Results 1 to 10 of about 78,148 (290)
Geographical Detector-based influence factors analysis for Echinococcosis prevalence in Tibet, China. [PDF]
PLoS Neglected Tropical Diseases, 2021 Echinococcosis, caused by genus Echinococcus, is the most pathogenic zoonotic parasitic disease in the world. In Tibet of the People's Republic of China, echinococcosis refers principally to two types of severe zoonosis, cystic echinococcosis (CE) and ...
Tian Ma +11 more
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Geographical detector-based risk assessment of the under-five mortality in the 2008 Wenchuan earthquake, China. [PDF]
PLoS ONE, 2011 On 12 May, 2008, a devastating earthquake registering 8.0 on the Richter scale occurred in Sichuan Province, China, taking tens of thousands of lives and destroying the homes of millions of people.
Yi Hu +4 more
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Specific urban units identified in tuberculosis epidemic using a geographical detector in Guangzhou, China. [PDF]
Infect Dis Poverty, 2022 Abstract Background A remarkable drop in tuberculosis (TB) incidence has been achieved in China, although in 2019 it was still considered the second most communicable disease. However, TB’s spatial features and risk factors in urban areas remain poorly understood.
Ren H, Lu W, Li X, Shen H.
europepmc +4 more sources
Environmental and social determinants of thyroid cancer: A spatial analysis based on the Geographical Detector. [PDF]
Front Endocrinol (Lausanne), 2022 IntroductionThyroid cancer has increased sharply in China in recent years. This change may be attributable to multiple factors. The current study aimed to explore the environmental and social determinants of thyroid cancer.MethodsIncidence data from 487 cancer registries in 2016 were collected.
Huo S, Liu Y, Sun A, Zhang B.
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Attribution analysis of land degradation in Hainan Island based on geographical detector
Ecological Indicators, 2022 Rapid and accurate surveys of land are essential for protecting ecosystems. This study aimed to survey the spatial–temporal land degradation patterns and explore its driving mechanism based on a geographical detector in Hainan Island from 2000 to 2020 ...
Wenyin Wu +6 more
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Geographical Detector-Based Identification of the Impact of Major Determinants on Aeolian Desertification Risk. [PDF]
PLoS One, 2016 Arid and semi-arid areas in North China are facing the challenge of a rising aeolian desertification risk (ADR) due to the intertwined effects of complex natural processes and intensified anthropogenic activities. An accurate quantitative assessment of the relationship between ADR and its determinants is beneficial for understanding the driving ...
Du Z, Xu X, Zhang H, Wu Z, Liu Y.
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Geographical Detector-Based Spatial Modeling of the COVID-19 Mortality Rate in the Continental United States. [PDF]
Int J Environ Res Public Health, 2021 Investigating the spatial distribution patterns of disease and suspected determinants could help one to understand health risks. This study investigated the potential risk factors associated with COVID-19 mortality in the continental United States. We collected death cases of COVID-19 from 3108 counties from 23 January 2020 to 31 May 2020.
Yue H, Hu T.
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Ecological Indicators, 2023 Grasshoppers are important elements for supporting ecosystem services which make it important to understand their spatial distribution characteristics to reduce outbreaks, implement effective control while minimizing non-target impacts.
Shuhua Wei +9 more
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Quantifying Spatiotemporal Dynamics of Vegetation and Its Differentiation Mechanism Based on Geographical Detector [PDF]
Environmental Science and Pollution Research, 2021 Abstract Understanding of the influence of factors on vegetation changes in different is still largely unknown. We have applied the Geographic Detector, a new spatial statistical method to study the interactive effects of factors on the spatial patterns of normalized vegetation index (NDVI) changes and determine the optimal characteristics of ...
Guangjie, Wang, Wenfu, Peng
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International Journal of Applied Earth Observation and Geoinformation, 2022 Geographical detector (GD) is a method to measure spatial associations using a power of determinant (PD) value that compares the variance of data within spatial zones and in the whole study area. Recent studies have implemented GD in diverse fields, such as environmental and socio-economic issues.
Zhang, Zehua, Song, Yongze, Wu, Peng
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