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基于RS与GIS的雅安市土地利用景观格局变化分析研究 总被引：1，自引：0，他引：1
以TM遥感影像等为数据源,借助RS与GIS技术,选择了能反映研究区景观空间格局的景观指数,分析研究了雅安市2000年至2007间的景观空间格局动态变化.从两期景观指数对比得出:林地是研究区景观基质类型,研究期内景观异质性升高,破碎度增大. 相似文献
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为了研究近30年内西辽河流域湿地景观格局变化特征,本文基于1985年TM数据、2000年ETM数据和2015年OLI数据,利用景观格局软件Fragstats4.2,选取了8个景观格局指标,进而分析30年来西辽河湿地景观格局变化情况,结果表明:1)各湿地类型总斑块数和斑块密度呈下降趋势,湿地逐渐转化为建设用地和非建设用地,湿地主导类型变为人工湿地; 2)研究区湿地破碎化虽然有所减弱,但景观格局变化依然明显; 3)湿地大面积减少,湿地多样性大大降低,空间连通性较优,景观类型趋于单一化。 相似文献
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黄土高原上黄小流域土地利用景观格局分析 总被引：1，自引：0，他引：1
景观格局是景观生态学研究的三大内容之一,是研究景观过程与景观功能的基础。本文以黄土高原上黄小流域1982年~2008年的6期土地利用图为数据基础,选取反映研究区景观格局特征的景观指数,运用所选景观指数对研究区土地利用的空间格局进行定量研究并分析了其变化的驱动因素。结果表明:利用主成分分析法选择的7个景观指数可以有效地反映研究区土地利用景观格局的基本特征。 相似文献
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融合多尺度影像数据的杞麓湖流域景观格局分析 总被引：2，自引：0，他引：2
景观格局是景观斑块秩序和规律的具体体现，分析景观格局特征能够在空间结构上推进流域生态保护红线的划定和管控工作，维持可持续发展的底线。基于不同遥感数据源测算的景观格局可能存在计算结果差异，以及对景观格局描述不一致的问题。本文以杞麓湖流域为研究区，选取最新的Sentinel-2、GF-1和Landsat 8卫星遥感影像，基于斑块尺度、类型尺度和景观尺度的7个景观指数，从景观类型分布和整体格局两个方面探讨了杞麓湖流域景观格局现状，并分析不同数据源对景观格局评价结果的异同。结果表明：①杞麓湖流域的景观格局以林地和耕地为基底，零碎分散着建设用地和其他用地；②不同卫星遥感影像对流域景观格局的描述存在差异，影像分辨率与斑块数目、最大斑块指数、形状指数、分离度指数存在显著的正相关关系，而对于测度整体的香农多样性指数、香农均匀度指数、优势度指数的影响相对较小。 相似文献
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针对传统景观格局分析方法的数据局限性,该文提出了一种基于数字高程模型地形信息量的景观格局预测分析方法。结合信息熵理论,利用数字高程模型计算地形信息量,研究不同分级地形信息量下景观格局特征的变化特征,以及不同景观类型在不同地形信息量等级的分布特征,对具有相似地形特征的区域建立利用地形信息量对其景观格局特征进行预测分析的方法。该文选择珠海市地形特征相似的两个区域进行了试验分析,对珠海市斗门区建立基于数字高程模型地形信息量的景观格局预测方法,预测在相似地形特征下南坪镇的景观格局特征,并以南坪镇真实的景观特征进行验证。实验结果显示,基于数字高程模型地形信息量的邻域景观预测分析方法不仅能正确预测分析不同地形信息量下的景观分析指数,同时也能正确预测不同景观类型的空间分布特征。 相似文献
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粤港澳大湾区已成为世界级城市群为目标的特大城市群。本文利用多期遥感数据,并结合景观格局指数研究大湾区2000—2020年的发展规律。结果表明:①大湾区主要的土地覆盖类型为林地、耕地与居住及建设用地,3种地类总占比多年来均在80%以上;②大湾区的居住及建设用地在20年间增长了115.21%,面积达到9 183.47 km2,是大湾区内面积增长最多、变化速率最快的用地类型;③大湾区内的景观格局破碎度、斑块密度不断降低,景观聚集度与景观丰富程度不断升高,区域景观格局分布状况日趋合理。 相似文献
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国内外学者对于景观格局的地形分异研究,经历了从景观类型分布高程差异到景观指数高程分异研究的过程,目前处在景观格局静态地形分异阶段。本文利用浙江西部桐庐县1996、2004的土地利用现状图和DEM数据,对其1996-2004年景观格局动态演变特征的高程分异规律进行研究。研究对桐庐县1996、2004年的土地利用现状图进行处理获得景观类型分布图,通过1∶10000的DEM数据的分带操作,生成不同高程带的景观类型分布图。选取斑块密度、景观形状指数、分维数、破碎度、香农多样性指数、香农均匀度指数等景观格局指数,并在ArcGIS和Fragstats的支持下,计算出各带两个年份的景观格局指数并作对比分析。结果表明:研究区景观格局演变具有明显的高程分异特征,不仅表现为景观类型分布的变化与高程变化相关,而且体现在景观格局指数的变化值随高程上升而增减的趋势也有一定的规律性:景观水平上所有指数变化的剧烈程度大致与高程呈负相关关系,景观类型水平上各景观类型的破碎度、和斑块密度变化程度随海拔升高趋于缓和。 相似文献
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Changes in landscape composition and configuration patterns of Sancaktepe Municipal District in the Asian side of Istanbul Metropolitan City of Turkey were analysed using landscape metrics. Class-level and landscape-level metrics were calculated from the land cover/land use data using Patch Analyst, an extension in the Arc View GIS. The land cover/land use data were derived from classified satellite images of Landsat Thematic Mapper of 2002 and 2009 for Sancaktepe District. There was evidence of increase in agglomeration process of built-up patches as indicated by the increases in mean patch size, decrease in total edge and number of patches between 2002 and 2009. The urban expansion pattern experienced overall was not fragmented but concentrated due to infilling around existing patches. Changes in Area-Weighted Mean Shape Index and Area-Weighted Patch Fractal Dimension Index indicated that the physical shapes within built-up, forest and bareland areas were relatively complex and irregular. A conclusion is made in this study that spatial metrics are useful tools to describe the urban landscape composition and configuration in its various aspects and certain decisions whether to approve a specific development in urban planning could, for example, be based on some measures of urban growth form or pattern in terms of uniformity and irregularity, attributable to the dynamic processes of agglomeration and fragmentation of land cover/land use patches caused by urban expansion. 相似文献
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Multitemporal land cover classification over urban areas is challenging, especially when using heterogeneous data sources with variable quality attributes. A prominent challenge is that classes with similar spectral signatures (such as trees and grass) tend to be confused with one another. In this paper, we evaluate the efficacy of image point cloud (IPC) data combined with suitable Bayesian analysis based time-series rectification techniques to improve the classification accuracy in a multitemporal context. The proposed method uses hidden Markov models (HMMs) to rectify land covers that are initially classified by a random forest (RF) algorithm. This land cover classification method is tested using time series of remote sensing data from a heterogeneous and rapidly changing urban landscape (Kuopio city, Finland) observed from 2006 to 2014. The data consisted of aerial images (5 years), Landsat data (all 9 years) and airborne laser scanning data (1 year). The results of the study demonstrate that the addition of three-dimensional image point cloud data derived from aerial stereo images as predictor variables improved overall classification accuracy, around three percentage points. Additionally, HMM-based post processing reduces significantly the number of spurious year-to-year changes. Using a set of 240 validation points, we estimated that this step improved overall classification accuracy by around 3.0 percentage points, and up to 6 to 10 percentage points for some classes. The overall accuracy of the final product was 91% (kappa = 0.88). Our analysis shows that around 1.9% of the area around Kuopio city, representing a total area of approximately 0.61 km2, experienced changes in land cover over the nine years considered. 相似文献
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A Jeyaram R Balasubramanian Y Vxxx N Krishna Murthy R L Karale Balbhir Singh 《Journal of the Indian Society of Remote Sensing》1993,21(3):167-177
Landsat MSS (1982) and IRS LISS-II (1989) data have been used to study the land use/land cover changes in Dalli-Rajhara iron ore mine area. Supervised classification has been performed on the temporal data to generate land use/land cover maps. Land use/land cover categories generated from IRS LISS-II data of 36 m resolution has been resampled to 80 m and areal statistics have been computed for 2, 4, 8 and 10 km wide strips around Dalli-Rajhara iron ore mine. The environmental impact due to on-going mining activities in the area has been analysed. The results of this study indicate that due to increase in mine-related and agricultural activities, forests have been degraded and also forest areas have been reduced considerably. 相似文献
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Reliable and up-to-date urban land cover information is valuable in urban planning and policy development. Due to the increasing demand for reliable land cover information there has been a growing need for robust methods and datasets to improve the classification accuracy from remotely sensed imagery. This study sought to assess the potential of the newly launched Landsat 8 sensor’s thermal bands and derived vegetation indices in improving land cover classification in a complex urban landscape using the support vector machine classifier. This study compared the individual and combined performance of Landsat 8’s reflective, thermal bands and vegetation indices in classifying urban land use-land cover. The integration of Landsat 8 reflective bands, derived vegetation indices and thermal bands overall produced significantly higher accuracy classification results than using traditional bands as standalone (i.e. overall, user and producer accuracies). An overall accuracy above 89.33% and a kappa index of 0.86, significantly higher than the one obtained with the use of the traditional reflective bands as a standalone data-set and other analysis stages. On average, the results also indicate high producer and user accuracies (i.e. above 80%) for most of the classes with a McNemar’s Z score of 9.00 at 95% confidence interval showing significant improvement compared with classification using reflective bands as standalone. Overall, the results of this study indicate that the integration of the Landsat 8’s OLI and TIR data presents an invaluable potential for accurate and robust land cover classification in a complex urban landscape, especially in areas where the availability of high resolution datasets remains a challenge. 相似文献
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为了弄清江苏沿海滩涂利用模式分布情况,定量分析其时空变化趋势,本文基于Google Earth Engine云计算平台和Landsat卫星遥感影像数据,结合随机森林分类方法,通过机器学习建立了滩涂利用模式自动识别分类方法,样本训练后识别准确率达93％以上.利用该方法提取了2002年、2014年和2019年江苏沿海的土地... 相似文献
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This study assesses the usefulness of Nigeriasat-1 satellite data for urban land cover analysis by comparing it with Landsat and SPOT data. The data-sets for Abuja were classified with pixel- and object-based methods. While the pixel-based method was classified with the spectral properties of the images, the object-based approach included an extra layer of land use cadastre data. The classification accuracy results for OBIA show that Landsat 7 ETM, Nigeriasat-1 SLIM and SPOT 5 HRG had overall accuracies of 92, 89 and 96%, respectively, while the classification accuracy for pixel-based classification were 88% for Landsat 7 ETM, 63% for Nigeriasat-1 SLIM and 89% for SPOT 5 HRG. The results indicate that given the right classification tools, the analysis of Nigeriasat-1 data can be compared with Landsat and SPOT data which are widely used for urban land use and land cover analysis. 相似文献
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To ensure successful conservation of ecological and cultural landscape values, detailed and up-to-date spatial information of existing habitat patterns is essential. However, traditional satellite-based and raster classifications rely on pixels that are assigned to a single category and often generalized. For many fragmented key habitats, such a strategy is too coarse and complementary data is needed. In this paper, we aim at detecting pixel-wise fractional coverage of broadleaved woodland and grassland components in a hemiboreal landscape. This approach targets ecologically relevant deciduous fractions and complements traditional crisp land cover classifications. We modeled fractional components using a k-NN approach, which was based on multispectral satellite data, assisted by a digital elevation model and a contemporary map database. The modeled components were then analyzed based on landscape structure indicators, and evaluated in conjunction with CORINE classification. The results indicate that both broadleaved forest and grassland components are widely distributed in the study area, principally organized as transition zones and small patches. Landscape structure indicators show a substantial variation based on the fractional threshold, pinpointing their dependency on the classification scheme and grain. The modeled components, on the other hand, suggest high internal variation for most CORINE classes, indicating their heterogeneous appearance and showing that the presence of deciduous components in the landscape are not properly captured in a coarse land cover classification. To gain a realistic perception of the landscape, and use this information for the needs of spatial planning, both fractional results and existing land cover classifications are needed. This is because they mutually contribute to an improved understanding of habitat patterns and structures, and should be used to complement each other. 相似文献
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Abstract Coastal wetland is a major part of wetlands in the world. Land cover and vegetation mapping in a deltaic lowland environment is complicated by the rapid and significant changes of geomorphic forms. Remote sensing provides an important tool for coastal land cover classification and landscape analysis. The study site in this paper is the Yellow River Delta Nature Reserve (YRDNR) at the Yellow River mouth in Shangdong province, China. Yellow River Delta is one of the fastest growing deltas in the world. YRDNR was listed as a national level nature reserve in 1992. The objectives of this paper are two fold: to study the land cover status of YRDNR, and to examine the land cover change since it was declared as a nature reserve. Land cover and vegetation mapping in YRDNR was developed using multi‐spectral Landsat Thematic Mapper (TM) imagery acquired in 1995. Land cover and landscape characteristics were analyzed with the help of ancillary GIS. Land use investigation data in 1991 were used for comparison with Landsat classification map. Our results show that YRDNR has experienced significant landscape change and environmental improvement after 1992. 相似文献
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This paper discusses the development and implementation of a method that can be used with multi-decadal Landsat data for computing general coastal US land use and land cover (LULC) maps consisting of seven classes. With Mobile Bay, Alabama as the study region, the method that was applied to derive LULC products for nine dates across a 34-year time span. Classifications were computed and refined using decision rules in conjunction with unsupervised classification of Landsat data and Coastal Change and Analysis Program value-added products. Each classification’s overall accuracy was assessed by comparing stratified random locations to available high spatial resolution satellite and aerial imagery, field survey data and raw Landsat RGBs. Overall classification accuracies ranged from 83 to 91% with overall κ statistics ranging from 0.78 to 0.89. Accurate classifications were computed for all nine dates, yielding effective results regardless of season and Landsat sensor. This classification method provided useful map inputs for computing LULC change products. 相似文献