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Nattakan Supajaidee, Nawinda Chutsagulprom and Sompop Moonchai
Ordinary kriging (OK) is a popular interpolation method for its ability to simultaneously minimize error variance and deliver statistically optimal and unbiased predictions. In this work, the adaptive moving window kriging with K-means clustering (AMWKK)...
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Hosang Han and Jangwon Suh
The accurate prediction of soil contamination in abandoned mining areas is necessary to address their environmental risks. This study employed a combined model of machine learning and geostatistics to predict the spatial distribution of soil contaminatio...
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Abdelkrim Lachgar, David J. Mulla and Viacheslav Adamchuk
One of the challenges in site-specific phosphorus (P) management is the substantial spatial variability in plant available P across fields. To overcome this barrier, emerging sensing, data fusion, and spatial predictive modeling approaches are needed to ...
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Djouhaina Brella, Lazhar Belkhiri, Ammar Tiri, Hichem Salhi, Fatma Elhadj Lakouas, Razki Nouibet, Adeltif Amrane, Ryma Merdoud and Lotfi Mouni
In this study, we analyzed the quality and the potential noncarcinogenic health risk of nitrate in groundwater in the El Milia plain, Kebir Rhumel Basin, Algeria. Moran?s I and the ordinary kriging (OK) interpolation technique were used to examine the sp...
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Waqas Ahmed, Khan Muhammad, Hylke Jan Glass, Snehamoy Chatterjee, Asif Khan and Abid Hussain
Geostatistical estimation methods rely on experimental variograms that are mostly erratic, leading to subjective model fitting and assuming normal distribution during conditional simulations. In contrast, Machine Learning Algorithms (MLA) are (1) free of...
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Yuratikan Jantaravikorn and Suwit Ongsomwang
Salt mining and shrimp farming have been practiced in the Non Thai district and the surrounding areas for more than 30 years, creating saline soil problems. To solve the soil salinity problem, soil salinity prediction and mapping utilizing the electromag...
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Diego Di Curzio, Alessia Di Giovanni, Raffaele Lidori, Mario Montopoli and Sergio Rusi
Accurate knowledge of the rain amount is a crucial driver in several hydrometeorological applications. This is especially true in complex orography territories, which are typically impervious, thus, leaving most mountain areas ungauged. Due to their spat...
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Linda Permata
Pág. 259 - 273
A conventional surface mapping is calculated by any means of linear interpolator such as nearest neighborhood point (NNP), inverse distance (IDW)/inverse distance square (IDS), polygon, contour weighing, Ordinary Kriging (OK). The latter is included in g...
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Abbas Abbaszadeh Shahri, Ali Kheiri and Aliakbar Hamzeh
Infrastructures play an important role in urbanization and economic activities but are vulnerable. Due to unavailability of accurate subsurface infrastructure maps, ensuring the sustainability and resilience often are poorly recognized. In the current pa...
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Panagiotis Tziachris, Vassilis Aschonitis, Theocharis Chatzistathis, Maria Papadopoulou and Ioannis (John) D. Doukas
In the current paper we assess different machine learning (ML) models and hybrid geostatistical methods in the prediction of soil pH using digital elevation model derivates (environmental covariates) and co-located soil parameters (soil covariates). The ...
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