scholarly journals SPATIAL MODELING OF THE THREAT OF DAMAGE TO THE PEATLAND ECOSYSTEM IN THE MAINLAND OF BENGKALIS REGENCY, RIAU PROVINCE

2020 ◽  
Vol 21 (2) ◽  
pp. 193-208
Author(s):  
Rizki Atthoriq Hidayat ◽  
Muhammad Hanif
Keyword(s):  
Spatial Data ◽  
Spatial Modeling ◽  
Hot Spots ◽  
Euclidean Distance ◽  
Anthropogenic Activities ◽  
Google Earth ◽  
Engine Modeling ◽  
Gis Data ◽  
High Level ◽  
High Threat

Peatlands are the stretch of ecosystem landscape with unique characteristics, both physically, chemically, and biodiversity. Anthropogenic activities in peatland use and disasters pose a threat to the preservation of the peatland ecosystem, which has impacts toward abiotic to the element of biodiversity (biotic). The purpose of this research is to model how the threat of the peatland ecosystem by using spatial data modeling. The method in this research using cloud-based GIS data analysis from Google earth engine, modeling distance parameter to variable modeling of interaction among landscapes on the peatland, and weight sum the value over raster-based spatial layer to determinate the thereat in the peatland ecosystem. The results of this study found zones where hot spots often occur. Modeling with euclidean distance to all modeling variables (except temperature) gives a clear effect on how the threats from each landscape interact with each other. We found that the threat of peatland damage in the high threat class dominates the plantation area reaching 30.9% of the total peatland area, whereas the forest landscape only has a high threat with a percentage of 1.9% and a low threat which the ecosystem is stable and natural reaching over 34.7 %. From this model, we succeeded in bringing up the idea to determine the priority area for policies where need to be done in handling the protection of peatland ecosystems, especially in plantations where the highest percentage of the ecosystem threat is in the high level with integrated peatland management. Keywords: Peatland ecosystem, landscape, threat

scholarly journals Mapping Vegetation Species Succession in a Mountainous Grassland ecosystem using Landsat and Sentinel-2 data

2021 ◽  
Author(s):  
Efosa Gbenga Adagbasa ◽  
Geofrey Mukwada
Keyword(s):  
Spatial Data ◽  
Environmental Changes ◽  
Anthropogenic Activities ◽  
Google Earth ◽  
Grass Species ◽  
Species Succession ◽  
Learning Classifier ◽  
Landsat 7 ◽  
Vegetation Species ◽  
Sentinel 2

Vegetation species succession and composition are significant factors determining the rate of ecosystem biodiversity recovery after being disturbed and subsequently vital for sustainable and effective natural resource management and biodiversity. The succession and composition of grasslands ecosystems worldwide have significantly been affected by accelerated environmental changes due to natural and anthropogenic activities. Therefore, understanding spatial data on the succession of grassland vegetation species and communities through mapping and monitoring is essential to gain knowledge on the ecosystem and other ecosystem services. This study used a random forest machine learning classifier on the Google Earth Engine platform to classify grass vegetation species with Landsat 7 ETM+ and ASTER multispectral imager (MI) data resampled with the current Sentinel-2 MSI data to map and estimate the changes in vegetation species succession. The results indicate that ASTER IM has the least accuracy of 72%, Landsat 7 ETM+ 84%, and Sentinel-2 had the highest of 87%. The result also shows that other species had replaced four dominant grass species totaling about 49 km 2 throughout the study.

scholarly journals Issues of GIS data management

2006 ◽  
Vol 1 ◽  
pp. 56-63 ◽  
Author(s):  
Tomáš Richta
Keyword(s):  
Density Distribution ◽  
Spatial Data ◽  
Large Scale ◽  
Lower Amount ◽  
Cad Systems ◽  
Small Areas ◽  
Gis Applications ◽  
Spatial Management ◽  
Gis Data ◽  
High Level

The paper deals with current issues of spatial data modelling and management used by spatial management applications. As a case study for explaining the problem, we use comparison of two main groups of software tools covering this area GIS and CAD systems - and the posibilities of their integration. Studying its functionality, we have found two main problematic issues. The first of them is the density distribution characteristics of stored data according to described area. CAD systems are oriented towards modeling individual man-made objects and structures with relatively high level of detail, so the data stored covers small areas with huge amount of information. On the other side GIS applications maintain large-scale models of real world with significantly lower amount of detail. Here the density distribution of data coverage is better balanced. So the combination of described different densities is the first problem. The second watched issue is the way of storing spatial data. While CAD data are usually stored in individual files (like DXF, IGES), GIS data tend to be stored in files or realtional databases. The question we see is, if it is possible to store CAD data along with GIS data in the same database in spite of different distribution densities and different data models. Our paper describes ways of solving this problem.

Estimating productivity of earthmoving operations using spatial technologies1This paper is one of a selection of papers in this Special Issue on Construction Engineering and Management.

2012 ◽  
Vol 39 (9) ◽  
pp. 1072-1082 ◽  
Author(s):  
Ali Montaser ◽  
Ibrahim Bakry ◽  
Adel Alshibani ◽  
Osama Moselhi
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
Data Fitting ◽  
Google Earth ◽  
Simulation Software ◽  
Distribution Functions ◽  
Automated Classification ◽  
Cycle Times ◽  
Automated Method ◽  
Spreadsheet Application

This paper presents an automated method for estimating productivity of earthmoving operations in near-real-time. The developed method utilizes Global Positioning System (GPS) and Google Earth to extract the data needed to perform the estimation process. A GPS device is mounted on a hauling unit to capture the spatial data along designated hauling roads for the project. The variations in the captured cycle times were used to model the uncertainty associated with the operation involved. This was carried out by automated classification, data fitting, and computer simulation. The automated classification is applied through a spreadsheet application that classifies GPS data and identifies, accordingly, durations of different activities in each cycle using spatial coordinates and directions captured by GPS and recorded on its receiver. The data fitting was carried out using commercially available software to generate the probability distribution functions used in the simulation software “Extend V.6”. The simulation was utilized to balance the production of an excavator with that of the hauling units. A spreadsheet application was developed to perform the calculations. An example of an actual project was analyzed to demonstrate the use of the developed method and illustrates its essential features. The analyzed case study demonstrates how the proposed method can assist project managers in taking corrective actions based on the near-real-time actual data captured and processed to estimate productivity of the operations involved.

scholarly journals Immersive Gesture Interfaces for Navigation of 3D Maps in HMD-Based Mobile Virtual Environments

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Yea Som Lee ◽  
Bong-Soo Sohn
Keyword(s):  
Virtual Environments ◽  
User Study ◽  
Simple Algorithm ◽  
3D Models ◽  
Google Earth ◽  
Depth Camera ◽  
Immersive Virtual Reality ◽  
Head Mounted Displays ◽  
Gesture Interfaces ◽  
High Level

3D maps such as Google Earth and Apple Maps (3D mode), in which users can see and navigate in 3D models of real worlds, are widely available in current mobile and desktop environments. Users usually use a monitor for display and a keyboard/mouse for interaction. Head-mounted displays (HMDs) are currently attracting great attention from industry and consumers because they can provide an immersive virtual reality (VR) experience at an affordable cost. However, conventional keyboard and mouse interfaces decrease the level of immersion because the manipulation method does not resemble actual actions in reality, which often makes the traditional interface method inappropriate for the navigation of 3D maps in virtual environments. From this motivation, we design immersive gesture interfaces for the navigation of 3D maps which are suitable for HMD-based virtual environments. We also describe a simple algorithm to capture and recognize the gestures in real-time using a Kinect depth camera. We evaluated the usability of the proposed gesture interfaces and compared them with conventional keyboard and mouse-based interfaces. Results of the user study indicate that our gesture interfaces are preferable for obtaining a high level of immersion and fun in HMD-based virtual environments.

scholarly journals Land Cover Classification Based on Cloud Computing Platform

2020 ◽  
Vol 55 (2) ◽  
Author(s):  
Nghia Viet Nguyen ◽  
Thu Hoai Thi Trinh ◽  
Hoa Thi Pham ◽  
Trang Thu Thi Tran ◽  
Lan Thi Pham ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Land Cover ◽  
Spatial Data ◽  
Google Earth ◽  
Computer Hardware ◽  
Commercial Software ◽  
Computing Platform ◽  
Land Cover Data ◽  
Cloud Computing Platform ◽  
Google Earth Engine

Land cover is a critical factor for climate change and hydrological models. The extraction of land cover data from remote sensing images has been carried out by specialized commercial software. However, the limitations of computer hardware and algorithms of the commercial software are costly and make it take a lot of time, patience, and skills to do the classification. The cloud computing platform Google Earth Engine brought a breakthrough in 2010 for analyzing and processing spatial data. This study applied Object-based Random Forest classification in the Google Earth Engine platform to produce land cover data in 2010 in the Vu Gia - Thu Bon river basin. The classification results showed 7 categories of land cover consisting of plantation forest, natural forest, paddy field, urban residence, rural residence, bare land, and water surface, with an overall accuracy of 73.9% and kappa of 0.70.

scholarly journals Estimation of Building Heights and DEM Accuracy Assessment Using ICESat-2 Data Products

2021 ◽  
Vol 10 (1) ◽  
pp. 37
Author(s):  
Goddu Pavan Sai Goud ◽  
Ashutosh Bhardwaj
Keyword(s):  
Spatial Data ◽  
Rural Areas ◽  
Urban Areas ◽  
Accuracy Assessment ◽  
Urban Expansion ◽  
Population Expansion ◽  
Cost Effective ◽  
Absolute Error ◽  
Google Earth ◽  
Surface Geometry

The use of remote sensing for urban monitoring is a very reliable and cost-effective method for studying urban expansion in horizontal and vertical dimensions. The advantage of multi-temporal spatial data and high data accuracy is useful in mapping urban vertical aspects like the compactness of urban areas, population expansion, and urban surface geometry. This study makes use of the ‘Ice, cloud, and land elevation satellite-2′ (ICESat-2) ATL 03 photon data for building height estimation using a sample of 30 buildings in three experimental sites. A comparison of computed heights with the heights of the respective buildings from google image and google earth pro was done to assess the accuracy and the result of 2.04 m RMSE was obtained. Another popularly used method by planners and policymakers to map the vertical dimension of urban terrain is the Digital Elevation Model (DEM). An assessment of the openly available DEM products—TanDEM-X and Cartosat-1 has been done over Urban and Rural areas. TanDEM-X is a German earth observation satellite that uses InSAR (Synthetic Aperture Radar Interferometry) technique to acquire DEM while Cartosat-1 is an optical stereo acquisition satellite launched by the Indian Space Research Organization (ISRO) that uses photogrammetric techniques for DEM acquisition. Both the DEMs have been compared with ICESat-2 (ATL-08) Elevation data as the reference and the accuracy has been evaluated using Mean error (ME), Mean absolute error (MAE) and Root mean square error (RMSE). In the case of Greater Hyderabad Municipal Corporation (GHMC), RMSE values 5.29 m and 7.48 m were noted for TanDEM-X 90 and CartoDEM V3 R1 respectively. While the second site of Bellampalli Mandal rural area observed 5.15 and 5.48 RMSE values for the same respectively. Therefore, it was concluded that TanDEM-X has better accuracy as compared to the CartoDEM V3 R1.

scholarly journals Olomouc - Possibilities of Geovisualization of the Historical City

2011 ◽  
Vol 6 ◽  
pp. 267-274
Author(s):  
Stanislav Popelka ◽  
Alžběta Brychtová
Keyword(s):  
Spatial Data ◽  
Large Scale ◽  
18Th Century ◽  
3D Visualization ◽  
3D Models ◽  
Google Earth ◽  
Point Of View ◽  
World Heritage Site ◽  
Historical Maps ◽  
The City

Olomouc, nowadays a city with 100,000 inhabitants, has always been considered as one of the most prominent Czech cities. It is a social and economical centre, which history started just about the 11th century. The present appearance of the city has its roots in the 18th century, when the city was almost razed to the ground after the Thirty years’ war and a great fire in 1709. After that, the city was rebuilt to a baroque military fortress against Prussia army. At the beginning of the 20th century the majority of the fortress was demolished. Character of the town is dominated by the large number of churches, burgher’s houses and other architecturally significant buildings, like a Holy Trinity Column, a UNESCO World Heritage Site. Aim of this project was to state the most suitable methods of visualization of spatial-temporal change in historical build-up area from the tourist’s point of view, and to design and evaluate possibilities of spatial data acquisition. There are many methods of 2D and 3D visualization which are suitable for depiction of historical and contemporary situation. In the article four approaches are discussed comparison of historical and recent pictures or photos, overlaying historical maps over the orthophoto, enhanced visualization of historical map in large scale using the third dimension and photorealistic 3D models of the same area in different ages. All mentioned methods were geolocalizated using the Google Earth environment and multimedia features were added to enhance the impression of perception. Possibilities of visualization, which were outlined above, were realized on a case study of the Olomouc city. As a source of historical data were used rapport plans of the bastion fortress from the 17th century. The accuracy of historical maps was confirmed by cartometric methods with use of the MapAnalyst software. Registration of the spatial-temporal changes information has a great potential in urban planning or realization of reconstruction and particularly in the propagation of the region and increasing the knowledge of citizens about the history of Olomouc.

scholarly journals Sistem Informasi Geografis Berbasis Web Digitasi Persil Bangunan

2015 ◽  
Vol 1 (1) ◽  
pp. 20-28
Author(s):  
Arief Susanto
Keyword(s):  
Information System ◽  
Spatial Data ◽  
Local Governments ◽  
Spatial Information ◽  
Geographic Information ◽  
Process Data ◽  
Desktop Application ◽  
Gis Data ◽  
Google Map Api ◽  
Advanced Development

Geographic Information Systems ( GIS abbreviated as Geographic Information System ) is a specialized information system that manages data having spatial information . Most to process data in the form of GIS data are still many who use desktop application or can only run on one computer while the more advanced development requires us to produce information more easily is to develop a GIS online ( via the Internet ) and can be accessed Anywhere You . This application is designed using DFD modeling and created using the programming language PHP with MySQL database as well as utilizing Google Map API . As well as to facilitate the collection of data by the field of local government development . Moreover , the existence of GIS aims to help local governments in the search for building plots parcels and ownership of data previously not been structured to be more structural and facilitate spatial data collection .

scholarly journals The Design and Testing of 3DmoveR: an Experimental Tool for Usability Studies of Interactive 3D Maps

2018 ◽  
pp. 31-63 ◽  
Author(s):  
Lukáš Herman ◽  
Tomáš Řezník ◽  
Zdeněk Stachoň ◽  
Jan Russnák
Keyword(s):  
Spatial Data ◽  
Response Times ◽  
3D Visualization ◽  
User Interaction ◽  
Google Earth ◽  
Web Based ◽  
3D Environments ◽  
Camera Position ◽  
Interactive 3D ◽  
3D Scene

Various widely available applications such as Google Earth have made interactive 3D visualizations of spatial data popular. While several studies have focused on how users perform when interacting with these with 3D visualizations, it has not been common to record their virtual movements in 3D environments or interactions with 3D maps. We therefore created and tested a new web-based research tool: a 3D Movement and Interaction Recorder (3DmoveR). Its design incorporates findings from the latest 3D visualization research, and is built upon an iterative requirements analysis. It is implemented using open web technologies such as PHP, JavaScript, and the X3DOM library. The main goal of the tool is to record camera position and orientation during a user’s movement within a virtual 3D scene, together with other aspects of their interaction. After building the tool, we performed an experiment to demonstrate its capabilities. This experiment revealed differences between laypersons and experts (cartographers) when working with interactive 3D maps. For example, experts achieved higher numbers of correct answers in some tasks, had shorter response times, followed shorter virtual trajectories, and moved through the environment more smoothly. Interaction-based clustering as well as other ways of visualizing and qualitatively analyzing user interaction were explored.

Sign in / Sign up

Export Citation Format

Share Document