Shp Files Research Articles

Декомпозиция ретроспективных топографических карт для послойной оценки типов регионального природопользования

On the example of the most developed part of the lake Baikal basin, the decomposition of the digital coverage content from 12 sheets of the topographic map scale 1:84 000, compiled by the Corps of Military Topographers in 1896-1912, was performed. As a result of vectorization of retrospective layers of topographic objects and subsequent transformation of their shp files into classes of spatial objects of the ArcGIS environment, two cartographic sets of spatial object classes were formed that characterize two types of regional environmental management - traditional pastoral and invasive agricultural. As a result of layer-by-layer geoinformation modeling of cartographic sets on a modern topographic basis and a digital relief model, primary areas of settlement and economic use of the territory were established, physical and geographical characteristics of the past economic use of the territory were determined, and separate mapping of spatial and temporal life support structures of different types of nature management was performed. For operational digital visualization, a technological solution is proposed for storing and mapping sets of spatial object classes by organizing a file-based geodata of the ArcGIS information environment. Cartographic reconstructions of pastoral and agricultural nature management at the beginning of the 20th century are presented, as well as a general cartographic reconstruction of nature management on a landscape basis, which allows us to assert that traditional pastoral nature management does not involve the transformation of the Earth's surface and is characterized by continuous restorative dynamics of natural landscapes, and invasive nature management is based on the violation of soil cover, which later led to the emergence of areas of water and wind erosion.

Картографическая реконструкция природопользования на основе ретроспективных топографических карт

Taking the most developed part of the Baikal basin as example a digital cartographic reconstruction of the regional nature management of the early XX century is compiled; it enables establishing the physical and geographical characteristics of the territory economic use in the past. As a result of nature management objects retrospective layers vectorization and subsequent transformation of their shp files into the ArcGIS environment spatial object classes, two cartographic sets of such classes were formed. They characterize two types of regional nature use, traditional pastoral and invasive agricultural. As a result of layer-by-layer geoinformation modeling of cartographic sets on a modern topographic basis and a digital relief model, primary areas of settlement and economic use of the territory were established, and various mapping of spatial and temporal life support structures of nature management different types was performed. For operational digital visualization, a technological solution is proposed for storing and mapping sets of classes of spatial objects through arrangement of a file-based geodata of the ArcGIS information environment. Cartographic reconstructions of pastoral and agricultural nature management at the beginning of the XX century are presented, as well as its general cartographic reconstruction on landscape basis.

Sistem Informasi Geografis Pemetaan Reklame Berbasis Web

Licensing of billboards is managed by a government agency, namely the Medan City One Stop Integrated Service and Investment Service (DPMPTSP) in the fields of Licensing, Spatial Planning and Development. This study discusses the problems that occur in the Medan City DPMPTSP regarding mapping and monitoring billboard licensing by utilizing Leaflet JS technology as a medium for integrating maps into the web. The system is equipped with a route feature closest to the billboard location and is equipped with a mapping and a list of road locations that are justified and not allowed for advertising. This study uses Quantum GIS to convert shp files into GeoJSON format and Leaflet JS for map visualization. The system created can make it easier for DPMPTSP to manage and find out the status of billboards quickly and accurately and can provide information related to licensing the installation of billboards to the general public.

Easy MPE: Extraction of Quality Microplot Images for UAV-Based High-Throughput Field Phenotyping.

Microplot extraction (PE) is a necessary image processing step in unmanned aerial vehicle- (UAV-) based research on breeding fields. At present, it is manually using ArcGIS, QGIS, or other GIS-based software, but achieving the desired accuracy is time-consuming. We therefore developed an intuitive, easy-to-use semiautomatic program for MPE called Easy MPE to enable researchers and others to access reliable plot data UAV images of whole fields under variable field conditions. The program uses four major steps: (1) binary segmentation, (2) microplot extraction, (3) production of ∗.shp files to enable further file manipulation, and (4) projection of individual microplots generated from the orthomosaic back onto the raw aerial UAV images to preserve the image quality. Crop rows were successfully identified in all trial fields. The performance of the proposed method was evaluated by calculating the intersection-over-union (IOU) ratio between microplots determined manually and by Easy MPE: the average IOU (±SD) of all trials was 91% (±3).

The Use of Useful Statistics of Soil Texture According to Standardized Depth Between Two Digital Soil Maps

In Korea, a soil survey was conducted at a scale of 1: 5,000, and classification was performed based on USDA's Soil Taxonomy. Now the computerized soil map is in use. DSM work has been performed based on the soil map. Even so far, we have been building DBs in various ways and trying DSM continuously. Since 2002, data can be found on the Internet through the Korean soil information system (heugtoram) and it is also available on mobile system. Based on the 1: 5,000 scale, various detailed thematic maps are produced. The useful information has been provided to farmers, policy makers, and researchers. The basic data of the soil was used around 1970. In 2014, we tried to compare it with the newly upgraded data. R program was used to generalize the texture data (sand, silt & clay content) of soil depth. Conversion of vector data (polygon, shp file) of soil map into raster data (30 m) was performed. Soil texture data for depth were generalized to 0-5, 5-15, 15-30, 30-60, 60-100, 100-200 cm for sand, silt and clay contents and tried to compare the difference of the results. The number of polygons was the same in both sand, silt and clay contents. The total number of polygons was 1,381,126 and the number of polygons contained in the soil series was 1,308,700. As the depth increased, soils with rocks or shallow soils were not shown. Mean, standard deviation and mean deviation were analyzed for comparisons of DSM. The standard deviations were very variable and difficult to compare. The results were different from those obtained when the mean deviation was used. To compare the differences between the two maps, by converting the state in which a negative number exists to an absolute value, the average deviation to be performed is more uniform. Comparison between standard and mean deviation of sand content. Depth(cm) Map 1 Map 2 Map2 - Map1 SD MD SD MD SD MD Sand 0-5 23.85 19.88 22.96 18.94 13.02 9.29 5-15 23.61 19.85 22.89 18.98 12.36 8.87 15-30 24.43 20.31 23.40 19.45 12.40 8.94 30-60 26.07 21.61 25.04 20.80 12.13 8.79 60-100 27.77 23.53 27.28 23.05 13.72 9.60 100-200 28.61 24.59 28.51 24.43 11.99 6.94 Silt 0-5 17.39 14.29 16.67 13.58 10.96 7.93 5-15 17.15 14.07 16.47 13.44 10.64 7.72 15-30 17.53 14.57 16.63 13.66 11.07 7.99 30-60 18.06 14.80 17.52 14.47 11.11 8.03 60-100 18.94 15.83 18.39 15.29 11.93 8.12 100-200 19.37 16.50 19.46 16.52 10.81 5.84 Clay 0-5 9.79 7.86 8.90 7.16 7.46 5.58 5-15 9.89 7.79 9.08 7.30 6.98 5.12 15-30 11.42 8.76 10.38 8.16 7.48 5.31 30-60 12.98 10.17 12.15 9.71 7.29 5.02 60-100 13.82 10.91 13.20 10.97 7.85 5.37 100-200 14.39 11.39 13.13 10.93 6.94 3.91 * Map 1: 1999 data of soil texture. ** Map 2: 2014 data of soil texture.

Etude De L’évolution Du Trait De Côte À L’aide De L’outil Mobitc : Cas Du Littoral De Grand-Bassam

This study proposes an assessment of the historical coastline (TDC) mobility of the Ivorian coastline, specifically the Grand-Bassam coastline (Côte d'Ivoire), and suggests reflections on the sustainable management of the coastal environment in Côte d'Ivoire, taking into account coastal erosion. The objective is to evaluate, using the MobiTC software, the spatio-temporal and statistical evolution of the morphology of the Grand-Bassam coastal zone in order to plan appropriate coastal developments. Specifically, it is to extract images on google earth, to treat them under MobiTC and to analyze the rate of spatio-temporary and statistical evolution of coastlines. To do this, data from QuickBird images provided by Google Earth from 1984, 1988, 1992, 1996, 2000, 2004, 2008, 2012 and 2016 in the study area were used. Different software was used for image processing. The ENVI 5.1 software allowed georeferencing and thresholding to make the images superimposable and highlight the baseline. The digitization of the images was done with ArcGis software. The QGIS 2.18 software was used to convert the .shp files to the mid / mif format of the MobiTC software. The latter makes it possible to understand the statistical evolution of the coastline dynamics from the creation of a baseline, the skeleton of envelopes and traces. The variations observed between 1984 and 2016 show a fattening of 0.23 m / year in some sectors and an erosion rate of 0.34 m / year in other sectors. It is noted that 62.79% of the coastline is accretion and 37.21% is eroding.

Analysis of Home Range of Eurasian Eagle Owl (Bubo bubo) by WT-100

This study aimed to estimate the home range of Eurasian Eagle Owl (Bubo bubo) from May to November 2012. Bubo bubo were rescued by Chungnam Wild Animal Rescue Center. WT-100 weigh 83g. Analysis of home ranges used a SHP File and ArcGIS 9.0 for GIS, and used a Kernel Density Estimation (KDE) and Minimum Convex Polygon (MCP) for analysis. Home range were 39.1 km2 (MCP) and 27.8 km 2 (KDE 95%), 20.9km2 (KDE 90%), 4.2km2 (KDE 50%). Home range of Bubo bubo showed very similar results to the previous study. That is result of opportunistic foraging tactics to selecting prey.

Transferring Google Earth observations to GIS-software: example from gully erosion study

High-resolution images available on Google Earth are increasingly being consulted in geographic studies. However, most studies limit themselves to visualizations or on-screen measurements. Google Earth allows users to create points, lines, and polygons on-screen, which can be saved as Keyhole Markup Language (KML) files. Here, the use of R statistics freeware is proposed to easily convert these files to the shapefile format [or ‘.shp file format’], which can be loaded into Geographic Information System (GIS) software (ESRI ArcGIS 9 in our example). The geospatial data integration in GIS strongly increases the analysis possibilities.

GML 기반 계층적 POI 정보 가시화를 위한 GVP 개발

최근 GIS 서비스는 단순한 지도 가시화뿐만 아니라 각 개체의 위치 정보를 표시해주는 POI 서비스까지 요구한다. 하지만 POI 서비스는 개체의 위치 정보가 불충분하여 단순 지명 서비스만을 제공하고 있다. 게다가 GIS 서비스의 기반이 되는 대부분의 지리공간데이터 역시 표준화가 이루어지지 않았다. 본 논문에서는 계층적이고 사용자 중심적인 POI DB를 설계하고, 지도 가시화의 이질성과 비호환성을 극복하기 위해 GML 표준을 수용하는 GVP(GML Viewer POI)를 구축한다. GVP는 SHP 파일의 속성 정보를 관리하는 dBase 파일에 3-Layer 구조로 설계된 POI DB를 추가한다. 이에 따라서 POI 가시화는 디렉터리 형태의 그룹화된 POI 정보가 제공되므로 계층적인 검색이 가능하다. 지도 가시화와 POI 가시화로 구성된 GVP는 속성을 각각의 객체 형태로 재생성하여 사용자 이벤트에 대한 빠른 응답을 지원한다. Today, GIS service requires not only a simple map visualization but also geographical information of each object. However, POI service provides simply geographical naming service only because of lacking in geographical information of objects. In addition, geographical space data representation functioning that is the basis for most GIS has not been standardized yet. In this paper, it is designed that POI DB that is hierarchical and user-oriented and it is constructed that GVP(GML Viewer POI) that is the basis of GML specification to overcome difference and incompatibility of map visualization. GVP adds POI DB in a 3-Layer structure to dBase file managing the information of SHP file attributes. Therefore, POI visualization enables hierarchical search, by providing POI information in directory-type grouping. Consisting of map visualization and POI visualization, GVP regenerates attributes in the form of individual objects and responds to user events immediately.

Noise mapping using measured noise and GPS data

In this paper, we introduce a system to easily produce a noise map using noise and GPS data measured simultaneously. The system consists of a sound level meter, a GPS receiver, a database program to manage the measured data, and a program to produce the noise map including a computer model of the target area. The GPS receiver interfaced to the sound level meter allows simultaneous measurement and storage of the noise level and the global position at a location. The database program directly imports one or more measured data stored in the sound level meter. Then, selected measurement results are exported to the noise mapping program for producing colour-coded or noise contour line maps using measured data at user-defined locations. The noise map produced can be exported to DXF and SHP files with other modeling items, for post-processing in GIS software. To demonstrate the capability of the developed system, we show a noise map for a university campus produced by the system.

Construction of lineament maps related to groundwater occurrence with ArcView and Avenue™ scripts

A set of lineament maps has been constructed, comprising a lineament distribution map, a lineament length density map, a lineament counts density map and a lineament cross-point density map. The ArcView SHP file is used as input format. Two Avenue™ script files (Remove-node and Generalize) have been developed, in which input errors can be minimized, to optimize the original digitized lineament map data. For analyzing the lineament characteristics, five Avenue™ script files (L-STAT, Dist-to-Line, Dist-to-Cross-point, L-Selection and PL-DENS) calculating the lineament statistics (lineament length density, counts density, cross-point density, distance between a well and the nearest lineament, and distance between a well and the nearest lineament cross-point) have been developed with Avenue™ language using ArcView 3.1 GIS software. It is very easy to calculate the lineament-related values with the above five script files. They are also useful for drawing lineament density maps and for revising and compiling existing lineament density maps with ArcView 3.1 GIS software. Lineament alignment or lineament density distribution can play an important role in groundwater exploration or productivity analysis. These script files, together with well data, can facilitate analysis of the relationship between groundwater characteristics and lineament distribution.