Spatial Data Sources Research Articles

Applications of the PyTOPKAPI model to ungauged catchments

Many catchments in developing countries are poorly gauged/totally ungauged which hinders water resource management and flood prediction in these countries. This study explored the application of the PyTOPKAPI model to South African (Mhlanga) and Ethiopian (Gilgel Ghibe) case study catchments to test its suitability for simulating stream flows from ungauged catchments. The aim is to extend the model application to poorly gauged/totally ungauged catchments in developing countries. The model uses digital elevation data and other spatial data sources to set up the model parameters and the forcing files. To generate reliable stream flows, models generally need to be calibrated, which typically relies on the availability of reliable stream flow data. We show how application of simple lumped models for average runoff ratios, such as that proposed by Schreiber in 1904, can be used as an alternative to detailed calibration with gauged flows. This approach seems to be new; and we show how the proposed method, together with the PyTOPKAPI model, can be used to predict runoff responses in ungauged catchments for water resource applications and flood forecasting in developing countries.

A Refined Crop Drought Monitoring Method Based on the Chinese GF-1 Wide Field View Data

In this study, modified perpendicular drought index (MPDI) models based on the red-near infrared spectral space are established for the first time through the analysis of the spectral characteristics of GF-1 wide field view (WFV) data, with a high spatial resolution of 16 m and the highest frequency as high as once every 4 days. GF-1 data was from the Chinese-made, new-generation high-resolution GF-1 remote sensing satellites. Soil-type spatial data are introduced for simulating soil lines in different soil types for reducing errors of using same soil line. Multiple vegetation indices are employed to analyze the response to the MPDI models. Relative soil moisture content (RSMC) and precipitation data acquired at selected stations are used to optimize the drought models, and the best one is the Two-band enhanced vegetation index (EVI2)-based MPDI model. The crop area that was statistically significantly affected by drought from a local governmental department, and used for validation. High correlations and small differences in drought-affected crop area was detected between the field observation data from the local governmental department and the EVI2-based MPDI results. The percentage of bias is between −21.8% and 14.7% in five sub-areas, with an accuracy above 95% when evaluating the performance via the data for the whole study region. Generally the proposed EVI2-based MPDI for GF-1 WFV data has great potential for reliably monitoring crop drought at a relatively high frequency and spatial scale. Currently there is almost no drought model based on GF-1 data, a full exploitation of the advantages of GF-1 satellite data and further improvement of the capacity to observe ground surface objects can provide high temporal and spatial resolution data source for refined monitoring of crop droughts.

Location‐based social media behavior and perception: Views of university students

Location‐based social media (), a specific type of volunteered geographic information (), is increasingly being used as a spatial data source for researchers in geography and related disciplines. Many questions, though, have been raised about data in terms of its quality and its contributors. While a number of studies have explored users’ demographics and motivations for contribution to explicitly geographic forms of , such as OpenStreetMap and Wikimapia, few have focused on these aspects with implicitly geographic forms of , such as (for example, Twitter and Instagram). This study, through use of an online survey, specifically assesses the behavior and perceptions of 253 university students, noting differences found in gender, race, and academic standing. We find that the greatest differences are those between males and females, rather than through race or academic standing, and appears less biased than other forms of .

Mapping fine‐scale urban housing prices by fusing remotely sensed imagery and social media data

AbstractThe accurate mapping of urban housing prices at a fine scale is essential to policymaking and urban studies, such as adjusting economic factors and determining reasonable levels of residential subsidies. Previous studies focus mainly on housing price analysis at a macro scale, without fine‐scale study due to a lack of available data and effective models. By integrating a convolutional neural network for united mining (UMCNN) and random forest (RF), this study proposes an effective deep‐learning‐based framework for fusing multi‐source geospatial data, including high spatial resolution (HSR) remotely sensed imagery and several types of social media data, and maps urban housing prices at a very fine scale. With the collected housing price data from China's biggest online real estate market, we produced the spatial distribution of housing prices at a spatial resolution of 5 m in Shenzhen, China. By comparing with eight other multi‐source data mining techniques, the UMCNN obtained the highest housing price simulation accuracy (Pearson R = 0.922, OA = 85.82%). The results also demonstrated a complex spatial heterogeneity inside Shenzhen's housing price distribution. In future studies, we will work continuously on housing price policymaking and residential issues by including additional sources of spatial data.

The DHS Program's Modeled Surfaces Spatial Datasets.

Spatially interpolated map surface datasets for key development indicators are being produced and publicly shared using population-based surveys from the USAID-funded Demographic and Health Survey (DHS) Program. Each modeled surface is produced with standardized geostatistical modeling methods. For each indicator, a package is available that includes spatial raster grids of 5 × 5 km pixels for the point estimate surface and an uncertainty surface, along with validation statistics and other model diagnostic data. The maps are publicly available for download on the DHS Program Spatial Data Repository at http://spatialdata.dhsprogram.com/. The modeled surfaces are produced with publicly available geo-referenced data on each indicator as collected by the DHS Program, augmented with other relevant spatial data sources that act as covariates. A Bayesian model-based geostatistical (MBG) approach is used to generate the modeled surfaces. Spatially modeled surfaces can be used to support and improve decision-making at multiple levels within many development programs including health, population, family planning, nutrition, and water and sanitation. The modeled surfaces can be used in their original 5 × 5 km pixel format, operationalized to other geographic areas as relevant for the program, or linked to DHS or other survey data for additional analysis.

Ecosystem Services Mapping Uncertainty Assessment: A Case Study in the Fitzroy Basin Mining Region

Ecosystem services mapping is becoming increasingly popular through the use of various readily available mapping tools, however, uncertainties in assessment outputs are commonly ignored. Uncertainties from different sources have the potential to lower the accuracy of mapping outputs and reduce their reliability for decision-making. Using a case study in an Australian mining region, this paper assessed the impact of uncertainties on the modelling of the hydrological ecosystem service, water provision. Three types of uncertainty were modelled using multiple uncertainty scenarios: (1) spatial data sources; (2) modelling scales (temporal and spatial) and (3) parameterization and model selection. We found that the mapping scales can induce significant changes to the spatial pattern of outputs and annual totals of water provision. In addition, differences in parameterization using differing sources from the literature also led to obvious differences in base flow. However, the impact of each uncertainty associated with differences in spatial data sources were not so great. The results of this study demonstrate the importance of uncertainty assessment and highlight that any conclusions drawn from ecosystem services mapping, such as the impacts of mining, are likely to also be a property of the uncertainty in ecosystem services mapping methods.

Multi-temporal transect analysis of peri-urban developments in Faridabad, India

ABSTRACTDynamic land-use changes in peri-urban areas in the Global South are often characterized by a juxtaposition of planned and unplanned, formal and informal, legal and illegal developments. India faces rapid (peri-)urbanization and great challenges to govern these sprawling, spatially fragmented, and socially uneven developments at the fringe of cities. Under these circumstances, up-to-date maps of (peri-)urban development processes are essential for effective governance. However, mapping the processes of urbanization is a challenging exercise. The developed map visualizes the heterogeneous spatio-temporal reality of peri-urban India using the case study of the dynamically growing city of Faridabad, a satellite city of Delhi. The multi-temporal map is based on field mapping and the interpretation of Google Earth imagery. These spatial data sources have been triangulated with findings from qualitative semi-structured interviews with different stakeholders, expert interviews, and secondary data in order to incorporate and visualize contextual spatial knowledge in the map.

Reliability of Local Scale Human Pressure Modeling at the Seafloor of the Baltic Sea

ABSTRACTEfforts to understand anthropogenic stress in marine environments have introduced methods of cumulative human pressure modeling in the broad-scale mapping of large sea areas. This paper examines the usability of such modeling in the shallow seafloor and complex shoreline conditions of the Archipelago Sea in the northern Baltic Sea. We employed public spatial data sources to describe the spatial patterns of 24 different human pressures with their normalized values in a 20 m × 20 m pixel size. Public data were also used to classify the seafloor into six different environmental types. The model output was assessed against environmental data from regular seafloor monitoring. Visual examination shows general agreement between the cumulative human pressure model and the health of the benthic fauna, seabed oxygen and, to a degree, also the tributyltin. However, although none of these field parameters show high statistical correlation with the cumulative pressure status, multiple parameters assessed simultaneously could provide a sufficient reference. Local-scale disagreements between the cumulative model and the field parameters particularly occur near the largest harbor in the region where regular dredging is practiced. Model sensitivity to different input variables was further tested by comparing 36 dissimilar variants. The comparisons reveal a general stability across the inclusion, exclusion, or modification of such spatially restricted human pressure data, which only induced local-scale details. High instabilities occurred when the tested input data had a large spatial coverage. As the cumulative human impact model reduces several human pressures into one index, it should be considered as a broad scale descriptor of the likely overall health status of the sea. When implemented with accurate local-scale data it can help coastal and marine spatial planning but it should not be considered as a predictive depiction of any particular environmental characteristic. The cumulative pressure map is particularly powerful in providing unforeseen insights into the distributions of overall anthropogenic influences within the study region, and through these it can also contribute to environmental policies.

A history of the occurence of Blidinje lake (Bosnia and Herzegovina)

Blidinje lake, or more commonly just Blidinje, is the biggest mountain lake in Bosnia and Herzegovina. It is situated in Herzegovina, between the mountains Vran and Čvrsnica, at an altitude of approximately 1,180 m. Some publications refer to it as a glacial lake. Although undoubtedly there is evidence of the prior existence of glaciers and glacial relief in the area around the lake, the morphology of the lake’s bottom and shores, changeability of the surface, and a number of records on the lake’s origin challenge the theory of the lake’s glacial origin. The aim of this paper is to use cartographic sources of spatial data, historical records, geomorphological analysis, existing literature and interviews with the local population in order to determine how and when Blidinje lake was formed. The methods used in the paper are the analysis of the available written and oral sources, geomorphological analysis, the analysis of old maps, and the analysis of toponymy. The existing historical and contemporary maps were used to perform lake surface measuring in GIS environment. All data acquired were used to disprove the glacial origin theory and to provide evidence that the lake was formed artificially by the end of the 19th century.

Exploring the relationship between density and completeness of urban building data in OpenStreetMap for quality estimation

ABSTRACTOpenStreetMap (OSM) is a free spatial data source based on crowd sourced data. Although the OSM data have a range of applications, such as generating 3D models, and routing and navigation, quality issues are still significant concerns when using the data. Several studies have undertaken quality assessments by comparing OSM data with reference data. However, reference data are not always available due to high costs or licensing restrictions, and very few studies have quantitatively estimated the quality of OSM data under conditions where the corresponding reference data are not available. This study proposed the use of a building density (or building coverage ratio) indicator as a proxy, and designed a series of experiments involving different study areas to quantitatively explore the relationship between building density and building completeness for OSM data in urban areas. The residuals (estimated building completeness and reference building completeness) were also analyzed. Two main results were found from the experiments. (1) There was an approximate linear relationship between building density and building completeness in the OSM data. More precisely, the building completeness of OSM data was approximately 3.4–4 times the building density of OSM data. (2) Approximately 70–80% of the absolute residuals were smaller than 10%, and 80–90% of them were smaller than 20%. This shows that, in most cases, estimated building completeness was close to the corresponding reference building completeness. Therefore, we concluded that the building density indicator is a potential proxy for the quantitative completeness estimation of OSM building data in urban areas. The limitations of using this indicator were also addressed.

Spatial Characteristics of Twitter Users—Toward the Understanding of Geosocial Media Production

Social media is a rich source of spatial data but it has also many flaws and well-known limitations, especially in regard to representation and representativeness, since very little is known about the demographics of the user population. At the same time, the use of locational services, is in fact, dependent on those characteristics. We address this gap in knowledge by exploring divides between Twitter users, based on the spatial and temporal distribution of the content they produce. We chose five cities and data from 2015 to represent different socio-spatial contexts. Users were classified according to spatial and non-spatial measures: home range estimation; standard distance; nearest neighbor index, and; proposed localness index. There are distinct groups of geosocial media producers, which suggests that such datasets cannot be treated as uniform representations. We found a positive correlation between spatial behavior and posting activity. It is suggested that there are universal patterns of behavior that are conditioned by software services—the example of Foucauldian “technologies of self”. They can also represent the dominance of the most prolific users over the whole data stream. Results are discussed in the context of the importance and role of user location in social media.

ANÁLISIS COMPARATIVO ENTRE SALINAS SOLARES TRADICIONALES Y OTRAS ACTIVIDADES ECONÓMICAS EN UN ESTUARIO PROTEGIDO PORTUGUÉS

This study shows that Traditional Solar Saltworks can be competitive with other land uses in the Nature Reserve of Castro Marim and Vila Real de Santo Antonio Saltmarshes (“Reserva Natural do Sapal de Castro Marim e Vila Real de Santo António”, in Portuguese), sited in the estuary of the Guadiana River (SW Iberian Peninsula, Europe); particularly, if they are specialized in extraction of Fleur de Sel (or Flower of Salt), a gourmet variety of sea salt. Artisanal sea salt production based on solar evaporationmethods of millennial history in the area is an environmentally sustainable activity in harmony withsaltmarsh landscape. Two crystallizers of a 1 ha Traditional Solar Saltworks were monitored during 70 days from June to August 2015 with the purpose of gathering detailed production data. Monitoring comprised weighing of daily Fleur de Sel harvest while coarse salt survey in one crystallizer, implied packing and weighing after two months. The competitiveness of this new commercialized variety ofsea salt was assessed with respect to other ongoing economic activities in the area, such as aquaculture,industrial salt production, and tourism. Comparison focused on the relationship between the occupied surface and production´s revenue. Water consumption was used as an economic and environmental sustainability indicator. Data were obtained through in-situ monitoring, literature review and from official statistics and spatial data sources. The results indicate that Fleur de Sel extraction in Traditional Solar Saltworks can be a high profile land use form in the area of Nature Reserve, which on a long-term basisis a sustainable activity from a socio-economic and environmental point of view.

Ad-hoc combination and analysis of heterogeneous and distributed spatial data for environmental monitoring – design and prototype of a web-based solution

ABSTRACTWith regard to a multi-dimensional and multi-facetted implementation of the vision of a Digital Earth, capabilities to combine and analyze heterogeneous spatial data sources on the web are becoming increasingly important. In this article, an online system is conceptualized and implemented to facilitate spatial data analysis and decision making specifically for environmental applications. It supports a dynamic search and binding of suitable geoprocessing functionality with respect to the given input data and target description. Geoprocessing patterns are used to create an application-oriented abstraction layer on top of generic geoprocessing services available on the web. As an application scenario the determination and quality assessment for water body structures is taken. For this use case authoritative data, remote sensing imagery and citizen science data gets combined to gain a comprehensive picture of the various spatial, temporal and thematic aspects influencing the quality of inland waters. The prototypical implementation makes use of open standards to facilitate the integration with existing spatial data infrastructures.

Ranking the City: The Role of Location-Based Social Media Check-Ins in Collective Human Mobility Prediction

Technological advances have led to an increasing development of data sources. Since the introduction of social networks, numerous studies on the relationships between users and their behaviors have been conducted. In this context, trip behavior is an interesting topic that can be explored via Location-Based Social Networks (LBSN). Due to the wide availability of various spatial data sources, the long-standing field of collective human mobility prediction has been revived and new models have been introduced. Recently, a parameterized model of predicting human mobility in cities, known as rank-based model, has been introduced. The model predicts the flow from an origin toward a destination using “rank” concept. However, the notion of rank has not yet been well explored. In this study, we investigate the potential of LBSN data alongside the rank concept in predicting human mobility patterns in Manhattan, New York City. For this purpose, we propose three scenarios, including: rank-distance, the number of venues between origin and destination, and a check-in weighted venue schema to compute the ranks. When trip distribution patterns are considered as a whole, applying a check-in weighting schema results in patterns that are approximately 10 percent more similar to the ground truth data. From the accuracy perspective, as the predicted numbers of trips are closer to real number of trips, the trip distribution is also enhanced by about 50 percent.

Orchestrating French Music Conservatories: European Political Interventions and Local Governance

Supported by the omnipresent State in the past, French music education leans increasingly towards a more liberal and competitive model. In the current context of a decentralized economy and European integration, music conservatories are called upon to contribute to regional and municipal development and enhance European student mobility. How do conservatories react to the restructuring of the competitive field? How do they affect European territorial cohesion? Are they managing adaptive or hybrid strategies with new conceptions of music education? Alternatively, do they gradually move away from the marketplace and become an obsolete and difficult heritage to maintain? To answer these questions, it is necessary to analyze the current balance of power among the different elements of the French multi-level system of conservatories, including communal, inter-communal, departmental, regional, national and European institutions. By combining different sources of spatial and statistical data, this paper contributes to constructing a comparative institutional geography of French multi-level territorial divisions. Extraction and treatment of the small data with SPSS statistical software allowed us to build a number of small-scale datasets that were merged to broader geographical databases from the French National Institute of Statistics and Economic Studies (INSEE). The geographical units that structure the INSEE databases (the zip and district codes, codes of regions, departments, GPS coordinates) made possible the location of each conservatory within municipal, departmental, regional and national spaces. A cartographic approach to studying music conservatories allows the identification of problems that deserve further detailed qualitative and statistical study in the future.

Osnovni geografski čimbenici suvremene preobrazbe Ilovika

Ilovik Island (5.51 km2) along with adjacent Sv. Petar Islet (0.95 km2) are the most southern part of Cres-Lošinj archipelago, and due to their geographical position, they represent a bridge between the above-mentioned archipelago and northern islands of Zadar archipelago (Premuda, Silba, Olib, Škarda and Ist Islands). This paper was written as a result of several field researches and the analysis of different spatial data sources within the project titled Geographical Bases of the Development of Small Croatian Islands, and it presents basic natural and geographical features of Ilovik Island as well as possibilities for its future socio-economic development.

Geografske osnove društveno-gospodarske revitalizacije Unija

Unije Island (16.88 sq. km, 90 inhabitants in 2001), together with the adjacent islets Samunčiel, Mišnjak and Školjić, makes western part of Cres-Lošinj group of islands and due to its position, it is a bridge between that group of islands and Istria Peninsula. Within the project titled Geographical Bases for the Development of Small Croatian Islands the authors did a field research and the analysis of different spatial data sources in order to analyze basic natural-geographic features, particularly from the point of view of their importance for historical-geographic development of the island and its future socio-economic development. The authors pointed out the basic geographic structures and processes that could contribute to optimal socio-economic revitalization of the island.

Mapping of coastal landforms and volumetric change analysis in the south west coast of Kanyakumari, South India using remote sensing and GIS techniques

The coastal landforms along the south west coast of Kanyakumari have undergone remarkable change in terms of shape and disposition due to both natural and anthropogenic interference. An attempt is made here to map the coastal landforms along the coast using remote sensing and GIS techniques. Spatial data sources, such as, topographical map published by Survey of India, Landsat ETM+ (30m) image, IKONOS image (0.82m), SRTM and ASTER DEM datasets have been comprehensively analyzed for extracting coastal landforms. Change detection methods, such as, (i) topographical change detection, (ii) cross-shore profile analysis, (iii) Geomorphic Change Detection (GCD) using DEM of Difference (DoD) were adopted for assessment of volumetric changes of coastal landforms for the period between 2000 and 2011. The GCD analysis uses ASTER and SRTM DEM datasets by resampling them into common scale (pixel size) using pixel-by-pixel based Wavelet Transform and Pan-Sharpening techniques in ERDAS Imagine software. Volumetric changes of coastal landforms were validated with data derived from GPS-based field survey. Coastal landform units were mapped based on process of their evolution such as beach landforms including sandy beach, cusp, berm, scarp, beach terrace, upland, rockyshore, cliffs, wave-cut notches and wave-cut platforms; and the fluvial landforms. Comprising of alluvial plain, flood plains, and other shallow marshes in estuaries. The topographical change analysis reveals that the beach landforms have reduced their elevation ranging from 1 to 3m probably due to sediment removal or flattening. Analysis of cross-shore profiles for twelve locations indicate varying degrees of loss or gain of coastal landforms. For example, the K3-K3′ profile across the Kovalam coast has shown significant erosion (−0.26 to −0.76m) of the sandy beaches resulting in the formation of beach cusps and beach scarps within a distance of 300m from the shoreline. The volumetric change of sediment load estimated based on DoD model depict a loss of 241.69m3/km2 for 62.82km2 of the area and land gain of 6.96m3/km2 for 202.80km2 of the area during 2000–2011. However, an area of 26.38km2 unchanged by maintaining equilibrium in sediment budgeting along the coastal stretch. The study apart from providing insight into the decadal change of coastal settings also supplements a database on the vulnerability of the coast, which would help the coastal managers in future.

Analysis of Site Suitability of Mosques Locations Using GIS: A Case Study of Khartoum State

The distribution of mosques needs to be assessed to help authorities to choose the appropriate location for the new mosques proposals, or to extend the existing mosques, the distribution and capacity of mosques is a serious problem in Islamic towns. This research aimed at finding appropriate planning standards, selection criteria for mosques locations and capacity by studying the current locations, distributions and capacities of the existing mosques. An aerial photograph was used as a source of spatial data. The distinctive orientation of the mosques to Gibla (Mecca holy mosque direction) facilitated their identification among other buildings. A layer of mosques was created in GIS. Each mosque area was calculated from the layer and saved in the attribute table. The actual capacity of each mosque (number of worshipers) was calculated by dividing the mosque area by 1 square meter. A buffer tool was applied, depending on the optimal distance for worshipers to access the mosques; the houses within the buffer area of each mosque were calculated to estimate the expected maximum number of worshipers for Friday prayer. The actual capacities of mosques were compared to the expected population. The results indicated that some mosques were found to be suitable; some needed to be extended within the existing location, while others could not be extended within the existing location and a new location must be determined for a new mosque within the buffer area to accommodate the expected number of worshipers.

РОБОЧА ШКАЛА МІРИ АНТРОПІЗАЦІЇ ФІЗИКО-ГЕОГРАФІЧНИХ ТАКСОНІВ УКРАЇНИ ТА ЇЇ ВЕРИФІКАЦІЙНА РЕАЛІЗАЦІЯ

In order to progress previously proposed interoperable for Ukrainian and all-European approaches procedure of anthropization extent analysis for Ukrainian landscapes, new operating scale of anthropization extent for physical-geographic taxons of Ukraine was substantiated and developed. The operating scale of anthropization extent relies, first of all, on created geoinformation basis, which is accessible for area of examination selected for the scale realization. Such area consists of physical-geographic regions and districts as plain landscape aggregations for zones of mixed and broad-leaved forests and forest-steppe. The geoinformation basis was organized by application and appropriate processing of up-to-date open digital spatial data sources. These sources contain, in particular, interactive raster land cover maps of European Space Agency (2015) and National Geomatics Center of China (2011), data of cartographic web-service OpenStreetMap, subject raster electronic maps collected in the National Atlas of Ukraine and other representative sources. There were stated peculiarities of development and implementation for the operating scale of anthropization extent, which embodies 55 operating land use and/or land cover (LULC) systems causing determinate anthropization extent, presented by corresponding to mentioned systems categories and indexes. Initial verifying realization of the anthropization extent operating scale was executed for the examination area, namely for its 25 physical-geographic regions, considering 130 physical-geographic districts, which form these regions. Realization of the scale proved, for the first, overall for examination area unfavorable geoecological situation in land use. Under such situation most of investigated regions and districts are indicated by categories of moderate-great and great anthropization (or β-euhemerobic and α-euhemerobic degree). For the second, there was constructed classed choropleth of anthropization extent categories’ fields, which were simulated for 1 km grid. For the third, there were typified percent distributions by regions for total LULC systems’ areas according to categories of these systems defined by their geoecological favorableness / unfavorableness (or degree of naturalness). Verifying-analogous comparison obtained model anthropization indicators with adequate representative foreign European results (concerning Germany and plain territory of central and west parts of Europe on the whole) proved their coincidence by content. All these jointly verify the objectivity of tools, proposed for model assessment of anthropization extent, and implementation validity of these tools. Prospects for further research were defined, aimed at detailed anthropization extent analysis, first of all by analysis of anthropization extent categories’ fields within physical-geographic districts especially by application of appropriate quasi-spectra and cumulative curves for anthropization indexes and areas.