Spatial-temporal Analysis using Two-stage Clustering and GIS-based MCDM to Identify Potential Market Regions

This paper develops an optimization model for the diffusion effects of free samples under dynamic changes in potential market based on the characteristics of independent product and presents a two-stage method to figure out the sampling level. The impact analysis of the key factors on the sampling level shows that the increase of the external coefficient or internal coefficient has a negative influence on the sampling level. And the changing rate of the potential market has no significant influence on the sampling level whereas the repeat purchase has a positive one. Using logistic analysis and regression analysis, the global sensitivity analysis gives a whole analysis of the interaction of all parameters, which provides a two-stage method to estimate the impact of the relevant parameters in the case of inaccuracy of the parameters and to be able to construct a 95% confidence interval for the predicted sampling level. Finally, the paper provides the operational steps to improve the accuracy of the parameter estimation and an innovational way to estimate the sampling level.

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Spatial-Temporal Analysis of Mortality Using Splines

Biometrics ◽

10.2307/2533266 ◽

1995 ◽

Vol 51 (4) ◽

pp. 1352 ◽

Cited By ~ 6

Author(s):

A. van der Linde ◽

K.-H. Witzko ◽

K.-H. Jockel

Keyword(s):

Temporal Analysis ◽

Spatial Temporal Analysis

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Spatial-temporal Analysis of Soil Erosion in Grassland over the Past Three Decades in Sanjiangyuan Region, Qinghai Province, China

Geo-information Science ◽

10.3724/sp.j.1047.2011.00012 ◽

2011 ◽

Vol 13 (1) ◽

pp. 12-21 ◽

Cited By ~ 3

Author(s):

Lin HUANG ◽

Quanqin SHAO ◽

Jiyuan LIU

Keyword(s):

Soil Erosion ◽

Temporal Analysis ◽

Qinghai Province ◽

The Past ◽

Spatial Temporal Analysis

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Gross Primary Production and False Spring: a spatio-temporal analysis

10.5194/egusphere-egu2020-17837 ◽

2020 ◽

Author(s):

Emma Izquierdo-Verdiguier ◽

Raúl Zurita-Milla ◽

Álvaro Moreno-Martinez ◽

Gustau Camps-Valls ◽

Anja Klisch ◽

...

Keyword(s):

Climate Change ◽

Remote Sensing ◽

Primary Production ◽

Gross Primary Production ◽

Damage Index ◽

Temporal Analysis ◽

Environmental Stressors ◽

Impact Of Climate Change ◽

False Spring ◽

Spatial Temporal Analysis

Phenological information can be obtained from different sources of data. For instance, from remote sensing data or products and from models driven by weather variables. The former typically allows analyzing land surface phenology whereas the latter provide plant phenological information. Analyzing relationships between both sources of data allows us to understand the impact of climate change on vegetation over space and time. For example, the onset of spring is advanced or delayed by changes in the climate. These alterations affect plant productivity and animal migrations.Spring onset monitoring is supported by the Extended Spring Index (SI-x), which are a suite of regression-based models for key indicator plant species. These models (Schwartz et al. in 2013) are based on daily maximum and minimum temperature from the first day of the year (January 1st). The primary products of these models are the timing of first leaf and first bloom, but they also provide derivative products such as the timing of last freeze day and the risk of frost damage day (damage index) for each year. This information helps to understand if vegetation could have suffered from environmental stressors such as droughts or a late frost events. The effects of environmental stressors in vegetation could be captured by the false spring index, which relates the first leaf day and the last freeze day. Moreover, this information could be used to understand plant productivity as well as to evaluate the economic impact of climate change.Previous works studied the relationship between remote sensing and plant level products by means of spatial-temporal analysis between Gross Primary Production (GPP) and a spring onset index. However, they did not consider the possible impact of false spring effect in these relationships. Here, we present a spatial-temporal analysis between GPP and the damage index to better understand the effect of false springs (in annual gross photosynthesis data). The analysis is done for the period 2000 to 2015 over the contiguous US and at spatial resolution of 1 km. We used the MODIS annual sum of GPP and the damage and false spring indices derived from the SI-x models.

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Sustainable use of an extractivist reserve: a spatial-temporal analysis of environmental dynamics

Brazilian Journal of Biological Sciences ◽

10.21472/bjbs.040719 ◽

2017 ◽

Vol 4 (7) ◽

pp. 195-201

Author(s):

Joélia Natália Bezerra da Silva ◽

Janaína Vital de Albuquerque ◽

Luana de Oliveira Rodrigues

Keyword(s):

Remote Sensing ◽

Temporal Dynamics ◽

Vegetation Indices ◽

Sustainable Use ◽

Temporal Analysis ◽

Conservation Unit ◽

Climatic Regions ◽

Cardisoma Guanhumi ◽

Surrounding Areas ◽

Spatial Temporal Analysis

Due to its large territory, Brazil has different climatic regions, which determines biome variations and equally diverse ecosystems, of this variety of vegetal landscapes, accompanies the diversity of climates. In this context, results of studies carried out locally, which guide measures, decision-making laws and regulations that reach large scales in the territory, need to be carefully planned, because there is a high risk of disregarding environmental specificities of the studied areas. Therefore, this study aimed to analyze the environmental dynamics resulting from the impacts of the last decades that have affected the habitat of the guaiamum (Cardisoma guanhumi) in the Acaú-Goiana Extractivist Reserve (RESEX) and surrounding areas. The analysis of the spatial-temporal dynamics, in the RESEX and adjacent areas, was made from the vegetation indices (SAVI) through remote sensing. In this way, three images of the RESEX were analyzed, two from the year 2010 and one from 2015, in which the RESEX was already in full legal operation. It is noticeable that there are some areas within the Conservation Unit with small plots of exposed soil, which can demonstrate the occurrence of fires.

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DISPARITIES IN MUNICIPAL WASTE MANAGEMENT ACROSS EU-27. A GEOGRAPHICAL APPROACH

10.31235/osf.io/bf68j ◽

2016 ◽

Author(s):

Florin Constantin MIHAI

Keyword(s):

Waste Management ◽

Environmental Issues ◽

Hierarchical Cluster ◽

Temporal Analysis ◽

Municipal Waste ◽

Member States ◽

Municipal Waste Management ◽

Territorial Disparities ◽

Spatial Temporal Analysis ◽

The Eu

Inadequate waste management leads to many environmental issues and theadoption of an efficient and sustainable waste management has become apriority objective of the EU. However, besides the demographic factors, thevarious socio-economic and geographical conditions of this complex spacelead to major disparities in municipal waste management between North andSouth, East and West. This paper aims to do a spatial-temporal analysis ofthe Eurostat indicators using ascending hierarchical cluster analysis thatdivides the member states into five typological classes. The resulted mapshighlight territorial disparities among the Member States on municipalwaste management and also reveal the evolution of environmental policiesbetween 2003-2009 related to the EU acquis.

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