作为复杂适应系统的农业文化遗产：复杂性的挑战

本文首先阐述了农业系统的复杂性,并对农业系统所面对不确定性,以及外部系统的冲击和压力而形成的动态性进行了分析,提出“复杂适应性系统理论”为研究活态的农业系统,尤其为研究中国的全球重要农业文化遗产（GIAHS）提供了可能,而这些农业文化遗产系统（或其中某些部分）对于研究抵抗力和自我良性管理具有重要的意义.本文认为当前研究中的相关方法将会对整个系统的认识产生新的见解,同时避免把系统分解为各组分进行微观研究再重新还原成整体的研究思路.本文通过综述与GIAHS相关的方法并将旅游引入农村系统（作为一种扰动）,认为可以创造新的方法来认识农村发展干预措施对古老景观的影响,特别是分布在中国农村的许多景观.     

Adaptive neural-based fuzzy inference system (ANFIS) approach for modelling hydrological time series

Abstract

The main aim of this study is to develop a flow prediction method, based on the adaptive neural-based fuzzy inference system (ANFIS) coupled with stochastic hydrological models. An ANFIS methodology is applied to river flow prediction in Dim Stream in the southern part of Turkey. Application is given for hydrological time series modelling. Synthetic series, generated through autoregressinve moving-average (ARMA) models, are then used for training data sets of the ANFIS. It is seen that the extension of input and output data sets in the training stage improves the accuracy of forecasting by using ANFIS.     

Evaluation of environmental parameters in logistic regression models for landslide susceptibility mapping

Abstract

The aim of this study was to determine how well the landslide susceptibility parameters, obtained by data-dependent statistical models, matched with the parameters used in the literature. In order to achieve this goal, 20 different environmental parameters were mapped in a well-studied landslide-prone area, the Asarsuyu catchment in northwest Turkey. A total of 4400 seed cells were generated from 47 different landslides and merged with different attributes of 20 different environmental causative variables into a database. In order to run a series of logistic regression models, different random landslide-free sample sets were produced and combined with seed cells. Different susceptibility maps were created with an average success rate of nearly 80%. The coherence among the models showed spatial correlations greater than 90%. Models converged in the parameter selection peculiarly, in that the same nine of 20 were chosen by different logistic regression models. Among these nine parameters, lithology, geological structure (distance/density), landcover-landuse, and slope angle were common parameters selected by both the regression models and literature. Accuracy assessment of the logistic models was assessed by absolute methods. All models were field checked with the landslides resulting from the 12 November 1999, Kayna?li Earthquake (Ms = 7.2).     

An improved direction relation detection model for spatial objects

Direction is a common spatial concept that is used in our daily life. It is frequently used as a selection condition in spatial queries. As a result, it is important for spatial databases to provide a mechanism for modeling and processing direction queries and reasoning. Depending on the direction relation matrix, an inverted direction relation matrix and the concept of direction pre- dominance are proposed to improve the detection of direction relation between objects. Direction predicates of spatial systems are also extended. These techniques can improve the veracity of direction queries and reasoning. Experiments show excellent efficiency and performance in view of direction queries.     

A fast clonal selection algorithm for feature selection in hyperspectral imagery

Clonal selection feature selection algorithm (CSFS) based on clonal selection algorithm (CSA), a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm (FCSFS) for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager (PHI) and the airborne visible/infrared imaging spectrometer (AVIRIS), respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.     

Biophysical factors of remote sensing approach in urban green analysis

Greenery in an urban environment is an important consideration when studying temperature, and such enquiry can benefit human health. The purpose of this paper is to investigate how ambient temperature in urban areas is affected by forests and parks. The focus is on biophysical parameters related to these green areas, such as impervious surface percentages, albedo, areal coverage, elevation, and leaf area index (LAI). Geographic information systems and remote sensing were used to quantify green spaces using a pixel-based method. It was found that coverage area has little correlation with temperature. Factor analysis was used to determine the minimum number of independent factors, which explained 63% of the variance of that temperature. Only elevation, LAI and albedo were significant biophysical factors. Guidelines for greenery programmes should include these significant data-sets to understand the influence of green areas on heat reduction.     

Understanding interlinkages between long-term trajectory of exposure and vulnerability,path dependency and cascading impacts of disasters in Saint-Martin (Caribbean)

This empirical and interdisciplinary study investigates the contribution of deeply enrooted social-political factors to the accumulation of exposure and vulnerability and amplification of cascading impacts of disasters, with implications on the creation and reinforcement of path dependency maintaining social-ecological systems on a maladaptive trajectory. Applying the Trajectory of Exposure and Vulnerability approach to Saint-Martin (Caribbean), we more specifically highlight how the causal chain linking historical geopolitical and political-institutional drivers to legal, economic, demographic, sociocultural, planning-related and environmental drivers, created the accumulation of exposure and vulnerability over time and contributed to the propagation and amplification of the impacts of tropical cyclones Irma and José in 2017. We find that historical social-political dynamics involving unsustainable development and settlement patterns, the weakness of local institutions, population mistrust in public authorities, high social inequalities and environmental degradation maintained Saint-Martin on a maladaptive trajectory through powerful reinforcing mechanisms operating both between and during cyclonic events. This study demonstrates that long-term interdisciplinary approaches are required for a better understanding of path dependency and the identification of levers to break it in risk-prone contexts. In Saint-Martin, breaking path dependency requires the alignment of local institutional capacities with national risk reduction policies, the promotion of social justice and involvement of local communities in decision making. This study therefore confirms the relevance of backward-looking approaches to support forward-looking climate adaptation.     

Gold Deposits in the Sanandaj–Sirjan Zone: Orogenic Gold Deposits or Intrusion‐Related Gold Systems?

Most of the known large gold deposits in Iran are located along the Sanandaj–Sirjan Zone, western Iran, which hosts a wide range of gold deposit types. Gold deposits in the belt, hosted in upper Paleozoic to upper Mesozoic volcano‐sedimentary sequences of lower greenschist to lower amphibolite metamorphic grade, appear to represent mainly orogenic and intrusion‐related gold deposit types. The largest resource occurs at Muteh, with smaller deposits/occurrences at Zartorosht, Qolqoleh, Kervian, Qabaqloujeh, Kharapeh, and Astaneh. Although a major part of the gold deposits in the Sanandaj–Sirjan Zone are related to metamorphic devolatilization, some deposits including Muteh and Astaneh are related to short‐lived disruptions in an extensional tectonic regime and are associated with magma generation and emplacement. The age of gold ore formation in the orogenic gold deposits is Late Cretaceous to Tertiary, reflecting peak‐metamorphism during regional Cretaceous–Paleocene convergence and compression. The Oligocene to Pliocene age of most intrusion‐related gold systems is consistent with the young structural setting of the gold ore bodies; these deposits are sequestered along normal faults, correlated with Middle to Late Tertiary extensional tectonic events. This relationship is comparable to the magmatic‐metallogenetic evolution of the Urumieh‐Dokhtar magmatic arc, where the number of different types of gold‐copper deposits and the magnitude of the larger ones followed development of a magmatic arc. The appropriate explanation may be related to two different stages of gold mineralization consisting of a first compressional phase during the Late Cretaceous to Early‐Middle Tertiary, which is related to orogenic gold mineralization in the Qolqoleh, Kervian, Qabaqloujeh, Kharapeh, and Zartorosht deposits, and the extensional phase during the Eocene to Pliocene that is recognized by young intrusion‐related gold mineralization in the Muteh and Astaneh deposits.     

Climatic Versus Tectonic Control on Storm Cyclicity in Mesoproterozoic Koldaha Shale, Vindhyan Supergroup, Central India

The 1.2 Ga-old Koldaha shale, central India reveals three orders of depositional cyclicities in its basal storm-dominated shelf succession. Visual appraisal as well as Fourier and MEM analyses concurs in this respect. Only the major storm events at intervals of a few thousands of years have left recognizable imprints. Interbedding of storm sandstones and fairweather shales is apparently climate-controlled. Packaging of about seven such climatic cycles results the second-order cyclicity befitting eccentricity cycles of contemporary scale. Nonetheless, for the erratic storm bed-thickness trends within the cycles some other factor/s might have played a role. The third order cycles are, more dominantly, correlatable with basinal tectonics.     

基于均值漂移的粒子滤波算法设计及其在导航数据处理中的应用

针对标准粒子滤波算法中存在的计算量大和粒子的权值退化的缺陷,将均值漂移算法和PF算法进行融合,设计基于均值漂移搜索算法的粒子滤波新算法。该算法仍遵从粒子滤波算法的计算框架,基本原理是利用MS算法对粒子的聚类作用,将均值漂移思想融合到粒子滤波算法的重要性采样过程中,对粒子集进行确定性搜索,使每个粒子收敛于局部最优值,这样粒子的状态表示更接近真实的状态分布,因此只需较少的粒子数便可达到未嵌入MS的使用大量粒子数的粒子滤波状态估计的性能,从而在缓解粒子的权值退化的同时提高粒子滤波算法的实时性。大量的数值试验和对GPS/DR组合导航数据处理的结果验证了该方法的有效性。