Spatial technologies such as GIS and remote sensing are widely used for environmental and natural resource studies. Spatial Accuracy Assessment provides state-of-the-science methods, techniques and real-world solutions designed to validate spatial data, to meet quality assurance objectives, and to ensure cost-effective project implementation and completion. If you use GIS, remote sensing and other spatial mapping technologies for resource management, land use planning, engineering or environmental studies, this vital reference will save you time and money.
Accuracy assessment of maps derived from remotely sensed data has continued to grow since the first edition of this groundbreaking book. As a result, the much-anticipated new edition is significantly expanded and enhanced to reflect growth in the field. The new edition features three new chapters, including: Fuzzy accuracy assessmentPositional accu
The past 10 years have brought amazing changes to the technologies used to turn remotely sensed data into maps. As a result, the principles and practices necessary for assessing the accuracy of those maps have also evolved and matured. This third edition of Assessing the Accuracy of Remotely Sensed Data: Principles and Practices is thoroughly updated and includes five new chapters. Now 15 chapters long, this text is the only one of its kind to provide geospatial analysts with the requisite considerations, tools, and theory necessary to conduct successful and efficient map accuracy assessments; and map users with the knowledge to fully understand the assessment process to ensure effective use of maps. See What’s New in the Third Edition: All original chapters have been updated to include new standards, practices, and methodologies. A new chapter on planning accuracy assessments. A new chapter on assessing maps created using object-based technologies. Two case study chapters - one showcasing the assessment of maps created from traditional methods, and one on the assessment of object-based maps. Emphasis on considering and planning for positional accuracy in concert with thematic accuracy. An appendix containing the internationally recognized ASPRS Positional Accuracy Standards. A new final chapter summarizing the key concepts, considerations and lessons learned by the authors in their decades of implementing and evaluating accuracy assessments. Assessing map accuracy is complex; however, the discussions in this book, together with the many figures, tables, and case studies, clearly present the necessary concepts and considerations for conducting an assessment that is both is practical, statistically reliable, and achievable.
Accurate traffic forecasts for highway planning and design help ensure that public dollars are spent wisely. Forecasts inform discussions about whether, when, how, and where to invest public resources to manage traffic flow, widen and remodel existing facilities, and where to locate, align, and how to size new ones. The TRB National Cooperative Highway Research Program's NCHRP Report 934: Traffic Forecasting Accuracy Assessment Research seeks to develop a process and methods by which to analyze and improve the accuracy, reliability, and utility of project-level traffic forecasts. The report also includes tools for engineers and planners who are involved in generating traffic forecasts, including: Quantile Regression Models, a Traffic Accuracy Assessment, a Forecast Archive Annotated Outline, a Deep Dive Annotated Outline, and Deep Dive Assessment Tables.
Based upon a special symposium sponsored by the U.S. Environmental Protection Agency (EPA), Remote Sensing and GIS Accuracy Assessment evaluates the important scientific elements related to the performance of accuracy assessments for remotely sensed data, GIS data analysis, and integration products. Scientists from federal, state, and local governments, academia, and nongovernmental organizations present technical papers which examine sampling issues, reference data collection, edge and boundary effects, error matrix and fuzzy assessments, error budget analysis, and change detection accuracy assessment. This compilation contains 20 chapters that represent important symposium outcomes.
Spatial technologies such as GIS and remote sensing are widely used for environmental and natural resource studies. Spatial Accuracy Assessment provides state-of-the-science methods, techniques and real-world solutions designed to validate spatial data, to meet quality assurance objectives, and to ensure cost-effective project implementation.
This international symposium on theory and techniques for assessing the accuracy of spatial data and spatial analyses included more than ninety presentations by representatives from government, academic, and private institutions in over twenty countries throughout the world. To encourage interactions across disciplines, presentations in the general subject areas of spatial statistics, geographic information systems, remote sensing, and multidisciplinary approaches were intermixed throughout the three days of sessions.
The concept of remote sensing as a way of capturing information from an object without making contact with it has, until recently, been exclusively focused on the use of Earth observation satellites. The emergence of unmanned aerial vehicles (UAV) with Global Navigation Satellite System (GNSS) controlled navigation and sensor-carrying capabilities has increased the number of publications related to new remote sensing from much closer distances. Previous knowledge about the behavior of the Earth's surface under the incidence different wavelengths of energy has been successfully applied to a large amount of data recorded from UAVs, thereby increasing the special and temporal resolution of the products obtained. More specifically, the ability of UAVs to be positioned in the air at pre-programmed coordinate points; to track flight paths; and in any case, to record the coordinates of the sensor position at the time of the shot and at the pitch, yaw, and roll angles have opened an interesting field of applications for low-altitude aerial photogrammetry, known as UAV photogrammetry. In addition, photogrammetric data processing has been improved thanks to the combination of new algorithms, e.g., structure from motion (SfM), which solves the collinearity equations without the need for any control point, producing a cloud of points referenced to an arbitrary coordinate system and a full camera calibration, and the multi-view stereopsis (MVS) algorithm, which applies an expanding procedure of sparse set of matched keypoints in order to obtain a dense point cloud. The set of technical advances described above allows for geometric modeling of terrain surfaces with high accuracy, minimizing the need for topographic campaigns for georeferencing of such products. This Special Issue aims to compile some applications realized thanks to the synergies established between new remote sensing from close distances and UAV photogrammetry.
The goal of this research is to develop a new approach to remote sensing thematic accuracy assessment in which the spectral distances between the classes in a thematic classification are used as inputs to the error estimation process. The conceptual basis for this new approach is that the confusion of relatively spectrally different classes represents a more severe error than confusing relatively spectrally similar classes. Therefore, the accuracy estimate of a classification can be adjusted to take into account the 'spectral severities' (or misclassification costs) of the errors in that classification. The benefits of including inter-class spectral distances in the accuracy assessment process are shown in the context of the development of two new accuracy assessment measures called Spectrally Weighted Kappa (SWK) and Spectrally Weighted Fuzzy (SWF). These two new accuracy assessment methods are introduced and tested for their performance relative to current techniques. The results of this research demonstrate that inter-class spectral distances can be used effectively in accuracy assessment of thematic classifications. The SWK approach can provide information about the spectral costs of errors in a classification that is not as apparent with traditional methods. In addition, SWK provides a quantitative base for establishing weights for Weighted Kappa analysis and allows for the possibility of improving a classification during its development. The SWF method improves upon current fuzzy accuracy assessment techniques by providing a way to establish membership functions that is based on inter-class spectral distances. We have shown that the SWF method can provide fuzzy membership values that are similar to those that a well-trained human might choose. Therefore, in cases where multiple interpreters would normally have been used to create fuzzy membership values, the SWF method can be employed reduce inter-interpreter bias. In addition, the SWF method provides a quanti.
