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31.
针对卫星遥感技术监测地表温度(land surface temperature,LST)存在时空分辨率矛盾这一难题,以TsHARP温度降尺度算法为基础,根据地表覆盖类型的不同,分别选择与LST相关性更好的光谱指数(归一化植被指数,NDVI;归一化建造指数,NDBI;改进的归一化水体指数,MNDWI;增强型裸土指数,EBSI)提出了新的转换模型,并从定性和定量两个角度评价了TsHARP法和新模型的降尺度精度。结果表明:两种模型在提高LST空间分辨率的同时又能较好地保持MODIS LST影像热特征的空间分布格局,消除了原始1km影像中的马赛克效应,两种模型均能够达到较好的降尺度效果;全局尺度分析表明,不管是在降尺度结果的空间变异性还是精度方面,本文提出的模型(RMSE:1.635℃)均要优于TsHARP法(RMSE:2.736℃);TsHARP法在水体、裸地和建筑用地这些低植被覆盖区表现出较差的降尺度结果,尤其对于裸地和建筑用地更为明显(|MBE|3℃),新模型提高了低植被覆盖区地物的降尺度精度;不同季节的降尺度结果表明,两种模型都是夏、秋季的降尺度结果优于春、冬季,新模型的降尺度结果四季均好于TsHARP法,其中春、冬季的降尺度精度提升效果要优于夏、秋季。 相似文献
32.
Comparison of precipitation and evapotranspiration of five different land-cover types in the high mountainous region 总被引：1，自引：0，他引：1
Many rivers originate in high mountainous regions. However, the effects of climate warming on the runoff and water balance in these regions remain unclear due to the lack of observational data from harsh environments, and the variable influences of climate change on alpine land-cover types with different water balances. Using observations and simulations from CoupModel, water-balance values collected at five alpine land-cover types (steppe, shrub meadow, moist meadow, swamp meadow, and moraine) in a small alpine watershed, the Qilian Mountains in Northwest China, from October 2008 to September 2014, were compared. Measured evapotranspiration, multilayer soil temperatures and water contents, and frozen-depth data were used to validate CoupModel outputs. The results show that elevation is the primary influence on precipitation, evapotranspiration, and runoff coefficients in alpine regions. Land-cover types at higher elevations receive more precipitation and have a larger runoff coefficient. Notably, climate warming not only increases evapotranspiration but also particularly increases the evapotranspiration/precipitation ratio due to an upward shift in the optimum elevation of plant species. These factors lead to decrease runoff coefficients in alpine basins. 相似文献
33.
基于土地利用/覆被变化表征的现代绿洲演变过程——以天山北坡三工河流域为例 总被引：5，自引：0，他引：5
本文以天山北坡三工河流域为例,利用1958年、1968年和1978年3期航片、1987年彩红外航片、1998年Landsat TM、2004年SPOT 5和2014年Landsat OLI影像,构建绿洲及其外围荒漠7期土地利用/土地覆被数据集,综合分析1950s屯垦戍边以来现代绿洲演变和外围荒漠植物群落变化。结果表明：①1950年以来,屯垦戍边使位于三工河冲洪积扇中下部的老绿洲不断向冲积平原扩张,老绿洲外围以柽柳和梭梭为建群种的土质荒漠景观不断转变为新绿洲,绿洲面积增加了4倍多。其中1958-1968年和2000s以来是绿洲变化最为显著的两个阶段,这两个阶段分别对应了农业用地和建设用地增幅最大的时期。② 三工河流域的现代绿洲演变过程中存在“地方管辖区”和“兵团农场区”两种基本管理模式,也正是这两种模式相互渗透、相互交叉融合,共同推动了现代绿洲演变。③三工河流域1950s-2004年现代绿洲演变具有干旱区绿洲演变的普遍特征,但2004年以后的演变仅适用于有较大规模跨流域调水或新增水源的绿洲演变情形。现代绿洲的扩张以荒漠植被的砍伐和破坏为代价,导致绿洲外围植物群落结构发生了显著的变化,这使得绿洲外围荒漠生态系统的保护愈加困难 相似文献
34.
Hyperspectral image and full-waveform light detection and ranging (LiDAR) data provide useful spectral and geometric information for classifying land cover. Hyperspectral images contain a large number of bands, thus providing land-cover discrimination. Waveform LiDAR systems record the entire time-varying intensity of a return signal and supply detailed information on geometric distribution of land cover. This study developed an efficient multi-sensor data fusion approach that integrates hyperspectral data and full-waveform LiDAR information on the basis of minimum noise fraction and principal component analysis. Then, support vector machine was used to classify land cover in mountainous areas. Results showed that using multi-sensor fused data achieved better accuracy than using a hyperspectral image alone, with overall accuracy increasing from 83% to 91% using population error matrices, for the test site. The classification accuracies of forest and tea farms exhibited significant improvement when fused data were used. For example, classification results were more complete and compact in tea farms based on fused data. Fused data considered spectral and geometric land-cover information, and increased the discriminability of vegetation classes that provided similar spectral signatures. 相似文献
35.
梭磨河流域气候波动和土地覆被变化对径流影响的模拟研究 总被引：16，自引：4，他引：12
利用一个集总式水文模型(CHARM),模拟了不同的气候与土地覆被条件下长江上游梭磨河流域的水量平衡,定量区分气候波动和土地覆被变化对水文影响的“贡献率”。模型模拟的初步结果表明,从20世纪60年代到80年代,径流深增加了45.7mm,其中,由气候波动所引起的年平均径流深的增加占63.9%,由土地覆被变化所引起的径流深的增加占20.8%,其他条件的变化所引起的径流深的增加占15.3%。 相似文献
36.
Impacts of agriculture and urbanization on the climate of the Northeastern United States 总被引：5，自引：0，他引：5
The climate sensitivity to specification of agricultural and urban land cover was investigated using the climate version of the Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5) for 1990 over northeastern United States. The simulations were for 5 yr at a spatial resolution of 36 km. Urbanization resulted in near-surface temperature increases of more than 1 K over the urban sites during both winter and summer. The increase in summer temperature due to urbanization was more widespread than that due to the effect of agricultural land use. The conversion of forest to agricultural land resulted in a decrease in temperature of more than 0.5 K during winter and an increase of more than 1 K during summer over the sites of perturbation. The reduced temperature during winter is related to snow cover. Agricultural lands are covered by snow while the trees in non-agricultural areas protrude through the snow, reducing the albedo of the surface. The warming during summer reflects reduced evaporation. Urbanization also reduces the diurnal temperature range (DTR) by about 0.4 K. 相似文献
37.
Kirby Calvert Peter Luciani Warren Mabee 《International journal of geographical information science》2014,28(2):274-295
Insufficient spatial coverage of existing land-cover data is a common limitation to timely and effective spatial analysis. Achieving spatial completeness of land-cover data is the most challenging for large study areas which straddle ecological or administrative boundaries, and where individuals and agencies lack access to, and the means to process, raw data from which to derive spatially complete land-cover maps. In many cases, various sources of secondary data are available, so that land-cover map assimilation and synthesis can resolve this research problem. The following paper develops a reliable and repeatable framework for assimilating and synthesizing pre-classified data sets. Assimilation is achieved through data reformatting and map legend reconciliation in the context of a specific application. Individual maps are assessed for accuracy at various geographic scales and levels of thematic precision, with an emphasis on the ‘area of overlap’, in order to extract information that guides the synthesis process. The quality of the synthesized land-cover data set is evaluated using advanced accuracy assessment methods, including a measure describing the ‘magnitude of disagreement’. This method is applied to derive a seamless thematic map of the land cover of eastern Ontario from two disparate map series. The importance of assessing data quality throughout the process using multiple reference data sets is highlighted, and limitations of the method are discussed. 相似文献
38.
Chunyang He Anni Wei Peijun Shi Qiaofeng Zhang Yuanyuan Zhao 《International Journal of Applied Earth Observation and Geoinformation》2011
Detecting land-use/land-cover (LULC) changes in rural–urban fringe areas (RUFAs) timely and accurately using satellite imagery is essential for land-use planning and management in China. Although traditional spectral-based change-vector analysis (CVA) can effectively detect LULC change in many cases, it encounters difficulties in RUFAs because of deficiencies in the spectral information of satellite images. To detect LULC changes in RUFAs effectively, this paper proposes an extended CVA approach that incorporates textural change information into the traditional spectral-based CVA. The extended CVA was applied to three different pilot RUFAs in China with different remotely sensed data, including Landsat Thematic Mapper (TM), China–Brazil Earth Resources Satellite (CBERS) and Advanced Land Observing Satellite (ALOS) images. The results demonstrated the improvement of the extended CVA compared to the traditional spectral-based CVA with the overall accuracy increased between 4.66% and 8.00% and the kappa coefficient increased between 0.10 and 0.15, respectively. The advantage of the extended CVA lies in its integration of both spectral and textural change information to detect LULC changes, allowing for effective discrimination of LULC changes that are spectrally similar but texturally different in RUFAs. The extended CVA has great potential to be widely used for LULC-change detection in RUFAs, which are often heterogeneous and fragmental in nature, with rich textural information. 相似文献
39.
面向遥感大范围应用的目标,自动化程度仍是遥感影像分类面临的重要问题,样本的人工选择难以适应当前土地覆盖信息自动化提取的实际应用需求。为了构建一套基于先验知识的遥感影像全自动分类流程,本文将空间信息挖掘技术引入到遥感信息提取过程中,提出了一种面向遥感影像对象级分类的样本自动选择方法。该方法通过变化检测将不变地物标示在新的目标影像上,并将过去解译的地物类别知识迁移至新的影像上,建立新的特征与地物关系,从而完成历史专题数据辅助下目标影像的自动化的对象级分类。实验结果表明,在已有历史专题层的图斑知识指导下,该方法能有效地自动选择适用于新影像分类的可靠样本,获得较好的信息提取效果,提高了对象级分类的效率。 相似文献
40.
Amy C. Burnicki Daniel G. Brown Pierre Goovaerts 《International journal of geographical information science》2013,27(7):1043-1060
We examined the impact of temporal dependence between patterns of error in classified time-series imagery through a simulation modeling approach. This research extended the land-cover-change simulation model we previously developed to investigate: (1) the assumption of temporal independence between patterns of error in classified time-series imagery; and (2) the interaction of patterns of change and patterns of error in a post-classification change analysis. In this research, the thematic complexity of the classified land-cover maps was increased by increasing the number of simulated land-cover classes. Simulating maps with increased categorical resolution permitted the incorporation of: (1) higher-order, more complex spatial and temporal interactions between land-cover classes; and (2) patterns of error that better reproduce the complex error interactions that often occur in time-series classified imagery. The overall modeling framework was divided into two primary components: (1) generation of a map representing true change; and (2) generation of a suite of change maps that had been perturbed by specific patterns of error. All component maps in the model were produced using simulated annealing, which enabled us to create a series of map realizations with user-defined spatial and temporal patterns. Comparing the true map of change to the error-perturbed maps of change using accuracy assessment statistics showed that increasing the temporal dependence between classification errors did not improve the accuracy of resulting maps of change when the categorical scale of the land-cover classified maps was increased. The increased structural complexity within the time series of maps effectively inhibited the impact of temporal dependence. However, results demonstrated that there are interactions between patterns of error and patterns of change in a post-classification change analysis. These interactions played a major role in determining the accuracy associated with the maps of change. 相似文献