Spatial Optimization Strategies for High Temperature Heat Exposure Based on Thermally Vulnerable Populations and Case Studies

The objective of this study is to investigate the factors that contribute to brittleness and to identify strategies for mitigating these factors in populations with varying degrees of thermal vulnerability,based on the potential impact of extreme heat exposure on human survival and habitability.The physiological condition of lower adaptability to high temperature environments and the assessment of individuals who may have higher tolerance time in high temperature environments based on spatial perspectives suggest the need for targeted spatial optimization strategies for commuters and disadvantaged populations.This is demonstrated through a case study.These optimization measures encompass a variety of aspects,including the integration of transportation systems,the expansion of grey space corridors,the improvement of green space layout,and the implantation of green infrastructure.The study aims to reduce the exposure time of thermally vulnerable individuals to high temperature environments through spatial optimization strategies,to enhance the resilience of urban green spaces to heat stress,and to reduce the probability of heat-wave occurrence.

A Cautionary Note on the Application of GIS in Spatial Optimization Modeling

Spatial optimization as part of spatial modeling has been facilitated significantly by integration with GIS techniques. However, for certain research topics, applying standard GIS techniques may create problems which require attention. This paper serves as a cautionary note to demonstrate two problems associated with applying GIS in spatial optimization, using a capacitated p-median facility location optimization problem as an example. The first problem involves errors in interpolating spatial variations of travel costs from using kriging, a common set of techniques for raster files. The second problem is inaccuracy in routing performed on a graph directly created from polyline shapefiles, a common vector file type. While revealing these problems, the paper also suggests remedies. Specifically, interpolation errors can be eliminated by using agent-based spatial modeling while the inaccuracy in routing can be improved through altering the graph topology by splitting the long edges of the shapefile. These issues suggest the need for caution in applying GIS in spatial optimization study.

Exploring Smart Growth Boundaries of Urban Agglomeration with Land Use Spatial Optimization:A Case Study of Changsha-Zhuzhou-Xiangtan City Group,China

Urban agglomeration is the main spatial organization mode used by the Chinese government to promote the policy of new urbanization strategy.Hence,a better understanding of the urban growth boundary(UGB)has profound theoretical and practical significance regarding sustainable urban development.This study devised a raster-based land use spatial optimization(LUSO)framework,and utilized ant colony optimization(ACO)algorithm to delimit the smart growth boundaries of the Changsha-Zhuzhou-Xiangtan city group(CZTCG)in China.The aim of this study is to design a LUSO model to explore an optimal pattern of urban agglomeration for sustainable growth.Multi growth scenario including a single development center,multipolar development and balanced development patterns are generated by the LUSO model for the year of 2050,and the optimum spatial pattern is chosen based on objectives comparison and the present stage of economic and social development in CZTCG.The main results are listed as the following.1)It is feasible to identify the growth boundaries of the urban agglomeration using the land use spatial optimization model,and the optimal form of the spatial pattern can be defined.2)With the growth trend of the urban agglomeration gradually spreads from a single center to multi-centers and even small towns,the total optimization target performance gradually increases,which means that the traditional pie-shaped development does not meet the maximum comprehensive benefit of the city group.3)Subject to the regional social and economic development stage,absolute fair development or simply developing the central city is not conducive to promoting the coordinated development of the urban agglomeration.Gradient equalization and gradual advancement are the best choice for UGB delineation of urban agglomeration.The findings of this study would be useful to identify the UGB in CZTCG for more sustainable urban development in the future.

Combining spatial and economic criteria in tree-level harvest planning

Background:Modern remote sensing methods enable the prediction of tree-level forest resource data.However,the benefits of using tree-level data in forest or harvest planning is not clear given a relative paucity of research.In particular,there is a need for tree-level methods that simultaneously account for the spatial distribution of trees and other objectives.In this study,we developed a spatial tree selection method that considers tree-level(relative value increment),neighborhood related(proximity of cut trees)and global objectives(total harvest).Methods:We partitioned the whole surface area of the stand to trees,with the assumption that a large tree occupies a larger area than a small tree.This was implemented using a power diagram.We also utilized spatially explicit tree-level growth models that accounted for competition by neighboring trees.Optimization was conducted with a variant of cellular automata.The proposed method was tested in stone pine(Pinus pinea L.)stands in Spain where we implemented basic individual tree detection with airborne laser scanning data.Results:We showed how to mimic four different spatial distributions of cut trees using alternative weightings of objective variables.The Non-spatial selection did not aim at a particular spatial layout,the Single-tree selection dispersed the trees to be cut,and the Tree group and Clearcut selections clustered harvested trees at different magnitudes.Conclusions:The proposed method can be used to control the spatial layout of trees while extracting trees that are the most economically mature.

Evaluation, simulation, and optimization of land use spatial patterns for high-quality development: A case study of Zhengzhou city, China

High-intensity land use and resource overloaded-induced regional land use spatial pattern(LUSP)are essential and challenging for high-quality development.The empirical studies have shown that a scientific land uses spatial layout,and the supporting system should be based on a historical perspective and require better considering the double influence between the current characteristics and future dynamics.This study proposes a comprehensive framework that integrates the resource environment carrying capacity(RECC)and land use change(LUC)to investigate strategies for optimizing the spatial pattern of land use for high-quality development.China’s Zhengzhou city was the subject of a case study whose datasets include remote sensing,spatial monitoring,statistics,and open sources.Three significant results emerged from the analysis:(1)The RECC has significant spatial differentiation but does not follow a specific spatial law,and regions with relatively perfect ecosystems may not necessarily have better RECC.(2)From 2020 to 2030,the construction land and farmland will fluctuate wildly,with the former increasing by 346.21 km^(2) and the latter decreasing by 295.98 km^(2).(3)The study area is divided into five zones,including resource conservation,ecological carrying,living core,suitable construction,and grain supply zones,and each one has its LUSP optimization orientation.This uneven distribution of RECC reflects functional defects in the development and utilization of LUSP.In addition,the increase in construction land and the sharp decline of farmland pose potential threats to the sustainable development of the study area.Hence,these two elements cannot be ignored in the future high-quality development process.The findings indicate that the LUSP optimization based on dual dimensions of RECC and LUC is more realistic than a single-dimension solution,exhibiting the LUSP optimization’s effectiveness and applicability.

Who is in the Lower Reaches,Who Suffers Disasters?——Take Minqin County,a Disappearing Oasis as a Case

Minqin Oasis is located in the lower reaches of the Shiyanghe River Basin, northeast of the Heixi Corridor, at the middle of the Silk Road. Because of the its existence, Badain Jaran Desert and Tengger Desert cannot converge and develop in the south. It has always been an important green barrier to guarantee the eco-security of Hexi Corridor and the Silk Road for thousands of years. But in recent decades, Minqin Oasis is becoming smaller and the desert is becoming larger. Many people, especially the governmental officials in the lower reaches think that the upper and middle reaches have robbed the lower reaches of water resources, and caused insufficient water usage and the deteriorated eco-environment, in the lower reaches, However, the governmental officials in the upper and middle reaches claim that the whole river basin should take the upper and middle reaches as the key regions to develop economy. To address the above argument, we analyze the reasons why Minqin Oasis is disappearing, and find that there are two main factors. One is the quick development of population and economy in the upper and middle reaches; the other is the rapid development of population and economy in the lower reaches. The two factors both have great effect on the water utilization for eco-environment in the lower reaches. So Minqin Oasis is disappearing not only because of the upper and middle reaches but also because of the growth of population and economy itself. The lower reaches should not completely blame the upper and middle reaches. The upper and middle reaches should also pay more attention to the eco-environment in the lower reaches. The whole river basin should develop a harmonious and sustainable relationship among the upper, middle and lower reaches.

Spatial resource allocation via extremal optimization enhanced by cell-based local search

A new treatment is presented for land use planning problems by means of extremal optimization(EO)in conjunction to cell-based neighborhood local search.EO,inspired by self-organized critical models of evolution has been applied mainly to the solution of classical combinatorial optimization problems.Cell-based local search has been employed by the author elsewhere in problems of spatial resource allocation in combination with genetic algorithms and simulated annealing.In this paper,it complements EO in order to enhance its capacity for a spatial optimization problem.The hybrid method thus formed is compared to methods of the literature on a specific resource allocation problem by taking into account both the development and the transportation cost.It yields better results both in terms of objective function values and in terms of compactness.The latter is an important quantity for spatial planning and its meaning is discussed.The appearance of significant compactness values as emergent results is investigated.

Spatial Resilience to Wildfires through the Optimal Deployment of Firefighting Resources:Impact of Topography on Initial Attack Effectiveness

Strongly affected by the escalating impacts of climate change,wildfires have been increasing in frequency and severity around the world.The primary aim of this study was the development of specific territorial measures—estimating the optimal locations of firefighting resources—to enhance the spatial resilience to wildfires in the fire-prone region of Chalkidiki Prefecture in northern Greece.These measures focus on the resistance to wildfires and the adaptation of strategies to wildfire management,based on the estimation of burn probability,including the effect of anthropogenic factors on fire ignition.The proposed location schemes of firefighting resources such as vehicles consider both the susceptibility to fire and the influence of the topography on travel simulation,highlighting the impact of road slope on the initial firefighting attack.The spatial scheme,as well as the number of required firefighting forces is totally differentiated due to slope impact.When we ignore the topography effect,a minimum number of fire vehicles is required to achieve the maximization of coverage(99.2%of the entire study area)giving priority to the most susceptible regions(that is,employing 18 of 24 available fire vehicles).But when we adopt more realistic conditions that integrate the slope effect with travel time,the model finds an optimal solution that requires more resources(that is,employing all 24 available fire vehicles)to maximize the coverage of the most vulnerable regions within 27 min.This process achieves 80%of total coverage.The proposed methodology is characterized by a high degree of flexibility,and provides optimized solutions to decision makers,while considering key factors that greatly affect the effectiveness of the initial firefighting attack.

A Parametric Genetic Algorithm Approach to Assess Complementary Options of Large Scale Wind-solar Coupling

The transitional path towards a highly renewable power system based on wind and solar energy sources is investigated considering their intermittent and spatially distributed characteristics. Using an extensive weather-driven simulation of hourly power mismatches between generation and load, we explore the interplay between geographical resource complementarity and energy storage strategies. Solar and wind resources are considered at variable spatial scales across Europe and related to the Swiss load curve, which serve as a typical demand side reference. The optimal spatial distribution of renewable units is further assessed through a parameterized optimization method based on a genetic algorithm. It allows us to explore systematically the effective potential of combined integration strategies depending on the sizing of the system, with a focus on how overall performance is affected by the definition of network boundaries. Upper bounds on integration schemes are provided considering both renewable penetration and needed reserve power capacity. The quantitative trade-off between grid extension, storage and optimal wind-solar mix is highlighted.This paper also brings insights on how optimal geographical distribution of renewable units evolves as a function of renewable penetration and grid extent.

Urban Development Boundary Simulation Based on“Double Evaluation”and FLUS Model

The delimitation of urban development boundaries plays an important role in optimizing the nation land space.“Double evaluation”is one of the important means to study and predict the scale of new construction land in the future and to determine the spatial distribution of urban construction land.This study combines the“double evaluation”with the FLUS(Future Land-Use Simulation)model to study the delimitation of the urban development boundary of Yichang.The results show that:(1)the“double evaluation”method comprehensively considers the carrying capacity of the resource environmental bear and the suitability of urban development;(2)the FLUS model can better couple the“double evaluation”method for Land Use/Land Cover(LULC)suitability evaluation,Land Use/land Cover Change(LUCC)simulation and urban development boundary delineation,and the overall accuracy of the simulation reaches 96%;(3)according to the requirements of relevant national policies,this study divides the urban development boundary of the study area into concentrated construction areas,elastic development areas and special purpose areas.This function-based division can meet the requirements of urban flexible development,ecological protection and urban safety.This research combines the FLUS model,which is widely used in the simulation of LUCC,with the double evaluation method used in China’s new round of land and space planning to obtain the result of the urban development boundary.This result is consistent with the existing plan of the study area.

Optimization of spatial structure designs of control rod using Monte Carlo code RMC

Control rod is the most important approach to control reactivity in reactors,which is currently a cluster of pins filled with boron carbide(B4C).In this case,neutrons are captured in the outer region,and thus the inner absorber is inefficient.Moreover,the lifetime of the control rod is challenged due to the high reactivity worth loss resulted from the excessive degradation of B4C in the high flux area.In this work,some control rod designs are proposed with optimized spatial structures including the spatially mixed rod,radially moderated rod,and composite control rod with small-sized pins.The control rod worth and effective absorption cross section of these designs are computed using the Monte Carlo code RMC.A long-time depletion calculation is conducted to evaluate their burnup stability.For the spatially mixed rod,rare-earth absorbers are combined with B4C in spatial structure.Compared with the homogenous B4C rod,mixed designs ensure more sufficient reactivity worth in the lifetime of the reactor.The minimum reactivity loss at the end of the cycle is only 1.8%from the dysprosium titanate rod,while the loss for pure B4C rod is nearly 12%.For the radially moderated design,a doubled neutronic efficiency is achieved when the volume ratio of moderator equals approximately 0.3,while excessive moderating may lead to the failure of control rods.The control rod with small-sized pins processes an enhanced safety performance and saves the investment in absorbers.The rod worth can be further enhanced by introducing small moderator pins,and the reactivity loss caused by the reduction of absorbers is sustainable.

Memory access optimization for particle operations in computational fluid dynamics-discrete element method simulations

Computational Fluid Dynamics-Discrete Element Method is used to model gas-solid systems in several applications in energy,pharmaceutical and petrochemical industries.Computational performance bot-tlenecks often limit the problem sizes that can be simulated at industrial scale.The data structures used to store several millions of particles in such large-scale simulations have a large memory footprint that does not fit into the processor cache hierarchies on current high-performance-computing platforms,leading to reduced computational performance.This paper specifically addresses this aspect of memory access bottlenecks in industrial scale simulations.The use of space-flling curves to improve memory access patterns is described and their impact on computational performance is quantified in both shared and distributed memory parallelization paradigms.The Morton space flling curve applied to uniform grids and k-dimensional tree partitions are used to reorder the particle data-structure thus improving spatial and temporal locality in memory.The performance impact of these techniques when applied to two benchmark problems,namely the homogeneous-cooling-system and a fluidized-bed,are presented.These optimization techniques lead to approximately two-fold performance improvement in particle focused operations such as neighbor-list creation and data-exchange,with~1.5 times overall improvement in a fluidization simulation with 1.27 million particles.

Territorial Resilience Through Visibility Analysis for Immediate Detection of Wildfires Integrating Fire Susceptibility,Geographical Features,and Optimization Methods

Climate change effects tend to reinforce the frequency and severity of wildfires worldwide,and early detection of wildfire events is considered of crucial importance.The primary aim of this study was the spatial optimization of fire resources(that is,watchtowers)considering the interplay of geographical features(that is,simulated burn probability to delimit fire vulnerability;topography effects;and accessibility to candidate watchtower locations)and geo-optimization techniques(exact programming methods)to find both an effective and financially feasible solution in terms of visibility coverage in Chalkidiki Prefecture of northern Greece.The integration of all geographical features through the Analytical Hierarchy Process indicated the most appropriate territory for the installment of watchtowers.Terrain analysis guaranteed the independence and proximity of location options(applying spatial systematic sampling to avoid first order redundancy)across the ridges.The conjunction of the above processes yielded 654 candidate watchtower positions in 151,890 ha of forests.The algorithm was designed to maximize the joint visible area and simultaneously minimize the number of candidate locations and overlapping effects(avoiding second order redundancy).The results indicate four differentiated location options in the study area:(1)75locations can cover 90%of the forests(maximum visible area);(2)47 locations can cover 85%of the forests;(3)31locations can cover 80.2%of the forests;and(4)16 locations can cover 70.6%of the forests.The last option is an e fficient solution because it covers about 71%of the forests with just half the number of watchtowers that would be required for the third option with only about 10%additional forest coverage.However,the final choice of any location scheme is subject to agency priorities and their respective financial flexibility.

Land-use zoning in fast developing coastal area with ACO model for scenario decision-making

Potential ecological environment risks have been emerged as the result of land-use change(e.g.urbanization)in coastal areas.Conflicts between urban growth and ecological conservation should be brought to the forefront especially in the fast developing coastal areas.An optimized landscape pattern for land-use planning could reduce the risk at the regional scale.The cell-based allocation of different land use into the geospace(i.e.land-use spatial zoning,LUSZ)to form optimal pattern with planning objectives and constrains could be viewed as a spatial optimization problem.This study aims to develop a framework incorporated with ant colony algorithm optimization(ACO)to solve LUSZ problem based on the planning guideline of China.Three planning scenarios(i.e.development focusing on urban growth,development considering ecological conversion,and coordinative development between growth and protection)were devised and analyzed with the study area of Doumen District.Comparative analysis with landscape metrics and suitability evaluation indicates that scenario of coordinative development is more available and plausible for land-use change management.This study provides a quantitative and feasible procedure to achieve optimal development pattern on given planning objectives.Moreover,it also demonstrates that cell-based spatial optimization model can generate optimal planning scenarios for decision-making.

基于主体功能区的京津冀城市群碳收支时空分异与碳补偿分区

Research on the carbon budget and zoning for carbon compensation in major functional zones(MFZs)is important for formulating strategies for low-carbon development for each functional zone,promoting the collaborative governance of the regional ecological environment,and achieving high-quality development.Such work can also contribute to achieving peak emissions and carbon neutrality.This paper constructs a theoretical framework for the carbon budget and carbon compensation from the perspective of the MFZ,uses 157 county-level units of the Beijing-Tianjin-Hebei urban agglomeration(BTHUA)as the study area,and introduces the concentration index,normalized revealed comparative advantage index,and Self Organizing Mapping-K-means(SOM-K-means)model to examine spatio-temporal variations in the carbon budget and carbon compensation zoning for the BTHUA from the perspective of MFZs.The authors propose a scheme for the spatial minimization of carbon emissions as oriented by low-carbon development.The results show that:(1)From 2000 to 2017,the carbon budget exhibited an upward trend of volatility,its centralization index was higher than the“warning line”of 0.4,and large regional differences in it were noted on the whole.(2)There were significant regional differences in the carbon budget,and carbon emissions exhibited a core-periphery spatial pattern,with a high-value center at Beijing-Tianjin-Tangshan that gradually decreased as it moved outward.However,the spatial pattern of carbon absorption tended to be stable,showing an inverted“U-shaped”pattern.It was high in the east,north,and west,and was low in the middle and the south.(3)The carbon budget was consistent with the strategic positioning of the MFZ,and the optimized development zone and key development zone were the main pressure-bearing areas for carbon emissions,while the key ecological functional zone was the dominant zone of carbon absorption.The difference in the centralization index of carbon absorption among the functional zones was smaller than that in the centralization index of carbon emissions.(4)There were 53 payment areas,64 balanced areas,and 40 obtaining areas in the study area.Nine types of carbon compensation zones were finally formed in light of the strategic objectives of the MFZ,and directions and strategies for low-carbon development are proposed for each type.(5)It is important to strengthen research on the carbon balance and horizontal carbon compensation at a microscopic scale,enrich the theoretical framework of regional carbon compensation,integrate it into the carbon trading market,and explore diversified paths for achieving peak emissions and carbon neutrality.

An accurate selectivity estimation method for window queries and an implementation thereof

Spatial selectivity estimation is crucial to choose the cheapest execution plan for a given query in a query optimizer.This article proposes an accurate spatial selectivity estimation method based on the cumulative density(CD)histograms,which can deal with any arbitrary spatial query window.In this method,the selectivity can be estimated in original logic of the CD histogram,after the four corner values of a query window have been accurately interpolated on the continuous surface of the elevation histogram.For the interpolation of any corner points,we first identify the cells that can affect the value of point(x,y)in the CD histogram.These cells can be categorized into two classes:ones within the range from(0,0)to(x,y)and the other overlapping the range from(0,0)to(x,y).The values of the former class can be used directly,whereas we revise the values of any cells falling in the latter class by the number of vertices in the corresponding cell and the area ratio covered by the range from(0,0)to(x,y).This revision makes the estimation method more accurate.The CD histograms and estimation method have been implemented in INGRES.Experiment results show that the method can accurately estimate the selectivity of arbitrary query windows and can help the optimizer choose a cheaper query plan.