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Journal articles on the topic 'Spatial variables measurement'

Author: Grafiati

Published: 7 June 2025

Last updated: 16 July 2025

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1

Deák, Tamás, András Dobai, Zoltán Károly Kovács, Ferenc Molnár, and Endre Dobos. "Spatial extension of soil water regime variables derived from soil moisture values using geomorphological variables in Hungary." Hungarian Geographical Bulletin 73, no. 4 (2024): 337–53. https://doi.org/10.15201/hungeobull.73.4.1.

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Accurate measurement and spatial extension of soil properties are essential in geoinformatics and precision agriculture for effective resource management, particularly irrigation planning. This study addresses the challenge of extending soil moisture data and related soil water regime variables in heterogeneous agricultural landscapes by integrating geomorphological variables (GVs) derived from high-resolution digital elevation models (DEM). In digital soil mapping, machine learning and geostatistical models often struggle with validation due to data scarcity and variability across space throu

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Juhl, Sebastian. "Measurement Uncertainty in Spatial Models: A Bayesian Dynamic Measurement Model." Political Analysis 27, no. 3 (2018): 302–19. http://dx.doi.org/10.1017/pan.2018.35.

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According to spatial models of political competition, parties strategically adjust their ideological positions to movements made by rival parties. Spatial econometric techniques have been proposed to empirically model such interdependencies and to closely convert theoretical expectations into statistical models. Yet, these models often ignore that the parties’ ideological positions are latent variables and, as such, accompanied by a quantifiable amount of uncertainty. As a result, the implausible assumption of perfectly measured covariates impedes a proper evaluation of theoretical proposition

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ICHIYANAGI, Mitsuhisa, Yohei SATO, and Koichi HISHIDA. "F112 Spatial-Distribution Measurement of Multi-Variables for Mixing in Microchannel." Proceedings of the Thermal Engineering Conference 2005 (2005): 219–20. http://dx.doi.org/10.1299/jsmeted.2005.219.

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van Leeuwen, T. T., and G. R. van der Werf. "Spatial and temporal variability in the ratio of trace gases emitted from biomass burning." Atmospheric Chemistry and Physics 11, no. 8 (2011): 3611–29. http://dx.doi.org/10.5194/acp-11-3611-2011.

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Abstract. Fires are a major source of trace gases and aerosols to the atmosphere. The amount of biomass burned is becoming better known, most importantly due to improved burned area datasets and a better representation of fuel consumption. The spatial and temporal variability in the partitioning of biomass burned into emitted trace gases and aerosols, however, has received relatively little attention. To convert estimates of biomass burned to trace gas and aerosol emissions, most studies have used emission ratios (or emission factors (EFs)) based on the arithmetic mean of field measurement out

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Ramtvedt, Eirik Næsset, Terje Gobakken, and Erik Næsset. "Fine-Spatial Boreal–Alpine Single-Tree Albedo Measured by UAV: Experiences and Challenges." Remote Sensing 14, no. 6 (2022): 1482. http://dx.doi.org/10.3390/rs14061482.

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The boreal–alpine treeline is a fine-spatial heterogeneous ecotone with small single trees, tree clusters and open snow surfaces during wintertime. Due to climate change and decreased grazing of domestic animals, the treelines expand both upwards into the mountains and northwards into the tundra. To quantify and understand the biophysical radiative climatic feedback effect due to this expansion, it is necessary to establish measurement strategies of fine-spatial albedo by which relationships with the tree structure and snow-masking effect can be quantified. In this study, we measured single-tr

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Reis, Aliny Aparecida Dos, Andressa Ribeiro, Rafaella Carvalho Mayrinck, José Marcio de Mello, Anderson Pedro Bernardina Batista, and Antonio Carlos Ferraz Filho. "Temporal stability of stratifications using different dendrometric variables and geostatistical interpolation." Ciência Florestal 32, no. 1 (2022): 102–21. http://dx.doi.org/10.5902/1980509843274.

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Stratifying a forest results in more precise and cheaper inventories. This study aimed to select the stratifying variable that estimates more precise and stable inventory over the years for a eucalyptus plantation in Minas Gerais state, Brazil. The continuous forest inventory was performed annually from 2.7 to 6.8 years, and based on the field measurements, arithmetic mean diameter (d), height (h), dominant height (Hdom), basal area (G), volume (V), and mean annual increment in volume (MAI) were calculated. Semivariograms were generated and the exponential, spherical and Gaussian models were f

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Sexstone, G. A., and S. R. Fassnacht. "What drives basin scale spatial variability of snow water equivalent during two extreme years?" Cryosphere Discussions 7, no. 3 (2013): 2943–77. http://dx.doi.org/10.5194/tcd-7-2943-2013.

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Abstract. This study uses a combination of field measurements and Natural Resource Conservation Service (NRCS) operational snow data to understand the drivers of snow water equivalent (SWE) spatial variability at the basin scale. Historic snow course snowpack density observations were analyzed within a multiple linear regression snow density model to estimate SWE directly from snow depth measurements. Snow surveys were completed on or about 1 April 2011 and 2012 and combined with NRCS operational measurements to investigate the spatial variability of SWE. Bivariate relations and multiple linea

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Lusiana, Evellin Dewi, Arief Darmawan, Sarah Hutahaean, Muhammad Musa, Mohammad Mahmudi, and Sulastri Arsad. "Factors Affecting Dissolved Oxygen at Bengawan Solo River: A Spatial Filtering with Eigenvector Technique." Jurnal Varian 5, no. 1 (2021): 1–8. http://dx.doi.org/10.30812/varian.v5i1.1407.

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The quality of the river changes according to the development of the surrounding environment which is influenced by various human activities. Analysis of factors affecting Dissolved Oxygen (DO) at Bengawan Solo River is crucial for river management purpose and pollution control. Previous research suggested the use classic multiple linear regression. However, DO measurement were usually took place of sampling sites along the river channel. Therefore, there is a high chance that the measurements results may spatially correlated. As the consequence, the utilization of multiple linear regression t

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Erin, Lee Hestir, E. Brando Vittorio, Bresciani Mariano, et al. "Measuring freshwater aquatic ecosystems: The need for a hyperspectral global mapping satellite mission." Remote Sensing of Environment 167 (September 15, 2015): 181–95. https://doi.org/10.1016/j.rse.2015.05.023.

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Freshwater ecosystems underpin global water and food security, yet are some of the most endangered ecosystems in the world because they are particularly vulnerable to land management change and climate variability. The US National Research Council's guidance to NASA regarding missions for the coming decade includes a polar orbiting, global mapping hyperspectral satellite remote sensing mission, the Hyperspectral Infrared Imager (HyspIRI), to make quantitative measurements of ecosystem change. Traditionally, freshwater ecosystems have been challenging tomeasure with satellite remote sensing

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Hogland, John, and David L. R. Affleck. "Mitigating the Impact of Field and Image Registration Errors through Spatial Aggregation." Remote Sensing 11, no. 3 (2019): 222. http://dx.doi.org/10.3390/rs11030222.

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Remotely sensed data are commonly used as predictor variables in spatially explicit models depicting landscape characteristics of interest (response) across broad extents, at relatively fine resolution. To create these models, variables are spatially registered to a known coordinate system and used to link responses with predictor variable values. Inherently, this linking process introduces measurement error into the response and predictors, which in the latter case causes attenuation bias. Through simulations, our findings indicate that the spatial correlation of response and predictor variab

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Sun, Shuai, and Haiping Zhang. "Flow-Data-Based Global Spatial Autocorrelation Measurements for Evaluating Spatial Interactions." ISPRS International Journal of Geo-Information 12, no. 10 (2023): 396. http://dx.doi.org/10.3390/ijgi12100396.

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Spatial autocorrelation analysis is essential for understanding the distribution patterns of spatial flow data. Existing methods focus mainly on the origins and destinations of flow units and the relationships between them. These methods measure the autocorrelation of gravity or the positional and directional autocorrelations of flow units that are treated as objects. However, the intrinsic complexity of actual flow data necessitates the consideration of not only gravity, positional, and directional autocorrelations but also the autocorrelations of the variables of interest. This study propose

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Anekawati, Anik, Bambang Widjanarko Otok, Purhadi Purhadi, and Sutikno Sutikno. "Lagrange Multiplier Test for Spatial Autoregressive Model with Latent Variables." Symmetry 12, no. 8 (2020): 1375. http://dx.doi.org/10.3390/sym12081375.

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The focus of this research is to develop a Lagrange multiplier (LM) test of spatial dependence for the spatial autoregressive model (SAR) with latent variables (LVs). It was arranged by the standard SAR, where the independent variables were replaced by factor scores of the exogenous latent variables from a measurement model (in structural equation modeling) as well as their dependent variables. As a result, an error distribution of the SAR-LVs should have a different distribution from the standard SAR. Therefore, this LM test for the SAR-LVs is based on the new distribution. The estimation of

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Sexstone, G. A., and S. R. Fassnacht. "What drives basin scale spatial variability of snowpack properties in northern Colorado?" Cryosphere 8, no. 2 (2014): 329–44. http://dx.doi.org/10.5194/tc-8-329-2014.

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Abstract. This study uses a combination of field measurements and Natural Resource Conservation Service (NRCS) operational snow data to understand the drivers of snow density and snow water equivalent (SWE) variability at the basin scale (100s to 1000s km2). Historic snow course snowpack density observations were analyzed within a multiple linear regression snow density model to estimate SWE directly from snow depth measurements. Snow surveys were completed on or about 1 April 2011 and 2012 and combined with NRCS operational measurements to investigate the spatial variability of SWE near peak

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Okabayashi Miyaji, Renato, Felipe Valencia de Almeida, Lucas de Oliveira Bauer, et al. "Spatial Interpolation of Air Pollutant and Meteorological Variables in Central Amazonia." Data 6, no. 12 (2021): 126. http://dx.doi.org/10.3390/data6120126.

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The Amazon Rainforest is highlighted by the global community both for its extensive vegetation cover that constantly suffers the effects of anthropic action and for its substantial biodiversity. This dataset presents data of meteorological variables from the Amazon Rainforest region with a spatial resolution of 0.001° in latitude and longitude, resulting from an interpolation process. The original data were obtained from the GoAmazon 2014/5 project, in the Atmospheric Radiation Measurement (ARM) repository, and then processed through mathematical and statistical methods. The dataset presented

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Bohari, Abdul Manaf, and Malliga Marimuthu . "A Study on Financial-Accounting Methods for Prospecting the Lifetime Value of Hypermarket Business: A Critical Used of Geospatial Method." Information Management and Business Review 5, no. 4 (2013): 155–67. http://dx.doi.org/10.22610/imbr.v5i4.1039.

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Recently, the hypermarket profitability is an important issue for the world wide retailing industry with vast literature was found on its definitions, measurements, and models of studied. In general, majority of related work showed that various methodologies and models have been applied to evaluate the profitability of hypermarket, where more dominants on financial and accounting methods. Specifically, estimate the hypermarket profitability are always dominating by financial and accounting methods and approaches with finale attention on maximizing the customer lifetime value (CLV). In fact, mo

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Zhou, Qianqian, Nan Chen, and Siwei Lin. "A Poverty Measurement Method Incorporating Spatial Correlation: A Case Study in Yangtze River Economic Belt, China." ISPRS International Journal of Geo-Information 11, no. 1 (2022): 50. http://dx.doi.org/10.3390/ijgi11010050.

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The UN 2030 Agenda sets poverty eradication as the primary goal of sustainable development. An accurate measurement of poverty is a critical input to the quality and efficiency of poverty alleviation in rural areas. However, poverty, as a geographical phenomenon, inevitably has a spatial correlation. Neglecting the spatial correlation between areas in poverty measurements will hamper efforts to improve the accuracy of poverty identification and to design policies in truly poor areas. To capture this spatial correlation, this paper proposes a new poverty measurement model based on a neural netw

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Cruz-Sandoval, Marco, Elisabet Roca, and María Isabel Ortego. "Compositional Data Analysis Approach in the Measurement of Social-Spatial Segregation: Towards a Sustainable and Inclusive City." Sustainability 12, no. 10 (2020): 4293. http://dx.doi.org/10.3390/su12104293.

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The location and context in which people live influences and conditions their opportunities in life. This becomes relevant in a world subject to rapid urban and demographic growth, in which different economic, social, and political forces generate and accentuate disparities in cities. The foregoing generates an unequal distribution of the different social groups in the territory known as socio-spatial segregation. The study of this phenomenon incorporates a large number of variables belonging to different dimensions. Nonetheless, few studies have addressed socio-spatial segregation with a mult

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Brown, Luke A., Fernando Camacho, Vicente García-Santos, et al. "Fiducial Reference Measurements for Vegetation Bio-Geophysical Variables: An End-to-End Uncertainty Evaluation Framework." Remote Sensing 13, no. 16 (2021): 3194. http://dx.doi.org/10.3390/rs13163194.

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With a wide range of satellite-derived vegetation bio-geophysical products now available to users, validation efforts are required to assess their accuracy and fitness for purpose. Substantial progress in the validation of such products has been made over the last two decades, but quantification of the uncertainties associated with in situ reference measurements is rarely performed, and the incorporation of uncertainties within upscaling procedures is cursory at best. Since current validation practices assume that reference data represent the truth, our ability to reliably demonstrate complian

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Dong, Ah Hyeon, and Jung Eun Kang. "Study on the Impact of Disaster Resilience on Disaster Damage Using Spatial Regression Analysis." Journal of the Korean Society of Hazard Mitigation 25, no. 2 (2025): 47–61. https://doi.org/10.9798/kosham.2025.25.2.47.

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This study developed and measured a disaster resilience index for local communities by utilizing the concept of “disaster resilience” to address the increasing damage caused by climate change-related disasters. Based on prior research, this study conceptualized disaster resilience into three components: resistance, recovery, and transformation. It further categorized resilience into four dimensions: social, economic, infrastructure, and institutional resilience. For each dimension, five measurement variables were selected, resulting in 60 measurement variables used to develop the disaster resi

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Puerto, Pablo, Daniel Heißelmann, Simon Müller, and Alberto Mendikute. "Methodology to Evaluate the Performance of Portable Photogrammetry for Large-Volume Metrology." Metrology 2, no. 3 (2022): 320–34. http://dx.doi.org/10.3390/metrology2030020.

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The increased relevance of large-volume metrology (LVM) in industrial applications entails certain challenges: measurements must be cost-efficient and the technologies must be easy to use while ensuring accuracy and reliability. Portable photogrammetry shows great potential to overcome such challenges, but industrial users do not yet rely on its accuracy for large scenarios (3 to 64 m), especially when mass-market cameras are not conceived of as industrial metrology instruments. Furthermore, the measurement results might also depend on the operator’s skills and knowledge of the key process var

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Lefebvre-Ropars, Gabriel, and Catherine Morency. "Walkability: Which Measure to Choose, Where to Measure It, and How?" Transportation Research Record: Journal of the Transportation Research Board 2672, no. 35 (2018): 139–50. http://dx.doi.org/10.1177/0361198118787095.

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The urban structure of neighborhoods has a decisive impact on active mobility, but this impact is hard to evaluate in a mode choice model because of the high collinearity between urban form variables and the uncertainty surrounding adequate spatial measurement parameters. Several composite scores, or walkability measures, have emerged from the literature, each using its own method and including different variables. No consensus has been reached on the size of the catchment area that should be used to measure walkability and most studies only measure walkability at the origin of the trip withou

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Liu, Zhaohua, Jiangping Long, Hui Lin, et al. "Combination Strategies of Variables with Various Spatial Resolutions Derived from GF-2 Images for Mapping Forest Stock Volume." Forests 14, no. 6 (2023): 1175. http://dx.doi.org/10.3390/f14061175.

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Spectral features (SFs) and texture features (TFs) extracted from optical remote sensing images can capture the structural composition and growth information of forests, and combining remote sensing variables with a few ground measurement samples is a common method for mapping forest stock volume (FSV). However, the accuracy of mapping FSV using optical images with a high spatial resolution (one meter or sub-meters) is often lower than medium resolutions (larger than 10 m) using the same types of features and approaches. To overcome the limitations of high spatial resolution images in mapping

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Lubis, Elvina Nora, Andrea Emma Pravitasari, and Dwi Putro Tejo Baskoro. "Indeks Pembangunan Berkelanjutan Lokal dan Sebaran Spasialnya di Kabupaten Mandailing Natal, Provinsi Sumatera Utara." Journal of Regional and Rural Development Planning 5, no. 3 (2021): 174–86. http://dx.doi.org/10.29244/jp2wd.2021.5.3.174-186.

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The concept of sustainable development is very important to increase our quality of life. Measurement of development based on specific indicators is one of the approaches to describe sustainable development. At the local level, measuring sustainable development using specific indicators is still rare. Since each location has their own unique characteristics, measuring sustainability at the regional level could not always be applied locally. The availability of data at the village level strongly encourages the local measurement of sustainable development index. The economic, social, and environ

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Brosy, Caroline, Karina Krampf, Matthias Zeeman, et al. "Simultaneous multicopter-based air sampling and sensing of meteorological variables." Atmospheric Measurement Techniques 10, no. 8 (2017): 2773–84. http://dx.doi.org/10.5194/amt-10-2773-2017.

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Abstract. The state and composition of the lowest part of the planetary boundary layer (PBL), i.e., the atmospheric surface layer (SL), reflects the interactions of external forcing, land surface, vegetation, human influence and the atmosphere. Vertical profiles of atmospheric variables in the SL at high spatial (meters) and temporal (1 Hz and better) resolution increase our understanding of these interactions but are still challenging to measure appropriately. Traditional ground-based observations include towers that often cover only a few measurement heights at a fixed location. At the same

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Saar, Steven H. "Infrared Measurements of Stellar Magnetic Fields." Symposium - International Astronomical Union 154 (1994): 437–47. http://dx.doi.org/10.1017/s0074180900124696.

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I review the advantages, techniques, and results of measurement of magnetic fields on cool stars in the infrared (IR). These measurements have generated several important results, including the following: the first data on the magnetic parameters of dMe and RS CVn variables; evidence for field strength confinement by photospheric gas pressure; support for the correlation between magnetic flux and rotation, with possible saturation at high rotation rates; indications of horizontal and/or vertical magnetic field structure; and evidence of spatial variations in B over a stellar surface. I discuss

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Spławińska, M. "Models For Determining Annual Average Daily Traffic On The National Roads." Archives of Civil Engineering 61, no. 2 (2015): 141–60. http://dx.doi.org/10.1515/ace-2015-0019.

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AbstractOne of the basic parameters which describes road traffic is Annual Average Daily Traffic (AADT). Its accurate determination is possible only on the basis of data from the continuous measurement of traffic. However, such data for most road sections is unavailable, so AADT must be determined on the basis of short periods of random measurements. This article presents different methods of estimating AADT on the basis of daily traffic (VOL), and includes the traditional Factor Approach, developed Regression Models and Artificial Neural Network models. As explanatory variables, quantitative

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Castellini, Mirko, Anna Maria Stellacci, Matteo Tomaiuolo, and Emanuele Barca. "Spatial Variability of Soil Physical and Hydraulic Properties in a Durum Wheat Field: An Assessment by the BEST-Procedure." Water 11, no. 7 (2019): 1434. http://dx.doi.org/10.3390/w11071434.

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Spatial variability of soil properties at the field scale can determine the extent of agricultural yields and specific research in this area is needed. The general objective of this study was to investigate the relationships between soil physical and hydraulic properties and wheat yield at the field scale and test the BEST-procedure for the spatialization of soil hydraulic properties. A simplified version of the BEST-procedure, to estimate some capacitive indicators from the soil water retention curve (air capacity, ACe, relative field capacity, RFCe, plant available water capacity, PAWCe), wa

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Goddijn-Murphy, L. M., D. K. Woolf, P. E. Land, J. D. Shutler, and C. Donlon. "The OceanFlux Greenhouse Gases methodology for deriving a sea surface climatology of CO<sub>2</sub> fugacity in support of air–sea gas flux studies." Ocean Science 11, no. 4 (2015): 519–41. http://dx.doi.org/10.5194/os-11-519-2015.

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Abstract. Climatologies, or long-term averages, of essential climate variables are useful for evaluating models and providing a baseline for studying anomalies. The Surface Ocean CO2 Atlas (SOCAT) has made millions of global underway sea surface measurements of CO2 publicly available, all in a uniform format and presented as fugacity, fCO2. As fCO2 is highly sensitive to temperature, the measurements are only valid for the instantaneous sea surface temperature (SST) that is measured concurrently with the in-water CO2 measurement. To create a climatology of fCO2 data suitable for calculating ai

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Trujillo, E., and M. Lehning. "Theoretical analysis of errors when estimating snow distribution through point measurements." Cryosphere 9, no. 3 (2015): 1249–64. http://dx.doi.org/10.5194/tc-9-1249-2015.

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Abstract. In recent years, marked improvements in our knowledge of the statistical properties of the spatial distribution of snow properties have been achieved thanks to improvements in measuring technologies (e.g., LIDAR, terrestrial laser scanning (TLS), and ground-penetrating radar (GPR)). Despite this, objective and quantitative frameworks for the evaluation of errors in snow measurements have been lacking. Here, we present a theoretical framework for quantitative evaluations of the uncertainty in average snow depth derived from point measurements over a profile section or an area. The err

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Trujillo, E., and M. Lehning. "Theoretical framework for estimating snow distribution through point measurements." Cryosphere Discussions 9, no. 1 (2015): 1–44. http://dx.doi.org/10.5194/tcd-9-1-2015.

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Abstract. In recent years, marked improvements in our knowledge of the statistical properties of the spatial distribution of snow properties have been achieved thanks to improvements in measuring technologies (e.g. LIDAR, TLS, and GPR). Despite of this, objective and quantitative frameworks for the evaluation of errors and extrapolations in snow measurements have been lacking. Here, we present a theoretical framework for quantitative evaluations of the uncertainty of point measurements of snow depth when used to represent the average depth over a profile section or an area. The error is define

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Hwang, Ji Hyoun, and Hyunsoo Lee. "Parametric Model for Window Design Based on Prospect-Refuge Measurement in Residential Environment." Sustainability 10, no. 11 (2018): 3888. http://dx.doi.org/10.3390/su10113888.

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As the concept of prospect-refuge defines a preferred environment, the spatial elements that provide good conditions for the catalyst of the theory have been extensively studied. The well-known architectural element of this theory is the window that optimizes visual openness to outdoor or enclosure from outdoor. The aim of this paper is to develop a design method for prospect-refuge condition by adjusting window design attributes. A parametric design model that measures spatial conditions and presents design alternatives for the window is proposed in two major phases. First, this paper explain

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Darra, Nicoleta, Emmanouil Psomiadis, Aikaterini Kasimati, Achilleas Anastasiou, Evangelos Anastasiou, and Spyros Fountas. "Remote and Proximal Sensing-Derived Spectral Indices and Biophysical Variables for Spatial Variation Determination in Vineyards." Agronomy 11, no. 4 (2021): 741. http://dx.doi.org/10.3390/agronomy11040741.

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Remote-sensing measurements are crucial for smart-farming applications, crop monitoring, and yield forecasting, especially in fields characterized by high heterogeneity. Therefore, in this study, Precision Viticulture (PV) methods using proximal- and remote-sensing technologies were exploited and compared in a table grape vineyard to monitor and evaluate the spatial variation of selected vegetation indices and biophysical variables throughout selected phenological stages (multi-seasonal data), from veraison to harvest. The Normalized Difference Vegetation Index and the Normalized Difference Re

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Dengel, Sigrid, Alexander Graf, Thomas Grünwald, et al. "Standardized precipitation measurements within ICOS: rain, snowfall and snow depth: a review." International Agrophysics 32, no. 4 (2018): 607–17. http://dx.doi.org/10.1515/intag-2017-0046.

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Abstract Precipitation is one of the most important abiotic variables related to plant growth. Using standardised measurements improves the comparability and quality of precipitation data as well as all other data within the Integrated Carbon Observation System network. Despite the spatial and temporal variation of some types of precipitation, a single point measurement satisfies the requirement as an ancillary variable for eddy covariance measurements. Here the term precipitation includes: rain, snowfall (liquid water equivalent) and snow depth, with the latter two being of interest only wher

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Choi, Wonei, Hanlim Lee, Daewon Kim, and Serin Kim. "Improving Spatial Coverage of Satellite Aerosol Classification Using a Random Forest Model." Remote Sensing 13, no. 7 (2021): 1268. http://dx.doi.org/10.3390/rs13071268.

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The spatial coverage of satellite aerosol classification was improved using a random forest (RF) model trained with observational data including target (aerosol type) and input (satellite measurement) variables. The AErosol RObotic NETwork (AERONET) aerosol-type dataset was used for the target variables. Satellite input variables with many missing data or low mean-decrease accuracy were excluded from the final input variable set, and good performance in aerosol-type classification was achieved. The performance of the RF-based model was evaluated on the basis of the wavelength dependence of sin

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Yuliara, I. Made, Ni Nyoman Ratini, and I. Gde Antha Kasmawan. "Integration of Sentinel-2A Imagery and Laboratory Measurements for Estuarine Pb and TSS Concentration Monitoring in Suwung, Denpasar City, Indonesia." Asian Journal of Research and Reviews in Physics 7, no. 4 (2023): 68–73. http://dx.doi.org/10.9734/ajr2p/2023/v7i4150.

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Research has been carried out on integrating the results of Sentinel-2A and laboratory image data measurements in the form of a mathematical model that can be used to estimate the concentration and spatial distribution of Pb and Total Suspended Solid (TSS) of the Suwung estuary, Denpasar city, Bali, Indonesia. Integration is carried out using the regression method and correlation of the pixel value measurement results of the Sentinel-2A and laboratory images. Pixel values in Sentinel-2A image data which represent TSS concentrations are obtained by applying the TSS algorithm and Pb pixel values

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Chen, Chuanfa, Baojian Hu, and Yanyan Li. "Easy-to-use spatial random-forest-based downscaling-calibration method for producing precipitation data with high resolution and high accuracy." Hydrology and Earth System Sciences 25, no. 11 (2021): 5667–82. http://dx.doi.org/10.5194/hess-25-5667-2021.

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Abstract. Precipitation data with high resolution and high accuracy are significantly important in numerous hydrological applications. To enhance the spatial resolution and accuracy of satellite-based precipitation products, an easy-to-use downscaling-calibration method based on a spatial random forest (SRF-DC) is proposed in this study, where the spatial autocorrelation of precipitation measurements between neighboring locations is considered. SRF-DC consists of two main stages. First, the satellite-based precipitation is downscaled by the SRF with the incorporation of high-resolution variabl

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Revill, Andrew, Anna Florence, Alasdair MacArthur, Stephen Hoad, Robert Rees, and Mathew Williams. "The Value of Sentinel-2 Spectral Bands for the Assessment of Winter Wheat Growth and Development." Remote Sensing 11, no. 17 (2019): 2050. http://dx.doi.org/10.3390/rs11172050.

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Leaf Area Index (LAI) and chlorophyll content are strongly related to plant development and productivity. Spatial and temporal estimates of these variables are essential for efficient and precise crop management. The availability of open-access data from the European Space Agency’s (ESA) Sentinel-2 satellite—delivering global coverage with an average 5-day revisit frequency at a spatial resolution of up to 10 metres—could provide estimates of these variables at unprecedented (i.e., sub-field) resolution. Using synthetic data, past research has demonstrated the potential of Sentinel-2 for estim

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Yu, Zhuohui, Qingning Lin, and Changli Huang. "Re-Measurement of Agriculture Green Total Factor Productivity in China from a Carbon Sink Perspective." Agriculture 12, no. 12 (2022): 2025. http://dx.doi.org/10.3390/agriculture12122025.

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Accurate measurement of agricultural total factor productivity (AGTFP) is crucial to measure the level of sustainable agricultural development, and agricultural carbon sink is an important element to leverage the development of green transformation. Few studies have incorporated agricultural carbon sink into the measurement framework of AGTFP, and the evolutionary dynamics and related spatial effects of Chinese AGTFP from the perspective of carbon sinks are unclear. On this basis, the paper used a provincial-level agricultural panel data set of China from 2000 to 2019 to measure the provincial

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Ambali, Omotuyole Isiaka, Francisco Jose Areal, and Nikolaos Georgantzis. "On Spatially Dependent Risk Preferences: The Case of Nigerian Farmers." Sustainability 13, no. 11 (2021): 5943. http://dx.doi.org/10.3390/su13115943.

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Rice farmers’ attitudes toward risk-taking have been identified as one of the factors affecting investment decisions and wealth accumulation. While existing studies have identified the socio-economic factors driving farmers’ risk attitudes, spatial variables that may correlate with decisions are often ignored in the risk models due to difficulties in measurement. We studied unobserved spatial heterogeneity in farmer’s risk preferences by incorporating spatial dependency into a farmer’s risk preference model. We used data from a survey conducted with Nigerian farmers between March and May 2016.

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Olagbaju, Peter Oluwadamilare, Olanrewaju Bola Wojuola, and Victor Tshivhase. "Radionuclides Contamination in Soil: Effects, Sources and Spatial Distribution." EPJ Web of Conferences 253 (2021): 09006. http://dx.doi.org/10.1051/epjconf/202125309006.

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Radionuclide concentrations in the soil depend on the geological and anthropogenic activities of an area. They influence level of gamma radiation in the environment, which can cause significant health risk in humans. Due to the non-uniform distribution of radionuclides in the soil, various measurement methods have been adopted to monitor our environment. The challenges involved in collecting environmental samples, duration, technicality and cost of measurement have led to various models for predicting unmeasured locations. This article presents geostatistical method using kriging techniques, w

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Zhang, Wenhua, Yinghai Ke, Lindi J. Quackenbush, and Lianjun Zhang. "Using error-in-variable regression to predict tree diameter and crown width from remotely sensed imagery." Canadian Journal of Forest Research 40, no. 6 (2010): 1095–108. http://dx.doi.org/10.1139/x10-073.

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Automated individual tree detection and delineation from high spatial resolution imagery provides good opportunities for forest inventory at a large scale. However, the accuracy of delineated crown size compared with ground measurements may not be sufficient. Thus, ordinary least squares (OLS) regression is no longer an appropriate approach to estimating and predicting variables from the delineated tree crown because both response variable and regressor are subject to measurement errors. In this study, we describe the functional and structural relationships between field-measured tree variable

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Beikahmadi, Niloufar, Antonio Francipane, and Leonardo Valerio Noto. "Smart Data Blending Framework to Enhance Precipitation Estimation through Interconnected Atmospheric, Satellite, and Surface Variables." Hydrology 10, no. 6 (2023): 128. http://dx.doi.org/10.3390/hydrology10060128.

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Accurate precipitation estimation remains a challenge, though it is fundamental for most hydrological analyses. In this regard, this study aims to achieve two objectives. Firstly, we evaluate the performance of two precipitation products from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM-IMERG) for Sicily, Italy, from 2016 to 2020 by a set of categorical indicators and statistical indices. Analyses indicate the favorable performance of daily estimates, while half-hourly estimates exhibited poorer performance, revealing larger discrepancies between satellit

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Tran, Thuong, Duy Tran, Hoa Pham, et al. "Exploring Spatial Relationship Between Electrical Conductivity and Spectral Salinity Indices in the Mekong Delta." Journal of Environmental Science and Management 23, no. 1 (2020): 39–49. http://dx.doi.org/10.47125/jesam/2020_1/05.

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The negative impact of salinization concurrent with drought is a severe problem that creates challenges for agriculture in deltas and coastal lowlands. This study aims to investigate the spatial relationship among the field measured electrical conductivity (EC) and spectral salinity indices derived from Remote sensed data in the Mekong Delta using Geographically Weighted Regression (GWR). A wide range of Landsat 8 Operational Land Images (OLI) products, including single bands, band ratios, vegetation indices (NDVI and EVI), intensity indices (INT), and brightness indices (BI) were employed for

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Li, Chang Hua, Zhi Jie Li, Long Fei Yuan, Xin Liu, and Fan Zhang. "A Retrieval Model of Spatial Configuration Based on Space Syntax Histogram." Advanced Materials Research 1044-1045 (October 2014): 1011–15. http://dx.doi.org/10.4028/www.scientific.net/amr.1044-1045.1011.

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With the application of space syntax theory in urban planning and architecture designing is growing continuously, the number of the urban spatial configuration models based on space syntax will be more and more. However, the use of these models still lacks of some intelligent retrieval models currently. This paper splits the urban spatial configuration into regular grid structure, and uses visibility segmentation to construct the relationship diagrams and then extracts space syntax variables from each node to form the four-dimensional histogram. Furthermore, this method calculates the similari

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Rico-González, Markel, José Pino Ortega, Fabio Yuzo Nakamura, Felipe Arruda Moura, and Asier Los Arcos. "Identification, Computational Examination, Critical Assessment and Future Considerations of Spatial Tactical Variables to Assess the Use of Space in Team Sports by Positional Data: A Systematic Review." Journal of Human Kinetics 77, no. 1 (2021): 205–21. http://dx.doi.org/10.2478/hukin-2021-0021.

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Abstract The aim of the review was to identify the spatial tactical variables used to assess the use of space in team sports using positional data. In addition, we examined computational methods, performed a critical assessment and suggested future considerations. We considered four electronic databases. A total of 3973 documents were initially retrieved and only 15 articles suggested original spatial variables or different computation methods. Spatial team sport tactical variables can be classified into 3 principal types: occupied space, total field coverage by several players; exploration sp

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Georges, Blandine, Adrien Michez, Hervé Piegay, Leo Huylenbroeck, Philippe Lejeune, and Yves Brostaux. "Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium)." PeerJ 9 (November 22, 2021): e12494. http://dx.doi.org/10.7717/peerj.12494.

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Managers need to know how to mitigate rising stream water temperature (WT) due to climate change. This requires identifying the environmental drivers that influence thermal regime and determining the spatial area where interventions are most effective. We hypothesized that (i) extreme thermal events can be influenced by a set of environmental factors that reduce thermal sensitivity and (ii) the role played by those factors varies spatially. To test these hypotheses, we (i) determined which of the environmental variables reported to be the most influential affected WT and (ii)identified the spa

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Chen, Howard, Mark C. Schall, and Nathan Fethke. "Effects of Movement Speed and Magnetic Disturbance on the Accuracy of Inertial Measurement Units." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (2017): 1046–50. http://dx.doi.org/10.1177/1541931213601745.

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This study evaluated the effects of motion speed and magnetic disturbance on the spatial orientation accuracy of an inertial measurement unit (IMU) on the hand. Thirteen participants performed six trials of a repetitive material transfer task. Movement speed (15, 30, 45 transfers/minute) and magnetic disturbance (absent, present) were the independent variables. Optical motion capture was the reference. Root-mean-square differences (RMSD) exceeded 20° when inclination measurements (pitch and roll) were calculated using the IMU accelerometer. A linear Kalman filter and a proprietary, embedded Ka

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Alsaeedi, Abdulaziz, and Fahad Alomairi. "Designing A Proposed Educational Program Based on Geographical Cloud Computing and Measuring its Effectiveness in Developing Research and Analysis Skills for Remote Sensing Big Data for Spatial Phenomena among Humanities Track Students at the Secondary Stage in Makkah." International Journal for Research in Education 48, no. 1 (2024): 28–65. http://dx.doi.org/10.36771/ijre.48.1.24-pp28-65.

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The study aims at designing a proposed educational program based on geographic cloud computing and measuring its effectiveness in developing research and analysis skills for remote sensing big data for spatial phenomena among humanities track students at the secondary stage in Makkah. To achieve this; An available random sample of (29) students was selected from the study population. The study followed the quasi-experimental approach with a one-group design and used the observation card, and the attitude test to collect data. Results showed; There are statistically significant differences at t

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Kinupp, V. F., and William E. Magnusson. "Spatial patterns in the understorey shrub genus Psychotria in central Amazonia: effects of distance and topography." Journal of Tropical Ecology 21, no. 4 (2005): 363–74. http://dx.doi.org/10.1017/s0266467405002440.

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We evaluated the effects of topography on the distribution of understorey herbs, shrubs and small trees of the pantropical genus Psychotria (Rubiaceae) in a 10000-ha rain-forest reserve in central Amazonia. As plots were long and thin, and followed altitudinal isoclines, we were able to avoid the trade off between plot size and precision of measurement of topographical variables. The minimum distance between plots (1 km) was sufficient to avoid spatial autocorrelation in topographical variables. However, indices of plot similarity based on species composition were spatially autocorrelated to d

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Toham, Andilo, Ernan Rustiadi, Bambang Juanda, and Rilus Kinseng. "Relationship of Participative planning, Planning Alignment and Regional Development Performance: Evidence from Special Region of Yogyakarta." Procedia of Social Sciences and Humanities 1 (January 30, 2021): 49–56. http://dx.doi.org/10.21070/pssh.v1i.18.

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Participatory planning is a necessity. Unfortunately, participatory planning has various problems that make it ineffective. Human resource capacity as an input factor for participatory planning is still inadequate. The participatory planning process has not optimized the best way of producing the outputs that are needed by the community. Spatial aspects of planning, activities in the space, and budgeting must be aligned. However, empirical facts show the inconsistency of development planning. The purpose of this study is to analyze the relationship between community participation in planning a

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