.

Large-scale survey method for the integrity of historical urban walls: application to the case of Volterra (Italy)

Several relevant collapses of historical urban walls happened in Tuscany in the last ten years, due to rainfalls. The wide extension of the walls, with difficulties of proper monitoring, joined with lack of maintenance, contributed to the failures. This recalled the attention on their vulnerability, in view to ensure a proper safety level and appropriate cultural heritage protection.In this paper, a method of extensive and quick structural survey to identify the mechanical characteristics of an historical urban wall path is proposed. It is based on geographic method of management of the territory (GIS database, satellite data). The data are obtained throughout a discretization of the walls in a wide set of vertical sections. A reduced subset of sections is directly surveyed, while the others are indirectly identified via numerical procedure, with the help of GIS data. A specific form to take note of the most relevant features is edited. The method is tested on the entire perimeter of the Middle Age walls of Volterra (2,6 km), affected by two relevant collapses in 2014. The procedure of survey is conceived to perform structural analysis to evaluate the vulnerability to landslides and earthquake risks, in view to determine restoration strategies and consolidation or monitoring programs.

Analysis of GIS-Based Disaster Risk and Land Use Changes in The Impacted Area of Mudflow Disaster Lapindo

The mudflow disaster Lapindo in Sidoarjo Indonesia, that has occurred since 2006, until now still poses a risk of danger to residential settlements in the impacted areas. This study aims to make disaster risk analysis and land use changes in disaster impacted areas since before the disaster occurred until now. This research is expected to be very useful as a basis for developing spatial policies in the region. The method used is quantitative based on satellite imagery, then GIS-based data is analyzed quantitatively. GIS-based disaster risk analysis can be used as a reference in spatial revisions that can anticipate spatial regional developments, especially for the needs of residential settlements. Observations from satellite imagery show a very significant level of change in residential land which is now 42.1% and the level of disaster risk varies with the medium-high index. With the results of this study, in an effort to improve the resilience index of the region, planning the location of residential land should use land outside the impacted area in order to ensure the safety and security of the community.