Effects of Spatial Aggregation on Forest Landscape Model Simulation in Northeastern China

Issues of scale and aggregation become important when large range of space and time scales is considered in landscape models.However,identifying appropriate levels of aggregation to accurately represent the processes and components of ecological systems is challenging.A raster-based spatially explicit forest landscape model,LANDIS,was used to study the effects of spatial aggregation on simulated spatial pattern and ecological process in Youhao Forest Bureau of the Small Khingan Mountain in Northeastern China.The model was tested over 500 simulation years with systematically increased levels of spatial aggregation.The results show that spatial aggregation significantly influences the simulation of fire disturbance,species abundance,and spatial pattern.Simulated fire regime was relatively insensitive to grain size between 30.m and 270.m in the region.Spatial aggregation from 300.m to 480.m dramatically decreased fire return interval(FRI) and increased mean fire size.Generally,species abundance and its aggregation index(AI) remained higher level over simulation years at the fine-grained level of spatial aggregation than at coarser grains.In addition,the simulated forest dynamics was more realistic at finer grains.These results suggest that appropriate levels of spatial aggregation for the model should not be larger than 270m.

S^(2)ANet:Combining local spectral and spatial point grouping for point cloud processing

Background Despite the recent progress in 3D point cloud processing using deep convolutional neural networks,the inability to extract local features remains a challenging problem.In addition,existing methods consider only the spatial domain in the feature extraction process.Methods In this paper,we propose a spectral and spatial aggregation convolutional network(S^(2)ANet),which combines spectral and spatial features for point cloud processing.First,we calculate the local frequency of the point cloud in the spectral domain.Then,we use the local frequency to group points and provide a spectral aggregation convolution module to extract the features of the points grouped by the local frequency.We simultaneously extract the local features in the spatial domain to supplement the final features.Results S^(2)ANet was applied in several point cloud analysis tasks;it achieved stateof-the-art classification accuracies of 93.8%,88.0%,and 83.1%on the ModelNet40,ShapeNetCore,and ScanObjectNN datasets,respectively.For indoor scene segmentation,training and testing were performed on the S3DIS dataset,and the mean intersection over union was 62.4%.Conclusions The proposed S^(2)ANet can effectively capture the local geometric information of point clouds,thereby improving accuracy on various tasks.

Spatial analysis of snail distribution in Jiangning county

Objective: To explore the spatial distribution of oncomelenia snails in Jiangning County. Methods: Cluster analysis and the Spatial Scan Statistics were performed based on the density of alive-snails in habitats and its rate infected by the 5. japonicum. Results : Although areas of snail habitats and density of the alive-snails in marshland in 2000 are higher significantly than that in mountain areas in Jiangning County, the numbers of habitats in mountain are more than that in marshland and they distributed sporadically. The snail habitats were classified into 4 in marshlands and 3 classes in mountain areas respectively in cluster analysis. Although they are mainly the one with low density of alive and infected snails, we should alert that there are also some habitats with high snail density and infection rate, which is important for the transmission of schis-tosomia. The analysis of Spatial Scan Statistics detected 2 significant spatial aggregations for alive-snail in marshland and 4 in mountain areas respectively with p-values less than 0. 01. There are also 2 significant spatial aggregations for infected snails in marshland. Conclusion: The significant spatial aggregations for alive-snails and infected snails indicated that there are some factors in the habitats suitable for the survival of snails and the transmission of schistosomia.

The Analysis of Spatial-Temporal Evolution of City Accessibility Based on Highway Network in Henan Province in China

Accessibility is an important tool to evaluate the maturity of a regional traffic network structure which describes the traffic convenience in the traffic network. The paper defines a new accessibility index by using the resident population weighted average value of the sum of inverse of the traveling time distance and time threshold coming from ordinary traffic network, and then uses this accessibility index to analyze the spatial-temporal characteristics of Henan highway network, as well as its evolution patterns from 2005 to 2020. The results show that with the expansion and improvement of Henan highway network, city accessibility level has been significantly improved, spatial convergence is obvious, the cities in the north central are always High-High aggregation area, the cities in the south are always Low-Low aggregation area, gradually forming the characteristics of Northwest high and Southeast low, relative balance between East and West. There is some non-conforming phenomenon in highway mileage growth and improvement of the city accessibility levels, but this situation is being weakened, the highway network layout is gradually rationalized, the spatial distribution of city accessibility and that of population are beginning to converge.

Effects of microtopography on spatial point pattern of forest stands on the semi-arid Loess Plateau,China

Microtopography may affect the distribution of forests through its effect on rain redistribution and soil water distribution on the semi-arid Loess Plateau,China.In this study,we investigated the characteristics of microtopography on two shady slopes（slope A,5 hm2,uniform slope;slope B,5 hm2,microtopography slope） and surveyed the height,the diameter at breast height and the location（x,y coordinates） of all selected individual trees（Robinia pseudoacacia Linn.,Pyrus betulifolia Bunge,Populus hopeiensis Hu ＆ Chow,Armeniaca sibirica Lam.,Populus simonii Carr.and Ulmus pumila Linn.） on slope A and slope B in the watersheds of Wuqi county,Shaanxi province.Subsequently,the effects of microtopography on the spatial pattern of forest stands were analyzed using Ripley＇s K（r） function.The results showed that：（1） The maximal aggregation radiuses of the tree species on the uniform slope（slope A） were larger than 40 m,whereas those of the tree species on the microtopography slope（slope B） were smaller than 30 m.（2） On slope B,the spatial association of R.pseudoacacia with P.betulifolia,A.sibirica,P.simonii and U.pumila varied from being strongly negative to positive at microtopography scales.The spatial association of Populus hopeiensis Hu ＆ Chow with U.pumila also varied from being strongly negative to positive at microtopography scales.However,there was no spatial association between P.betulifolia and P.hopeiensis,P.betulifolia and A.sibirica,P.betulifolia and P.simonii,P.betulifolia and U.pumila,P.hopeiensis and A.sibirica,P.hopeiensis and P.simonii,A.sibirica and P.simonii,A.sibirica and U.pumila,and P.simonii and U.pumila.On slope A,the spatial association between tree species were strongly negative.The results suggest that microtopography may shape tree distribution patterns on the semi-arid Loess Plateau.

Effect of Spatial and Temporal Scales on Habitat Suitability Modeling:A Case Study of Ommastrephes bartramii in the Northwest Pacific Ocean

Temporal and spatial scales play important roles in fishery ecology,and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution.The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling,with the western stock of winter-spring cohort of neon flying squid （Ornmastrephes bartramii） in the northwest Pacific Ocean as an example.In this study,the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature （SST） from remote sensing during August to October of 2003-2008 were used.We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales （0.5°,1 ° and 2°）,four longitude scales （0.5°,1°,2° and 4°）,and three temporal scales （week,fortnight,and month）.The coefficients of variation （CV） of the weekly,biweekly and monthly suitability index （SI） were compared to determine which temporal and spatial scales of SI model are more precise.This study shows that the optimal temporal and spatial scales with the lowest CV are month,and 0.5° latitude and 0.5° longitude for O.bartramii in the northwest Pacific Ocean.This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts.We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.

Research on the Optimal Aggregation Method of Judgment Matrices Based on Spatial Steiner-Weber Point

This paper is to provide a novel approach for the spatial aggregation of judgment matrices.The optimal aggregation method of judgment matrices based on spatial Steiner-Weber point can effectively aggregate the preference information of group members and achieve the optimization of group preference.The method comprises three key elements:The spatial mapping of the judgment matrices,the spatial optimal aggregation model of the judgment matrices,and the plant growth simulation algorithm(PGSA)is used to find the optimal aggregation points.Firstly,the judgment matrices are mapped into a set of spatial multidimensional coordinates by using spatial mapping rules.Secondly,the spatial Steiner-Weber point is used as the prototype to construct the spatial aggregation model.Thirdly,the PGSA algorithm is used to find the spatial aggregation points,whose spatial weighted Euclidean distance to all the decision makers’preference points is minimal.The optimal aggregation matrix is composed of these optimal aggregation points,which can accurately reflect the decision maker's comprehensive opinions.Finally,the effectiveness and rationality of this method are verified by comparing with the classical group preference aggregation methods.

A multi-resolution global land cover dataset through multisource data aggregation

Recent developments of 30 m global land characterization datasets （e.g., land cover, vegetation continues field） represent the finest spatial resolution inputs for global scale studies. Here, we present results from further improvement to land cover map- ping and impact analysis of spatial resolution on area estimation for different land cover types. We proposed a set of methods to aggregate two existing 30 m resolution circa 2010 global land cover maps, namely FROM-GLC （Finer Resolution Observa- tion and Monitoring-Global Land Cover） and FROM-GLC-seg （Segmentation）, with two coarser resolution global maps on development, i.e., Nighttime Light Impervious Surface Area （NL-ISA） and MODIS urban extent （MODIS-urban）, to produce an improved 30 m global land cover map-FROM-GLC-agg （Aggregation）. It was pos-processed using additional coarse res- olution datasets （i.e., MCD12Q1, GlobCover2009, MOD44W etc.） to reduce land cover type confusion. Around 98.9% pixels remain 30 m resolution after some post-processing to this dataset. Based on this map, majority aggregation and proportion ag- gregation approaches were employed to create a multi-resolution hierarchy （i.e., 250 m, 500 m, 1 km, 5 km, 10 km, 25 km, 50 km, 100 km） of land cover maps to meet requirements for different resolutions from different applications. Through accuracy assessment, we found that the best overall accuracies for the post-processed base map （at 30 m） and the three maps subse- quently aggregated at 250 m, 500 m, 1 km resolutions are 69.50%, 76.65%, 74.65%, and 73.47%, respectively. Our analysis of area-estimation biases for different land cover types at different resolutions suggests that maps at coarser than 5 km resolution contain at least 5% area estimation error for most land cover types. Proportion layers, which contain precise information on land cover percentage, are suggested for use when coarser resolution land cover data are required.