Dynamics in the Spatial Continuity of Insect Density

2015 ◽  
pp. 133-141
Author(s):  
Shelby J. Fleischer ◽  
Paul Blom ◽  
Daniel Emmen ◽  
Art Hower
Keyword(s):  
Spatial Continuity ◽  
Insect Density

scholarly journals Evaluating Machine Learning and Geostatistical Methods for Spatial Gap-filling of Monthly ESA CCI Soil Moisture in China

2021 ◽  
Vol 13 (14) ◽  
pp. 2848
Author(s):  
Hao Sun ◽  
Qian Xu
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Water Resource Management ◽  
Large Scale ◽  
Gap Filling ◽  
Spatial Continuity ◽  
Study Results ◽  
Data Gaps

Obtaining large-scale, long-term, and spatial continuous soil moisture (SM) data is crucial for climate change, hydrology, and water resource management, etc. ESA CCI SM is such a large-scale and long-term SM (longer than 40 years until now). However, there exist data gaps, especially for the area of China, due to the limitations in remote sensing of SM such as complex topography, human-induced radio frequency interference (RFI), and vegetation disturbances, etc. The data gaps make the CCI SM data cannot achieve spatial continuity, which entails the study of gap-filling methods. In order to develop suitable methods to fill the gaps of CCI SM in the whole area of China, we compared typical Machine Learning (ML) methods, including Random Forest method (RF), Feedforward Neural Network method (FNN), and Generalized Linear Model (GLM) with a geostatistical method, i.e., Ordinary Kriging (OK) in this study. More than 30 years of passive–active combined CCI SM from 1982 to 2018 and other biophysical variables such as Normalized Difference Vegetation Index (NDVI), precipitation, air temperature, Digital Elevation Model (DEM), soil type, and in situ SM from International Soil Moisture Network (ISMN) were utilized in this study. Results indicated that: 1) the data gap of CCI SM is frequent in China, which is found not only in cold seasons and areas but also in warm seasons and areas. The ratio of gap pixel numbers to the whole pixel numbers can be greater than 80%, and its average is around 40%. 2) ML methods can fill the gaps of CCI SM all up. Among the ML methods, RF had the best performance in fitting the relationship between CCI SM and biophysical variables. 3) Over simulated gap areas, RF had a comparable performance with OK, and they outperformed the FNN and GLM methods greatly. 4) Over in situ SM networks, RF achieved better performance than the OK method. 5) We also explored various strategies for gap-filling CCI SM. Results demonstrated that the strategy of constructing a monthly model with one RF for simulating monthly average SM and another RF for simulating monthly SM disturbance achieved the best performance. Such strategy combining with the ML method such as the RF is suggested in this study for filling the gaps of CCI SM in China.

scholarly journals Changes of Spatial Characteristics: Socio-Cultural Sustainability in Historical Neighborhood in Beijing, China

2021 ◽  
Vol 13 (11) ◽  
pp. 6212
Author(s):  
Huiming Liu ◽  
Bin Li
Keyword(s):  
Open Space ◽  
Morphological Characteristics ◽  
Analytical Framework ◽  
City Development ◽  
Original Design ◽  
Spatial Characteristics ◽  
Spatial Continuity ◽  
Cultural Sustainability ◽  
The City ◽  
Beijing China

This paper uses a typological approach as a tool to establish an analytical framework from a physical perspective to understand ‘place‘ and to identify key spatial characteristics that could adapt to local needs to deliver socio-cultural sustainability. Six representative housing types with their spaces and uses that were introduced in a historic neighborhood in Beijing, China are selected as case studies. Their morphological characteristics at the building, open space and neighborhood scales are examined, and typological transformations among the cases in terms of the degree of spatial continuity are identified. The paper proposes an analytical framework consisting of fifteen indicators to assess socio-cultural sustainability at the different morphological scales (building, open space and block/neighborhood) of the residents of the six cases. The score of changes from its original design is brought into calculations of continuities of spatial characteristics, which present the transitions and transformations of morphological characteristics in relation to adaptation of local needs and uses. The analysis results show that the spatial characteristics were changed when political-socioeconomic ideologies changed, and local needs and uses were transformed to follow these mutations, and finally, the methods of use in different morphological scales mostly differed from historical norms. Although the continuities of spatial characteristics were significantly changed, they are positively and continually accommodating the transformations and transitions of local needs and uses. On the other hand, the invariant spatial characteristics are important, which last despite transformation of the city development and changing of political-social-economic ideologies, and could be maintained for future development to enhance sociocultural sustainability.

scholarly journals Spatial continuity of soil attributes in an Atlantic Forest remnant in the Mantiqueira Range, MG

2013 ◽  
Vol 37 (1) ◽  
pp. 68-77 ◽  
Author(s):  
Marcela de Castro Nunes Santos ◽  
José Marcio de Mello ◽  
Carlos Rogério de Mello ◽  
Léo Fernandes Ávila
Keyword(s):  
Atlantic Forest ◽  
Spatial Dependence ◽  
Soil Bulk Density ◽  
Exchange Capacity ◽  
Dependence Structure ◽  
Spatial Continuity ◽  
Soil Attributes ◽  
Forest Remnant ◽  
Spatial Dependence Structure

The spatial characterization of soil attributes is fundamental for the understanding of forest ecosystems. The objective of this work was to develop a geostatistical study of chemical and physical soil attributes at three depths (D1 - 0-20 cm; D2 - 20-50 cm; D3 - 50-100 cm), in an Experimental Hydrographic Micro-catchment entirely covered by Atlantic Forest, in the Mantiqueira Range region, Minas Gerais. All the considered variables presented spatial dependence structure in the three depths, and the largest degrees of spatial dependence were observed for pH in the three depths, soil cation exchange capacity potential in D3, soil organic matter in D1 and D3 and clay and soil bulk density in D2. The method most used for the adjustments of semi-variogram models was the Maximum Likelihood and the most selected model was the Exponential. Furthermore, the ordinary kriging maps allowed good visualization of the spatial distribution of the variables.

Further Comment: Spatial Continuity Measures

1994 ◽  
Vol 26 (5) ◽  
pp. 639-649
Author(s):  
Robert F. Shurtz
Keyword(s):  
Spatial Continuity

Covariance table and PPMT: Spatial continuity mapping of multiple variables

2019 ◽  
pp. 106-114
Author(s):  
J. Kloeckner ◽  
C.Z. da Silva ◽  
J.F.C.L. Costa
Keyword(s):  
Spatial Continuity ◽  
Multiple Variables

scholarly journals Comprehensive Insights into Spatial-Temporal Evolution Patterns, Dominant Factors of NDVI from Pixel Scale, as a Case of Shaanxi Province, China

2021 ◽  
Vol 18 (19) ◽  
pp. 10053
Author(s):  
Hongliang Gu ◽  
Min Chen
Keyword(s):  
Vegetation Indices ◽  
Geographic Location ◽  
Boosted Regression Trees ◽  
Shaanxi Province ◽  
Location Factors ◽  
Annual Average ◽  
Spatial Continuity ◽  
The North ◽  
Driving Mechanisms ◽  
Pixel Scale

Based on long term NDVI (1982–2015), climate, topographic factors, and land use type data information in Shaanxi Province, multiple methods (linear regression, partial and multiple correlation analysis, redundancy analysis and boosted regression trees method) were conducted to evaluate the spatial-temporal change footprints and driving mechanisms in the pixel scale. The results demonstrated that (1) the overall annual average and seasonal NDVI in this region showed a fluctuating upward trend, especially in spring. The difference between the end of season (eos) and start of season (sos) gradually increased, indicating the occurrence of temporal “greening” across most Shaanxi Province. (2) The overall spatial distribution of annual mean NDVI in Shaanxi Province was prominent in the south and low in the north, and 98.83% of the areas had a stable and increasing trend. Pixel scale analysis reflected the spatial continuity and heterogeneity of NDVI evolution. (3) Trend and breakpoint evaluation results showed that evolutionary trends were not homogeneous. There were obvious breakpoints in the latitude direction of NDVI evolution in Shaanxi Province, especially between 32–33°N and in the north of 37° N. (4) Compared with precipitation, the annual average temperature was significantly correlated with the vegetation indices (annual NDVI, max NDVI, time integrated NDVI) and phenology metrics (sos, eos). (5) Considering the interaction between environmental variables, the NDVI evolution was dominated by the combined influence of climate and geographic location factors in most areas.

scholarly journals 3D implicit modeling applied to the evaluation of CO2 geological storage in the shales of the Irati Formation, Paraná Basin, Southeastern Brazil

2021 ◽  
Author(s):  
Saulo B. de Oliveira ◽  
Colombo C. G. Tassinari ◽  
Richardson M. A-A. ◽  
Ignacio Torresi
Keyword(s):  
Black Shales ◽  
Hydrocarbon Exploration ◽  
Southeastern Brazil ◽  
Geological Storage ◽  
Spatial Continuity ◽  
Irati Formation ◽  
Aquifer Systems ◽  
Paraná Basin ◽  
Implicit Modeling ◽  
Parana Basin

Abstract The Paris Agreement established global ambitious targets for reducing carbon dioxide (CO2) emissions, requiring the rapid and extensive development of low carbon technologies, and one of the most efficient is CO2 geological storage. Among the deep geological formations used for CO2 storage, the shale layers have been a new emerging topic showing to be efficient because they are abundant and have a high content of organic matter, being favorable for CO2 retention. However, one of the challenges in evaluating a location for possible reservoirs is the adequate geological characterization and storage volume estimates. This research evaluated the Irati Formation of the Paraná Basin, through the information from hydrocarbon exploration wells in Southeastern Brazil, where most stationary sources of carbon emissions are located. Three-dimensional (3D) implicit modeling techniques were applied not only for the volume calculation purpose, but also in the site selection stage, generating thematic 3D models of thickness, depth, structures, and distance to aquifer systems. The limestones, shales, and black shales of the Irati Formation were locally divided into six units according to geological composition and spatial continuity. The E black shale unit was considered for CO2 geological storage indicating a theoretical capacity of 1.85 Gt of CO2. The potential of the achieved capacity is promising not only for been greater than the total of CO2 locally produced but also for supporting the implantation of new projects in this region.

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