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1.
TM图像自应用于土地资源调查以来,对其应用潜力争议很大。鉴于此,本文以河北省南皮县为研究区,利用常规方法,分析、评价了TM图像在县级土地利用制图与农业分区中的应用效果,并与SPOT图像进行了对比分析。研究结果表明,利用TM图像进行县级土地利用制图与农业发展分区,可以得到令人满意的结果,借助TM图像包括中红外在内的多波段光谱信息的优势,可以达到SPOT多波段图像的应用效果。本研究为我国应用TM图像进行县级土地资源调查与制定发展规划提供了一个实例。  相似文献   

2.
本研究选取黄土高原典型丘陵沟壑区——陕西省米脂县为试验区,用TM磁带、TM假彩色合成影像、SPOT多光谱影像和彩色红外航空像片同时对试区进行土地利用现状分类与制图的比较研究。通过对土地利用现状分类系统、TM图像计算机增强处理与自动分类、TM最佳波段组合、三种影像的目视判读与制图、以及遥感信息源的综合评价等多方面的试验研究,为遥感技术在黄土高原1:5万土地利用现状调查制图中的应用提供了一套技术数据及可行的方法。  相似文献   

3.
海南岛土地资源利用的现状与未来调整   总被引:6,自引:0,他引:6  
本文通经TM卫星图像解译分析了海南岛土地利用现状的几个重要方面,即土地利用结构、土地生产率、土地利用空间布局、土地利用技术、土地利用率、土地规划与管理;论述了未来海南岛土地利用的导向原则:①联系地区发展战略调整土地利用结构;②土地利用更多地服从市场导向;③热带作物仍占重要地位,④贯彻“持续”原则;⑤加强宏观控制;⑥稳定耕地面积。文章最后指出了实现土地充分合理利用的几条途径。  相似文献   

4.
数字土地利用现状图是当前进行土地利用研究的基础数据之一,在土地利用现状图绘制过程中始终涉及制图概括的问题,文章在结合宁夏回族自治区中卫市土地利用现状调查的基础上,探讨了土地利用专题图的制图概括理论和技术方法。  相似文献   

5.
作为土地资源调查工作主要成果的土地利用现状图,主要为反映土地利用的特点和利用的合理程度,改良土地利用方式并进一步挖掘土地潜力提供科学依据。目前土地利用数据由大比例尺向中小比例尺转换工作主要由手工操作或是基于商用软件包进行;由于手工操作环节多,工作量大、所耗周期长、技术性强、作业人员的干扰因素多,较易产生误差和错误;而商用软件包在进行土地利用数据制图综合的过程中则缺乏相关的知识规则。本文以此问题为出发点进行研究,结合土地利用数据制图综合理论体系,在ArcEngine环境下对土地利用制图综合规则及操作进行开发,生成土地利用数据制图综合模块;利用实例数据对土地利用数据制图综合模块的功能进行检验,实验结果显著地克服了手工操作中的缺点,并使综合制图的自动化体系得到完善。  相似文献   

6.
数字土地利用现状图的制图概括   总被引:7,自引:0,他引:7  
数字土地利用现状图是当前进行土地利用研究的基础数据之一 ,在土地利用现状图绘制过程中将始终涉及制图概括的问题 ,本文在结合苏州工业园区农村地域土地利用现状调查的基础上 ,探讨了土地利用专题图的制图概括理论和技术方法。  相似文献   

7.
数字土地利用现状图的制图概括   总被引:4,自引:0,他引:4  
数字土地利用现状图是当前进行土地利用研究的基础数据之一 ,在土地利用现状图绘制过程中将始终涉及制图概括的问题 ,本文在结合苏州工业园区农村地域土地利用现状调查的基础上 ,探讨了土地利用专题图的制图概括理论和技术方法。  相似文献   

8.
制图表达是ArcGIS 9.2推出的制图新机制,土地利用图是要以完美符号来表现土地利用类型分布的图件。本文结合横山县第二次土地调查项目1∶10 000土地利用图集制作的实际工作,详细介绍了制图表达用于土地利用图编制的基本过程。结果表明制图表达方法的引入,不仅实现了图面符号的人性化显示,又提高了多图件编制的工作效率。  相似文献   

9.
正为了积极响应党中央、国务院和国土资源部领导的号召,利用好第二次全国土地调查的数据成果,充分展现我国土地利用现状,满足多元化和人性化的地理空间信息服务需求,中国大地出版社(地质出版社)利用当今最先进的三维立体技术将地形特征信息与土地利用专题图有机结合,集成了地理信息系统、三维立体制图技术、CTP数字制版技术、光栅材料及特种印刷技术,科学、直观地反映土地利用的空间分布规律、发展变化过程;多角度、多比例尺、全面系统地展现全国、省、市(县)各级行政单位的土地利用调查研究成果。将三维立体技术应用到土地利用系列图上,突破了传统地图制图中纸质载体单一的局限性,实现裸眼三维立体土地利用现状的可视化效果。  相似文献   

10.
陕北黄土高原地形破碎、交通不便、土地利用不合理、水土流失严重、生态环境脆弱。为了扭转这种局面,必须查清区内土地资源的类型及其分布状况,以便合理地评价和利用土地资源,改善当地的经济状况和生态环境。 本文以陕北11个县(市)为例,对利用TM图像进行1:10万土地类型遥感调查与制图的工作方法和程序进行了讨论,对区内土地类型区域分异因素和分异规律进行了分析,并在此基础上,提出了土地类型分区及分区治理措施的建议。  相似文献   

11.
Spatial land use information is one of the key input parameters for regional agro-ecosystem modeling. Furthermore, to assess the crop-specific management in a spatio-temporal context accurately, parcel-related crop rotation information is additionally needed. Such data is scarcely available for a regional scale, so that only modeled crop rotations can be incorporated instead. However, the spectrum of the occurring multiannual land use patterns on arable land remains unknown. Thus, this contribution focuses on the mapping of the actually practiced crop rotations in the Rur catchment, located in the western part of Germany. We addressed this by combining multitemporal multispectral remote sensing data, ancillary information and expert-knowledge on crop phenology in a GIS-based Multi-Data Approach (MDA). At first, a methodology for the enhanced differentiation of the major crop types on an annual basis was developed. Key aspects are (i) the usage of physical block data to separate arable land from other land use types, (ii) the classification of remote sensing scenes of specific time periods, which are most favorable for the differentiation of certain crop types, and (iii) the combination of the multitemporal classification results in a sequential analysis strategy. Annual crop maps of eight consecutive years (2008–2015) were combined to a crop sequence dataset to have a profound data basis for the mapping of crop rotations. In most years, the remote sensing data basis was highly fragmented. Nevertheless, our method enabled satisfying crop mapping results. As an example for the annual crop mapping workflow, the procedure and the result of 2015 are illustrated. For the generation of the crop sequence dataset, the eight annual crop maps were geometrically smoothened and integrated into a single vector data layer. The resulting dataset informs about the occurring crop sequence for individual areas on arable land, so that crop rotation schemes can be derived. The resulting dataset reveals that the spectrum of the practiced crop rotations is extremely heterogeneous and contains a large amount of crop sequences, which strongly diverge from model crop rotations. Consequently, the integration of remote sensing-based crop rotation data can considerably reduce uncertainties regarding the management in regional agro-ecosystem modeling. Finally, the developed methods and the results are discussed in detail.  相似文献   

12.
全球土地覆盖制图在过去的10年中取得重要进展,空间分辨率从300 m增加至30 m,分类详细程度也有所提高,从10余个一级类到包含29类的二级分类体系。然而,利用光学遥感数据在大空间范围制图方面仍有诸多挑战。本文主要介绍在农田、居住区、水体和湿地制图方面的挑战,讨论在使用多时相和多传感器遥感数据上的困难,这将是未来遥感应用的趋势。由于各种地表覆盖数据产品有自己定义的地表覆盖类型体系和处理流程,通过调和以及集成各种全球土地覆盖制图产品能够满足新的应用目的,并且可以最大程度地利用已有的土地覆盖数据。然而,未来全球土地覆盖制图需要能够按照新应用需求动态生成地表覆盖数据产品的能力。过去的研究表明有效地提高局部尺度制图的分类精度,更好的算法、更多种特征变量(新类型的数据或特征)以及更具代表性的训练样本都非常重要。我们却认为特征变量的使用更重要。本文提出了一个全球土地覆盖制图的新范式。在这个新范式中,地表覆盖类型的定义被分解为定性指标的类、定量指标的植被郁闭度和高度。非植被类型通过它们的光谱和纹理信息提取。复合考虑类、郁闭度和高度3种指标来定义和区别包含植被的地表覆盖类型。郁闭度和高度不能在分类算法中提取,需要借助其他直接测量或间接反演方法。新的范式还表明,一个普遍适用的训练样本集有效地提高了在非洲大陆尺度土地覆盖分类。为了确保更加容易地实现从传统的土地覆盖制图到全球土地覆盖制图新范式的转变,建议构建一体化的数据管理和分析系统。通过集成相关的观测数据、样本数据和分析算法,逐步建成全球土地覆盖制图在线系统,构建全球地表覆盖制图门户网站,为数据生产者、数据用户、专业研究人员、决策人员搭建合作互助的平台。  相似文献   

13.
A brief history of land-use mapping sets the stage for a survey of contemporary land-use mapping across the world, and more specifically, the applications of remote sensing methods in such mapping. Other issues addressed include the need to refine the definition of land use to encompass the totality of geographic space, to formally recognize the difference between large-scale maps of agricultural land-use and smaller-scale general land-use maps, and to investigate more closely the wisdom and desirability of a standardized world land-use classification. Four types of land-use maps are identified: diagnostic/informational, historical, dynamic, and predictive. Translated from: Vestnik Leningradskogo Universiteta, 1983, No. 24, pp. 52-61.  相似文献   

14.
Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial–temporal variability is a challenging task.We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain.The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.  相似文献   

15.
Until recently, land surveys and digital interpretation of remotely sensed imagery have been used to generate land use inventories. These techniques however, are often cumbersome and costly, allocating large amounts of technical and temporal costs. The technological advances of web 2.0 have brought a wide array of technological achievements, stimulating the participatory role in collaborative and crowd sourced mapping products. This has been fostered by GPS-enabled devices, and accessible tools that enable visual interpretation of high resolution satellite images/air photos provided in collaborative mapping projects. Such technologies offer an integrative approach to geography by means of promoting public participation and allowing accurate assessment and classification of land use as well as geographical features. OpenStreetMap (OSM) has supported the evolution of such techniques, contributing to the existence of a large inventory of spatial land use information. This paper explores the introduction of this novel participatory phenomenon for land use classification in Europe's metropolitan regions. We adopt a positivistic approach to assess comparatively the accuracy of these contributions of OSM for land use classifications in seven large European metropolitan regions. Thematic accuracy and degree of completeness of OSM data was compared to available Global Monitoring for Environment and Security Urban Atlas (GMESUA) datasets for the chosen metropolises. We further extend our findings of land use within a novel framework for geography, justifying that volunteered geographic information (VGI) sources are of great benefit for land use mapping depending on location and degree of VGI dynamism and offer a great alternative to traditional mapping techniques for metropolitan regions throughout Europe. Evaluation of several land use types at the local level suggests that a number of OSM classes (such as anthropogenic land use, agricultural and some natural environment classes) are viable alternatives for land use classification. These classes are highly accurate and can be integrated into planning decisions for stakeholders and policymakers.  相似文献   

16.
结合Landsat-8遥感数据,采用多级决策树分类方案,利用归一化植被指数、波段比值、主成分分量等光谱特征参数并融合其他非遥感知识,对黄河三角洲地区土地利用与覆盖的信息展开了全面的提取、研究与分析,获得了该地区5个一级类、12个二级类地物的分布情况,分类总体精度93.88%,优于传统监督分类。同时采用聚类、分类叠加和人机交互等分类后处理操作以获得更贴近地面实际的制图效果,开展基于海岸线的缓冲区分析以获得各地物特别是距离海岸线10 km、20 km范围内地物类型的空间分布并完成相关制图与分析,为黄河三角洲地区滨海土地的利用与开发提供了数据支持。  相似文献   

17.
随着城市人口增长、城镇化趋势扩大、可利用资源急剧减少,动态地掌握城市土地利用现状变化,是有效利用城市的土地资源、加强土地资源监管的重要基础,土地利用现状的调查是最基础的土地资源调查。本文通过分析上海土地利用调查现状和测绘地理信息资源情况,基于测绘地理信息更新机制,结合“多测合一”、季度卫星影像、基础测绘、细化调查等测绘工作,探索了一种动态、可靠的多周期、全覆盖的土地利用变化动态发现方法,并通过试点提出了土地利用变化发现的建议。  相似文献   

18.
Pasture land occupies extensive areas and is increasingly of interest for sustainable intensification, land use diversification, greenhouse gas emission mitigation, and bioenergy expansion. Accurate maps of pasture and other managed land covers are needed for monitoring, intercomparison, assessing potential uses, and planning. Yet, land maps can be generated from different types of classification datasets – i.e. as a land use or land cover type – as well as different sources. In this study our aim was to assess and compare land use and land cover definitions for pasture, and examine variability in the resulting pasture land classification maps. First, we conducted a review of pasture definitions in commonly used mapping databases. We then performed a case study involving Brazil, a dominant global producer of pasture-based livestock. Six geospatial databases were harmonized and compared to each other and to MODIS land cover for Brazil including the Cerrado and Amazon biomes, which are internationally recognized for their ecological value. Total pasture area estimates for Brazil ranged by a factor greater than four, from about 430,000 km2 to over 1.7 million km2. Our analysis showed high variability in pasture land maps depending on the definitions, methods and underlying datasets used to generate them. The results are illustrative of a symptomatic problem for all manage land datasets, demonstrating the need for land categories studies and geospatial data resources that fully define land terms and describe measurable management attributes. Additionally, the suitability of individual geospatial datasets for different types of land mapping must be better described and reported. These recommendations would help bring more consistency in the consideration of managed lands in research, reporting, and policy development, as demonstrated here for pasture land using six case study datasets from multiple sources.  相似文献   

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