Improving correction quality for in-situ portable X-ray fluorescence (PXRF) using robust geographically weighted regression with categorical land-use types at a regional scale

Geoderma ◽  
2022 ◽  
Vol 409 ◽  
pp. 115615
Author(s):  
Mingkai Qu ◽  
Hongbo Liu ◽  
Xu Guang ◽  
Jian Chen ◽  
Yongcun Zhao ◽  
...  
Keyword(s):  
Land Use ◽  
Geographically Weighted Regression ◽  
Regional Scale ◽  
Weighted Regression ◽  
X Ray ◽  
Land Use Types

scholarly journals Soil Greenhouse Gas Emissions under Different Land-Use Types in Savanna Ecosystems of Kenya

2019 ◽  
Author(s):  
Sheila Wachiye ◽  
Lutz Merbold ◽  
Timo Vesala ◽  
Janne Rinne ◽  
Matti Räsänen ◽  
...  
Keyword(s):  
Land Use ◽  
Greenhouse Gas ◽  
Ghg Emissions ◽  
Measurement Data ◽  
Mitigation Strategies ◽  
P Value ◽  
Land Use Types ◽  
Wide Range ◽  
Carbon Dioxide Co2

Abstract. For effective climate change mitigation strategies, adequate data on greenhouse gas (GHG) emissions from a wide range of land-use and land cover types area prerequisite. However, GHG field measurement data are still scarce for many land-use types in Africa, causing a high uncertainty in GHG budgets. To address this knowledge gap, we present in situ measurements of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) emissions in the lowland part of southern Kenya. We conducted chamber measurements on gas exchange from four dominant land-use types (LUTs) and included (1) cropland, (2) grazed savanna, (3) bushland, and (4) conservation land. Between 29 November 2017 to 3 November 2018, eight measurement campaigns were conducted accounting for regional seasonality (including wet and dry seasons and transitions periods) in each LUT. Mean CO2 emissions for the whole observation period were significantly higher (p-value 

scholarly journals Determination of the Peak Hour Ridership of Metro Stations in Xi’an, China Using Geographically-Weighted Regression

2020 ◽  
Vol 12 (6) ◽  
pp. 2255 ◽  
Author(s):  
Lijie Yu ◽  
Yarong Cong ◽  
Kuanmin Chen
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Geographically Weighted Regression ◽  
Urban Land Use ◽  
Weighted Regression ◽  
Metro Station ◽  
Geographically Weighted Regression Model ◽  
Extra Peak ◽  
Deviation Coefficient

The ridership of a metro station during a city’s peak hour is not always the same as that during the station’s own peak hour. To investigate this inconsistency, this study introduces the peak deviation coefficient to describe this phenomenon. Data from 88 metro stations in Xi’an, China, are used to analyze the peak deviation coefficient based on the geographically weighted regression model. The results demonstrate that when the land around a metro station is mainly land for work, primary and middle schools, and residences, its station’s peak hour is consistent with the city’s peak hour. Additionally, the station’s peak hour is more likely to deviate from the city’s peak hour for suburban stations. There are two ridership options when designing stations, namely the extra peak hour ridership during a city’s peak hour and that during a station’s peak hour, and the larger of the two is used to design metro stations. The mixed land use ratio must be considered in urban land use planning, because although non-commuting land can mitigate the traffic pressure of a city’s peak hour, it may cause the deviation of the station’s peak hours from that of the city.

Estimating the Effects of DEM and Land Use Types on Soil Moisture Using HJ-1A CCD/IRS Images: A Case Study in Minhou County

2013 ◽  
Vol 726-731 ◽  
pp. 4572-4576 ◽  
Author(s):  
Yu Qin Liu ◽  
Jin Ming Sha ◽  
De Sheng Wang
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Land Surface ◽  
Vegetation Index ◽  
Vegetation Indexes ◽  
Land Use Types ◽  
Research Findings ◽  
Soil Moisture Status

Soil moisture is of great significance for regional resources and environments. The combination of land surface temperature (Ts) and vegetation index (VI) is appropriate for monitoring the regional surface soil moisture status. In this study, we employed HJ-1B CCD/IRS images,DEMand land use types to obtain the information about soil moisture for Minhou county in FuZhou. Firstly,TVDIreflected the soil moisture status was analyzed with in-situ soil moisture measurements based on two kinds of different vegetation indexes (NDVI/EVI). Secondly, the relationship betweenTVDIandDEMwas analyzed. Finally, the soil moisture status of each land use type was explored combined with the main land use types of study area. Research findings indicate that: (1)TVDIcan effectively reflect the spatial pattern of soil moisture andTs/EVIhas a higher accuracy thanTs/NDVI; (2) the spatial distribution of soil moisture is obviously affected by the altitude; (3) there exists correlationship between soil moisture and land use types in study area.

scholarly journals Examining Hotspots of Traffic Collisions and their Spatial Relationships with Land Use: A GIS-Based Geographically Weighted Regression Approach for Dammam, Saudi Arabia

2020 ◽  
Vol 9 (9) ◽  
pp. 540 ◽  
Author(s):  
Muhammad Tauhidur Rahman ◽  
Arshad Jamal ◽  
Hassan M. Al-Ahmadi
Keyword(s):  
Land Use ◽  
Saudi Arabia ◽  
Traffic Safety ◽  
Geographically Weighted Regression ◽  
Significant Proportion ◽  
Urban Land Use ◽  
Weighted Regression ◽  
Spatial Relationships ◽  
Population Densities ◽  
Crash Types

Examining the relationships between vehicle crash patterns and urban land use is fundamental to improving crash predictions, creating guidance, and comprehensive policy recommendations to avoid crash occurrences and mitigate their severities. In the existing literature, statistical models are frequently used to quantify the association between crash outcomes and available explanatory variables. However, they are unable to capture the latent spatial heterogeneity accurately. Further, the vast majority of previous studies have focused on detailed spatial analysis of crashes from an aggregated viewpoint without considering the attributes of the built environment and land use. This study first uses geographic information systems (GIS) to examine crash hotspots based on two severity groups, seven prevailing crash causes, and three predominant crash types in the City of Dammam, Kingdom of Saudi Arabia (KSA). GIS-based geographically weighted regression (GWR) analysis technique was then utilized to uncover the spatial relationships of traffic collisions with population densities and relate it to the land use of each neighborhood. Results showed that Fatal and Injury (FI) crashes were mostly located in residential neighborhoods and near public facilities having low to medium population densities on highways with relatively higher speed limits. Distribution of hotspots and GWR-based analysis for crash causes showed that crashes due to “sudden lane deviation” accounted for the highest proportion of crashes that were concentrated mainly in the Central Business District (CBD) of the study area. Similarly, hotspots and GWR analysis for crash types revealed that “collisions between motor vehicles” constitute a significant proportion of the total crashes, with epicenters mostly stationed in high-density residential neighborhoods. The outcomes of this study could provide analysts and practitioners with crucial insights to understand the complex inter-relationships between traffic safety and land use. It can provide useful guidance to policymakers for better planning and effective management strategies to enhance safety at zonal levels.

scholarly journals Exploring the Spatial Variation of the Relationship between Land Use and Water Quality in a Drainage Basin Using Geographically Weighted Regression

2020 ◽  
Vol 12 (2) ◽  
pp. 147-168
Author(s):  
Samuel Azua ◽  
Taiye Oluwafemi Adewuyi ◽  
Lazarus Mustapha Ojigi ◽  
Omafuvwe Joseph Mudiare
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Geographically Weighted Regression ◽  
Drainage Basin ◽  
Water Quality Management ◽  
Mixed Forest ◽  
Weighted Regression ◽  
Landsat 8 ◽  
Sample Points ◽  
The Relationship

The focus of this study is to determine the relationship between land use and water quality in the River Mu drainage basin for effective water quality management. Various land uses in the study area were identified and mapped using Landsat 8 OLI of 2016. Water samples were also collected from 112 sample sites using Stratified Random Sampling methods. The samples were analysed in terms of physicochemical parameters using standard methods. The results of land use and water quality parameters were regressed using Geographically Weighted Regression (GWR) to determine whether there exist spatially varying relationships. The results revealed that the local R2 values varied between 0.0 and 0.5, indicating a weak relationship between land use and water pollution, except for mixed forest and pH which recorded local R2 values of 0.7 towards the western region of the study area. This shows that the relationship between the two variables varied spatially across the drainage basin. The one-sample Kolmogorov Smirmov test-p<0.05 revealed that there were significant differences in pH (0.00), EC (0.00), turbidity (0.001), TDS (0.048), DO (0.003), NH4+ (0.002), Ca2+ (0.00), Cl- (0.036), Fe3+ (0.00) and Cr2+ (0.039) across the different sample points, whereas K+ (0.134), PO43- (0.715) and NO3- (0.501) were not significantly different across the different sample points. The study recommended that the procedure for water management be localized to sub-catchment and basin levels, to provide adequate attention to each sub-catchment depending on the level and nature of pollution identified.

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