Effects of Spatiotemporal Constraints on Geostatistical Analysis of Groundwater Depth

Ground Water ◽  
2021 ◽  
Author(s):  
Amit Hellman ◽  
Gilboa Pe'er ◽  
Maribeth L. Kniffin ◽  
Ronnie Kamai
Keyword(s):  
Geostatistical Analysis ◽  
Groundwater Depth

Physical influencing factors of groundwater depth in Hotan Oasis

2009 ◽  
Vol 17 (1) ◽  
pp. 174-177 ◽  
Author(s):  
Min LIU ◽  
Ling-Mei HUANG ◽  
Bing SHEN ◽  
Yan-Jun SHEN
Keyword(s):  
Influencing Factors ◽  
Groundwater Depth

Geostatistical analysis of tuna (Thunnus obesus) longline fishing grounds in the Atlantic Ocean

2013 ◽  
Vol 20 (1) ◽  
pp. 198-204 ◽  
Author(s):  
Lingzhi LI ◽  
Lei WANG ◽  
Jian LIU ◽  
Qin LIU ◽  
Hongliang HUANG
Keyword(s):  
Atlantic Ocean ◽  
Geostatistical Analysis ◽  
Thunnus Obesus

scholarly journals Spatio-temporal distribution patterns of Plutella xylostella (Lepidoptera: Plutellidae) in a fine-scale agricultural landscape based on geostatistical analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jian-Yu Li ◽  
Yan-Ting Chen ◽  
Meng-Zhu Shi ◽  
Jian-Wei Li ◽  
Rui-Bin Xu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Plutella Xylostella ◽  
Agricultural Landscape ◽  
Seasonal Pattern ◽  
Distribution Patterns ◽  
Geostatistical Analysis ◽  
Distribution Model ◽  
Detailed Knowledge ◽  
Fine Scale ◽  
Spatio Temporal

AbstractA detailed knowledge on the spatial distribution of pests is crucial for predicting population outbreaks or developing control strategies and sustainable management plans. The diamondback moth, Plutella xylostella, is one of the most destructive pests of cruciferous crops worldwide. Despite the abundant research on the species’s ecology, little is known about the spatio-temporal pattern of P. xylostella in an agricultural landscape. Therefore, in this study, the spatial distribution of P. xylostella was characterized to assess the effect of landscape elements in a fine-scale agricultural landscape by geostatistical analysis. The P. xylostella adults captured by pheromone-baited traps showed a seasonal pattern of population fluctuation from October 2015 to September 2017, with a marked peak in spring, suggesting that mild temperatures, 15–25 °C, are favorable for P. xylostella. Geostatistics (GS) correlograms fitted with spherical and Gaussian models showed an aggregated distribution in 21 of the 47 cases interpolation contour maps. This result highlighted that spatial distribution of P. xylostella was not limited to the Brassica vegetable field, but presence was the highest there. Nevertheless, population aggregations also showed a seasonal variation associated with the growing stage of host plants. GS model analysis showed higher abundances in cruciferous fields than in any other patches of the landscape, indicating a strong host plant dependency. We demonstrate that Brassica vegetables distribution and growth stage, have dominant impacts on the spatial distribution of P. xylostella in a fine-scale landscape. This work clarified the spatio-temporal dynamic and distribution patterns of P. xylostella in an agricultural landscape, and the distribution model developed by geostatistical analysis can provide a scientific basis for precise targeting and localized control of P. xylostella.

scholarly journals The Application of Geostatistical Analysis on Radiometric Mapping Data to Recognized the Uranium and Thorium Anomaly in West Sulawesi, Indonesia.

2021 ◽  
Vol 819 (1) ◽  
pp. 012030
Author(s):  
I Gde Sukadana ◽  
I Wayan Warmada ◽  
Agung Harijoko ◽  
Frederikus Dian Indrastomo ◽  
Heri Syaeful
Keyword(s):  
Geostatistical Analysis ◽  
Mapping Data
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