Regional-Scale Spatio-Temporal Analysis ofAnastrepha ludens(Diptera: Tephritidae) Populations in the Citrus Region of Santa Engracia, Tamaulipas, Mexico

2015 ◽  
Vol 108 (4) ◽  
pp. 1655-1664 ◽  
Author(s):  
Venancio Vanoye-Eligio ◽  
Ludivina Barrientos-Lozano ◽  
Roberto Pérez-Castañeda ◽  
Griselda Gaona-García ◽  
Manuel Lara-Villalon
Keyword(s):  
Regional Scale ◽  
Temporal Analysis ◽  
Spatio Temporal

scholarly journals Regional-scale Spatio-Temporal Analysis of Impacts of Weather on Traffic Speed in Chicago using Probe Data

2019 ◽  
Vol 155 ◽  
pp. 551-558
Author(s):  
Kuldeep Kurte ◽  
Srinath Ravulaparthy ◽  
Anne Berres ◽  
Melissa Allen ◽  
Jibonananda Sanyal
Keyword(s):  
Regional Scale ◽  
Temporal Analysis ◽  
Traffic Speed ◽  
Spatio Temporal

scholarly journals Spatially Explicit Soil Compaction Risk Assessment of Arable Soils at Regional Scale: The SaSCiA-Model

2018 ◽  
Vol 10 (5) ◽  
pp. 1618 ◽  
Author(s):  
Michael Kuhwald ◽  
Katja Dörnhöfer ◽  
Natascha Oppelt ◽  
Rainer Duttmann
Keyword(s):  
Risk Assessment ◽  
Sustainable Agriculture ◽  
Soil Compaction ◽  
Regional Scale ◽  
Temporal Analysis ◽  
Agricultural Landscapes ◽  
Spatially Explicit ◽  
Arable Soils ◽  
Actual Field ◽  
Spatio Temporal

Soil compaction caused by field traffic is one of the main threats to agricultural landscapes. Compacted soils have a reduced hydraulic conductivity, lower plant growth and increased surface runoff resulting in numerous environmental issues such as increased nutrient leaching and flood risk. Mitigating soil compaction, therefore, is a major goal for a sustainable agriculture and environmental protection. To prevent undesirable effects of field traffic, it is essential to know where and when soil compaction may occur. This study developed a model for soil compaction risk assessment of arable soils at regional scale. A combination of (i) soil, weather, crop type and machinery information; (ii) a soil moisture model and (iii) soil compaction models forms the SaSCiA-model (Spatially explicit Soil Compaction risk Assessment). The SaSCiA-model computes daily maps of soil compaction risk and associated area statistics for varying depths at actual field conditions and for entire regions. Applications with open access data in two different study areas in northern Germany demonstrated the model’s applicability. Soil compaction risks strongly varied in space and time throughout the year. SaSCiA allows a detailed spatio-temporal analysis of soil compaction risk at the regional scale, which exceed those of currently available models. Applying SaSCiA may support farmers, stakeholders and consultants in making decision for a more sustainable agriculture.

scholarly journals On the spatio-temporal analysis of hydrological droughts from global hydrological models

2011 ◽  
Vol 8 (1) ◽  
pp. 619-652 ◽  
Author(s):  
G. A. Corzo Perez ◽  
M. H. J. van Huijgevoort ◽  
F. Voß ◽  
H. A. J. van Lanen
Keyword(s):  
Time Series ◽  
20Th Century ◽  
Large Scale ◽  
Southern Oscillation ◽  
Regional Scale ◽  
Spatial Coherence ◽  
Temporal Analysis ◽  
Global Scale ◽  
Scale Models ◽  
Spatio Temporal

Abstract. The recent concerns for world-wide extreme events related to climate change phenomena have motivated the development of large scale models that simulate the global water cycle. In this context, analyses of extremes is an important topic that requires the adaptation of methods used for river basin and regional scale models. This paper presents two methodologies that extend the tools to analyze spatio-temporal drought development and characteristics using large scale gridded time series of hydrometeorological data. The methodologies are distinguished and defined as non-contiguous and contiguous drought area analyses (i.e. NCDA and CDA). The NCDA presents time series of percentages of areas in drought at the global scale and for pre-defined regions of known hydroclimatology. The CDA is introduced as a complementary method that generates information on the spatial coherence of drought events at the global scale. Spatial drought events are found through CDA by clustering patterns (contiguous areas). In this study the global hydrological model WaterGAP was used to illustrate the methodology development. Global gridded time series (resolution 0.5°) simulated with the WaterGAP model from land points were used. The NCDA and CDA were applied to identify drought events in subsurface runoff. The percentages of area in drought calculated with both methods show complementary information on the spatial and temporal events for the last decades of the 20th century. The NCDA provides relevant information on the average number of droughts, duration and severity (deficit volume) for pre-defined regions (globe, 2 selected climate regions). Additionally, the CDA provides information on the number of spatially linked areas in drought as well as their geographic location on the globe. An explorative validation process shows that the NCDA results capture the overall spatio-temporal drought extremes over the last decades of the 20th century. Events like the El Niño Southern Oscillation (ENSO) in South America and the pan-European drought in 1976 appeared clearly in both analyses. The methodologies introduced provide an important basis for the global characterization of droughts, model inter-comparison, and spatial events validation.

Spatio-Temporal Analysis of Frontal Midline Theta Rhythm in EEG during 3-D Maze Task

2009 ◽  
Vol 129 (10) ◽  
pp. 1778-1784
Author(s):  
Yasuaki Uehara ◽  
Keita Tanaka ◽  
Yoshinori Uchikawa ◽  
Bong-Soo Kim
Keyword(s):  
Theta Rhythm ◽  
Temporal Analysis ◽  
Maze Task ◽  
Frontal Midline Theta ◽  
Spatio Temporal

Spatio-temporal analysis and prediction of grain security in Shaanxi Province

2010 ◽  
Vol 17 (4) ◽  
pp. 770-775
Author(s):  
Ren YANG ◽  
Zhi-Yuan REN ◽  
Qian XU ◽  
Mei-Xia WANG
Keyword(s):  
Temporal Analysis ◽  
Shaanxi Province ◽  
Spatio Temporal ◽  
Grain Security

scholarly journals Spatio-Temporal Analysis of Water Quality Parameters in Machángara River with Nonuniform Interpolation Methods

Water ◽  
2016 ◽  
Vol 8 (11) ◽  
pp. 507 ◽  
Author(s):  
Iván Vizcaíno ◽  
Enrique Carrera ◽  
Margarita Sanromán-Junquera ◽  
Sergio Muñoz-Romero ◽  
José Luis Rojo-Álvarez ◽  
...  
Keyword(s):  
Water Quality ◽  
Temporal Analysis ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Interpolation Methods ◽  
Spatio Temporal
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