Raster Data Research Articles

A raster-based typification method for multiscale visualization of building features considering distribution patterns

ABSTRACT In map multiscale visualization, typification is the process of replacing original objects, such as buildings, using a smaller number of objects while maintaining initial geometrical and distribution characteristics. During the past few decades, many vector-based methods for building typification have been developed, whereas raster-based methods have received less attention. In this paper, a new method for the typification of buildings with different distribution patterns called superpixel building typification (SUBT) is developed based on raster data. Using this method, buildings with different distribution patterns, such as linear, grid and irregular patterns, are first grouped by image connected component detection and superpixel analysis. Then, the new positions for building typification are determined by superpixel resegmentation. Finally, a new representation of the buildings is determined through analysis of the orientation and shape of the buildings in each superpixel. To test the proposed SUBT method, buildings from both cities and countrysides in China are applied to perform typification. The experimental results show that the proposed SUBT method can realize typification for buildings with linear, grid and irregular distributions while effectively maintaining the original distribution characteristics of the buildings.

Altitude-mediated soil properties, not geography or climatic distance, explain the distribution of a tropical endemic herb.

Understanding the ecological processes that govern species' range margins is a fundamental question in ecology with practical implications in conservation biology. The center‐periphery hypothesis predicts that organisms have higher abundance at the center of their geographic range. However, most tests of this hypothesis often used raster data, assuming that climatic conditions are consistent across one square km. This assumption is not always justified, particularly for mountainous species for which climatic conditions can vary widely across a small spatial scale. Previous studies rarely evenly sample occurrence data across the species' distribution. In this study, we sampled an endemic perennial herb, Thunbergia atacorensis (Acanthanceae), throughout its range in West Africa using 54 plots and collected data on (a)biotic variables, the species density, leaf mass per area, and basal diameter. We built a structural equation model to test the direct and indirect effects of distance from geographic and climatic niche centers, and altitude on Thunbergia density as mediated by abiotic and biotic factors, population demographic structure, and individual size. Contrary to the prediction of the center‐periphery hypothesis, we found no significant effect of distance from geographic or climatic niche centers on plant density. This indicates that even the climatic center does not necessarily have optimal ecological conditions. In contrast, plant density varied with altitudinal gradient, but this was mediated by the effect of soil nitrogen and potassium which had positive effect on plant size. Surprisingly, we found no direct or mediating effect of interspecific competition on plant density. Altogether, our results highlight the role of geography, climatic, and ecological mismatch in predicting species distribution. Our study highlights that where altitudinal gradient is strong local‐scale heterogeneity in abiotic factors can play important role in shaping species range limits.

Automatic Segmentation of Sinkholes Using a Convolutional Neural Network

AbstractSinkholes are the most abundant surface features in karst areas worldwide. Understanding sinkhole occurrences and characteristics is critical for studying karst aquifers and mitigating sinkhole‐related hazards. Most sinkholes appear on the land surface as depressions or cover collapses and are commonly mapped from elevation data, such as digital elevation models (DEMs). Existing methods for identifying sinkholes from DEMs often require two steps: locating surface depressions and separating sinkholes from non‐sinkhole depressions. In this study, we explored deep learning to directly identify sinkholes from DEM data and aerial imagery. A key contribution of our study is an evaluation of various ways of integrating these two types of raster data. We used an image segmentation model, U‐Net, to locate sinkholes. We trained separate U‐Net models based on four input images of elevation data: a DEM image, a slope image, a DEM gradient image, and a DEM‐shaded relief image. Three normalization techniques (Global, Gaussian, and Instance) were applied to improve the model performance. Model results suggest that deep learning is a viable method to identify sinkholes directly from the images of elevation data. In particular, DEM gradient data provided the best input for U‐net image segmentation models to locate sinkholes. The model using the DEM gradient image with Gaussian normalization achieved the best performance with a sinkhole intersection‐over‐union (IoU) of 45.38% on the unseen test set. Aerial images, however, were not useful in training deep learning models for sinkholes as the models using an aerial image as input achieved sinkhole IoUs below 3%.

GeoSPARQL query support for scientific raster array data

This paper presents the design of a GeoSPARQL query processing solution for scientific raster array data, called GeoLD. The solution enables the implementation of SPARQL endpoints on top of OGC standard Web Coverage Processing Services (WCPS). Thus, the semantic querying of scientific raster data is supported without the need of specific raster array functions in the language. To achieve this, first Coverage to RDF mapping solutions were defined, based on the well-known W3C standard mappings for relational data. Next, the SPARQL algebra is extended with a new operator that delegates part of the GeoSPARQL query in WCPS services. Query optimization replaces those parts of the SPARQL query plan that may be delegated to a WCPS service by instances of such new WCPS operator. A first prototype has been implemented by extending the ARQ SPARQL query engine of Apache Jena. Petascope was used as the WCPS implementation on top of the Rasdaman raster array database. An initial evaluation with real meteorological data shows, as it was initially expected, that the approach outperforms an existing reference relational database based GeoSPARQL implementation.

The Process of Making, Organizing and Using Thematic Layers in GIS

s Geographic Information System (GIS), as part of the Geoinformation Sciences, deals with a complete system of creating, handling, storing, manipulating, using analysis and presenting information related to the Earth’s surface it is in the direct function of solving fundamental problems / issues arising from that process. The organization of data is according to the system of thematic data layers. The research conducted includes the formation of GIS for different types of research for the Tara Mountain area, Serbia. During these researches, various thematic data layers were created. The types of data used in the creation of these layers are: vector, attribute with organized database, raster data and digital models. The processed contents present abiotic, biotic and anthropogenic elements of the real environment. The paper presents specific indicators created in the process of GIS development. Qualitative, quantitative and visual representation of the real environment was achieved. The results of multicriteria thematic and topological analyzes are also presented. System decisioning support is achieved.

Supervised Classification Model Using Google Earth Engine Development Environment for Wasit Governorate

As a result of the advancements that have occurred in the technical field of geomatics, particularly after the development of developmental programming environments, they have become the most important machine for conducting image analyses of satellite data, creating and modifying spatial analysis tools, and performing large data analyses at a fast rate without the need for high-end specifications on the personal computer. This study has several objectives, including the definition and popularization of the use of the power of Google Earth Engine (GEE) in the speed of conducting spatial analyzes, which cite by conducting a classification at the level of a governorate and obtaining results with speed and relatively good quality. By using the Google Earth Engine (GEE) platform and through Javascript programming language, a classification of the land cover of Wasit Governorate, Iraq was created under the supervision of a satellite image (Landsat 8) by creating a training sample, Google Maps’ High Resolution basemap imagery was used to create this map to identify classes of landcover (water, bare soil, vegetation, and urban). Each source pixel is assigned to one of the previously mentioned classes. Then to create a land cover map of the region using the Statistical Machine Intelligence and Learning Engine (SMILE) classifier from the JAVA library, which is used by Google Earth Engine (GEE) to implement these algorithms. The result is an array of pixels (raster data). The pixel value represents the class that was previously determined by the samples.

QScout: A QGIS plugin tool suite for georeferencing and analysis of field‐scouted and remote sensing data

AbstractField scouting is an important part of many research methodologies in plant pathology and plant phenomics. However, linking scouting data to field imagery is often hampered by the time‐consuming task of georeferencing with a GIS. Here, we present the QScout tool suite for integrating remote sensing imagery and raster data with field‐scouting data in QGIS, an open‐source GIS program. The central features of QScout are the Drop Pins and Locate Pins plugins, allowing the user to easily link scouted data to remote sensing imagery. QScout also includes the Value Grabber and Grid Aggregator plugins, which transfer raster data into pins and aggregate the data from the pins into a grid, respectively. The final tools, Drop, Grab, and Aggregate and Locate, Grab, and Aggregate, are plugins that combine subsets of the four core plugins. The interface allows GIS users to effectively make use of field‐scouted observations with remote imagery and can improve data organization, analysis, and identification of locations of interest for further scouting or targeted management. QScout is publicly available as a GitHub repository: (https://github.com/GoldLabGrapeSPEC/QScout).

Reviewing Methods for Controlling Spatial Data Quality from Multiple Perspectives

Spatial data is the core and operation object of geographic information system (GIS). The quality of spatial data determines the application of GIS and the effectiveness of decision-making to a great extent. This article introduces two important types of spatial data, vector data and raster data. Then, this paper discusses the uncertainty and sources of errors in spatial data, and discusses the methods of checking and preventing uncertainty and errors from the aspects and processes of digitization, so as to ensure the quality of spatial data. Finally, this paper explores cutting-edge approaches to improving spatial data quality, including the Area preserving method for improved categorical raster resampling, and using hierarchical grid index to detect and correct errors in vector elevation data. By studying effective data quality control methods, the quality of spatial data in GIS can be guaranteed, and the basic guarantee for the wide application and development of geographic information science can be provided.

Synthesizing Optical and SAR Imagery From Land Cover Maps and Auxiliary Raster Data

We synthesize both optical RGB and synthetic aperture radar (SAR) remote sensing images from land cover maps and auxiliary raster data using generative adversarial networks (GANs). In remote sensing, many types of data, such as digital elevation models (DEMs) or precipitation maps, are often not reflected in land cover maps but still influence image content or structure. Including such data in the synthesis process increases the quality of the generated images and exerts more control on their characteristics. Spatially adaptive normalization layers fuse both inputs and are applied to a full-blown generator architecture consisting of encoder and decoder to take full advantage of the information content in the auxiliary raster data. Our method successfully synthesizes medium (10 m) and high (1 m) resolution images when trained with the corresponding data set. We show the advantage of data fusion of land cover maps and auxiliary information using mean intersection over unions (mIoUs), pixel accuracy, and Fr\'echet inception distances (FIDs) using pretrained U-Net segmentation models. Handpicked images exemplify how fusing information avoids ambiguities in the synthesized images. By slightly editing the input, our method can be used to synthesize realistic changes, i.e., raising the water levels. The source code is available at https://github.com/gbaier/rs_img_synth and we published the newly created high-resolution dataset at https://ieee-dataport.org/open-access/geonrw.

三峡库区低山丘陵区多尺度景观指数响应及适宜粒度

PDF HTML阅读 XML下载 导出引用 引用提醒 三峡库区低山丘陵区多尺度景观指数响应及适宜粒度 DOI: 10.5846/stxb202106081511 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 三峡库区农林复合小流域土壤氮磷流失与径流侵蚀耦合机制研究（32171877） Suitable granularity and response of multi-scale landscape in low mountain and hilly area of the Three Gorges Reservoir Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:景观格局具有典型的空间异质性和尺度依赖性。在对景观格局进行分析研究时需跨越多个尺度，空间粒度大小在尺度聚合分析中至关重要。三峡库区低山丘陵区斑块破碎、景观格复杂性显著、景观格局特征及尺度变异规律仍待明确，本文以三峡库区秭归县为研究区，设定1-400m内23个粒度梯度水平，定量评估县域、乡镇以及小流域不同幅度上的景观格局指数以及拟合函数，探讨多空间幅度景观格局指数随粒度大小的变化特征。基于景观指数的粒度效应特征和拟合函数的曲线特征（最大曲率点、极值点），明确适宜不同幅度的山地景观格局指数研究的粒度阈值，以揭示库区低山丘陵区景观结构的复杂性和变异性。结果表明：不同景观指数对空间粒度变化和空间幅度变化的响应存在差异，不同景观指数的空间粒度响应主要呈现增加、降低、波动和无明显规律变化的趋势，其中斑块密度、最大斑块面积等指数对斑块形状和大小的变化敏感，而多样性指数的粒度变化敏感度较低；部分指数如斑块密度、边缘密度、周长面积分维数等对空间幅度的变化并不敏感，而最大斑块面积、景观形状指数、散布与并列指数、分离度等指数对空间幅度的变化敏感，适合进行不同幅度适宜粒度阈值的推定；边缘密度、平均斑块大小、景观形状指数、蔓延度、相似邻接比例等多个景观指数可高度拟合曲线函数，通过拟合函数的曲线特征分析确定景观指数的变化转折点，降低人工判断的差异性；基于251个小流域、12个乡镇和秭归县的6072幅栅格数据的各景观指数变化趋势和变化转折点，综合各景观指数的转折变化点，得出小流域、乡镇、秭归县景观格局分析的第一尺度粒度阈值分别为3m、4m、7m，第二尺度粒度阈值分别为50m、100m、100m，空间幅度越小则景观格局分析所需要的适宜粒度越小。 Abstract:Landscape patterns have typically spatial heterogeneity and scale dependence; thus it needs to span multiple scales in landscape pattern analysis. Therefore, the spatial granularity is crucial in scale aggregation. In the hilly area of the Three Gorges Reservoir area, patches are fragmented, landscape complexity is significant, and landscape pattern characteristics and scale variation are still to be clarified. In this study, we focused on Zigui County in the Three Gorges Reservoir, set 23 grain size gradient levels within 1-400 m, quantitatively evaluated the landscape pattern index and fitting function of the county, towns, and small basins at different amplitudes to explore more margin space landscape pattern index characteristics associated with the change in particle size. Based on the grain size effect characteristics of the landscape index and the curve characteristics (maximum curvature point and extreme value point) of the fitting function, a suitable grain size threshold of the mountain landscape pattern index with different amplitudes was determined, so as to reveal the complexity and variability of mountain landscape structure in the hilly region of the Three Gorges Reservoir. The responses of different landscape indices to the changes in spatial granularity and spatial amplitude differed. The responses of different landscape indices to the changes in spatial granularity can be summarized as four trends:increase, decrease, fluctuation, and no obvious regular change. Patch Density and the Largest Shape Index are sensitive to changes in patch shape and size, whereas the sensitivity of Diversity Index to the change in grain size is inapparent. Patch Density, Edge Density, and Perimeter-Area Fractal Dimension are not sensitive to the change in spatial amplitude, whereas the Largest Patch Index, Landscape Shape Index, Interspersion and Juxtaposition Index, and Splitting Index are sensitive to the change in spatial amplitude and are suitable for prediction of the threshold of appropriate grain size for different amplitudes. Landscape indices such as Edge Density, Mean Patch Size, Landscape Shape Index, Contagion Index, and Percentage of Like Adjacency can be highly fitted to the curve function, and the curve characteristics of the fitting function can be used to identify the turning point of the change in the landscape index and reduce the difference in artificial judgment. Based on the changing trends and turning points of the landscape indices of 6072 raster data of 251 small basins, 12 townships, and Zigui County, the first-scale granularity threshold for landscape pattern analysis of small basins, towns, and Zigui County is 3 m, 4 m, and 7 m, while the second-scale particle size threshold is 50 m, 100 m, and 100 m, respectively, integrating the turning points of each landscape index. Thus, the smaller the spatial amplitude, the smaller the suitable grain size for landscape pattern analysis. 参考文献 相似文献 引证文献

Webmapping of Floods in the West of the Ivorian Coast

To provide answers to the problem of the management of its coastal zone, Côte d’Ivoire has initiated a pooling of data collected on the coast to feed its environmental information management system. To this end, it was a question of creating an interactive platform for decision support for the development of this coastal zone. To achieve this objective, high spatial resolution raster data from 15 to 90 m from the Shuttle Radar Topography Mission and land cover vector data from 2017 were collected for processing in Websig software (QGIS 3.4, PostGreSql 10.5, PostGIS), published and displayed in Geoserveur for programming HTML, CSS and JavaScript codes in Atom. The results first made it possible to visualize the main issues in the interface, in particular, the rivers, the classified forests, the degraded forests, the intact forests, the housing and the industrial plantations and then to assess the risks of floods in Sassandra and San-Pédro. For overflow hazards 100 m beyond the shore, it is the houses, part of the forests and some bare soil that are submerged. As for the risks of overflowing 200 to 500 m beyond the shore, it is a large part of the housing, soils and intact forests that will be flooded. This tool must be made available to the final beneficiaries (users) by putting it online and listing it in the main search engines.

Enabling Efficient Distributed Spatial Join on Large Scale Vector-Raster Data Lakes

Both the increasing number of GPS-enabled mobile devices and the geographic crowd-sourcing initiatives, such as Open Street Map, are determinants for the large amount of vector spatial data that is currently being produced. On the other hand, the automatic generation of raster data by remote sensing devices and environmental modeling processes was always leading to very large datasets. Currently, huge data generation rates are reached by improved sensor observation systems and data processing infrastructures. As an example, the Sentinel Data Access System of the Copernicus Program of the European Space Agency (ESA) was publishing 38.71 TB of data per day during 2020. This paper shows how the assumption of a new spatial data model that includes multi-resolution parametric spatial data types, enables achieving an efficient implementation of a large scale distributed spatial analysis system for integrated vector-raster data lakes. In particular, the proposed implementation outperforms the state-of-the-art Spark-based spatial analysis systems by more than one order of magnitude during vector-raster spatial join evaluation.

Georeferencing 3D Tiles Generated from Photogrammetry-Derived Mesh Using Ground Control Points

In order to achieve efficient visualization of massive 3D photogrammetry models on the web-based virtual globe, original photogrammetry 3D models should be converted into 3D Tiles with accurate georeferencing information to render on the correct surface position. There are a few software tools and online platforms for generating 3D Tiles and various ways to generate 3D Tiles were reported, but none of them do not provide a way to georeference 3D Tiles with GCPs. This paper is intended to suggest an approach to georeference 3D Tiles with GCPs based on the Kabsch algorithm which is very similar to georeferencing raster data with GCPs in the traditional GIS. First, we mathematically describe how to apply the Kabsch algorithm for georeferencing 3D Tiles with GCPs. Following this description, we demonstrate our implementation allowing constructing GCPs and calculating the “transform” property of 3D Tiles. Finally, we tested the suggested method in Construkted Reality which is the platform to stream and visualize massive photogrammetry and point clouds datasets.

The Orthophotomap of Lublin 1944: from Luftwaffe photographs to map application – idea, methods, contemporary challenges of processing and publishing archival aerial photographs

Abstract The origins of aerial photography can be traced back to the second half of the 19th century, and periods of World Wars contributed to the development of techniques for developing and disseminating aerial photographs for military purposes. In the literature, we find descriptions of the Polish Military Geographical Institute’s (WIG) use of aerial photography to update topographic maps of nearly 40% of the country’s area at the time. Unfortunately, the fate of the pre-war collection of photographs is difficult to establish. Given this, the aerial photographs from the period of the Second World War (German and Allied) constitute the oldest possible complete and consistent photographic documentation of Poland. The series of German prints (373-GXPRINTS) collected at the National Archives and Records Administration in College Park (NARA, USA) are maintained according to the most liberal policy on access and further use. At the same time, the organisation of the NARA archive and the extent to which the collection has been digitised (over one million images) leave a deficiency, and searching for images requires knowledge, methods and experience. In 2020–2021, the Department of Geomatics and Cartography of the Maria Curie-Skłodowska University implemented the project Development of the Ortophotomap of Lublin 1939–1945 (NCN, Miniatura 4.0. No. 2020/04/X/HS4/00382). The result of the project is a dedicated web portal https://ortolub.umcs.pl, consisting of a digital repository of aerial images, a map application and standardised GIS raster data services. The author believes this is a unique source base, with unprecedented detail. The publication of the project results under the Creative Commons CC-BY-SA 4.0 licence is intended to foster the widest possible use of wartime aerial images in scientific research and popularisation activities. The process of developing a historical orthophotomap, as presented in the article, is universal and can be repeated on any set of aerial photographs. At the same time, development work is needed to automate the operations as fully as possible. In conclusion, current challenges and prospects for the development of historical orthophotomaps of national coverage are indicated.

Land Geoparcel-Based Spatial Downscaling for the Microwave Remotely Sensed Soil Moisture Product

The spatial downscaling of soil moisture (SM) provides a technical tool to solve the problem of coarse resolution of passive microwave products. However, conventional methods are developed based on the kilometer scale grid pixels of remote sensing images. The regular rough grids will lead to the mixing and uncertainty of SM information. In this paper, we formulate a novel land geoparcel-based spatial downscaling technique for the Soil Moisture Active Passive (SMAP) satellite products. It is developed by combining XGBoost (eXtreme Gradient Boosting) machine learning algorithm with the support of geoparcel vector data and a variety of auxiliary raster data. The downscaling effect is evaluated by using SMAP 9km products and site measured data in Tongnan District of Chongqing, China. The experiments show that the geoparcel-based downscaling method maintains the dynamic range of the original SM product, and conserves energy before and after downscaling. It is proved that our method effectively increases the spatial details of the original SM product with complete spatial coverage. The comparison and analysis with the ground verification data demonstrate that the formalized procedure with geoparcel-based spatial downscaling allows better results than those of using km-scale regular grids.

Exploring environmental connection: ecological network opportunities in the Shahdagh National Park, Azerbaijan

The high growth rate of consumption of natural resources by people in the last century have seriously and negatively affected ecosystems and led to the loss of biodiversity. At present, it is important to take the necessary measures to ensure sustainable development and biodiversity conservation. Ecological networks play an important role in maintaining and controlling the stability and balance of communication between ecosystem complexes. For this purpose, the possibility of creating an ecological network that includes core areas, buffer zones, ecological corridors and restoration areas in the section of Shamakhi district of the Shahdagh National Park was explored. The designated buffer zone of the national park includes 14 villages and 1 settlement type administrative unit. Mountainous landscapes predominate in the area, and the absolute height ranges from 500-200 m. Riverbeds, intermountain depression, mountain passes, trails and forests which should be planted in the areas we offer, were considered as main factors during the construction of ecological corridors in the national park and the buffer zones. The materials obtained from the literature and our field studies, also, vector and raster data were used during the site identification. The data was processed in software such as ArcGIS 10, ERDAS Imagine, Global Mapper, Google Earth, etc. Existing ecosystems were identified, and areas were calculated in separate elements of the ecological network in the study area.

Mapping Land Use and Land Cover in the Upper Ciliwung Watershed Using Landsat Tree Cover (TC) Data

<p class='IJASEITAbtract'>Land use and land cover (LULC) mapping using Landsat Tree Cover (TC) data that we employed was digital classification by converting Landsat TC raster data into Landsat TC vector data and determining LULC classes in the attribute table based on percent TC criteria (interval TC- min - TC-max). The classification was adapted from the LCCS classification and partially modified. Compared to conventional digital image classification (supervised and unsupervised classifications), our digital classification method is easier and faster because Landsat TC data does not require pre-processing and reclassification to improve classification accuracy. Landsat TC classification accuracy was assessed against the interpretation of a very high spatial resolution (VHSR) image available in Google Earth (GE). The purpose of the study was to determine the ability of Landsat TC data paired with percent TC criteria of LULC adapted from the LCCS classification and validated with VHSR in GE for mapping LULC in the tropics. This study was conducted in the Upper Ciliwung watershed, which is located in Bogor Regency, West Java Province, Indonesia. LULC mapping using Landsat TC data paired with percent TC criteria of LULC adapted from the LCCS classification and validated with VHSR in GE provided a useful tool for producing LULC map in the Upper Ciliwung watershed. This study classified LULC in the Upper Ciliwung watershed consisting of settlements, closed forests, medium forests, opened forests, mix gardens, tea plantations, shrub lands, grasslands, and rainfed croplands paddy fields, fish fonds, and bare lands with overall accuracy of 91%.

Bedrock Geologic Map of the Northern Half of the Bedford 30- X 60-Minute Quadrangle, Indiana

The Bedrock Geologic Map of the Northern Half of the Bedford 30- X 60-Minute Quadrangle is an Esri File Geodatabase that contains six feature data sets, five geodatabase tables, and two raster data sets detailing the bedrock geology of the northern half of the Bedford 30- X 60-minute quadrangle in Indiana. This data set conforms to "GeMS (Geologic Map Schema)--a standard format for the digital publication of geologic maps." For more information on GeMS please refer to the supplemental information within this metadata.

An Efficient Group-Based Replica Placement Policy for Large-Scale Geospatial 3D Raster Data on Hadoop.

Geospatial three-dimensional (3D) raster data have been widely used for simple representations and analysis, such as geological models, spatio-temporal satellite data, hyperspectral images, and climate data. With the increasing requirements of resolution and accuracy, the amount of geospatial 3D raster data has grown exponentially. In recent years, the processing of large raster data using Hadoop has gained popularity. However, data uploaded to Hadoop are randomly distributed onto datanodes without consideration of the spatial characteristics. As a result, the direct processing of geospatial 3D raster data produces a massive network data exchange among the datanodes and degrades the performance of the cluster. To address this problem, we propose an efficient group-based replica placement policy for large-scale geospatial 3D raster data, aiming to optimize the locations of the replicas in the cluster to reduce the network overhead. An overlapped group scheme was designed for three replicas of each file. The data in each group were placed in the same datanode, and different colocation patterns for three replicas were implemented to further reduce the communication between groups. The experimental results show that our approach significantly reduces the network overhead during data acquisition for 3D raster data in the Hadoop cluster, and maintains the Hadoop replica placement requirements.

Forest area changes throughout the years in Bjelovarsko-Bilogorska County

The results of forest cover reduction were obtained using raster data and administrative borders for the Republic of Croatia. Examples are taken from other countries to compare the results and show the reduction of cover, both forest and agricultural. The first part of this paper describes the situation in the Republic of Croatia, where Ministry of Environmental Protection provided analysis. The condition of land cover in the Republic of Croatia is presented. The second part of this paper is a description of the task development process in the software package "QGIS". From adding CLC raster data to, the actions performed in the program that were performed until the results arrived. Finally, the interpretation of the obtained data and the conclusion follow.