Comparison of regression-based and combined versions of Inverse Distance Weighted methods for spatial interpolation of daily mean temperature data

2016 ◽  
Vol 9 (17) ◽  
Author(s):  
Emine Tanır Kayıkçı ◽  
Selma Zengin Kazancı
Keyword(s):  
Spatial Interpolation ◽  
Temperature Data ◽  
Inverse Distance Weighted ◽  
Mean Temperature ◽  
Distance Weighted ◽  
Inverse Distance

scholarly journals The Utilization of Remote Sensing Imagery and Inverse Distance Weighted Scheme to Simulate the White Oil Effects on Soil Geotechnical Properties

2021 ◽  
pp. 2824-2833
Author(s):  
L. A. Jawad ◽  
H. W. Abdulwadud ◽  
Z. A. Hameed
Keyword(s):  
Spatial Interpolation ◽  
Liquid Limit ◽  
Soil Samples ◽  
Strength Parameter ◽  
Undisturbed Soil ◽  
Inverse Distance Weighted ◽  
Area Of Interest ◽  
Clayey Silt ◽  
Distance Weighted ◽  
Inverse Distance

     This research aims to utilize a complementarity of field excavations and laboratory works with spatial analyses techniques for a highly accurate modeling of soil geotechniques properties (i.e. having lower root mean square error value for the spatial interpolation). This was conducted, for a specified area of interest, firstly by adopting spatially sufficient and  well distributed samples (cores). Then, in the second step, a simulation is performed for the variations in properties when soil is contaminated with commonly used industrial material, which is white oil in our case. Cohesive (disturbed and undisturbed) soil samples were obtained from three various locations inside Baghdad University campus in AL-Jadiriya section of Baghdad, Iraq. The unified soil categorization system (USCS) was adopted and soil was categorized  as clayey silt of low plasticity (CL). The cores were contaminated in a synthetically manner using two specified values of white oil (5 and 10 % of its dry weight). Then, the samples were left for three days to certify homogeneity. The results of laboratory tests were enhanced by spatial interpolation mapping, using Inverse Distance Weighted scheme for normal soil samples and those with synthetic pollution. The liquid limit rates were raised slightly as contamination rates raised, while particle size was reduced; in contrary, shear strength parameter values were decreased.

scholarly journals Drought Index Mapping at Different Spatial Units

2008 ◽  
Vol 9 (6) ◽  
pp. 1523-1534 ◽  
Author(s):  
Jinyoung Rhee ◽  
Gregory J. Carbone ◽  
James Hussey
Keyword(s):  
Spatial Interpolation ◽  
Drought Index ◽  
Cross Validation ◽  
Interpolation Method ◽  
Inverse Distance Weighted ◽  
Frequency Distributions ◽  
Distance Weighted ◽  
Cross Validation Error ◽  
Index Mapping ◽  
Inverse Distance

Abstract This paper investigates the influence of spatial interpolation and aggregation of data to depict drought at different spatial units relevant to and often required for drought management. Four different methods for drought index mapping were explored, and comparisons were made between two spatial operation methods (simple unweighted average versus spatial interpolation plus aggregation) and two calculation procedures (whether spatial operations are performed before or after the calculations of drought index values). Deterministic interpolation methods including Thiessen polygons, inverse distance weighted, and thin-plate splines as well as a stochastic and geostatistical interpolation method of ordinary kriging were compared for the two methods that use interpolation. The inverse distance weighted method was chosen based on the cross-validation error. After obtaining drought index values for different spatial units using each method in turn, differences in the empirical binned frequency distributions were tested between the methods and spatial units. The two methods using interpolation and aggregation introduced fewer errors in cross validation than the two simple unweighted average methods. Whereas the method performing spatial interpolation and aggregation before calculating drought index values generally provided consistent drought information between various spatial units, the method performing spatial interpolation and aggregation after calculating drought index values reduced errors related to the calculations of precipitation data.

scholarly journals Comparison of Inverse Distance Weighted and Natural Neighbor Interpolation Method at Air Temperature Data in Malang Region

CAUCHY ◽  
2018 ◽  
Vol 5 (2) ◽  
pp. 48 ◽  
Author(s):  
Jaka Pratama Musashi ◽  
Henny Pramoedyo ◽  
Rahma Fitriani
Keyword(s):  
Air Temperature ◽  
Spatial Data ◽  
Spatial Interpolation ◽  
Interpolation Method ◽  
Inverse Distance Weighted ◽  
Natural Neighbor ◽  
Comparison Results ◽  
Data Record ◽  
Distance Weighted ◽  
Inverse Distance

The purpose of this study was to compare the results of Inverse Distance Weighted (IDW) and Natural Neighbor interpolation methods for spatial data of air temperature in the Malang Region.  Interpolation is one way to determine a point of events from several points around the known value.  Spatial interpolation can be used to estimate an area that does not have a data record using the value of its known surroundings.  38 points observation air temperature of Malang Region in 2016 is used as a sample point to interpolate the surrounding air temperature.  Obtained optimum parameter power value is 2 for IDW interpolation method.  The RMSE comparison results show that IDW method is better to be used than the Natural Neighbor Interpolation method with the RMSE values of 1,2292 for the IDW method and 1,6173 for the NN method.

scholarly journals The influence of distance weight on the inverse distance weighted method for ore-grade estimation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhan-Ning Liu ◽  
Xiao-Yan Yu ◽  
Li-Feng Jia ◽  
Yuan-Sheng Wang ◽  
Yu-Chen Song ◽  
...  
Keyword(s):  
Estimation Accuracy ◽  
Block Model ◽  
Minkowski Distance ◽  
Inverse Distance Weighted ◽  
Grade Estimation ◽  
M 10 ◽  
Weight Calculation ◽  
Distance Weighted ◽  
Inverse Distance ◽  
Ore Grade

AbstractIn order to study the influence of distance weight on ore-grade estimation, the inverse distance weighted (IDW) is used to estimate the Ni grade and MgO grade of serpentinite ore based on a three-dimensional ore body model and related block models. Manhattan distance, Euclidean distance, Chebyshev distance, and multiple forms of the Minkowski distance are used to calculate distance weight of IDW. Results show that using the Minkowski distance for the distance weight calculation is feasible. The law of the estimated results along with the distance weight is given. The study expands the distance weight calculation method in the IDW method, and a new method for improving estimation accuracy is given. Researchers can choose different weight calculation methods according to their needs. In this study, the estimated effect is best when the power of the Minkowski distance is 3 for a 10 m × 10 m × 10 m block model. For a 20 m × 20 m × 20 m block model, the estimated effect is best when the power of the Minkowski distance is 9.

scholarly journals IN BATHYMETRIC SURFACES: IDW OR KRIGING?

2017 ◽  
Vol 23 (3) ◽  
pp. 493-508 ◽  
Author(s):  
Italo Oliveira Ferreira ◽  
Dalto Domingos Rodrigues ◽  
Gérson Rodrigues dos Santos ◽  
Lidiane Maria Ferraz Rosa
Keyword(s):  
Universal Kriging ◽  
Digital Model ◽  
Inverse Distance Weighted ◽  
Scientific Methods ◽  
Distance Weighted ◽  
Sample Points ◽  
Computational Representation ◽  
Inverse Distance ◽  
Mineral Prospecting

Abstract: The representation of the submerged relief is very importance in diverse areas of knowledge such as Projects to build or reassess port dimensions, installation of moles, ducts, marinas, bridges, tunnels, mineral prospecting, waterways, dredging, silting control of river and lakes, and others. The depths of the aquatic bodies, indispensable for the representation of those, are obtained through the bathymetric surveys. However, the result of a bathymetric sampling is a grid of points that, for itself, it is not capable of generating directly the Digital Model of Depth (DMD), being necessary the use of interpolators. Currently, there are more than 40 available scientific methods of interpolation, each one with its particularities and characteristics. This study has the objective to analise, comparing, the efficiency of Universal Kriging (UK) and of the Inverse Distance Weighted (IDW) in the computational representation of bathymetric surfaces, varying in a decreasing way the quantity of sample points. Through the results, we can be stated the superiority of the interpolator Universal Kriging in efficiency in creating DMD with basis in the bathymetric surveys data.

scholarly journals PEMODELAN GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) SEASONAL PADA DATA CURAH HUJAN EMPAT KABUPATEN DI PROVINSI JAWA TENGAH

2019 ◽  
Vol 8 (4) ◽  
pp. 418-427
Author(s):  
Eko Siswanto ◽  
Hasbi Yasin ◽  
Sudarno Sudarno
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Space Time ◽  
Series Data ◽  
Inverse Distance Weighted ◽  
Modeling And Forecasting ◽  
Distance Weighted ◽  
The Relationship ◽  
Inverse Distance

In many applications, several time series data are recorded simultaneously at a number of locations. Time series data from nearby locations often to be related by spatial and time. This data is called spatial time series data. Generalized Space Time Autoregressive (GSTAR) model is one of space time models used to modeling and forecasting spatial time series data. This study applied GTSAR model to modeling volume of rainfall four locations in Jepara Regency, Kudus Regency, Pati Regency, and Grobogan Regency. Based on the smallest RMSE mean of forecasting result, the best model chosen by this study is GSTAR (11)-I(1)12 with the inverse distance weighted. Based on GSTAR(11)-I(1)12 with the inverse distance weighted, the relationship between the location shown on rainfall Pati Regency influenced by the rainfall in other regencies. Keywords: GSTAR, RMSE, Rainfall

scholarly journals ACIDENTES COM TRATORES NAS REGIÕES BRASILEIRAS

2019 ◽  
Vol 34 (01) ◽  
pp. 1-9
Author(s):  
Isabela Oliveira Lima ◽  
Leonardo De Almeida Monteiro ◽  
Elivania Maria Sousa Nascimento ◽  
Rafaela Paula Melo ◽  
Mara Alice Maciel dos Santos
Keyword(s):  
Rural Areas ◽  
Exponential Model ◽  
The South ◽  
Inverse Distance Weighted ◽  
The North ◽  
Gis Tools ◽  
Distance Weighted ◽  
E Mail ◽  
Inverse Distance ◽  
Agricultural Machines

ACIDENTES COM TRATORES NAS REGIÕES BRASILEIRAS   ISABELA OLIVEIRA LIMA1; LEONARDO DE ALMEIDA MONTEIRO2; ELIVANIA MARIA SOUSA NASCIMENTO3; RAFAELA PAULA MELO4 E MARA ALICE MACIEL DOS SANTOS5   [1] Doutoranda em Engenharia Agrícola, Departamento de Engenharia Agrícola, Bloco 804, s/n – Pici, cep:60455-760, Fortaleza - CE, Brasil. E-mail: [email protected] 2 Professor Doutor, Universidade Federal do Ceará-UFC, Departamento de Engenharia Agrícola, Bloco 804, s/n - Pici, cep:60455-760, Fortaleza - CE, Brasil. E-mail: [email protected] 3Doutoranda em Engenharia Agrícola, Departamento de Engenharia Agrícola, Bloco 804, s/n - Pici, cep:60455-760, Fortaleza - CE, Brasil. E-mail: [email protected] 4Doutora em Engenharia Agrícola, Departamento de Engenharia Agrícola, Bloco 804, s/n - Pici, cep:60455-760, Fortaleza - CE, Brasil. E-mail: [email protected] 5Mestre e Engenharia Agrícola, Departamento de Engenharia Agrícola, Bloco 804, s/n - Pici, cep:60455-760, Fortaleza - CE, Brasil. E-mail: [email protected]   RESUMO: Acidentes de trabalho no meio rural estão se tornando cada dia mais frequentes, e se faz necessário a identificação destes para que se possa implementar medidas preventivas. Em consonância a essa busca o presente trabalho objetivou-se a mapear acidentes com máquinas agrícolas sucedidos no Brasil no período de janeiro de 2013 a maio de 2016, usando técnicas de geoprocessamento para a confecção dos mapas. Os dados foram obtidos a partir de um compilado de informações de acidentes ocorridos no período. Foram desenvolvidos mapas pelo IDW (Inverse Distance Weighted), permitindo a identificação das áreas de maior e menor concentração de acidentes. Os dados analisados foram submetidos a uma verificação da dependência espacial das variáveis, pela análise geoestatística, segundo Yamamoto e Landim (2015). Os resultados demonstram uma maior concentração de acidentes na região Sul do país. As regiões Sul e Norte apresentaram médias de acidentes iguais a do território nacional. A menor média de acidentes foi na região Nordeste (1,2 acidentes/Estado). As regiões Sul, Sudeste, Centro oeste e Nordeste apresentaram como modelo efeito pepita puro (EPP), enquanto que a região Norte apresentou modelo exponencial. O uso de ferramentas de SIG mostrou-se eficiente para o mapeamento dos acidentes com tratores nas regiões brasileiras.   Palavras-chaves: Segurança, Prevenção, Georreferenciamento, Mecanização agrícola.   ACCIDENTS WITH TRACTORS IN THE BRAZILIAN REGIONS   ABSTRACT: Accidents at work in rural areas are becoming more frequent, and their identification is necessary so that preventive measures can be implemented. In line with this search, the present work aimed to map accidents with agricultural machines succeeded in Brazil from January 2013 to May 2016, using geoprocessing techniques to make maps. Data were obtained from a compilation of information on accidents occurring in the period. Maps were developed by IDW (Inverse Distance Weighted), allowing the identification of areas with the highest and lowest concentration of accidents. Os dados analisados foram submetidos a uma verificação da dependência espacial das variáveis, pela análise geoestatística, segundo Yamamoto e Landim (2015). The results show a higher concentration of accidents in the southern region of the country. The South and North regions had accident averages equal to the national territory. The lowest average of accidents was in the Northeast region (1.2 accidents / State). The South, Southeast, Midwest and Northeast regions presented as pure nugget effect (EPP) model, while the North region presented exponential model. The use of GIS tools proved to be efficient for the mapping of tractor accidents in the Brazilian regions.   Keywords: safety, prevention, georeferencing, agricultural mechanization.

scholarly journals Spatio-Temporal Analysis of PM10 in Southern Peninsular Malaysia

2018 ◽  
Vol 7 (3.9) ◽  
pp. 27
Author(s):  
Mohamad Saiful Mohamad Khir ◽  
Khalida Muda ◽  
Norelyza Hussein ◽  
Mohd Faisal Abdul Khanan ◽  
Mohd Nor Othman ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Pollutant Dispersion ◽  
Temporal Analysis ◽  
Peninsular Malaysia ◽  
Inverse Distance Weighted ◽  
Distance Weighted ◽  
Haze Episode ◽  
Spatio Temporal ◽  
Inverse Distance

In this study, the particulate matter with diameter less than 10 micrometers (PM10) is being observed. Other factors that influenced the pollutant dispersion are also being studied prior to identification of their relationship. The aim of this study is to identify the trend of PM10 concentrations in the Southern Peninsular of Malaysia during the period 2005 to 2015 by using spatio-temporal analysis in regards to air pollution. The inverse distance weighted (IDW) is used for the spatio interpolation data and mapping. The trends of the PM10 concentration are illustrated via map which indicates the affected and vulnerable area of Southern Peninsular Malaysia especially during Haze episode.  

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