首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 296 毫秒
1.
Spatial data quality is a paramount concern in all GIS applications. Existing spatial data accuracy standards, including the National Standard for Spatial Data Accuracy (NSSDA) used in the United States, commonly assume the positional error of spatial data is normally distributed. This research has characterized the distribution of the positional error in four types of spatial data: GPS locations, street geocoding, TIGER roads, and LIDAR elevation data. The positional error in GPS locations can be approximated with a Rayleigh distribution, the positional error in street geocoding and TIGER roads can be approximated with a log‐normal distribution, and the positional error in LIDAR elevation data can be approximated with a normal distribution of the original vertical error values after removal of a small number of outliers. For all four data types considered, however, these solutions are only approximations, and some evidence of non‐stationary behavior resulting in lack of normality was observed in all four datasets. Monte‐Carlo simulation of the robustness of accuracy statistics revealed that the conventional 100% Root Mean Square Error (RMSE) statistic is not reliable for non‐normal distributions. Some degree of data trimming is recommended through the use of 90% and 95% RMSE statistics. Percentiles, however, are not very robust as single positional accuracy statistics. The non‐normal distribution of positional errors in spatial data has implications for spatial data accuracy standards and error propagation modeling. Specific recommendations are formulated for revisions of the NSSDA.  相似文献   

2.
In this study, a MDC3A algorithm (Multi-Data Crossing Algorithm for Accuracy Accessing) was developed for accessing the accuracy of chl-a (chlorophyll-a) retrieval model in case of no sufficient available in situ measurements. Three simple estimation algorithms of chl-a concentration, i.e., two-band algorithm, three-band algorithm and four-band algorithm, were used as input dataset of MDC3A algorithm to illuminate its performance. These three simple algorithms were calibrated and validated by calibration and validation dataset collected on October 27–28, 2003. According to model calibration and validation results, it was found that the four-band algorithm (R 2?=?0.8676) had a superior performance to the two-band (R 2?=?0.5061) and three-band (R 2?=?0.5142) algorithm. The uncertainties in modeling prediction of these three simple algorithms were underestimated as 0.07 %, 0.04 % and 8.07 % for calibration dataset and 8.38 %, 9.33 % and 9.37 % for validation dataset by MDC3A algorithm through comparison with in situ measurements. Because the MDC3A algorithm was able to detect the random errors from measured values, but had an inadequate ability to detect systematical errors and gross errors from measured values. The uncertainty estimated by MDC3A algorithm was usually lower than that estimated by in situ measurements.  相似文献   

3.
Positional error is the error produced by the discrepancy between reference and recorded locations. In urban landscapes, locations typically are obtained from global positioning systems or geocoding software. Although these technologies have improved the locational accuracy of georeferenced data, they are not error free. This error affects results of any spatial statistical analysis performed with a georeferenced dataset. In this paper we discuss the properties of positional error in an address matching exercise and the allocation of point locations to census geography units. We focus on the error's spatial structure, and more particularly on impacts of error propagation in spatial regression analysis. For this purpose we use two geocoding sources, we briefly describe the magnitude and the nature of their discrepancies, and we evaluate the consequences that this type of locational error has on a spatial regression analysis of pediatric blood lead data for Syracuse, NY. Our findings include: (1) the confirmation of the recurrence of spatial clustering in positional error at various geographic resolutions; and, (2) the identification of a noticeable but not shockingly large impact from positional error propagation in spatial auto‐binomial regression analysis results for the dataset analyzed.  相似文献   

4.
Species distribution modeling (SDM) at fine spatial resolutions requires species occurrence data of high positional accuracy to achieve good model performance. However, wildlife occurrences recorded by patrols in ranger‐based monitoring programs suffer from positional errors, because recorded locations represent the positions of the ranger and differ from the actual occurrence locations of wildlife (hereinafter referred to as positional errors in patrol data). This study presented an evaluation of the impact of such positional errors in patrol data on SDM and developed a heuristic‐based approach to mitigating the positional errors. The approach derives probable wildlife occurrence locations from ranger positions, utilizing heuristics based on species preferred habitat and the observer's field of view. The evaluations were conducted through a case study of SDM using patrol records of the black‐and‐white snub‐nosed monkey (Rhinopithecus bieti) in Yunnan, China. The performance of the approach was also compared against alternative sampling methods. The results showed that the positional errors in R. bieti patrol data had an adverse effect on SDM performance, and that the proposed approach can effectively mitigate the impact of the positional errors to greatly improve SDM performance.  相似文献   

5.
Abstract

This study examines the potentials of remotely sensed data, GIS and some machine learning classifiers and ensemble techniques in the investigation of the non-linear relationship between malaria occurrences and socio-physical conditions in the Dak Nong province of Viet Nam. Accuracy assessment was determined with Receiver Operating Characteristic (ROC) curve and pair t-test. The results showed that the area under ROC of Random Subspace ensemble model performed better than the other models based on statistical indicators. Comparing pair t-test with Area Under Curve values showed a slight difference of about 1%. Therefore ensemble techniques had significantly improved the performance of the base classifier. However, the performances might vary according to geographic locations. It is concluded that the machine learning classifiers combined with remotely sensed data and GIS is promising for malaria vulnerability mapping, and the derived maps can be used as a fundamental basis for programmes on spatial disease control.  相似文献   

6.
Positional Accuracy of TIGER 2000 and 2009 Road Networks   总被引：1，自引：0，他引：1  
The Topologically Integrated Geographic Encoding and Referencing (TIGER) data are an essential part of the US Census and represent a critical element in the nation's spatial data infrastructure. TIGER data for the year 2000, however, are of limited positional accuracy and were deemed of insufficient quality to support the 2010 Census. In response the US Census Bureau embarked on the MAF/TIGER Accuracy Improvement Project (MTAIP) in an effort to improve the positional accuracy of the database, modernize the data processing environment and improve cooperation with partner agencies. Improved TIGER data were released for the entire US just before the 2010 Census. The current study characterizes the positional accuracy of the TIGER 2009 data compared with the TIGER 2000 data based on selected road intersections. Three US counties were identified as study areas and in each county 100 urban and 100 rural sample locations were selected. Features in the TIGER 2000 and 2009 data were compared with reference locations derived from high resolution natural color orthoimagery. Results indicate that TIGER 2009 data are much improved in terms of positional accuracy compared with the TIGER 2000 data, by at least one order of magnitude across urban and rural areas in all three counties for most accuracy metrics. TIGER 2009 is consistently more accurate in urban areas compared with rural areas, by a factor of at least two for most accuracy metrics. Despite the substantial improvement in positional accuracy, large positional errors of greater than 10 m are relatively common in the TIGER 2009 data, in most cases representing remnant segments of minor roads from older versions of the TIGER data. As a result, based on the US Census Bureau's suggested accuracy metric, the TIGER 2009 data meet the accuracy expectation of 7.6 m for two of the three urban areas but for none of the three rural areas. The suggested metric is based on the National Standard for Spatial Data Accuracy (NSSDA) protocol and was found to be very sensitive to the presence of a small number of very large errors. This presents challenges during attempts to characterize the accuracy of TIGER data or other spatial data using this protocol.  相似文献   

7.
史文中 《测绘学报》1997,26(2):160-167
本文提出了描述地理信息系统中几何特征位置不确定性的一个通用模型，从１维到Ｎ维，在每１维中，ＧＩＳ中的特征被划分为点，线段及线性特征。由于ＧＩＳ中数据含有误差。这些特征在ＧＩＳ中位置未必与其现实世界中的真实位置一致，而其真实位置只是在围绕着ＧＩＳ中量测位置的某一个区域内，本文提出的模型给出了这些区域的统计描述。  相似文献   

8.
The performance accuracy of Thiessen-polygon and kriging interpolation methods available in the standard GIS packages was evaluated based on magnitude of errors in predicting potential UV exposure across the continental U.S., and the results were compared with those of the ANUSPLIN routine that runs outside typical GIS through a series of C++ and FORTRAN commands. Input data consisted of global radiation measures recorded at 215 stations, latitude, longitude, and elevation from a 30 arc-second Digital Elevation Model. The objective was to identify the most accurate prediction method for facilitating measurement of potential UV exposure at local (e.g.1km2 grid cell) and county levels. The ANUSPLIN method produced the smallest prediction errors in estimating values of potential UV exposure at 1 km2 resolution; these measurements were aggregated to the county level. We examined how much variation was lost through aggregation, as well as the potential bias associated with the possibility that some counties have predominantly north or south facing slopes. The impact of using inferior procedures on the estimates and geographic patterns of potential UV exposure was also examined. ANUSPLIN generated results that are reproducible and for which uncertainty is known. These measurements will be used in subsequent analysis of the role of UV exposure in melanoma etiology.  相似文献   

9.
Abstract

The generalization of digital terrain models (DTMs) is a tool of great potential for simultaneous cartographic and photogrammetry generation processes at different scales, the main object of which is to feed different geographic information systems (GIS). These GIS enable multi-scale analysis and visualization through different data bases. This research proposes a semi-automatic DTM generalization process conditioned by a series of predefined parameters resulting in the generation of hybrid DTMs at different scales starting from a single cloud of points obtained through large-scale massive data acquisition processes. The generalization results obtained, applied on different areas of different relief, offer specific application ranks for each parameter with great precision, in contrast with DTMs obtained directly in each scale.  相似文献   

10.
Assessment of groundwater potential zones using GIS technique   总被引：1，自引：0，他引：1  
A case study was conducted to find out the groundwater potential zones in Kattakulathur block, Tamil Nadu, India with an aerial extent of 360.60 km2. The thematic maps such as geology, geomorphology, soil hydrological group, land use / land cover and drainage map were prepared for the study area. The Digital Elevation Model (DEM) has been generated from the 10 m interval contour lines (which is derived from SOI, Toposheet 1:25000 scale) and obtained the slope (%) of the study area. The groundwater potential zones were obtained by overlaying all the thematic maps in terms of weighted overlay methods using the spatial analysis tool in ArcGIS 9.2. During weighted overlay analysis, the ranking has been given for each individual parameter of each thematic map and weights were assigned according to the influence such as soil −25%, geomorphology − 25%, land use/land cover −25%, slope − 15%, lineament − 5% and drainage / streams − 5% and find out the potential zones in terms of good, moderate and poor zones with the area of 49.70 km2, 261.61 km2 and 46.04 km2 respectively. The potential zone wise study area was overlaid with village boundary map and the village wise groundwater potential zones with three categories such as good, moderate and poor zones were obtained. This GIS based output result was validated by conducting field survey by randomly selecting wells in different villages using GPS instruments. The coordinates of each well location were obtained by GPS and plotted in the GIS platform and it was clearly shown that the well coordinates were exactly seated with the classified zones.  相似文献   

11.
Abstract

Remote sensing and geographic information system (GIS) scientists and educators in general are utilizing global web sources for information of the latest developments in the use of satellite and GIS approaches, as well as to understand more fully environmental and natural resources processes in various geographic settings. West Virginia University (WVU) has embarked on a pioneering approach (as only the second university worldwide) to archive graduate theses and dissertations in electronic format with worldwide web access. This study illustrates the type of remote sensing and GIS research available through WVU's worldwide web ETD archive, and its potential uses by educators at a variety of levels of the education system for understanding remote sensing and GIS methodologies, as well as environmental and natural resource processes. Keywords: Geographic Information Systems (GIS), remote sensing, West Virginia University, Electronic Thesis and Dissertation (ETD).  相似文献   

12.
平面随机线元等概率密度误差模型边界包络线   总被引：1，自引：0，他引：1  
汤仲安 《测绘工程》2005,14(4):11-13,22
线状实体误差模型包络线既是GIS位置不确定性研究的重要内容,又是GIS可视化研究的关键指标.为了充分利用计算机技术求解符合GIS精度要求的误差模型包络线,基于文献[1,2]中探讨过的等概率密度误差模型建模机理和数值算法,研究了平面随机线元等概率密度误差模型边界包络线的确定原理和计算方法,并通过实例辅以可视化分析,验证了原理的正确性和可操作性.  相似文献   

13.
Geo‐questionnaire involves an integration of sketchable maps with questions, aimed at eliciting public preferences and attitudes about land allocation and services. Respondents can link their answers with corresponding locations on a map by marking points or sketching polygon features. Geo‐questionnaires have been used to learn about perceptions and preferences of city residents for specific types of land use, place‐based services, and development projects. This article reports on results of an empirical study, in which an online geo‐questionnaire was designed and implemented to elicit preferences of residents in guiding an urban development plan. Preferences collected in the form of polygon sketches were processed using GIS operations and mapped for visual interpretation. The article focuses on aggregation and analysis of respondent preferences including the analysis of positional and attribute uncertainty. Results of the study show that geo‐questionnaire is a scalable method for eliciting public preferences with a potential for meaningfully informing land use planning.  相似文献   

14.
Precision agriculture requires high-resolution information to enable greater precision in the management of inputs to production. Actionable information about crop and field status must be acquired at high spatial resolution and at a temporal frequency appropriate for timely responses. In this study, high spatial resolution imagery was obtained through the use of a small, unmanned aerial system called AggieAirTM. Simultaneously with the AggieAir flights, intensive ground sampling for plant chlorophyll was conducted at precisely determined locations. This study reports the application of a relevance vector machine coupled with cross validation and backward elimination to a dataset composed of reflectance from high-resolution multi-spectral imagery (VIS–NIR), thermal infrared imagery, and vegetative indices, in conjunction with in situ SPAD measurements from which chlorophyll concentrations were derived, to estimate chlorophyll concentration from remotely sensed data at 15-cm resolution. The results indicate that a relevance vector machine with a thin plate spline kernel type and kernel width of 5.4, having LAI, NDVI, thermal and red bands as the selected set of inputs, can be used to spatially estimate chlorophyll concentration with a root-mean-squared-error of 5.31 μg cm−2, efficiency of 0.76, and 9 relevance vectors.  相似文献   

15.
The Lower Mississippi Alluvial Valley (LMAV) was home to about ten million hectare bottomland hardwood (BLH) forests in the Southern U.S. It experienced over 80 % area loss of the BLH forests in the past centuries and large-scale afforestation in recent decades. Due to the lack of a high-resolution cropland dataset, impacts of land use change (LUC) on the LMAV ecosystem services have not been fully understood. In this study, we developed a novel framework by integrating the machine learning algorithm, county-level agricultural census, and satellite-based cropland products to reconstruct the LMAV cropland distribution during 1850–2018 at a 30-m resolution. Results showed that the LMAV cropland area increased from 0.78 × 104 km2 in 1850 to 6.64 × 104 km2 in 1980 and then decreased to 6.16 × 104 km2 in 2018. Cropland expansion rate was the largest in the 1960s (749 km2 yr−1) but decreased rapidly thereafter, whereas cropland abandonment rate increased substantially in recent decades with the largest rate of 514 km2 yr−1 in the 2010s. Our dataset has three notable features: (1) the depiction of fine spatial details, (2) the integration of the county-level census, and (3) the inclusion of a machine-learning algorithm trained by satellite-based land cover product. Most importantly, our dataset well captured the continuous increasing trend in cropland area from 1930–1960, which was misrepresented by other cropland datasets reconstructed from the state-level census. Our dataset would be important to accurately evaluate the impacts of historical deforestation and recent afforestation efforts on regional ecosystem services, attribute the observed hydrological changes to anthropogenic and natural driving factors, and investigate how the socioeconomic factors control regional LUC pattern. Our framework and dataset are crucial to developing managerial and policy strategies for conserving natural resources and enhancing ecosystem services in the LMAV.  相似文献   

16.
ABSTRACT

Conceptually, the theory and implementation of “map projection” in geographic information system (GIS) technology is difficult to comprehend for most introductory students and novice users. Compounding this difficulty is the concept of a “map projection file” that defines map projection parameters of geo-spatial data. The problem of the “missing projection file” appears ubiquitous for all users, especially in practice where data is widely shared. Another common problem is inadvertent misapplication of the “Define Projection” tool that can result in a GIS dataset with an incorrectly defined map projection file. GIS education should provide more guidance in differentiating the concepts of map projection versus projection files by increasing understanding and minimizing common errors. A novel pedagogical device is introduced in this paper: the seven possible states of GIS data with respect to map projection and definition. The seven possible states are: (1) a projected coordinate system (PCS) that is correctly defined, (2) a PCS that is incorrectly defined, (3) a PCS that is undefined, (4) a geographic coordinate system (GCS) that is correctly defined, (5) a GCS that is incorrectly defined, (6) a GCS that is undefined, and (7) a non-GCS. Recently created automated troubleshooting tools to determine a missing map projection file are discussed.  相似文献   

17.
Abstract

This paper presents a new model for handling positional uncertainty in the process of line simplification. It considers that positional uncertainty in a simplified line is caused by (a) positional uncertainty in an initial line propagated through the process and (b) a deviation of the simplified line from the initial line. In order to describe the uncertainty in the simplified line, the maximum distance is defined as a measure. This measure is further adopted to determine parameters to a line simplification algorithm. Therefore, this model makes a step forward in the implementation of an uncertainty indicator for the line simplification. As compared existing models, the proposed uncertainty model in this paper is more comprehensive in uncertainty assessment for line simplification.  相似文献   

18.
A sufficient number of satellite acquisitions in a growing season are essential for deriving agronomic indicators, such as green leaf area index (GLAI), to be assimilated into crop models for crop productivity estimation. However, for most high resolution orbital optical satellites, it is often difficult to obtain images frequently due to their long revisit cycles and unfavorable weather conditions. Data fusion algorithms, such as the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and the Enhanced STARFM (ESTARFM), have been developed to generate synthetic data with high spatial and temporal resolution to address this issue. In this study, we evaluated the approach of assimilating GLAI into the Simple Algorithm for Yield Estimation model (SAFY) for winter wheat biomass estimation. GLAI was estimated using the two-band Enhanced Vegetation Index (EVI2) derived from data acquired by the Operational Land Imager (OLI) onboard the Landsat-8 and a fusion dataset generated by blending the Moderate-Resolution Imaging Spectroradiometer (MODIS) data and the OLI data using the STARFM and ESTARFM models. The fusion dataset had the temporal resolution of the MODIS data and the spatial resolution of the OLI data. Key parameters of the SAFY model were optimised through assimilation of the estimated GLAI into the crop model using the Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm. A good agreement was achieved between the estimated and field measured biomass by assimilating the GLAI derived from the OLI data (GLAIL) alone (R2 = 0.77 and RMSE = 231 g m−2). Assimilation of GLAI derived from the fusion dataset (GLAIF) resulted in a R2 of 0.71 and RMSE of 193 g m−2 while assimilating the combination of GLAIL and GLAIF led to further improvements (R2 = 0.76 and RMSE = 176 g m−2). Our results demonstrated the potential of using the fusion algorithms to improve crop growth monitoring and crop productivity estimation when the number of high resolution remote sensing data acquisitions is limited.  相似文献   

19.
Crop yield estimation has an important role on economy development and its accuracy and speed influence yield price and helps in deciding the excess or deficit production conditions. The water productivity evaluates the irrigation command through water use efficiency (WUE). Remote sensing (RS) and geographical information system (GIS) techniques were used for crop yield and water productivity estimation of wheat crop (Triticum aestivum) grown in Tarafeni South Main Canal (TSMC) irrigation command of West Bengal State in India. One IRS P6 image and four wide field sensor (WiFS) images for different months of winter season were used to determine the Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) for area under wheat crop. The temporally and spatially distributed spectral growth profile and AREASUM of NDVI (ANDVI) and SAVI (ASAVI) with time after sowing of wheat crop were developed and correlated with actual crop yield of wheat (Yact). The developed relationships between ASAVI and Yact resulted high correlation in comparison to that of ANDVI. Using the developed model the RS based wheat yield (YRS) predicted from ASAVI varied on entire TSMC irrigation command from 22.67 to 33.13 q ha−1 respectively, which gave an average yield of 26.50 q ha−1. The RS generated yield based water use efficiency (WUEYRS) for water supplied from canal of TSMC irrigation command was found to be 6.69 kg ha−1 mm−1.  相似文献   

20.
Geographic Information Systems (GIS) algorithms are used to simplify, edge match, and overlay large data sets. Some of these GIS processes can cause considerable positional changes to spatial data which are sometimes difficult to assess. This study presents a visualization technique for the evaluation of GIS algorithms and their positional effects on spatial data. The technique is applicable to vector representations and can be used with any GIS operation that changes vector geometry. The technique employs a uniform reference grid to exploit the visual skills of human operators in the evaluation of positional changes in spatial databases after applying GIS transformations. Changes in grid cell length, area, and shape, along with a set of displacement vectors, can be analyzed to evaluate positional changes in spatial data and to compare the behaviors of different algorithms. The technique can assist GIS users in the documentation of positional changes and in the comparison and selection of algorithms for various mapping tasks. Such a technique may assist software developers in creating and selecting appropriate GIS algorithms.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号