Analisa Spasial Pemetaan Lokasi Wisata Agro (Studi Kasus Di Lombok Barat)

2017 ◽  
Vol 16 (1) ◽  
pp. 1
Author(s):  
Ahmat Adil
Keyword(s):  
Spatial Analysis ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Coffee Plantations ◽  
Community Forests ◽  
Natural Beauty ◽  
Tourism Potential ◽  
Point Line ◽  
Dimension Space

Lombok Barat is one of the districts on the island of Lombok and became a tourist destination, has the appeal of natural and cultural tourism. Conditions natural attractions consist of naturallandscapes, protected forests and community forests, beaches, plantations, and the diversity of marine potential. One element of the plantation sector which is currently untapped optimally is an agro-tourism. Agro-tourism potential is addressed from the natural beauty of the plantation and production in the plantation sector is sufficiently developed. Geographical Information Systems produces data aspects of spatial and non-spatial data. The main characteristics of the geographic information system is the ability to analyze a system such as statistical analysis and overlay called spatial analysis by adding the dimension '(space)' or geography. Spatial analysis conducted with mengoverlay two maps which then generates a new map analysis results. Spatial analysis process includes activities to create a buffer around a point (point), line (line) and area (polygon), analyzing a map with points, lines and areas with the overlay method, intersection, union, identity, and clips.  Based on the spatial analysis has been done it obtained the three locations that can be used for agro tourism, namely: a coffee plantation with an area of 9751995 m2, oil plantation area of 8.99343 million and 27.03261 million, vanilla and coffee plantations covering an area of 7,042,943 m2.

scholarly journals THE UNCERTAINTIES ON THE GIS BASED LAND SUITABILITY ASSESSMENT FOR URBAN AND RURAL PLANNING

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 523-530 ◽  
Author(s):  
H. Liu ◽  
Q. Zhan ◽  
M. Zhan
Keyword(s):  
Spatial Analysis ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Land Suitability ◽  
Geographical Information ◽  
Analysis Tool ◽  
Practical Applications ◽  
Whole Process ◽  
Suitability Assessment ◽  
Land Suitability Assessment

The majority of the research on the uncertainties of spatial data and spatial analysis focuses on some specific data feature or analysis tool. Few have accomplished the uncertainties of the whole process of an application like planning, making the research of uncertainties detached from practical applications. The paper discusses the uncertainties of the geographical information systems (GIS) based land suitability assessment in planning on the basis of literature review. The uncertainties considered range from index system establishment to the classification of the final result. Methods to reduce the uncertainties arise from the discretization of continuous raster data and the index weight determination are summarized. The paper analyzes the merits and demerits of the “Nature Breaks” method which is broadly used by planners. It also explores the other factors which impact the accuracy of the final classification like the selection of class numbers, intervals and the autocorrelation of the spatial data. In the conclusion part, the paper indicates that the adoption of machine learning methods should be modified to integrate the complexity of land suitability assessment. The work contributes to the application of spatial data and spatial analysis uncertainty research on land suitability assessment, and promotes the scientific level of the later planning and decision-making.

scholarly journals APLICACIÓN DE ÍNDICES DE FORMA EN LA DETERMINACIÓN DE POLÍGONOS SLIVERS DERIVADOS DE LAS DIMENSIONES LINEALES DE UNA FIGURA Y SU ÁREA

2017 ◽  
Author(s):  
Áurea Gallego Salguero ◽  
Miguel Sánchez Marco
Keyword(s):  
Spatial Analysis ◽  
Environmental Impact ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Work Design ◽  
Geographical Information ◽  
Government Agencies ◽  
Real Problem ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures

Nowadays cartography is more and more required by users, companies and government agencies. A lot of tasks need digital, updated and quality cartography: Civil work design, planning, landscaping, environmental impact, conservation, etc. This need of cartography is mostly solved by spatial data infrastructures and map servers that make downloading and getting maps easy. Later, using Geographical Information Systems (GIS) it is quite easy to perform queries and geoprocessing operations in order to get valuable information which is difficult to get with other tools. However slivers polygons are a serious problem. They can alter the results in spatial analysis, queries and map portray. A map with sliver polygons is a map with false polygons and therefore with errors. We need to remove them. Removing sliver polygons is simple once they have been located. The real problem is to manage to locate them. Some sliver polygons are small, others are large but in both cases sliver polygons are difficult to locate and tell them apart from other polygons. Scientists have used formulas to calculate the shape of objects for many years. Today there are dozens of formulas available that could be used in the characterization and location of polygons slivers. In this article many of these shape formulas are analyzed and conclusions are drawn on whether they can be used in locating sliver polygons.http://dx.doi.org/10.4995/CIGeo2017.2017.6567

scholarly journals A Geospatial database of gastric cancer patients and associated potential risk factors including lifestyle and air pollution

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Fatemeh Hashemi Amin ◽  
Mahtab Ghaemi ◽  
Sayyed Mostafa Mostafavi ◽  
Ladan Goshayeshi ◽  
Khadijeh Rezaei ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Cancer Patients ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Dietary Habits ◽  
Age Groups ◽  
Geographical Location ◽  
Geographical Information ◽  
Point Feature

Abstract Objectives Gastric cancer (GC) is a multifactorial disease and the fifth most frequent diagnosed cancer worldwide. It accounts for one third of cancer-related mortalities. Geospatial analysis using geographical information systems (GIS) can provide an efficient solution to identify spatial disparities associated with GC. As such, GIS enables policymakers to control cancer in a better way and identify the regions where interventions are needed. This study aims to publish a comprehensive dataset, which was applied to conduct a spatial analysis of GC patients in the city of Mashhad, Iran. Data description We provide a personal geodatabase, a Microsoft Access database that can store, query, and manage both spatial and non-spatial data, which contains four feature classes. “Male_Stomach_Cancer_Patients” and “Female_Stomach_Cancer_Patients” are point feature classes, which show the age and geographical location of 1156 GC cancer patients diagnosed between 2014 and 2017. “Air_Polution_Mashhad” is another point feature class that reveals the amount of six air pollutants, which was taken from Mashhad Environmental Pollutants Monitoring Center between 2017 and 2018. Finally, “Stomach_Cancer_and_Risk_Factors” is a polygon feature class of neighborhood division of Mashhad, consisting of contributor risk factors including dietary habits, smoking, alcohol use, body mass index and population by age groups for all 165 city neighborhoods.

A Geographical Information System (GIS) study of Triassic vertebrate biochronology

2005 ◽  
Vol 142 (4) ◽  
pp. 327-354 ◽  
Author(s):  
E. J. RAYFIELD ◽  
P. M. BARRETT ◽  
R. A. McDONNELL ◽  
K. J. WILLIS
Keyword(s):  
Spatial Data ◽  
Geographical Information Systems ◽  
Western Europe ◽  
Temporal Distribution ◽  
Geographical Information ◽  
Late Triassic ◽  
Spatial And Temporal Scales ◽  
Potential Index ◽  
The Stability ◽  
Land Vertebrate

Geographical Information Systems (GIS) have been applied extensively to analyse spatial data relating to varied environmental issues, but have not so far been used to address biostratigraphical or macroevolutionary questions over extended spatial and temporal scales. Here, we use GIS techniques to test the stability, validity and utility of proposed Middle and Late Triassic ‘Land Vertebrate Faunachrons’ (LVFs), a global biostratigraphical framework based upon terrestrial/freshwater tetrapod occurrences. A database of tetrapod and megafloral localities was constructed for North America and Western Europe that also incorporated information on relevant palaeoenvironmental variables. This database was subjected to various spatial analysis techniques. Our GIS analysis found support at a global level for Eocyclotosaurus as an Anisian index taxon and probably Aetosaurus as a Norian indicator. Other tetrapod taxa are useful biostratigraphical/biochronological markers on a regional basis, such as Longosuchus and Doswellia for Late Carnian time. Other potential index fossils are hampered, however, by taxonomic instability (Mastodonsaurus, Metoposaurus, Typothorax, Paleorhinus, Pseudopalatus, Redondasaurus, Redondasuchus) and/or are not clearly restricted in temporal distribution (Paleorhinus, Angistorhinus, Stagonolepis, Metoposaurus and Rutiodon). This leads to instability in LVF diagnosis. We found only in the western Northern Hemisphere is there some evidence for an Anisian–Ladinian biochronological unit amalgamating the Perovkan and Berdyankian LVFs, and a possible late Carnian unit integrating the Otischalkian and Adamanian.Megaplants are generally not useful for biostratigraphical correlation in the Middle and Upper Triassic of the study area, but there is some evidence for a Carnian-age floral assemblage that corresponds to the combined Otischalkian and Adamanian LVFs. Environmental biases do not appear to strongly affect the spatial distribution of either the tetrapods or megaplants that have been proposed as index taxa in biostratigraphical schemes, though several examples of apparent environmental bias were detected by the analysis. Consequently, we argue that further revision and refinement of Middle and Late Triassic LVFs is needed before they can be used to support global or multi-regional biostratigraphical correlations. Caution should therefore be exercised when using the current scheme as a platform for macroevolutionary or palaeoecological hypotheses. Finally, this study demonstrates the potential of GIS as a powerful tool for tackling palaeontological questions over extended timescales.

scholarly journals Optimal Site Selection for Sittinga Solar Park using Multi-Criteria Decision Analysis and Geographical Information Systems (GIS)

2016 ◽  
Author(s):  
Andreas Georgiou ◽  
Dimitrios Skarlatos
Keyword(s):  
Spatial Data ◽  
Geographical Information Systems ◽  
Power Plants ◽  
Solar Power ◽  
Geographical Information ◽  
Optimal Placement ◽  
Equal Weight ◽  
Analysis Tool ◽  
Study Region ◽  
Weighting Schemes

Abstract. Among the renewable powers sources, solar is rapidly becoming popular being inexhaustible, clean, and dependable. It is also becoming more efficient since the photovoltaic solar cells' power conversion efficiency is rising. Following these trends, solar power will become more affordable in years to come and considerable investments are to be expected. Despite the size of solar plants, the sitting procedure is a crucial factor for their efficiency and financial viability. Many aspects rule such decision; legal, environmental, technical, and financial to name some. This paper describes a general integrated framework to evaluate land suitability for the optimal placement of photovoltaic solar power plants, which is based on a combination of a Geographic Information System (GIS), remote sensing techniques and multi-criteria decision making methods. An application of the proposed framework for Limassol District in Cyprus is further illustrated. The combination of GIS and multi-criteria methods, consist an excellent analysis tool that creates an extensive database of spatial and non spatial data that will be used to simplify problems, to solve and promote the use of multiple criteria. A set of environmental, economic, social and technical constrains based on recent Cypriot legislation, European's Union policies and experts' advices, identifies the potential sites for solar park installation. The pair-wise comparison method in the context of the analytic hierarchy process (AHP) is applied to estimate the criteria weights in order to establish their relative importance in site evaluation. In addition, four different methods to combine information layers and check their sensitivity were used. The first considered all the criteria as being equally important and assign them equal weight, while the others grouped the criteria and graded them according to their objective perceived importance. The overall suitability of the study region for sitting solar park is appraised through the summation rule. Strict application of the framework depicts 3.0 % of the study region scoring best suitability index for solar resource exploitation, hence minimizing risk of a potential investment. However, using different weighting schemes for criteria, suitable areas may reach up to 83 % of the study region. The suggested methodological framework applied can be easily utilized by potential investors and renewable energy developers, through a front end web based application with proper GUI for personalized weighting schemes.

Understanding Accessibility

2016 ◽  
pp. 223-257
Author(s):  
Kivanc Ertugay ◽  
Sebnem H. Duzgun
Keyword(s):  
Spatial Data ◽  
Catchment Area ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Data Sets ◽  
Location Allocation ◽  
Modeling Process ◽  
Key Variables ◽  
Spatial Data Sets ◽  
Significant Support

Accessibility measures are generally concerned with equity and a better distribution of services in a territory and can be accepted as key variables for supporting supply/demand, location/allocation and service/catchment area related planning policies and strategies at national, regional, and local levels. Since accessibility measures need organization of huge and complex spatial data sets, accessibility modeling often lends itself to Geographical Information Systems (GIS) for analysis and presentation. Since numerous accessibility measures and modeling techniques ranging from simple to sophisticated can be found in the literature, this work aim to provide an overview of the theoretical framework and relevant background about GIS-based accessibility modeling process. The results could provide a significant support for the decision makers who are supposed to deal with transportation planning, accessibility modeling, location/allocation and service/catchment area related issues.

Understanding Accessibility

2018 ◽  
pp. 576-608
Author(s):  
Kivanc Ertugay ◽  
Sebnem H. Duzgun
Keyword(s):  
Spatial Data ◽  
Catchment Area ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Data Sets ◽  
Location Allocation ◽  
Modeling Process ◽  
Key Variables ◽  
Spatial Data Sets ◽  
Significant Support

Accessibility measures are generally concerned with equity and a better distribution of services in a territory and can be accepted as key variables for supporting supply/demand, location/allocation and service/catchment area related planning policies and strategies at national, regional, and local levels. Since accessibility measures need organization of huge and complex spatial data sets, accessibility modeling often lends itself to Geographical Information Systems (GIS) for analysis and presentation. Since numerous accessibility measures and modeling techniques ranging from simple to sophisticated can be found in the literature, this work aim to provide an overview of the theoretical framework and relevant background about GIS-based accessibility modeling process. The results could provide a significant support for the decision makers who are supposed to deal with transportation planning, accessibility modeling, location/allocation and service/catchment area related issues.

Spatial and Spatiotemporal Data Types as a Foundation for Representing Space-Time Data in GIS

2017 ◽  
pp. 1-28 ◽  
Author(s):  
Markus Schneider
Keyword(s):  
Spatial Data ◽  
Geographical Information Systems ◽  
Moving Objects ◽  
Spatial Databases ◽  
Query Languages ◽  
Geographical Information ◽  
Spatiotemporal Data ◽  
Data Types ◽  
Time Data ◽  
Use Of Data

A data type comprises a set of homogeneous values together with a collection of operations defined on them. This chapter emphasizes the importance of crisp spatial data types, fuzzy spatial data types, and spatiotemporal data types for representing static, vague, and time-varying geometries in Geographical Information Systems (GIS). These data types provide a fundamental abstraction for modeling the geometric structure of crisp spatial, fuzzy spatial, and moving objects in space and time as well as their relationships, properties, and operations. The goal of this chapter is to provide an overview and description of these data types and their operations that have been proposed in research and can be found in GIS, spatial databases, moving objects databases, and other spatial software tools. The use of data types, operations, and predicates will be illustrated by their embedding into query languages.

Intelligence from Space

2011 ◽  
pp. 194-226
Author(s):  
Paul Hendriks
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Spatial Analysis ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Specific Class ◽  
Step Procedure ◽  
Decision Making Processes ◽  
Projected Position ◽  
Spatial Element

The spatial element, which is omnipresent in data and information relevant to organizations, is much underused in the decision-making processes within organizations. This applies also to decision-making within the domain of Competitive Intelligence. The chapter explores how the CI function may benefit from developing a spatial perspective on its domain and how building, exploring and using this perspective may be supported by a specific class of information systems designed to handle the spatial element in data: Geographical Information Systems (GIS). The chapter argues that the key element for linking GIS to CI involves the identification of situations in which spatial analysis may support organizational decision-making within the CI domain. It presents a three-step procedure for identifying how CI may recognize spatial decision problems that are useful to boost the operation of the CI function. The first step concerns identifying relevant spatial variables, for instance by analyzing economic, demographic or political trends as to their spatial implications. The second step involves using GIS for positioning the organization with respect to the identified variables (present and projected position). The third step amounts to drawing strategic conclusions from Step 2 by assessing how the competition in relationship with the own organization would be positioned along the identified spatial analysis lines.

Spatial Autocorrelation and Association Measures

2011 ◽  
pp. 1502-1508
Author(s):  
J. Negreiros ◽  
M. Painho ◽  
I. Lopes ◽  
A.C. Costa
Keyword(s):  
Spatial Analysis ◽  
Spatial Autocorrelation ◽  
Spatial Data ◽  
Regional Analysis ◽  
Geographical Information ◽  
Association Measures ◽  
Share Data ◽  
Definition Of ◽  
Graphic Database

Several classical statements relating to the definition of GIS can be found in specialized literature such as the GIS International Journal, expressing the idea that spatial analysis can somehow be useful. GIS is successful not only because it integrates data, but it also enables us to share data in different departments or segments of our organizations. I like this notion of putting the world’s pieces back together again (ArcNews, 2000). “GIS is simultaneously the telescope, the microscope, the computer and the Xerox machine of regional analysis and the synthesis of spatial data” (Abler, 1988). “GIS is a system of hardware, software and liveware implemented with the aim of storing, processing, visualizing and analyzing data of a spatial nature. Other definitions are also possible” (Painho, 1999). “GIS is a tool for revealing what is otherwise invisible in geographical information” (Longley, Goodchild, Maguire, & Rhind, 2001). Certainly, GIS is not a graphic database.

Sign in / Sign up

Export Citation Format

Share Document