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论文分析了时间序列遥感影像中土地利用/土地覆盖短期变化的特点及其时空异常特征, 认为和环境、物候等因素造成的影像变化相比, 由人为活动引起的土地利用/土地覆盖变化具有典型的时间和空间异常特征, 并提出了基于密度异常的土地利用短期变化检测方法。研究工作选取珠江口地区1—5月作物生长期间的3个时间序列Radarsat雷达影像进行试验, 在影像分割的基础上, 构建了基于对象的特征变化矢量, 并将密度异常检测算法(DBAD)扩展到变化矢量的N维特征空间上, 运用随机搜索策略确定检测参数, 对Radarsat时间序列变化矢量中的“小模式”事件进行了检测。检测结果认为, 密度异常检测算法检测的是变化矢量在特征空间的密度分布, 与变化矢量的强度和方向无关, 因此能在时间序列影像中分离出由典型的、正常的作物生长或农事活动引起的影像光谱或回波变化, 进而识别出由人为活动或突发事件导致的土地利用/土地覆盖变化, 这是通常的图像差值等方法难以做到的。进一步的抽样检测说明, 密度异常检测方法对新增建设用地的检测准确率最高(>88%)；林地地表覆盖相对稳定, 检测误差也很低(8%)；农用地和养殖水面的异常变化检测误差在11%—22%之间；较大的检测误差主要集中在建设用地、农用地和未利用地之间的转换(16%—25%)；此外, 养殖水面的检测误差主要集中在河流沿岸及水面变化较大的养殖区域。影像分割结果特别是一些线状分割图斑以及混合地类图斑对误差也有一定的影响。 相似文献
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Phenological metrics-based crop classification using HJ-1 CCD images and Landsat 8 imagery 总被引：1，自引：0，他引：1
Xiaochun Zhang Qinxue Xiong Liping Di Junmei Tang Jin Yang Huayi Wu 《International Journal of Digital Earth》2018,11(12):1219-1240
Crop type data are an important piece of information for many applications in agriculture. Extracting crop type using remote sensing is not easy because multiple crops are usually planted into small parcels with limited availability of satellite images due to weather conditions. In this research, we aim at producing crop maps for areas with abundant rainfall and small-sized parcels by making full use of Landsat 8 and HJ-1 charge-coupled device (CCD) data. We masked out non-vegetation areas by using Landsat 8 images and then extracted a crop map from a long-term time-series of HJ-1 CCD satellite images acquired at 30-m spatial resolution and two-day temporal resolution. To increase accuracy, four key phenological metrics of crops were extracted from time-series Normalized Difference Vegetation Index curves plotted from the HJ-1 CCD images. These phenological metrics were used to further identify each of the crop types with less, but easier to access, ancillary field survey data. We used crop area data from the Jingzhou statistical yearbook and 5.8-m spatial resolution ZY-3 satellite images to perform an accuracy assessment. The results show that our classification accuracy was 92% when compared with the highly accurate but limited ZY-3 images and matched up to 80% to the statistical crop areas. 相似文献
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三维相位解缠是时序干涉合成孔径雷达（interferometric synthetic aperture radar，InSAR）技术的关键环节之一，解缠结果直接影响时序InSAR地面沉降监测的精度。针对地面沉降严重、地形坡度变化较大的区域，因相位欠采样引起的整周期解缠误差问题，提出了一种基于频域置信度的加权最小二乘相位解缠算法，并以此替代时空三维相位解缠中空间维以相位梯度为权重的加权最小二乘相位解缠算法。通过提高相位坡度变化估计的准确性，进而提高时空三维相位解缠的精度和稳定性。以北京地区地面沉降监测为例进行了验证，结果表明，与经典的时空三维相位解缠算法相比，改进算法得到的沉降监测结果精度更高，特别是对于坡度变化较大、失相干现象明显的沉降漏斗区，其沉降监测精度有明显改善。 相似文献
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In that orcharding in early-to-mid twentieth century southeastern Australia involved use of certain heavy metal and As compounds in regular pest-control spray procedures, some interest attaches to the possibility that these landparcels are underlain by’ soils with above-background Cu, Pb and As levels. Interpretation of Land-cover changes allowed land parcels previously occupied by orchards to be identified in the 1950s through time-series air-photos. A comparison of soil analysis results referring to soil samples from control sites, and from land parcels formerly occupied by orchardists, shows that contamination (above-background) levels of cations in the pesticides can be found in the top 6 cm of former orchard soils. It is clear that digital spatial data handling and culturally-informed air photo interpretation has a place in soil contamination studies, land-use planning (with particular reference to re-development) and in administration of public health. 相似文献
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YU Jie Ursula Pietrzak Jim Peterson 《地球空间信息科学学报》2005,8(4):257-261
In that orcharding in early-to-mid twentieth century southeastern Australia involved use of certain heavy metal and As compounds in regular pest-control spray procedures, some interest attaches to the possibility that these landparcels are underlain by soils with above-background Cu, Pb and As levels. Interpreta- tion of Land-cover changes allowed land parcels previously occupied by orchards to be identified in the 1950s through time-series air-photos. A comparison of soil analysis results referring to soil samples from control sites, and from land parcels formerly occupied by orchardists, shows that contamination （above-background） levels of cations in the pesticides can be found in the top 6 cm of former orchard soils. It is clear that digital spatial data handling and culturally-informed air photo interpretation has a place in soil contamination studies, land-use planning （with particular reference to re-development） and in administration of public health. 相似文献
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不同时相遥感影像变化检测已成为土地利用变更调查、城市扩张分析、自然灾害分析及其他环境问题必不可少的技术手段之一。本文提出了一种结合IR-MAD与均值漂移算法的密集城区遥感影像变化检测方法。该方法通过伪不变特征法完成两期影像的相对辐射校正，有效改善影像间的配准误差，并利用IR-MAD算法对校正后的影像进行迭代运算，采用均值漂移算法对迭代后的影像进行分割，同时运用形态学方法处理分割后的影像，最终提取变化图斑。试验结果表明，该方法可以有效检测出变化区域，可应用于城市地表覆盖的变化检测。 相似文献
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单一时相遥感数据土地利用与覆盖变化自动检测方法 总被引：14，自引：0，他引：14
针对基期(用于该研究的前一时期数据)T1仅拥有土地利用和覆盖图件(矢量格式)而另一期T2拥有遥感数据的情况,构建了基于知识引导的土地利用和覆盖变化自动检测技术与方法。T1时期土地利用与覆盖与T2期遥感数据在配准叠加情况下,以T1完整的土地利用与覆盖类型图斑为单元构建土地各类别遥感数据知识库,然后以图斑单元或以像素为单位计算遥感影像特征统计量,通过与知识库相关数据的比较与匹配自动检测出变化并识别出相应的土地利用与覆盖类别。文章最后通过试验验证了该方法的有效性。 相似文献
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土地覆盖的短期时空变化模式研究,对土地覆盖的快速、动态监测具有重要意义,也是遥感研究的新热点。本文利用2000—2001年的时间序列Radarsat图像,采用功率谱分析方法,对土地覆盖的短期时—空变化的周期特征进行了分析,由此建立了基于时间序列影像分析的神经网络预测模型,从植被主要生长季节的时间序列雷达卫星影像获取训练样本,对研究区域的典型土地覆盖的短期动态变化过程进行了学习。学习后的模型能够利用多个时间序列的Radarsat影像对下一时刻的影像进行模拟,并进一步检测变化。在模拟结果基础上,定义相对变化距离函数和检测门限,对模拟影像及实际影像中的变化区域进行了检测。检测精度范围在66.67%(农村居民点)—91.67%(水体)之间,平均检测精度为81.66%。由于时间序列信号的引入,神经网络模型能够较好地获取土地覆盖的短期动态变化信息。 相似文献
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基于偏差原则和正则化方法反演晴空地表BRDF和反照率 总被引：1，自引：1，他引：0
提出一种反演晴空地表反照率快速稳健的新算法——混合算法。该方法首先利用双参数模型函数确定正则参数的初始值,然后由基于Morozov偏差原则的高阶收敛算法确定正则参数,继而通过Tikhonov正则化手段来反演BRDF模型。从POLDER-3/PARASOL BRDF数据库中任意挑选不同覆盖的地表像元测量数据,与MODIS全反演法结果作比较,对比较结果给予了讨论;最后选择天津市地区的卫星图像进行反演实验,并就反演结果给出了误差分析和算法模型的评价。 相似文献
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本文从实际生产的角度阐述了城镇土地权属调查的工作流程、调查的工作程序、宗地划分的一般原则,并结合各地一些宗地处理的特殊方式以及解决问题的一些策略,对实际生产具有一定的借鉴作用。 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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Carlos Antonio da Silva Junior Marcos Rafael Nanni José Francisco de Oliveira-Júnior Everson Cezar Paulo Eduardo Teodoro Rafael Coll Delgado 《International Journal of Digital Earth》2019,12(3):270-292
This research aimed to analyze the possibility to estimate and automatically map large areas of soybean cultivation through the use of MODIS (Moderate-Resolution Imaging Spectroradiometer) images. Two major techniques were used: GEOgraphic-Object-Based Image Analysis (GEOBIA) and Data Mining (DM). In order to obtain the images, the segmentation algorithm implemented by Definiens Developer was used. A decision tree (DT) was created from a training set previously prepared. Time-series of images from the MODIS sensor aboard the Terra satellite were acquired in order to represent the wide variation of the vegetation pattern along the soybean crop cycle. The time-series data were used only for the CEI index. Furthermore, to compare the results obtained from GEOBIA, the slicing technique was used at the CEI level. After the training, the DT was applied to the vegetation indices generating the thematic map of the spatial distribution of soybean. In accordance with the error matrix and kappa parameter analysis, tests for statistical significance were created. Results indicate that the classification achieved by Kappa coefficients is 0.76. In short, the obtained results proved that combining vegetation indices and time-series data using GEOBIA return promising results for mapping soybean plantation on a regional scale. 相似文献
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顾及时态地块的土地划拨时空数据组织 总被引：9，自引：0，他引：9
以土地划拨为例，分析了地块分割、合并、复杂划拨和属性变化的特点，在此基础上构造了一个顾及时态对象的时空模型。该模型用非第一范式和两层时间标记组织地块的时空数据，并借助于活动地块表、不活动地块表和后向指针索引表建立了每个时态地块与其时态邻域地块之间的链接关系。 相似文献
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明晰集体土地产权,加快推进农村集体土地确权登记发证是当前国土资源管理中的一项重要任务。我国农村集体土地建设用地具有分布广、范围大、分散凌乱等特点,如果按照城镇地籍调查规程开展农村地籍调查,则面临着基础薄、任务重、投入高、时间紧等问题。为此,本文提出一套以高分辨率遥感影像为底图,快速绘制农村集体土地建设用地地块图形、并与实地丈量的边长、面积等属性数据关联、实现图属一体化管理的技术方法,并进行了精度评定试验。基于该技术开发了农村集体土地建设用地数据库建库工具和管理系统,实现了网络化农村集体土地建设用地管理,并在三个试点地区得到较好的应用。 相似文献
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In 1999, the Ministry of Land and Resources (MLR) of China launched the National Land Use Change Program especially to monitor the scale and distribution of urban expansion and the decrease in cultivated land through remote sensing technology. This Program has been carried out annually and continuously for seven years since then and played an important role in the policy-making of MLR about land management and planning. This paper gives an overview about this Program and discusses several research issues. First, the remote sensing data sources and other ancillary data used in this Program are presented. The approaches for image preprocessing, i.e. radiometric normalization, image geometric rectification and image fusion are then introduced with an emphasis on the algorithm development for image registration. Second, land use change detection technique is the most critical and complex aspect of the Program. The methodologies for change detection using either bi-temporal image pair or one existing land use map and one remotely sensed image are detailed. Third, since the data of land use changes derived from remote sensing will be operationally used for local and central government, field validation and accuracy assessment are crucial to ensure the reliability of change detection results. The strategy of field work and the resulting accuracy evaluations is presented. The land use and change information derived from remotely sensed data has wide applications for land management, including land use database updating, verification of land use planning and monitoring of national high-tech parks. Last, suggestions on how to make full use of the images and change detection result, to improve the consistency of land use classification and to develop change detection algorithms for diverse and complex remote sensing data are given. 相似文献
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多时相MODIS影像水田信息提取研究 总被引：5，自引：0，他引：5
水稻种植及其分布信息是土地覆被变化、作物估产、甲烷排放、粮食安全和水资源管理分析的重要数据源。基于遥感的水田利用监测中,通常采用时序NDVI植被指数法和影像分类法分别进行AVHRR和TM影像的水田信息获取。针对8天合成MODIS陆地表面反射比数据的特点和水稻生长特征,选取水稻种植前的休耕期、秧苗移植期、秧苗生长期和成熟期等多时相MODIS地表反射率影像数据,通过归一化植被指数、增强植被指数及利用对土壤湿度和植被水分含量较敏感的短波红外波段计算得到的陆表水指数进行水田信息获取。将提取结果与基于ETM＋影像的国土资源调查水田数据,通过网格化计算处理并进行对比分析,结果表明,利用MODIS影像的8天合成地表反射率数据,进行区域甚至全国的水田利用监测是可行的。 相似文献
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《International Journal of Digital Earth》2013,6(4):334-344
This paper presents a supervised polarimetric synthetic aperture radar (PolSAR) change detection method applied to specific land cover types. For each pixel of a PolSAR image, its target scattering vector can be modeled as having a complex multivariate normal distribution. Based on this assumption, the joint distribution of two corresponding vectors in a pair of PolSAR images is derived. Then, a generalized likelihood ratio test statistic for the equality of two likelihood functions of such joint distribution is considered and a maximum likelihood distance measure for specific land cover types is presented. Subsequently, the Kittler and Illingworth minimum error threshold segmentation method is applied to extract the specific changed areas. Experiments on two repeat-pass Radarsat-2 fully polarimetric images of Suzhou, China, demonstrate that the proposed change detection method gives a good performance in determining the specific changed areas in PolSAR images, especially the areas that have changed to water. 相似文献