Using Moran's I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China

Fu, Weijun; Jiang, Peikun; Zhou, Guomo; Zhao, Keli

doi:10.5194/bg-11-2401-2014

Cited by 172 publications

(84 citation statements)

References 38 publications

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“…In this study, the combination of various methods of spatial-temporal analysis enables to demonstrate a high dynamic of the bean production in Brazilian municipalities between 1990 and 2013. We choose the Moran's Index because it is the most popular procedure for spatial dependencies, being applied in many research areas [34]. Besides, growth and acceleration rates are widely used for measuring percentage change of economic variables over time [35].…”

Section: Discussionmentioning

confidence: 99%

Spatial-Temporal Patterns of Bean Crop in Brazil over the Period 1990–2013

Clemente

Júnior

Guimarães

et al. 2017

IJGI

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Abstract:The understanding of spatial dependence and distribution of agricultural production factors is a key issue for the territorial planning and regional development. This study evaluates the spatial-temporal dynamics of bean crops in Brazil over the period 1990-2013. Common bean (Phaseolus vulgaris L.) is one of the staple foods for the Brazilian population, with nationwide production and cultivated mostly by family farmers. The analyzed variables of this crop included harvested area, produced quantity, and average crop yield. We investigated spatial autocorrelations using the Global and Local Moran Index. The global spatial autocorrelation statistics demonstrated a general spatial dependence of bean production over Brazil, while the local spatial autocorrelation statistics detect statistically significant zones of high and low bean-production attributes. Maps of growth and acceleration rate of the variables were constructed, showing the areas that increased, decreased, or stagnated during the time series. The results showed a considerable reduction of the bean harvested area, but there were significant increases in produced quantity and average crop yield. Results showed distinct and significant patterns of bean-production variables in Brazilian territory over the different years. Regional differences and peculiarities are evident, emphasizing the need for directing investments to agricultural research and public policy.

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Section: Discussionmentioning

confidence: 99%

Spatial-Temporal Patterns of Bean Crop in Brazil over the Period 1990–2013

Clemente

Júnior

Guimarães

et al. 2017

IJGI

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“…I is an extension of the Pearson product-moment correlation coefficient to a univariate series and is a measure of spatial autocorrelation (Moran 1950;Fu et al 2014) according to the following equation:…”

Section: Discussionmentioning

confidence: 99%

Effects of wind and tree density on forest fire patterns in a mixed-tree species forest

Song

Lee

2016

Forest Science and Technology

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It is well known that global climate change causes an increase in forest fire frequency and severity. Thus, understanding fire dynamics is necessary to comprehend the mitigation of the negative effects of forest fires. Our objective was to inform how fire spreads in a simulated two-species forest with varying wind strengths. The forest in this study was comprised of two different tree species with varying probabilities of transferring fire that was randomly distributed in space at densities (C tot ) ranging from 0.0 (low) to 1.0 (high). We studied the distribution pattern of burnt trees by using local rules of the two-dimensional model. This model incorporated wind blowing from south to north with strength (P w ) ranging from 0.0 (low) to 1.0 (high). Simulation results showed that when C tot > 0.45 the fire covered the entire forest, but when C tot 0.45 the fire did not spread. The wind effect on the variation of the amount of the burnt tree was maximized at the critical density and dramatically decreased with increasing C tot . Additionally, we found that the term of C tot and P w plays an important role in determining the distribution.

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“…The delineation of zones of low and high contents in gold was conducted through the application of local cluster analysis (Anselin 1995; Fu et al 2014; Goovaerts et al 2005; Goovaerts 2010). The basic idea is to compute at each grid node a local indicator of spatial autocorrelation (LISA) and test whether this statistic is significantly positive, indicating the existence of an aggregate of grid nodes with similar gold content, either low or high.…”

Section: Methodsmentioning

confidence: 99%

A Multivariate Geostatistical Methodology to Delineate Areas of Potential Interest for Future Sedimentary Gold Exploration

2016

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This paper describes a multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration, with an application to an abandoned sedimentary gold mining region in Portugal. The main challenge was the existence of only a dozen gold measurements confined to the grounds of the old gold mines, which precluded the application of traditional interpolation techniques, such as cokriging. The analysis could, however, capitalize on 376 stream sediment samples that were analyzed for twenty two elements. Gold (Au) was first predicted at all 376 locations using linear regression (R2=0.798) and four metals (Fe, As, Sn and W), which are known to be mostly associated with the local gold’s paragenesis. One hundred realizations of the spatial distribution of gold content were generated using sequential indicator simulation and a soft indicator coding of regression estimates, to supplement the hard indicator coding of gold measurements. Each simulated map then underwent a local cluster analysis to identify significant aggregates of low or high values. The one hundred classified maps were processed to derive the most likely classification of each simulated node and the associated probability of occurrence. Examining the distribution of the hot-spots and cold-spots reveals a clear enrichment in Au along the Erges River downstream from the old sedimentary mineralization.

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Using Moran's I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China

Cited by 172 publications

References 38 publications

Spatial-Temporal Patterns of Bean Crop in Brazil over the Period 1990–2013

Spatial-Temporal Patterns of Bean Crop in Brazil over the Period 1990–2013

Effects of wind and tree density on forest fire patterns in a mixed-tree species forest

A Multivariate Geostatistical Methodology to Delineate Areas of Potential Interest for Future Sedimentary Gold Exploration

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