scholarly journals Analysis of Differences in the Spatial Distribution among Terrestrial Mammals Using Geodetector—A Case Study of China

2021 ◽  
Vol 10 (1) ◽  
pp. 21
Author(s):  
Yao Chi ◽  
Tianlu Qian ◽  
Caiying Sheng ◽  
Changbai Xi ◽  
Jiechen Wang
Keyword(s):  
Spatial Distribution ◽  
Species Richness ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Mammalian Species ◽  
Geographical Information ◽  
Individual Factor ◽  
Factors Affecting ◽  
Terrestrial Mammals ◽  
Spatial Differences

The survival and distribution of animals cannot be separated from a certain environment. How patterns in mammalian species depend on the environment remain unclear. This study incorporating spatial data on climate, precipitation, topography, and vegetation quantitatively analyzed the influence of specific geographical factors on the spatial distribution of terrestrial mammalian richness using the Geodetector model. We used the spatial analysis method of geographical information systems (GIS), separating the mammalian distribution of 621 species into 10 by 10 km grids to measure spatial richness. Our results showed that there were significant spatial differences in terrestrial mammalian richness in China. There was a low richness in the east and west, but high richness in the south. Individual factor detection results showed that annual precipitation (AP) and the minimum temperature of the coldest month (MTCM) were the dominant factors affecting the spatial pattern of mammal richness in China. Patterns in the distribution of species richness had distinct characteristics for different mammalian orders and were influenced by different environmental factors. The richness distribution of most orders was mainly affected by MTCM and AP. Interactive detection results showed that interacting factors in pairs play much bigger roles in the spatial distribution of species richness than individual factors. The synergistic effect of elevation with AP and MTCM best explained the distribution differences of species richness. We found that the Geodetector model is a valuable tool, hoping to be more widely used in biogeography.

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.

scholarly journals Multivariate clustering of reindeer herding districts in Sweden according to range prerequisites for reindeer husbandry

Rangifer ◽  
2009 ◽  
Vol 27 (2) ◽  
pp. 107-119
Author(s):  
Henrik Lundqvist ◽  
Öje Danell
Keyword(s):  
Geographical Information Systems ◽  
Large Scale ◽  
Global Climate ◽  
Meteorological Data ◽  
Principal Component ◽  
Geographical Information ◽  
Reindeer Herding ◽  
Factors Affecting ◽  
Decision Tools ◽  
Forage Value

The 51 reindeer herding districts in Sweden vary in productivity and prerequisites for reindeer herding. In this study we characterize and group reindeer herding districts based on relevant factors affecting reindeer productivity, i.e. topography, vegetation, forage value, habitat fragmentation and reachability, as well as season lengths, snow fall, ice-crust probability, and insect harassment, totally quantified in 15 variables. The herding districts were grouped into seven main groups and three single outliers through cluster analyses. The largest group, consisting of 14 herding districts, was further divided into four subgroups. The range properties of herding districts and groups of districts were characterized through principal component analyses. By comparisons of the suggested grouping of herding districts with existing administrative divisions, these appeared not to coincide. A new division of herding districts into six administrative sets of districts was suggested in order to improve administrative planning and management of the reindeer herding industry. The results also give possibilities for projections of alterations caused by an upcoming global climate change. Large scale investigations using geographical information systems (GIS) and meteorological data would be helpful for administrative purposes, both nationally and internationally, as science-based decision tools in legislative, economical, ecological and structural assessments. Abstract in Swedish / Sammanfattning: Multivariat gruppering av svenska samebyar baserat på renbetesmarkernas grundförutsettningar Svenska renskötselområdet består av 51 samebyar som varierar i produktivitet och förutsättningar för renskötsel. Vi analyserade variationen mellan samebyar med avseende på 15 variabler som beskriver topografi, vegetation, betesvärde, fragmentering av betesmarker, klimat, skareförekomst och aktivitet av parasiterande insekter och vi föreslår en indelning av samebyar i tio grupper. Den största gruppen, som bestod av 14 samebyar, delades vidare in i 4 undergrupper. Klusteranalyser med 4 olika linkage-varianter användes till att gruppera samebyarna. Principalkomponentsanalys användes för att kartlägga undersökta variabler och de resulterande samebygruppernas karaktär. Samebygrupperna följde inte länsgränser och tre samebyar föll ut som enskilda grupper. Denna undersökning ger underlag för jämförelser mellan samebyar med beaktande av likheter och olikheter i fråga om produktivitet och funktionella särdrag istället för länsgränser och historik. Vi föreslår en ny administrativ indelning i sex områden som skulle kunna fungera som ett alternativt underlag för planering och beslut som rör produktionsaspekter i rennäringen. Resultaten ger också underlag för förutsägelser av förändringar i samebyars produktionsförutsättningar till följd av klimatförändringar.

scholarly journals Spatial Analysis of Seasonal Precipitation Using Various Interpolation Methods in the Euphrates Basin, Turkey

2021 ◽  
Author(s):  
Okan Mert Katipoğlu
Keyword(s):  
Spatial Distribution ◽  
Geographical Information Systems ◽  
Polynomial Interpolation ◽  
Estimation Method ◽  
Summer Precipitation ◽  
Winter Precipitation ◽  
Geographical Information ◽  
Seasonal Precipitation ◽  
Interpolation Methods

Abstract It is vital to accurately map the spatial distribution of precipitation, which is widely used in many fields such as hydrology, climatology, meteorology, ecology, and agriculture. In this study, it was aimed to reveal the spatial distribution of seasonal long-term average precipitation in the Euphrates Basin by using various interpolation methods. For this reason, Simple Kriging (SK), Ordinary Kriging (OK), Universal Kriging (UK), Ordinary CoKriging (OCK), Empirical Bayesian Kriging (EBK), Radial Basis Functions (Completely Regularized Spline (CRS), Thin Plate Spline (TPS), Multiquadratic, Inverse Multiquadratic (IM), Spline with Tensor (ST)), Local Polynomial Interpolation (LPI), Global Polynomial Interpolation (GPI), Inverse Distance Weighting (IDW) methods have been applied in the Geographical Information Systems (GIS) environment. Long-term seasonal precipitation averages between 1966 and 2017 are presented as input for the prediction of precipitation maps. The accuracy of the precipitation prediction maps created was based on root mean square error (RMSE) values obtained from the cross-validation tests. The method of precipitation by interpolation yielding the lowest RMSE was selected as the most appropriate method. As a result of the study, OCK in spring and winter precipitation, LPI in summer precipitation, and OK in autumn precipitation were determined as the most appropriate estimation method.

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.

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