Raster Operations Research Articles

Determination of the impacts of urban-planning of the urban land area using GIS hotspot analysis

Public investments are commonly linked with urban growth and change in points of interest (POI). This study aims to detect the changes in 5 POI categories within 250, 500, and 1000 m catchment areas around major public investments and transportation lines between 2008 and 2019 in Eskisehir city, Turkey. Due to the high number of POI data in the area, hot spot maps were produced for the target years with Kernel Density Estimation (KDE) method and subtracted with raster operation to create the POI differencing maps. The results revealed that establishing the tram line (ESTRAM) affected the emergence of POIs from 2008 to 2019, while no significant influence of other public investments on the POIs was detected in the city. Still, some investments, including Atatürk Culture and Convention Center, Şelalepark, the Zoo, and the City Hospital, had limited impacts on POIs. This research is expected to contribute to the prediction of the effects of public investments on the spatial and functional development processes and provide an analytical framework.

SPECTRAL: AWESOME SPECTRAL INDICES DEPLOYED VIA THE GOOGLE EARTH ENGINE JAVASCRIPT API

Abstract. Spectral Indices derived from Remote Sensing (RS) data are widely used for characterizing Earth System dynamics. The increasing amount of spectral indices led to the creation of spectral indices catalogues, such as the Awesome Spectral Indices (ASI) ecosystem. Google Earth Engine (GEE) is a cloud-based geospatial processing service with an Application Programming Interface (API) that is accessible through JavaScript (Code Editor) and Python. Tools for computing indices, including raster operations, normalized differences, and expression evaluation methods have been developed in the API. However, users still have to hard-code spectral indices for the JavaScript library since there are no implementations that link catalogues of spectral indices to the Code Editor. Here we present spectral, a module that links the Awesome Spectral Indices (ASI) catalogue to GEE for querying and computing spectral indices inside the Code Editor. The module allows accessing and computing spectral indices from the catalogue for multiple remote sensing products in GEE. All indices can be queried by using a key-value model and computed by using a single method. The module demonstrates that spectral indices can be easily computed inside the Code Editor. Image and Image Collection objects can be used for the calculation of all spectral indices in the catalogue if the specific dataset counts with the required bands. We anticipate that spectral will be used by most GEE users for Earth System research. Analyses conducted by the community will be sped up by avoiding hard-coding and RS investigations will be boosted.

Linear and nonlinear ultrasound time reversal using a condensing raster operation

One of the weaknesses of nonlinear methods is the excitation power required to generate nonlinear effects such as higher order harmonics (single frequency) and sidebands (dual excitation). In conjunction with the high-power prerequisite, is the required sensitivity of sensors to capture nonlinear effects which can be multiple orders of magnitude lower than the fundamental/linear response of the system. In this work a semi-air coupled nonlinear ultrasound modulation method combining phase symmetry analysis and time reversal is developed, in the aim of alleviating some of these issues. Phase symmetry analysis is used to characterise the second order and modulated nonlinear responses of a dual frequency excitation signal containing a single frequency (f1) and a sweep burst (f2). Time reversal allows for optimal focusing, in this case at locations on composites panels with barely visible impact damage. Time reversed signals typically focus at single locations at a time, in this work, a raster time reversal methodology is proposed which focuses on multiple locations simultaneously. The raster methodology reduces distortions which may affect air-coupled techniques, reduces inspection time, and shows clear enhancement of damage imaging when compared against the raw fundamental response and standard time reversal.

Developing the Raster Big Data Benchmark: A Comparison of Raster Analysis on Big Data Platforms

Technologies around the world produce and interact with geospatial data instantaneously, from mobile web applications to satellite imagery that is collected and processed across the globe daily. Big raster data allow researchers to integrate and uncover new knowledge about geospatial patterns and processes. However, we are at a critical moment, as we have an ever-growing number of big data platforms that are being co-opted to support spatial analysis. A gap in the literature is the lack of a robust assessment comparing the efficiency of raster data analysis on big data platforms. This research begins to address this issue by establishing a raster data benchmark that employs freely accessible datasets to provide a comprehensive performance evaluation and comparison of raster operations on big data platforms. The benchmark is critical for evaluating the performance of spatial operations on big data platforms. The benchmarking datasets and operations are applied to three big data platforms. We report computing times and performance bottlenecks so that GIScientists can make informed choices regarding the performance of each platform. Each platform is evaluated for five raster operations: pixel count, reclassification, raster add, focal averaging, and zonal statistics using three raster different datasets.

The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data

High-accuracy peat maps are essential for peatland restoration management, but costly, labor-intensive, and require an extensive amount of peat drilling data. This study offers a new method to create an accurate peat depth map while reducing field drilling data up to 75%. Ordinary least square (OLS) adjustments were used to estimate the elevation of the mineral soil surface based on the surrounding soil parameters. Orthophoto and Digital Terrain Models (DTMs) from LiDAR data of Tebing Tinggi Island, Riau, were used to determine morphology, topography, and spatial position parameters to define the DTM and its coefficients. Peat depth prediction models involving 100%, 50%, and 25% of the field points were developed using the OLS computations, and compared against the field survey data. Raster operations in a GIS were used in processing the DTM, to produce peat depth estimations. The results show that the soil map produced from OLS provided peat depth estimations with no significant difference from the field depth data at a mean absolute error of ±1 meter. The use of LiDAR data and the OLS method provides a cost-effective methodology for estimating peat depth and mapping for the purpose of supporting peat restoration.

Employing a spatio-temporal contingency table for the analysis of cork oak cover change in the Sa Serra region of Sardinia

Land cover change analyses are common and, especially in the absence of explanatory variables, they are mainly carried out by employing qualitative methods such as transition matrices or raster operations. These methods do not provide any estimation of the statistical significance of the changes, or the uncertainty of the model and data, and are usually limited in supporting explicit biological/ecological interpretation of the processes determining the changes. Here we show how the original nearest-neighbour contingency table, proposed by Dixon to evaluate spatial segregation, has been extended to the temporal domain to map the intensity, statistical significance and uncertainty of land cover changes. This index was then employed to quantify the changes in cork oak forest cover between 1998 and 2016 in the Sa Serra region of Sardinia (Italy). The method showed that most statistically significant cork oak losses were concentrated in the centre of Sa Serra and characterised by high intensity. A spatial binomial-logit generalised linear model estimated the probability of changes occurring in the area but not the type of change. We show how the spatio-temporal Dixon’s index can be an attractive alternative to other land cover change analysis methods, since it provides a robust statistical framework and facilitates direct biological/ecological interpretation.

A compiler approach to map algebra: automatic parallelization, locality optimization, and GPU acceleration of raster spatial analysis

Computer architectures have evolved into parallel and heterogeneous systems with multi-core CPUs, many-core GPUs, and vector instructions. Meanwhile, advances in data collection technologies have led to a rapid increase in the spatial and temporal resolution of geographic data. Efficiently dealing with large volumes of geographic data demands, now more than ever, an effective use of modern parallel computers. However, parallel programming is distinctly more challenging than writing sequential scripts. Moreover, parallelism is not the only issue; data locality is critical, too. This work addresses the issues of data escalation and parallel transition using a compiler approach to map algebra. More specifically, we design and implement a framework that uses compiler techniques to automatically speed up raster spatial analysis. In this way, users simply write sequential map algebra scripts in Python, which are translated into a graph where optimizations are applied. Then the scripts are parallelized, reordered for locality, and executed on OpenCL devices such as multi-core CPUs and GPUs. The novelty of our approach resides in the efficient organization of the execution, which we achieve via compilation. Unlike interpreters, our framework reorders the raster operations to maximize data reuse and minimize memory movements. The reordering occurs at two hierarchical levels and is controlled by a scheduler and a fusion technique. This strategy targets data locality, which, as we show, is key to the performance of raster spatial analysis. The experiments report speed-ups of one to two orders of magnitude compared to traditional interpreters.

Real-Time Cloth Rendering with Fiber-Level Detail.

Modeling cloth with fiber-level geometry can produce highly realistic details. However, rendering fiber-level cloth models not only has a high memory cost but it also has a high computation cost even for offline rendering applications. In this paper we present a real-time fiber-level cloth rendering method for current GPUs. Our method procedurally generates fiber-level geometric details on-the-fly using yarn-level control points for minimizing the data transfer to the GPU. We also reduce the rasterization operations by collectively representing the fibers near the center of each ply that form the yarn structure. Moreover, we employ a level-of-detail strategy to minimize or completely eliminate the generation of fiber-level geometry that would have little or no impact on the final rendered image. Furthermore, we introduce a simple self-shadow computation method that allows lighting with self-shadows using relatively low-resolution shadow maps. We also provide a simple distance-based ambient occlusion approximation as well as an ambient illumination precomputation approach, both of which account for fiber-level self-occlusion of yarn. Finally, we discuss how to use a physical-based shading model with our fiber-level cloth rendering method and how to handle cloth animations with temporal coherency. We demonstrate the effectiveness of our approach by comparing our simplified fiber geometry to procedurally generated references and display knitwear containing more than a hundred million individual fiber curves at real-time frame rates with shadows and ambient occlusion.

L-Bench: An Android benchmark set for low-power mobile GPUs

In recent years GPUs have become one of the most important components in mobile application processors (APs). Thus, performance measurement and analysis of mobile GPUs are crucial to mobile AP manufacturers, device manufacturers, graphics application programmers, and end users. However, it is hard to analyze mobile GPUs in depth via existing high-level (with frames per second) or low-level benchmarks (with a fill rate, ALU performance, etc.). To bridge the gap between the benchmarks, we present a novel Android benchmark set for low-power GPUs, called L-Bench. This benchmark set consists of mid-level micro-benchmarks implemented on OpenGL ES 3.1, which are carefully chosen for different workloads. By analyzing the results, this benchmark suite provides not only frames per second of each benchmark but also performance of each GPU subsystem (geometry units, ALUs, texture mapping units, raster operations pipelines, caches/memory units, and tessellators) and overall GPU performance. For experiments, we perform our benchmark suite on five representative mobile devices that have different mobile GPUs, after that, we describe comprehensive analysis of each GPU architecture.

Embedding user-generated content into oblique airborne photogrammetry-based 3D city model

ABSTRACTOblique airborne photogrammetry-based three-dimensional (3D) city model (OAP3D) provides a spatially continuous representation of urban landscapes that encompasses buildings, road networks, trees, bushes, water bodies, and topographic features. OAP3D is usually present in the form of a group of unclassified triangular meshes under a multi-resolution data structure. Modifying such a non-separable landscape constitutes a daunting task because manual mesh editing is normally required. In this paper, we present a systematic approach for easily embedding user-generated content into OAP3D. We reduce the complexity of OAP3D modification from a 3D mesh operation to a two-dimensional (2D) raster operation through the following workflow: (1) A region of interest (ROI) is selected to cover the area that is intended to be modified for accommodating user-defined content. (2) Spatial interpolation using a set of manually controlled elevation samples is employed to generate a user-defined digital surface model (DSM), which is used to reform the ROI surface. (3) User-generated objects, for example, artistically painted road textures, procedurally generated water effects, and manually created 3D building models, are overlaid onto the reformed ROI.

Alternating scanning orders and combining algorithms to improve the efficiency of flow accumulation calculation

Conventionally, a raster operation that needs to scan the entire image employs only one scanning order (i.e., single scanning order (SSO)), and the scan usually runs from upper left to lower right and row by row. We explore the idea of alternately applying multiple scanning orders (MSO) to raster operations that are based on the local direction, using the flow accumulation (FA) calculation as an example. We constructed several FA methods based on MSO, and compared them with those widely used methods. Our comparison includes experiments over digital elevation models (DEMs) of different landforms and DEMs of different resolutions. For each DEM, we calculated both single-direction FA (SD-FA) and multi-direction FA (MD-FA). In the theoretical aspect, we deducted the time complexity of an MSO sequential algorithm (MSOsq) for FA based on empirical equations in hydrology. Findings from the experiments include the following: (1) an MSO-based method is generally superior to its counterpart SSO-based method. (2) The advantage of MSO is more significant in the SD-FA calculation than in the MD-FA calculation. (3) For SD-FA, the best method among the compared methods is the one that combines the MSOsq and the depth-first algorithm. This method surpasses the commonly recommended dependency graph algorithm, in both speed and memory use. (4) The differences between the compared methods are not sensitive to specific landforms. (5) For SD-FA, the advantage of MSO-based methods is more obvious in a higher DEM resolution, but this does not apply to MD-FA.

Geospatial data sharing, online spatial analysis and processing of Indian Biodiversity data in Internet GIS domain – A case study for raster based online geo-processing

Abstract. National Biodiversity Characterization at Landscape Level, a project jointly sponsored by Department of Biotechnology and Department of Space, was implemented to identify and map the potential biodiversity rich areas in India. This project has generated spatial information at three levels viz. Satellite based primary information (Vegetation Type map, spatial locations of road & village, Fire occurrence); geospatially derived or modelled information (Disturbance Index, Fragmentation, Biological Richness) and geospatially referenced field samples plots. The study provides information of high disturbance and high biological richness areas suggesting future management strategies and formulating action plans. The study has generated for the first time baseline database in India which will be a valuable input towards climate change study in the Indian Subcontinent. The spatial data generated during the study is organized as central data repository in Geo-RDBMS environment using PostgreSQL and POSTGIS. The raster and vector data is published as OGC WMS and WFS standard for development of web base geoinformation system using Service Oriented Architecture (SOA). The WMS and WFS based system allows geo-visualization, online query and map outputs generation based on user request and response. This is a typical mashup architecture based geo-information system which allows access to remote web services like ISRO Bhuvan, Openstreet map, Google map etc., with overlay on Biodiversity data for effective study on Bio-resources. The spatial queries and analysis with vector data is achieved through SQL queries on POSTGIS and WFS-T operations. But the most important challenge is to develop a system for online raster based geo-spatial analysis and processing based on user defined Area of Interest (AOI) for large raster data sets. The map data of this study contains approximately 20 GB of size for each data layer which are five in number. An attempt has been to develop system using python, PostGIS and PHP for raster data analysis over the web for Biodiversity conservation and prioritization. The developed system takes inputs from users as WKT, Openlayer based Polygon geometry and Shape file upload as AOI to perform raster based operation using Python and GDAL/OGR. The intermediate products are stored in temporary files and tables which generate XML outputs for web representation. The raster operations like clip-zip-ship, class wise area statistics, single to multi-layer operations, diagrammatic representation and other geo-statistical analysis are performed. This is indigenous geospatial data processing engine developed using Open system architecture for spatial analysis of Biodiversity data sets in Internet GIS environment. The performance of this applications in multi-user environment like Internet domain is another challenging task which is addressed by fine tuning the source code, server hardening, spatial indexing and running the process in load balance mode. The developed system is hosted in Internet domain (http://bis.iirs.gov.in) for user access.

An integrated cellular automata evolutionary-based approach for evaluating future scenarios and the expansion of urban drainage networks

The paper describes and demonstrates an integrated cellular automata evolutionary-based approach for evaluating future scenarios including the expansion of urban drainage networks. The approach can be used to derive a drainage network layout based on future land use scenarios. Two techniques are used to derive the layout of the system: one using agent-based modelling and the other using similar principles built as a set of raster operations within ArcGIS. The tools and models are applied to a case study in Birmingham, UK. The results show that both techniques perform well for carrying out a scoping analysis at an urban scale. The case study shows that the application of the proposed approach for simulating urban growth processes and the consequent expansion of the drainage networks can achieve promising results. The interconnected drainage model for Birmingham shows that future developments will contribute further to flooding problems if no improvements are made to the existing drainage system. The same approach can be used to identify those drainage system elements that require immediate attention and which need to be replaced in order to improve the overall system performance.

3차원 그래픽스 기하 파이프라인 기반의 래스터 파이프라인 구현

래스터 연산은 트루 컬러 이미지(픽스맵)나, 단색 이미지(비트맵)을 표현하기 위해서 광범위하게 사용된다. 이 기능은 이미지 프로세싱 기능이나, 폰트 출력 시에 강하게 요구된다. 반면에, OpenGL ES 하드웨어 등을 포함하는, 현재의 모바일 그래픽스 플랫폼들에서는 이 기능을 직접 제공하지는 않는다. 모바일 그래픽스 플랫폼들에서 이러한 래스터 연산을 완벽히 제공하기 위해서, 본 논문에서는 그래픽스 이미지들을 3차원 점들의 집합으로 해석하고, 풀-소프트웨어 구현 방식으로, 이들 3차원 점들을 전형적인 3차원 기하 파이프라인으로 처리하게 했다. 구현 결과는 충분한 실행 속도를 보였고, 정확도를 증명하기 위한 공식 검증 테스트(conformance test)들을 모두 통과하였다. Raster operations are widely used to display full-color graphics images (or pixmaps) and single-color images (or bitmaps). These features are strongly needed for image processing applications and font output. However, current mobile graphics platforms, including OpenGL ES hardware implementations, do not directly support these features. To fully support those raster operations on the mobile graphics platforms, we interpreted the graphics images as a set of 3D points, and processed those 3D points through the typical 3D geometry pipelines, in a full-software implementation. Our implementation shows sufficient execution speeds, and passed the official conformance tests to show its correctness.

Accelerating batch processing of spatial raster analysis using GPU

Batch processing of raster data performed by geographic information systems (GIS) is a time consuming procedure. Modern high performance GPUs are able to perform hundreds of arithmetical operations in parallel. These GPUs can help to reduce the computing time of such operations. In addition, most of the commonly used raster operations are I/O-bounded. Memory transfer between hard disk and RAM takes up more time than computations. The scope of this paper is to present an efficient two-level caching strategy for raster data and an acceleration of selected raster operations using the GPU, which were implemented as a plugin for the open source software GRASS. An example data flow based on a real world use-case will be presented and the obtainable and practically expectable speedup will be measured and discussed.

Terrain Sculptor: Generalizing Terrain Models for Relief Shading

Shaded relief derived from high-resolution terrain models often contains distracting terrain details that need to be removed for medium- and small-scale mapping. When standard raster filter operations are applied to digital terrain data, important ridge tops and valley edges are blurred, altering the characteristic shape of these features in the resulting shaded relief. This paper introduces Terrain Sculptor, a software application that prepares generalized terrain models for relief shading. The application uses a generalization methodology based on a succession of raster operations. Curvature coefficients detect and accentuate important relief features. Terrain Sculptor offers a graphical user interface to adjust the algorithm to various scales and terrain resolutions. The freeware application is available at http://www.terraincartography.com/terrainsculptor/.

Automated Reduction of Visual Complexity in Small-Scale Relief Shading

Shaded relief derived automatically from digital elevation models differs distinctly from traditional manual shading. Particularly at small scales, many small topographic details that are present in terrain models disturb the clear portrayal of the main relief features. Automatic shading is therefore not appropriate for high-quality cartographic products. This paper proposes a new method of generalizing digital elevation models for deriving small-scale shaded relief that resembles the manual style. The procedure consists of the following raster operations: undesirable topographic details are smoothed with low-pass filters, and the main landforms, such as ridgelines and valleys, are detected by curvature coefficients. Two secondary grids are derived, one exaggerating ridgelines, the other deepening valley bottoms, and the two grids are combined according to the character of the terrain; the grid with exaggerated ridgelines is used in mountainous areas, and the grid with deepened valley bottoms in lowland areas. Finally, shaded relief is derived from the combined elevation model. Following these processing steps, only a few manual corrections are necessary to produce high-quality small-scale relief shading.

AlexVG: An OpenVG implementation with SVG-Tiny support

Embedded systems and web browsers have started to provide two-dimensional vector graphics features, to finally support scalability of graphics outputs, while traditional graphics systems have focused on the raster and bitmap operations. Nowadays, SVG and Flash are actively used and OpenVG from Khronos group plays the role of a de facto low-level API standard to support them. In this paper, we represent the design and implementation process and the final results of the first commercial OpenVG implementation, AlexVG. From its design stage, our implementation aims at the cooperation with SVG-Tiny, another de facto standard for embedded systems. Currently, our overall system provides not only the OpenVG core features but also a variety of OpenVG application programs and SVG-Tiny media file playing capabilities. For the conformance with the standard specifications, our system completely passed the whole OpenVG conformance test suites and the graphics output portions of the SVG-Tiny conformance test suites. From the performance point of view, we focused on the efficiency and effectiveness especially on the mobile phones and embedded devices with limited resources. As the result, it showed impressive benchmarks on the small-scale CPUs such as ARMs, even without neither any other libraries nor acceleration hardware. We had started commercial services of our AlexVG products since September 2005, and successfully entered the retail market with a good deal of mobile phones up to the present time.

日本と英語圏の旅行案内書からみた東京の観光名所の空間分析

Geographers have made a variety of studies using guidebooks to clarify the meaning and distribution of tourist sites in cities. Nevertheless, few studies quantitatively examine the spatial distribution of tourism sites in detail. In addition, little is known about differences among attractions in terms of the cultural backgrounds of tourists. Hence, this study made a spatial analysis of tourist attractions described in guidebooks written for Japanese and English-speaking readers. Applying kernel density estimation and raster operation method with GIS, this study clarifies that tourism attractions in guidebooks differ between Japanese and Anglophone countries. English guidebooks recommend readers to visit not only cultural sites (e.g., historic places, museums, and theatres) but also sites for nightlife (e.g., bars and taverns). In contrast, Japanese guidebooks show less interest in these types of attraction, and tend to focus more on shopping and eating. The spatial distribution of the tourism attractions also indicates some differences between Japanese and Anglophone guidebooks. Specifically, the spatial extent of tourist attractions in English guidebooks is smaller than that in Japanese guidebooks, being located close to railway stations along Yamanote Line. English guidebooks are also characterized by tourist sites for nightlife, centering on the Roppongi district. Thus, attractions listed in guidebooks are regarded as a reflection of the interests and behavior patterns of tourists.

Monitoring land subsidence in Semarang, Indonesia

Semarang is one of the biggest cities in Indonesia and nowadays suffering from extended land subsidence, which is due to groundwater withdrawal, to natural consolidation of alluvium soil and to the load of constructions. Land subsidence causes damages to infrastructure, buildings, and results in tides moving into low-lying areas. Up to the present, there has been no comprehensive information about the land subsidence and its monitoring in Semarang. This paper examines digital elevation model (DEM) and benchmark data in Geographic Information System (GIS) raster operation for the monitoring of the land subsidence in Semarang. This method will predict and quantify the extent of subsidence in future years. The future land subsidence prediction is generated from the expected future DEM in GIS environment using ILWIS package. The procedure is useful especially in areas with scarce data. The resulting maps designate the area of land subsidence that increases rapidly and it is predicted that in 2020, an area of 27.5 ha will be situated 1.5–2.0 m below sea level. This calculation is based on the assumption that the rate of land subsidence is linear and no action is taken to protect the area from subsidence.