黑龙江省绥棱县多情景景观格局变化特征及碳储量时空演变分析

基于2000、2010、2020共3期绥棱县土地利用数据,利用InVEST模型测算2000—2020年绥棱县碳储量变化,并通过FLUS模型与Fragstats模型模拟出3种场景下绥棱县景观格局及碳储量变化。结果表明：1)2000—2010年期间,绥棱县景观破碎度增加,蔓延度下降;碳储量呈现上升趋势,共增加1.076×10⁵ t。2010—2020年期间,景观破碎度加剧,景观异质性增加;碳储量下降趋势明显,共减少0.609×10⁵ t。2)3种场景下景观异质性均有增加,生态保护场景相较其他2种场景有所缓解,自然发展场景与农田保护场景下碳储量均呈现下降趋势,分别为18.051×10⁶、18.059×10⁶ t,其中生态保护场景下碳存储量有所增加,为18.116×10⁶ t,相较自然发展场景高出6.08×10⁴ t。因此,通过分析绥棱县不同场景下土地景观格局变化特征,进而计算碳储量变化,为绥棱县国土空间规划提供参考依据,其中生态保护场景更有利于城镇发展,故应遵循...     

徐州市主城区绿地景观格局对PM2.5及PM10的影响

基于研究区7个国家监测站点的PM2.5、PM10数据,运用ArcGIS、Fragstats软件对徐州市主城区的遥感影像进行解译和绿地景观格局指数的计算,结合Excel、SPSS软件分析城市绿地景观格局在不同尺度上与PM2.5、PM10浓度之间的相关性,探寻绿地景观格局与PM2.5、PM10的关系,以期为进一步研究PM2.5、PM10的影响因素提供参考依据。结果表明:绿地、农业用地和水域与PM2.5呈负相关关系;建设用地、交通用地和未利用土地与PM2.5呈正相关关系;农业用地与PM10浓度具有季节性差异,冬季和春季农地会使PM10浓度降低,夏季和秋季会使PM10浓度增大。绿地斑块所占景观面积比、绿地最大斑块指数、面积加权平均斑块形状指数与PM2.5和PM10具有明显的负相关性,景观分离度指数与其呈正相关关系。     

近十年雄安新区景观格局动态变化及生态系统服务功能评价

为深入了解和解析雄安新区景观格局的时空特征及其生态发展趋势,利用2013-2022年间4期典型的遥感影像数据,结合Google Earth影像,通过支持向量机分类和目视解译法获得雄安新区的土地利用分类图,综合运用GIS技术和InVEST模型分析等方法,对近10年雄安新区景观格局变化特征及其生态质量进行分析评价。结果表明：(1)2013-2022年期间,建设用地、开阔水体、林地持续增长,其中林地在2017年以后呈快速增长趋势,占雄安新区总面积比例由10.75%增长到31.79%,耕地由于转出较多面积缩减迅速,主要转出为林地、开阔水体和建设用地,白洋淀湿地面积增加。(2)开阔水体、水生植被、耕地的景观破碎化程度在逐年增大,林地的空间连通性持续向好。雄安新区景观形状指数增加,其中,2022年景观丰富度最大,景观中优势斑块类型连通性增强,大比例斑块增加。(3)10年间,研究区碳储量增加60.59×10⁶ MgC,优良类生境区域面积和差等生境质量面积呈上升趋势,中等生境质量面积减小33.66%。需重点关注耕地、农村建设用地与城区的交汇处、交通道路与生态源地交汇处等的生态节点...     

Road Density and Landscape Pattern in Relation to Housing Density,and Ownership,Land Cover,and Soils

Roads are conspicuous components of landscapes and play a substantial role in defining landscape pattern. Previous studies have demonstrated the link between roads and their effects on ecological processes and landscape patterns. Less understood is the placement of roads, and hence the patterns imposed by roads on the landscape in relation to factors describing land use, land cover, and environmental heterogeneity. Our hypothesis was that variation in road density and landscape patterns created by roads can be explained in relation to variables describing land use, land cover, and environmental factors. We examined both road density and landscape patterns created by roads in relation to suitability of soil substrate as road subgrade, land cover, lake area and perimeter, land ownership, and housing density across 19 predominantly forested counties in northern Wisconsin, USA. Generalized least squares regression models showed that housing density and soils with excellent suitability for road subgrade were positively related to road density while wetland area was negatively related. These relationships were consistent across models for different road types. Landscape indices showed greater fragmentation by roads in areas with higher housing density, and agriculture, grassland, and coniferous forest area, but less fragmentation with higher deciduous forest, mixed forest, wetland, and lake area. These relationships provide insight into the complex relationships among social, institutional, and environmental factors that influence where roads occur on the landscape. Our results are important for understanding the impacts of roads on ecosystems and planning for their protection in the face of continued development.     

Land Use – Land Cover Conversion, Regeneration and Degradation in the High Elevation Bolivian Andes

Regional land-cover change affects biodiversity, hydrology, and biogeochemical cycles at local, watershed, and landscape scales. Developing countries are experiencing rapid land cover change, but assessment is often restricted by limited financial resources, accessibility, and historical data. The assessment of regional land cover patterns is often the first step in developing conservation and management plans. This study used remotely sensed land cover and topographic data (Landsat and Shuttle Radar Topography Mission), supervised classification techniques, and spectral mixture analysis to characterize current landscape patterns and quantify land cover change from 1985 to 2003 in the Altiplano (2535–4671 m) and Intermediate Valley (Mountain) (1491–4623 m) physiographic zones in the Southeastern Bolivian Andes. Current land cover was mapped into six classes with an overall accuracy of 88% using traditional classification techniques and limited field data. The land cover change analysis showed that extensive deforestation, desertification, and agricultural expansion at a regional scale occurred in the last 20 years (17.3% of the Mountain Zone and 7.2% of the Altiplano). Spectral mixture analysis (SMA) indicated that communal rangeland degradation has also occurred, with increases in soil and non-photosynthetic vegetation fractions in most cover classes. SMA also identified local areas with intensive management activities that are changing differently from the overall region (e.g., localized areas of increased green vegetation). This indicates that actions of local communities, governments, and environmental managers can moderate the potentially severe future changes implied by the results of this study.     

The Impact of Misclassification in Land Use Maps in the Prediction of Landscape Dynamics

Land use maps are widely used in modeling land use change, urban sprawl, and for other landscape related studies. A misclassification confusion matrix for land use maps is usually provided as a measure of their quality and uncertainty. However, this very important information is rarely considered in land use map based studies, especially in modeling landscape dynamics. Ignoring uncertainty of land use maps may cause models to provide unreliable predictions. This study is an attempt to investigate the impact of the accuracy of land use maps used as input for an urban sprawl model. In the study area, the regional confusion matrix has been localized using a topographical map. Based on the regional and local confusion matrices, several error levels have been defined. The results showed that a localized confusion matrix that reflected the characteristics of the study area had error rates that were much different than the regional confusion matrix. The predictions of the probability of urban sprawl based on the land use maps and defined error levels were quite different.     

1998—2008年新疆甜菜作物空间格局变化及其发展

从新疆各地区甜菜产量、甜菜的播种面积以及甜菜的单位面积产量3个指标入手,分析近十年来新疆甜菜在全国的状况以及新疆各地区甜菜生产状况,通过选取1998、2003、2008年的数据,利用MapInfo软件绘制甜菜作物生产状况分布图,经过对比分析初步了解新疆各地区甜菜生产布局变化。并对新疆地区甜菜作物提出了可持续发展的措施。     

双子山国家森林公园景观格局地形分异特征分析

以遥感影像和野外调研数据为基础数据,基于DEM数字高程数据提取双子山国家森林公园地形因子,运用GIS、RS技术对森林景观格局沿地形因子的分异特征进行分析,以期揭示双子山国家森林公园景观格局地形分异特征规律,为景观格局优化、森林合理经营与保护提供科学依据。结果表明:双子山国家森林公园景观格局随地形因子变化的分异特征显著。各森林景观主要分布在海拔200~400m和坡度为6°~15°的缓坡地区,针阔混交林与硬阔叶混交林优势分布明显,分布面积较大,但同时侵害了其它景观类型的生长环境;地势较低区域受人类干扰程度较大,景观分布面积相对较少,生物多样性不高,地势较高区域受自然环境原因影响,景观分布面积也相对不高。     

湟水流域农田土壤全氮空间分布特征及其影响因素分析

利用湟水流域已有文献中38个农田耕层(0~20cm)土壤全氮数据,采用传统统计学与地统计学相结合的方法,分析了该流域农田土壤全氮空间分布及影响因素。结果表明:土壤全氮均值为1.33g·kg~(-1),变异系数为47.37%,属中等变异。流域农田土壤全氮呈自北向南逐渐递减,由东向西先增加后减少的空间分布格局。按全国土壤全氮分级标准,高值区(1.50g·kg~(-1))集中在海拔较高的大通县、海晏县,低值区(1.00g·kg~(-1))集中于海拔稍低的民和县、湟中县,65.5%的区域达全国平均水平(1.30g·kg~(-1))。影响因子定量分析表明,不同的气候因子、土壤类型、海拔、施肥量都会影响该流域土壤全氮的空间分布,其中气温、海拔、降水为主要影响因子,对全氮变异的独立解释能力分别为35.7%、29.0%、21.3%。该研究初步揭示了湟水流域农田土壤全氮的空间分布特征,可为流域尺度农田的科学管理提供有益参考,并为合理开展施肥工作提供参考依据。     

地被植物与高尔夫球场景观绿化

在高尔夫球场景观绿化中地被植物的应用越来越受到重视,成为不可缺少的高尔夫球场景观的组成部分,通常在乔木、灌木和草坪组成的自然群落之间起着承上启下的作用.同时,由于高尔夫球场的特殊性,及地被植物生态习性各异、生长发育开花和休眠期也不尽相同,因此,地被植物可以在更好地满足高尔夫球场功能的同时,形成极为复杂的季相变化,与其它园林植物相比有特殊的优势和更为广泛的用途.     

基于生态绿当量的梅州市土地利用变化环境影响评价

以梅州市为例,利用1986年与2006年土地利用现状数据,以生态绿当量作为土地利用变化环境影响评价的度量指标,引用生态绿当量数学模型,测算出各区县各种用地类型的绿当量和区域总绿当量,用以衡量生态环境情况。结果表明：（1）1986年～2006年,梅州市及各区县生态绿当量均有所提高,生态环境有改善;（2）生态绿当量作为评价区域生态环境指标具有涵义明确,计算简单方便等优点,但也有一定的局限性。     

自然与文化特征在景观特色中的体现——以宝坻区潮阳大道绿化设计为例

通过对天津宝坻地域自然特征和湿地文化特征的挖掘,以及对潮阳大道地貌水意特征的把握,运用追景材料对主题意向的恰当表现,营造出融生态、文脉、自然和艺术等多维表现内容于一体的道路景观环境。     

城市园林景观特色的形成

城市园林景观能表达城市特色,会形成良好的城市发展环境。现代文明诞生以后、由于科学、艺术和社会的发展,设计思想和气候因素对现代城市园林景观设计产生更为强烈的影响。研究城市园林景观的特色应对城市内外所有景观资源、地理、历史人文状况进行调查概括,归纳总结出城市园林景观设计的主题,结合设计理念形成鲜明的城市园林景观特色。