Terraced fields and Mediterranean landscape structure: An analytical case study from Antikythera, Greece

Terraces are important capital investments in a range of agricultural landscapes worldwide, typically enduring well beyond any single farming cycle and over many human generations. This paper begins by emphasising that, while human population growth may often be loosely linked to terrace construction efforts, the association is by no means a straightforward one. We then argue that the choice of which parts of the landscape to terrace is driven by a range of cultural and environmental priorities that are most usefully explored by a combination of global, local and auto-correlative modelling, as well as via simulation-based methods. The results demonstrate that surficial geology, terrain slope, pre-existing terraces and pre-existing patterns of human habitation are all important structuring features. We also consider terraces as method for soil conservation, question the uncritical use of meso-scale erosion models and argue that patterns of catastrophic soil loss are often overstated in Mediterranean contexts. However, erosion modelling can, if deployed cautiously and comparatively, nonetheless be used to explore ways in which terraces do indeed manage localised soil movement in agriculturally favoured parts of the landscape, with our results suggesting that a substantial proportion of the erosion in this regions is indeed ameliorated by such measures.     

Null models reveal preferential sampling, spatial autocorrelation and overfitting in habitat suitability modelling

Nowadays, species are driven to extinction at a high rate. To reduce this rate it is important to delineate suitable habitats for these species in such a way that these areas can be suggested as conservation areas. The use of habitat suitability models (HSMs) can be of great importance for the delineation of such areas. In this study MaxEnt, a presence-only modelling technique, is used to develop HSMs for 223 nematode species of the Southern Bight of the North Sea. However, it is essential that these models are beyond discussion and they should be checked for potential errors. In this study we focused on two categories (1) errors which can be attributed to the database such as preferential sampling and spatial autocorrelation and (2) errors induced by the modelling technique such as overfitting, In order to quantify these adverse effects thousands of nulls models were created. The effect of preferential sampling (i.e. some areas where visited more frequenty than others) was investigated by comparing model outcomes based from null models sampling the actual sampling stations and null models sampling the entire mapping area (Raes and ter Steege, 2007). Overfitting is exposed by a fivefold cross-validation and the influence of spatial autocorrelation is assessed by separating test and training sets in space. Our results clearly show that all these effects are present: preferential sampling has a strong effect on the selection of non-random species models. Crossvalidation seems to have less influence on the model selection and spatial autocorrelation is also strongly present. It is clear from this study that predefined thresholds are not readily applicable to all datasets and additional tests are needed in model selection.     

珠江三角洲土地利用变化空间自相关分析

通过对复杂土地利用地学现象的空间与时间上的综合表达和描述,可揭示土地利用时空结构演变的内在规律,可以为研究区土地资源的合理利用、优化配置和可持续发展提供科学依据。本文利用珠江三角洲1990-2005年的土地利用数据,采用空间自相关分析方法对珠江三角洲土地利用／覆盖变化的空间特征进行了实证研究。通过对研究区全域空间自相关、单变量区域空间自相关、双变量区域空间自相关的计算,表明研究区土地利用／覆盖的全域空间自相关较弱,土地利用和开发存在随机性。单变量区域空间自相关和双变量区域空间白相关在不同区域、不同时期显现不同形态,揭示了研究区内部发展的差异性。空间自相关分析方法可直观地显示分析结果,不失为一种深入理解区域土地利用格局和变化的重要和有益的方法。     

Recursive residuals and model diagnostics for normal and non-normal state space models

Model diagnostics for normal and non-normal state space models are based on recursive residuals which are defined from the one-step ahead predictive distribution. Routine calculation of these residuals is discussed in detail. Various diagnostic tools are suggested to check, for example, for wrong observation distributions and for autocorrelation. The paper also discusses such topics as model diagnostics for discrete time series and model discrimination via Bayes factors. The case studies cover environmental applications such as analysing a time series of the number of daily rainfall occurrences and a time series of daily sulfur dioxide emissions.     

基于ESDA-GIS的黑龙江省区域经济差异研究

文章以黑龙江省81个县(市、区)为基本空间单元,在ArcView GIS软件和GeoDA空间统计分析软件的支持下,利用2009年黑龙江省县域人均GDP数据,对黑龙江省县域经济差异进行分析,分析结果表明:黑龙江省2009年总体经济差异较大,经济重心、人口重心和几何中心均有较大偏移,总体上黑龙江省2009年经济空间差异较大;全局Moran’s I指数为0.387 6,空间自相关特性明显,经济发展水平相似的地区在空间上集中分布。在此基础上绘制了局域Moran’s I散点图和LISA集聚图,并采用空间插值获得局域I值分异图。     

基于GIS和LSA的林地质量评价与保护分区

合理划定林地利用保护分区,对于稳定森林资源,维持生态平衡,协调经济建设与生态文明建设起到积极指导和规范作用.论文以海南省屯昌县为例,在科学评价林地质量的基础上,采用局部空间自相关分析法(LSA),探索林地质量在空间上的分布特性,耦合林地自然条件,社会经济及其空间属性,以作为林地保护分区的依据.结果显示:屯昌县林地质量分值在[5.40, 8.56]之间,整体水平中等偏上,内部差异性较小,其中,高等别林地主要分布在南坤镇与枫木镇交界处以及西昌镇西南部,低等别林地主要分布在坡心镇及南吕镇;全县林地质量在空间分布上表现出较强的正相关性,存在一定的空间聚集性特征;基于林地质量局部空间自相关分析的林地保护分区方案与林地质量评价结果基本吻合,可将全县分为重点保护区,积极保护区和一般保护区,不同保护区根据自相关类型的差异可采取不同的管护措施.该研究将空间属性纳入到林地保护分区方案的制定中,拓展了林地保护分区的手段,可为合理制定林地利用规划提供科学依据和思路借鉴.     

南疆西部不同植被类型NDVI对风沙灾害的响应

不同植被类型对风沙灾害的响应研究有助于风沙灾害的遥感监测评估和防灾减灾工作。采用传统统计学和空间自相关方法,利用MODIS的每日反射率和土地类型产品,分析了风沙灾害后南疆西部不同植被类型NDVI的变化规律及其空间分布特征。结果表明：风沙灾害后,研究区不同植被类型NDVI的差异在增大,NDVI变化值在一0．3865~0．4148之间,NDVI减小的面积占整个研究区面积的54．98％,变异系数增大值在2．44％～36．75％之间;受到风沙灾害的影响,研究区植被NDVI全局Moran’SI系数从0．7982减小到0．6786,但在空间上仍存在显著的正相关性,具有显著的空间集聚特征;由NDVI差值的局部空间自相关指标集聚图以及不同植被类型NDVI差值的空间关联区域面积百分比,可以发现落叶针叶林和裸地或低植被覆盖地受风沙灾害的影响较小,郁闭灌丛和作物受风沙灾害的影响较大。上述关于风沙灾害后南疆西部不同植被类型的变化及其空间格局的研究结果,不仅证明了防护林的风沙阻挡作用,也可以为风沙灾害的防治工作提供参考依据。     

黑龙江省粮食生产的时空格局及动因分析

采用空间自相关、聚类分析和多元回归模型等方法,论文探讨了2000 年以来黑龙江省粮食生产的时空动态及其主要影响因素.结果表明:① 黑龙江省粮食生产规模持续扩大,其中,大豆播种面积及其占农作物总播种面积的比重均经历了“上升-下降”的波动过程,玉米和水稻播种面积不断扩大,但其占农作物播种面积的比重分别在2009 和2011 年超过大豆;② 黑龙江省粮食生产具有一定的空间相关性,大豆空间集聚最显著,玉米次之,水稻最不明显;③ 粮食生产区域化和专门化态势增强,松嫩平原北部及大小兴安岭地区、松嫩平原东南部和三江平原北部分别形成了以大豆、玉米和水稻为主的粮食生产类型区;④ 多元回归分析表明,农业投入、经济环境、技术水平、市场因素是影响黑龙江省粮食生产及其结构时空变化的主要因素.     

中国农村居民食品消费碳排放的时空格局及其影响因素

在全球气候变化背景下,研究居民食品消费碳排放具有重要的意义。本文基于全国和地区农村居民家庭食品消费量调查数据及其人均食品消费碳排放的测算,运用ArcGIS空间统计分析、地理探测器因子探测等方法,分析2000—2019年中国农村居民家庭食品人均碳排放的时空格局及其驱动因素。结果表明：①碳排放结构中升降因素叠加,人均碳排放量增速不明显。②人均碳排放量存在空间集聚效应,但集聚程度呈下降趋势。③人均碳排放量、直接与间接排放量空间分异的影响因素不同。其中,人均碳排放量主要受到猪牛羊肉消费量、食品消费支出的影响。建议从优化农村居民的饮食结构,适度减少猪牛羊肉的消费量、增加综合碳折算系数较低的禽肉、蛋类、牛奶和鱼类等动物性食品的消费量,以及加强人均碳排放量较高地区饮食结构调整和优化的指导等方面,减少农村居民食品消费的人均碳排放量。     

长江旅游带旅游资源空间格局研究

旅游资源的空间格局是旅游产业规划、布局的重要基础。本文选择长江旅游带9省2市世界遗产地、国家级自然保护区、5A旅游景区、全国重点文物保护单位等12类共计4 729处旅游资源单体的空间分布数据,借助Arc GIS软件,运用空间自相关分析和核密度估计法对旅游资源空间格局进行了分析。结果表明,长江旅游带总体旅游资源、自然旅游资源和人文旅游资源在空间上均具有明显的聚类特征。总体旅游资源沿北纬30°线、G318国道以及沪昆、沪汉蓉高铁等交通主干线分布趋势明显;高级别旅游资源主要集中在长江三角洲地区;自然旅游资源主要集中在沪汉蓉及沪昆高铁沿线及其中间地带;人文旅游资源主要集聚在长江以南的长江三角洲、古徽州地区、滇西北地区以及黔东南少数民族地区。依据得出的旅游资源空间格局特征和分布规律,建议依托长江水道、G318国道和沿线高铁,打造东西向快速旅游通道和精品旅游线路;依托政策优势,联合多方组织机构形成跨区域旅游合作共同体。