Diffusion Model for Describing the Regional Spread of Huanglongbing from First-Reported Outbreaks and Basing an Area Wide Disease Management Strategy

Huanglongbing (HLB), a recent worldwide spreading disease on citrus, was detected in July 2009 in Yucatan State of Mexico. The objective of this study was to evaluate the fit of diffusion and classic disease gradient models to large-scale HLB spatial data originated from initial foci to improve sampling, monitoring, and control strategies for Diaphorina citri, vector of Candidatus Liberibacter asiaticus (CLas), putative agent of HLB. Four transect routes were selected: Yuc-1, Yuc-2, QRoo-1, and QRoo-2, based on the directionality of the prevailing winds and foci location of HLB infected plants. In these routes, 35 sites, 5 to 20 km apart, were selected for monthly evaluation during a 12-month period. A 10-insect sample and disease incidence and severity of HLB, further confirmed by PCR, were assessed per site. Mexican lime was more vulnerable (67.5%) than sweet orange (14%). Also, leaf symptoms were mostly found with homogeneous distribution but rarely reaching 100% of the tree canopy during the 12-month period. The diffusion model provided the best fit among the family of time-gradient curves (r2 = 0.90 to 0.99) due to the flexibility of a three-parameter model. The gradients were well conformed to the model in a 25 to 82.6 km range, having the east-west direction the longest effect. Yuc-2 and QRoo-2 transects showed 82.6 and 43.9 km gradients with a diffusion coefficient (Do) of 0.15 and 0.09, respectively. This study constitutes the first quantitative evidence of the regional spread of CLas from a single focus and the application of a flexible model that improved the fit and allowed to better compare different gradients. These results are useful to determine the size of Regional Areas of Diaphorina citri Control (ARCO), a management program currently implemented in Mexico to combat HLB.

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The Contribution of Neighborhood Tree and Greenspace to Asthma Emergency Room Visits: An Application of Advanced Spatial Data in Los Angeles County

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18073487 ◽

2021 ◽

Vol 18 (7) ◽

pp. 3487

Author(s):

Dohyung Kim ◽

Yongjin Ahn

Keyword(s):

Los Angeles ◽

Emergency Room ◽

Spatial Data ◽

Los Angeles County ◽

Large Scale ◽

Tree Canopy ◽

Neighborhood Environment ◽

Small Scale ◽

Emergency Room Visits ◽

Asthma Morbidity

This paper aims to investigate the role of neighborhood tree and greenspace on asthma morbidity, especially asthma emergency room visits. We employed advanced spatial data which allow for precisely capturing both the quantity and the features of tree and greenspace within a neighborhood environment. The results from the spatial regression models in Los Angeles County revealed that the features of trees and greenspace, such as the configuration of the tree canopy, the level of tree clustering, and private neighborhood greenspaces contribute to decreasing asthma morbidity, in addition to the quantity of tree and greenspace acreages. Notably, however, large scale greenspace, such as golf courses, school playgrounds, and parks fails to reduce the number of asthma emergency room visits at the statistically significant level. These findings imply that the creation of dense or clustered tree patches and small-scale neighborhood greenspaces might play a substantial role in mitigating air quality and consequently reducing asthma emergency room visits.

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A consistent link between drought and forest diebacks across Europe

10.5194/egusphere-egu2020-5679 ◽

2020 ◽

Author(s):

Cornelius Senf ◽

Allan Buras ◽

Christian Zang ◽

Anja Rammig ◽

Rupert Seidl

Keyword(s):

Vapor Pressure ◽

Large Scale ◽

Tree Mortality ◽

Vapor Pressure Deficit ◽

Tree Canopy ◽

Drought Indices ◽

Spatially Explicit ◽

Quantitative Evidence ◽

Drought Conditions ◽

Landsat Satellite

<p>Drought has been suggested as major driver of large-scale forest diebacks, but quantitative evidence covering large spatial and long temporal scales is rare for Europe. Combining spatially explicit maps of canopy mortality (i.e., partial or full loss of the dominant tree canopy) generated from Landsat satellite data for the period 1986-2016 and gridded drought indices (0.5&#176; resolution; including vapor pressure deficit, climatic water balance, and precipitation deficit), we report a consistent link between pulses of above-average tree mortality and drought conditions as measured in all three drought indices. As such, we deliver first quantitative evidence that drought conditions can trigger large-scale forest diebacks across Europe&#8217;s forests. A future increase in the severity and intensity of droughts as predicted for Europe might thus have unforeseen consequences for Europe&#8217;s forests, with large-scale forest diebacks likely becoming more common in the future.</p>

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Efficient Approximate Range Aggregation over Large-scale Spatial Data Federation

IEEE Transactions on Knowledge and Data Engineering ◽

10.1109/tkde.2021.3084141 ◽

2021 ◽

pp. 1-1

Author(s):

Yexuan Shi ◽

Yongxin Tong ◽

Yuxiang Zeng ◽

Zimu Zhou ◽

Bolin Ding ◽

...

Keyword(s):

Spatial Data ◽

Large Scale ◽

Data Federation

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Current Wildland Fire Patterns and Challenges in Europe: A Synthesis of National Perspectives

Air Soil and Water Research ◽

10.1177/11786221211028185 ◽

2021 ◽

Vol 14 ◽

pp. 117862212110281

Author(s):

Nieves Fernandez-Anez ◽

Andrey Krasovskiy ◽

Mortimer Müller ◽

Harald Vacik ◽

Jan Baetens ◽

...

Keyword(s):

Land Use ◽

Large Scale ◽

Wildland Fire ◽

Human Life ◽

Local Analysis ◽

Wildland Fires ◽

Fire Statistics ◽

Quantitative Evidence ◽

Wide Range ◽

Fire Patterns

Changes in climate, land use, and land management impact the occurrence and severity of wildland fires in many parts of the world. This is particularly evident in Europe, where ongoing changes in land use have strongly modified fire patterns over the last decades. Although satellite data by the European Forest Fire Information System provide large-scale wildland fire statistics across European countries, there is still a crucial need to collect and summarize in-depth local analysis and understanding of the wildland fire condition and associated challenges across Europe. This article aims to provide a general overview of the current wildland fire patterns and challenges as perceived by national representatives, supplemented by national fire statistics (2009–2018) across Europe. For each of the 31 countries included, we present a perspective authored by scientists or practitioners from each respective country, representing a wide range of disciplines and cultural backgrounds. The authors were selected from members of the COST Action “Fire and the Earth System: Science & Society” funded by the European Commission with the aim to share knowledge and improve communication about wildland fire. Where relevant, a brief overview of key studies, particular wildland fire challenges a country is facing, and an overview of notable recent fire events are also presented. Key perceived challenges included (1) the lack of consistent and detailed records for wildland fire events, within and across countries, (2) an increase in wildland fires that pose a risk to properties and human life due to high population densities and sprawl into forested regions, and (3) the view that, irrespective of changes in management, climate change is likely to increase the frequency and impact of wildland fires in the coming decades. Addressing challenge (1) will not only be valuable in advancing national and pan-European wildland fire management strategies, but also in evaluating perceptions (2) and (3) against more robust quantitative evidence.

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Spatial Agglomeration of China’s Forest Products Manufacturing Industry: Measurement, Characteristics and Determinants

Forests ◽

10.3390/f12081006 ◽

2021 ◽

Vol 12 (8) ◽

pp. 1006

Author(s):

Zhenhuan Chen ◽

Hongge Zhu ◽

Wencheng Zhao ◽

Menghan Zhao ◽

Yutong Zhang

Keyword(s):

Spatial Distribution ◽

Spatial Data ◽

Large Scale ◽

Manufacturing Industry ◽

Economies Of Scale ◽

Forest Products ◽

Spatial Data Analysis ◽

Forest Protection ◽

Spatial Agglomeration ◽

Continuous Space

China’s forest products manufacturing industry is experiencing the dual pressure of forest protection policies and wood scarcity and, therefore, it is of great significance to reveal the spatial agglomeration characteristics and evolution drivers of this industry to enhance its sustainable development. Based on the perspective of large-scale agglomeration in a continuous space, in this study, we used the spatial Gini coefficient and standard deviation ellipse method to investigate the spatial agglomeration degree and location distribution characteristics of China’s forest products manufacturing industry, and we used exploratory spatial data analysis to investigate its spatial agglomeration pattern. The results show that: (1) From 1988 to 2018, the degree of spatial agglomeration of China’s forest products manufacturing industry was relatively low, and the industry was characterized by a very pronounced imbalance in its spatial distribution. (2) The industry has a very clear core–periphery structure, the spatial distribution exhibits a “northeast-southwest” pattern, and the barycenter of the industrial distribution has tended to move south. (3) The industry mainly has a high–high and low–low spatial agglomeration pattern. The provinces with high–high agglomeration are few and concentrated in the southeast coastal area. (4) The spatial agglomeration and evolution characteristics of China’s forest products manufacturing industry may be simultaneously affected by forest protection policies, sources of raw materials, international trade and the degree of marketization. In the future, China’s forest products manufacturing industry should further increase the level of spatial agglomeration to fully realize the economies of scale.

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Estimating Forest Canopy Cover by Multiscale Remote Sensing in Northeast Jiangxi, China

Land ◽

10.3390/land10040433 ◽

2021 ◽

Vol 10 (4) ◽

pp. 433

Author(s):

Xiaolan Huang ◽

Weicheng Wu ◽

Tingting Shen ◽

Lifeng Xie ◽

Yaozu Qin ◽

...

Keyword(s):

Remote Sensing ◽

Large Scale ◽

Forest Canopy ◽

Canopy Cover ◽

Google Earth ◽

Tree Canopy ◽

Landsat Data ◽

High Resolution Data ◽

Modis Ndvi ◽

Tree Canopy Cover

This research was focused on estimation of tree canopy cover (CC) by multiscale remote sensing in south China. The key aim is to establish the relationship between CC and woody NDVI (NDVIW) or to build a CC-NDVIW model taking northeast Jiangxi as an example. Based on field CC measurements, this research used Google Earth as a complementary source to measure CC. In total, 63 sample plots of CC were created, among which 45 were applied for modeling and the remaining 18 were employed for verification. In order to ascertain the ratio R of NDVIW to the satellite observed NDVI, a 20-year time-series MODIS NDVI dataset was utilized for decomposition to obtain the NDVIW component, and then the ratio R was calculated with the equation R = (NDVIW/NDVI) *100%, respectively, for forest (CC >60%), medium woodland (CC = 25–60%) and sparse woodland (CC 1–25%). Landsat TM and OLI images that had been orthorectified by the provider USGS were atmospherically corrected using the COST model and used to derive NDVIL. R was multiplied for the NDVIL image to extract the woody NDVI (NDVIWL) from Landsat data for each of these plots. The 45 plots of CC data were linearly fitted to the NDVIWL, and a model with CC = 103.843 NDVIW + 6.157 (R2 = 0.881) was obtained. This equation was applied to predict CC at the 18 verification plots and a good agreement was found (R2 = 0.897). This validated CC-NDVIW model was further applied to the woody NDVI of forest, medium woodland and sparse woodland derived from Landsat data for regional CC estimation. An independent group of 24 measured plots was utilized for validation of the results, and an accuracy of 83.0% was obtained. Thence, the developed model has high predictivity and is suitable for large-scale estimation of CC using high-resolution data.

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Modeling and Implementation of Inter-Campuses Equipment Optimized Management Based on WebGIS

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.680.534 ◽

2013 ◽

Vol 680 ◽

pp. 534-539

Author(s):

Wei Feng Ma

Keyword(s):

Information Management ◽

Spatial Data ◽

Large Scale ◽

New Technology ◽

Rapid Expansion ◽

Mathematics Model ◽

Data Mapping ◽

Geographically Dispersed ◽

New Research ◽

Research Challenge

With the rapid expansion of the campus scale and the increasing of the geographically dispersed campus, how to adopt new theory, new method and new technology to realize the equipment optimized assignment and the information management is a new research challenge. It is the key to safeguard the national fund to use reasonably, and to speed up the development of education healthily. Through analyzing the domestic and foreign related research works, the paper proposed that it can take use of the spatial data expression and analysis with Geographic Information System (GIS) to realize the large-scale and inter-campuses equipment optimized assignment and information management. It discussed the mathematics model and the system architecture. Moreover, the paper described the key implementation technology in great detail such as spatial data mapping with MapInfo professional 9 and the development of WebGIS functions with MapXtreme. The results show that the solution is feasible and effective.

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A Research of Matching Algorithm and Strategy on Entity with Complex Area

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.209-211.252 ◽

2012 ◽

Vol 209-211 ◽

pp. 252-255

Author(s):

Li Guo ◽

Hai Ying Zheng ◽

Yong Hong Wang ◽

Bin Zhang

Keyword(s):

Spatial Data ◽

Large Scale ◽

Data Matching ◽

Large Scale Data ◽

Polygon Area ◽

Spatial Data Integration ◽

One And Many ◽

Complex Polygon ◽

Scale Data ◽

Matching Relation

Data matching technology is a key technology for spatial data integration and fusion. This paper represents a solution to the complex polygon area, defines the area overlapped rate in the aspect of geometric measure, presents the data matching idea based on area overlapped rate .Then, this paper discusses and realizes the data matching relation of area elements including one to one , many to one and many to many. At last, region targets are set as the study object, large scale data are taken for example. We draw the conclusion: this algorithm is efficient.

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Brothers or others in arms? Civilian constituencies and rebel fragmentation in civil war

Journal of Peace Research ◽

10.1177/0022343316675907 ◽

2017 ◽

Vol 55 (1) ◽

pp. 62-77 ◽

Cited By ~ 7

Author(s):

Eric S Mosinger

Keyword(s):

Social Networks ◽

Regression Analysis ◽

Collective Action ◽

Diffusion Model ◽

Theoretical Framework ◽

Quantitative Evidence ◽

Rebel Groups ◽

Two Factors ◽

Cross National

Why do united rebel fronts emerge in some insurgencies, while in other insurgencies multiple rebel groups mobilize independently to challenge the state, and often, each other? I develop a diffusion model of rebel fragmentation in which participation in rebellion spreads, completely or incompletely, through networks of civilians and dissidents. Using this theoretical framework I hypothesize that two factors jointly determine whether a rebel movement remains unified or fragments: the rebels’ investment in civilian mobilization, and the overall level of civilian grievances. The theory predicts that widely shared grievances motivate the formation of many small dissident groups willing to challenge the regime. Given the difficulty of collective action between disparate opposition actors, an emerging rebel movement will tend towards fragmentation when popular grievances are high. Yet extremely high civilian grievances can also help rebels activate broad, overlapping civilian social networks that serve to bridge together dissident groups. Mass-mobilizing rebel groups, benefiting from the participation of broad civilian networks, are most likely to forge and maintain a unified rebel front. I test this theory alongside several alternatives drawn from cross-national studies of conflict using regression analysis. The quantitative evidence lends considerable credence to the role of rebel constituencies in preventing or fomenting rebel fragmentation.

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