Spatial Pattern of Trees in the Major Forest Types of Northern Ontario

1974 ◽  
Vol 4 (1) ◽  
pp. 8-14 ◽  
Author(s):  
Bijan Payandeh
Keyword(s):  
Spatial Pattern ◽  
Spatial Patterns ◽  
Simulation Modelling ◽  
Species Group ◽  
Stand Development ◽  
Forest Types ◽  
Northern Ontario ◽  
Growth Simulation ◽  
Natural Stands ◽  
Mixedwood Stands

This paper describes the spatial pattern, expressed by Pielou's nonrandomness index, of trees within 13 sampled tracts from the major forest types of northern Ontario. Results indicate that: (a) the majority of natural coniferous or mixedwood stands have highly clustered patterns; (b) hardwood stands or the hardwood component of the mixedwood stands show nearly 'random' spatial patterns; and (c) uniform spacing in natural stands is very rare. Results also indicate that spatial patterns vary considerably during stand development for the various species group – size class combinations within a stand and between different forest types. The importance of spatial pattern and stand population dynamics is pointed out with regard to growth simulation modelling and mechanized harvesting and thinning studies.

Plot Edge Bias in Forest Stand Growth Simulation Models

1974 ◽  
Vol 4 (4) ◽  
pp. 419-423 ◽  
Author(s):  
Robert A. Monserud ◽  
Alan R. Ek
Keyword(s):  
Spatial Pattern ◽  
Spatial Patterns ◽  
Simulation Models ◽  
Bias Reduction ◽  
Forest Stand ◽  
Tree Size ◽  
Individual Tree ◽  
Growth Simulation ◽  
Relative Simplicity ◽  
Stand Growth

The problem of edge bias arising in the computation of individual tree competition in stand growth simulation models is discussed. The problem arises from difficulty in characterizing tree size and spatial patterns beyond the edge of the simulation plot. Various methods for reducing this bias are reviewed along with related assumptions and major sources of error. Methods which involve shifting the simulation plot image to form a set of border plots are judged best on the basis of likely bias reduction and the relative simplicity of introduced spatial pattern periodicity.

scholarly journals Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products

2021 ◽  
Vol 13 (5) ◽  
pp. 853
Author(s):  
Mohsen Soltani ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Principal Component ◽  
Small Scale ◽  
Dependence Structure ◽  
Test Case ◽  
Catchment Scale ◽  
Balance Approach

This study aims to improve the standard water balance evapotranspiration (WB ET) estimate, which is typically used as benchmark data for catchment-scale ET estimation, by accounting for net intercatchment groundwater flow in the ET calculation. Using the modified WB ET approach, we examine errors and shortcomings associated with the long-term annual mean (2002–2014) spatial patterns of three remote-sensing (RS) MODIS-based ET products from MODIS16, PML_V2, and TSEB algorithms at 1 km spatial resolution over Denmark, as a test case for small-scale, energy-limited regions. Our results indicate that the novel approach of adding groundwater net in water balance ET calculation results in a more trustworthy ET spatial pattern. This is especially relevant for smaller catchments where groundwater net can be a significant component of the catchment water balance. Nevertheless, large discrepancies are observed both amongst RS ET datasets and compared to modified water balance ET spatial pattern at the national scale; however, catchment-scale analysis highlights that difference in RS ET and WB ET decreases with increasing catchment size and that 90%, 87%, and 93% of all catchments have ∆ET < ±150 mm/year for MODIS16, PML_V2, and TSEB, respectively. In addition, Copula approach captures a nonlinear structure of the joint relationship with multiple densities amongst the RS/WB ET products, showing a complex dependence structure (correlation); however, among the three RS ET datasets, MODIS16 ET shows a closer spatial pattern to the modified WB ET, as identified by a principal component analysis also. This study will help improve the water balance approach by the addition of groundwater net in the ET estimation and contribute to better understand the true correlations amongst RS/WB ET products especially over energy-limited environments.

Spatial-Pattern-Induced Evolution of a Self-Replicating Loop Network

2006 ◽  
Vol 12 (4) ◽  
pp. 461-485 ◽  
Author(s):  
Keisuke Suzuki ◽  
Takashi Ikegami
Keyword(s):  
Pattern Formation ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Spiral Structure ◽  
Scale Interactions ◽  
Micro Scale ◽  
Macro Scale ◽  
Loop Network ◽  
Spatial Pattern Formation

We study a system of self-replicating loops in which interaction rules between individuals allow competition that leads to the formation of a hypercycle-like network. The main feature of the model is the multiple layers of interaction between loops, which lead to both global spatial patterns and local replication. The network of loops manifests itself as a spiral structure from which new kinds of self-replicating loops emerge at the boundaries between different species. In these regions, larger and more complex self-replicating loops live for longer periods of time, managing to self-replicate in spite of their slower replication. Of particular interest is how micro-scale interactions between replicators lead to macro-scale spatial pattern formation, and how these macro-scale patterns in turn perturb the micro-scale replication dynamics.

Spatial Patterns of Urban Innovation and Their Evolution from Perspectives of Capacity and Structure: Taking Shenzhen as an Example

2021 ◽  
Vol 11 (1) ◽  
pp. 7
Author(s):  
Erjie Hu ◽  
Di Hu ◽  
Handong He
Keyword(s):  
Spatial Distribution ◽  
Spatial Pattern ◽  
Distribution Pattern ◽  
Spatial Patterns ◽  
Spillover Effect ◽  
Tertiary Industry ◽  
Innovation Capacity ◽  
Structure Index ◽  
Secondary Industry ◽  
Spatial Spillover Effect

Innovation is a key factor for a country’s overall national strength and core competitiveness. The spatial pattern of innovation reflects the regional differences of innovation development, which can provide guidance for the regional allocation of innovation resources. Most studies on the spatial pattern of innovation are at urban and above spatial scale, but studies at urban internal scale are insufficient. The precision and index of the spatial pattern of innovation in the city needs to be improved. This study proposes to divide spatial units based on geographic coordinates of patents, designs the innovation capability and innovation structure index of a spatial unit and their calculation methods, and then reveals the spatial patterns of innovation and their evolutionary characteristics in Shenzhen during 2000–2018. The results show that: (1) The pattern of innovation capacity of secondary industry exhibited a pronounced spatial spillover effect with a positive spatial correlation. The innovation capacity and innovation structure index of the secondary industry evolved in a similar manner; i.e., they gradually extended from the southwest area to the north over time, forming a tree-like distribution pattern with the central part of the southwest area as the “root” and the northwest and northeast areas as the “canopy”. (2) The pattern of innovation capacity of tertiary industry also had a significant spatial spillover effect with a positive spatial correlation. There were differences between the evolutions of innovation capacity and innovation structure index of tertiary industry. Specifically, its innovation capacity presented a triangular spatial distribution pattern with three groups in the central and eastern parts of the southwest area and the south-eastern part of the northwest area as the vertices, while its innovative structure showed a radial spatial distribution pattern with the southwestern part of the southwest area as the source and a gradually sparse distribution toward the northeast. (3) There were differences between the evolution modes of secondary and tertiary industries. Areas with high innovation capacity in the secondary industry tended to be more balanced, while areas with high innovation capacity in the tertiary industry did not necessarily have a balanced innovation structure. Through the method designed in this paper, the spatial pattern of urban innovation can be more precise and comprehensive revealed, and provide useful references for the development of urban innovation.

scholarly journals The spatial pattern of methacholine bronchoconstriction recurs when supine independently of posture during provocation but does not recur between postures

2018 ◽  
Vol 125 (6) ◽  
pp. 1720-1730 ◽  
Author(s):  
Eric T. Geier ◽  
Kent Kubo ◽  
Rebecca J. Theilmann ◽  
Gordon K. Prisk ◽  
Rui C. Sá
Keyword(s):  
Spatial Pattern ◽  
Spatial Patterns ◽  
Odds Ratio ◽  
Dependent Lung ◽  
Lung Inflation ◽  
Imaging Condition ◽  
Prone Imaging ◽  
Ventilation Imaging ◽  
Supine Posture ◽  
Gravitational Influence

The location of lung regions with compromised ventilation (often called ventilation defects) during a bronchoconstriction event may be influenced by posture. We aimed to determine the effect of prone versus supine posture on the spatial pattern of methacholine-induced bronchoconstriction in six healthy adults (ages 21–41, 3 women) using specific ventilation imaging. Three postural conditions were chosen to assign the effect of posture to the drug administration and/or imaging phase of the experiment: supine methacholine administration followed by supine imaging, prone methacholine administration followed by supine imaging, and prone methacholine administration followed by prone imaging. The two conditions in which imaging was performed supine had similar spatial patterns of bronchoconstriction despite a change in posture during methacholine administration; the odds ratio for recurrent constriction was mean (SD) = 7.4 (3.9). Conversely, dissimilar spatial patterns of bronchoconstriction emerged when posture during imaging was changed; the odds ratio for recurrent constriction between the prone methacholine/supine imaging condition and the prone methacholine/prone imaging condition was 1.2 (0.9). Logistic regression showed that height above the dependent lung border was a significant negative predictor of constriction in the two supine imaging conditions ( P < 0.001 for each) but not in the prone imaging condition ( P = 0.20). These results show that the spatial pattern of methacholine bronchoconstriction is recurrent in the supine posture, regardless of whether methacholine is given prone or supine but that prone posture during imaging eliminates that recurrent pattern and reduces its dependence on gravitational height. NEW & NOTEWORTHY The spatial pattern of methacholine bronchoconstriction in the supine posture is recurrent and skewed toward the dependent lung, regardless of whether inhaled methacholine is administered while supine or while prone. However, both the recurrent pattern and the gravitational skew are eliminated if imaging is performed prone. These results suggest that gravitational influence on regional lung inflation and airway topography at the time of measurement play a role in determining regional bronchoconstriction in the healthy lung.

scholarly journals Spatial Pattern Oriented Multi-Criteria Sensitivity Analysis of a Distributed Hydrologic Model

2018 ◽  
Author(s):  
Mehmet Cüneyd Demirel ◽  
Julian Koch ◽  
Gorka Mendiguren ◽  
Simon Stisen
Keyword(s):  
Sensitivity Analysis ◽  
Spatial Variability ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Performance Measures ◽  
Sampling Strategy ◽  
Behavioral Model ◽  
Hydrologic Model ◽  
Actual Evapotranspiration ◽  
Model Parameters

Hydrologic models are conventionally constrained and evaluated using point measurements of streamflow, which represents an aggregated catchment measure. As a consequence of this single objective focus, model parametrization and model parameter sensitivity are typically not reflecting other aspects of catchment behavior. Specifically for distributed models, the spatial pattern aspect is often overlooked. Our paper examines the utility of multiple performance measures in a spatial sensitivity analysis framework to determine the key parameters governing the spatial variability of predicted actual evapotranspiration (AET). Latin hypercube one-at-a-time (LHS-OAT) sampling strategy with multiple initial parameter sets was applied using the mesoscale hydrologic model (mHM) and a total of 17 model parameters were identified as sensitive. The results indicate different parameter sensitivities for different performance measures focusing on temporal hydrograph dynamics and spatial variability of actual evapotranspiration. While spatial patterns were found to be sensitive to vegetation parameters, streamflow dynamics were sensitive to pedo-transfer function (PTF) parameters. Above all, our results show that behavioral model definition based only on streamflow metrics in the generalized likelihood uncertainty estimation (GLUE) type methods require reformulation by incorporating spatial patterns into the definition of threshold values to reveal robust hydrologic behavior in the analysis.

scholarly journals Spatial pattern evaluation of a calibrated national hydrological model – a remote sensing based diagnostic approach

2017 ◽  
Author(s):  
Gorka Mendiguren ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Hydrological Model ◽  
Remote Sensing Data ◽  
Driving Mechanism ◽  
Distributed Hydrological Model ◽  
Eof Analysis ◽  
Sensing Data ◽  
Spatio Temporal

Abstract. Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two source energy balance model (TSEB) driven mainly by satellite remote sensing data. The main hypothesis of the study is that while both approaches are essentially estimates, the spatial patterns of the remote sensing based approach are explicitly driven by observed land surface temperature and therefore represent the most direct spatial pattern information of ET; enabling its use for distributed hydrological model evaluation. Ideally the hydrological model simulation and remote sensing based approach should present similar spatial patterns and driving mechanism of ET. However, the spatial comparison showed that the differences are significant and indicating insufficient spatial pattern performance of the hydrological model. The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in 6 domains that are calibrated independently from each other, as it is often the case for large scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of Leaf Area Index (LAI), root depth (RD) and Crop coefficient (Kc) for each land cover type. This zonal approach of model parametrization ignores the spatio-temporal complexity of the natural system. To overcome this limitation, the study features a modified version of the DK-Model in which LAI, RD, and KC are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatio-temporal variability and spatial consistency between the 6 domains. The effects of these changes are analyzed by using the empirical orthogonal functions (EOF) analysis to evaluate spatial patterns. The EOF-analysis shows that including remote sensing derived LAI, RD and KC in the distributed hydrological model adds spatial features found in the spatial pattern of remote sensing based ET.

scholarly journals Effect of Disturbance Regimes on Spatial Patterns of Tree Species in Three Sites in a Tropical Evergreen Forest in Vietnam

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Do Thi Ngoc Le ◽  
Nguyen Van Thinh ◽  
Nguyen The Dung ◽  
Ralph Mitlöhner
Keyword(s):  
Spatial Patterns ◽  
Tree Species ◽  
Interspecific Interactions ◽  
Abundant Species ◽  
Evergreen Forest ◽  
Small Scale ◽  
Forest Types ◽  
Disturbance Regimes ◽  
Tropical Evergreen Forest ◽  
Disturbed Forest

The effects of disturbance regimes on the spatial patterns of the five most abundant species were investigated in three sites in a tropical forest at Xuan Nha Nature Reserve, Vietnam. Three permanent one-ha plots were established in undisturbed forest (UDF), lightly disturbed forest (LDF), and highly disturbed forest (HDF). All trees ≥5 cm DBH were measured in twenty-five 20 m × 20 m subplots. A total of 57 tree species belonging to 26 families were identified in the three forest types. The UDF had the highest basal area (30 m2 ha−1), followed by the LDF (17 m2 ha−1) and the HDF (13.0 m2 ha−1). The UDF also had the highest tree density (751 individuals ha−1) while the HDF held the lowest (478 individuals ha−1). Across all species, there were 417 “juveniles,” 267 “subadults,” and 67 “adults” in the UDF, while 274 “juveniles,” 230 “subadults,” and 36 “adults” were recorded in the LDF. 238 “juveniles,” 227 “subadults,” and 13 “adults” were obtained in the HDF. The univariate and bivariate data with pair- and mark-correlation functions of intra- and interspecific interactions of the five most abundant species changed in the three forest types. Most species indicated clumping or regular distributions at small scale, but a high ratio of negative interspecific small-scale associations was recorded in both the LDF and HDF sites. These were, however, rare in the UDF.

Improved Common Spatial Patterns on EEG Feature Extraction

2014 ◽  
Vol 926-930 ◽  
pp. 1814-1817
Author(s):  
Yu Yu Gao
Keyword(s):  
Feature Extraction ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Extraction Method ◽  
Common Spatial Pattern ◽  
Classification Result ◽  
Feature Extraction Method ◽  
Feature Information ◽  
Multi Class Classification ◽  
Recognition Capability

For extracting relatively stable and invariable feature from non-stationary EEG in mult-class pattern, many scholars study a feature extraction method, which is called as modified multi-classcommon spatial pattern. It adopts one-to-one strategy to expand common spatial pattern to multi-class classification. While for the solution of airspace filter, Kullback-Leibler distance defines pattern of discrimination of minimize difference within class and maximize difference between classes. And it establishes a function to measure difference within the class. The experiment verifies that the algorithm can obtain feature information with recognition capability which implys in the non-stationary EEG and acquires preferable classification result.

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