Improving the potential of pixel-based supervised classification in the absence of quality ground truth data

The accuracy of classified results is often measured in comparison with reference or “ground truth” information. However, in inaccessible or remote natural areas, sufficient ground truth data may not be cost-effectively acquirable. In such cases investigative measures towards the optimisation of the classification process may be required. The goal of this paper was to describe the impact of various parameters when applying a supervised Maximum Likelihood Classifier (MLC) to SPOT 5 image analysis in a remote savanna biome. Pair separation indicators and probability thresholds were used to analyse the effect of training area size and heterogeneity as well as band combinations and the use of vegetation indices. It was found that adding probability thresholds to the classification may provide a measure of suitability regarding training area characteristics and band combinations. The analysis illustrated that finding a balance between training area size and heterogeneity may be fundamental to achieving an optimum classified result.Furthermore, results indicated that the addition of vegetation index values introduced as additional image bands could potentially improve classified products and that threshold outcomes could be used to illustrate confidence levels when mapping classified results

Data visualization in yield component analysis: an expert study

Even though data visualization is a common analytical tool in numerous disciplines, it has rarely been used in agricultural sciences, particularly in agronomy. In this paper, we discuss a study on employing data visualization to analyze a multiplicative model. This model is often used by agronomists, for example in the so-called yield component analysis. The multiplicative model in agronomy is normally analyzed by statistical or related methods. In practice, unfortunately, usefulness of these methods is limited since they help to answer only a few questions, not allowing for a complex view of the phenomena studied. We believe that data visualization could be used for such complex analysis and presentation of the multiplicative model. To that end, we conducted an expert survey. It showed that visualization methods could indeed be useful for analysis and presentation of the multiplicative model

EVALUATING THE USE OF UNMANNED AERIAL SYSTEMS (UAS) FOR COLLECTING THEMATIC MAPPING ACCURACY ASSESSMENT REFERENCE DATA IN NEW ENGLAND FOREST COMMUNITIES

To overcome the main drivers of global environmental change, such as land use and land cover change, evolving technologies must be adopted to rapidly and accurately capture, process, analyze, and display a multitude of high resolution spatial variables. Remote sensing technologies continue to advance at an ever-increasing rate to meet end-user needs, now in the form of unmanned aerial systems (UAS or drones). UAS have bridged the gap left by satellite imagery, aerial photography, and even ground measurements in data collection potential for all matters of information. This new platform has already been deployed in many data collection scenarios, being modified to the needs of the end user. With modern remote sensing optics and computer technologies, thematic mapping of complex communities presents a wide variety of classification methods, including both pixel-based and object-based classifiers. One essential component of using the derived thematic data as decision-making information is first validating its accuracy. The process of assessing thematic accuracy over the years has come a long way, with site-specific multivariate analysis error matrices now being the premier evaluation mechanism. In order to perform any evaluation of certainty, or correctness, a comparison to a known standard must be made, this being reference data. Methods for reference data collection in both pixel-based and object-based classification assessments are indeterminate, but can all become quite limiting due to their immense costs. This research project set out to evaluate if the new, low cost UAS platform could collect reference data for use in thematic mapping accuracy assessments. We also evaluated several collection process methods for their efficiency and effectiveness, as the use of UAS is still relatively unknown in its ability to acquire data in densely vegetated landscapes. Collected imagery was calibrated and stitched together by way of structure-from-motion (SfM), attempting calibration and configuration in both Agisoft PhotoScan and Pix4DMapper Pro to form orthomosaic models. Our results showed that flying heights below 100m above the focus area surface, while acquiring ultra-high-detailed imagery, only resulted in a maximum of 62% image calibration when generating spatial models. Flying at our legal maximum flying height of 120m above the surface (just below 400ft), we averaged 97.49% image calibration, and a gsd of 3.23cm/pixel over the 398 ha. sampled. Using a classification scheme based on judging the percent coniferous composition of the sampled units, our results during optimal UAS sampling showed a maximum of 71.43% overall accuracy and 85.71% overall accuracy, respectively, for pixel-based and object-based thematic accuracy assessments, in direct comparison to ground sampled locations. Other randomly sampled procedures for each approach achieved slightly less agreement with ground data classifications. Despite the minor drawbacks brought about by the complexity of the environment, the classification results demonstrated OBIA acquiring exceptional accuracy in reference data collection. Future expansion of the project across more study areas, and larger forest landscapes could uncover increased agreement and efficiency of the UAS platform

Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins

The calibration of macroscale hydrological models is often challenged by the lack of adequate observations of river discharge and infrastructure operations. This modeling backdrop creates a number of potential pitfalls for model calibration, potentially affecting the reliability of hydrological models. Here, we introduce a novel numerical framework conceived to explore and overcome these pitfalls. Our framework consists of VIC-Res (a macroscale model setup for the Upper Mekong Basin), which is a novel variant of the Variable Infiltration Capacity (VIC) model that includes a module for representing reservoir operations, and a hydraulic model used to infer discharge time series from satellite data. Using these two models and global sensitivity analysis, we show the existence of a strong relationship between the parameterization of the hydraulic model and the performance of VIC-Res – a codependence that emerges for a variety of performance metrics that we considered. Using the results provided by the sensitivity analysis, we propose an approach for breaking this codependence and informing the hydrological model calibration, which we finally carry out with the aid of a multi-objective optimization algorithm. The approach used in this study could integrate multiple remotely sensed observations and is transferable to other poorly gauged and heavily regulated river basins.</p

Regional Structural Orientation of the Mount Sharp Group Revealed by In Situ Dip Measurements and Stratigraphic Correlations on the Vera Rubin Ridge

Ground‐based bedding orientation measurements are critical to determine the geologic history and processes of sedimentation in Gale crater, Mars. We constrain the dip of lacustrine strata of the Blunts Point, Pettegrove Point, and Jura members of the Murray formation using a combination of regional stratigraphic correlations and bed attitude measurements from stereo Mastcam images taken by the Mars Science Laboratory Curiosity rover. In situ bed attitude measurements using a principal component analysis‐based regression method reveal a wide range of dips and dip azimuths owing to a combination of high stereo errors, postdepositional deformation of strata (e.g., fracturing, rotation, and impact cratering), and different primary depositional dips. These constrain regional dips to be within several degrees of horizontal on average. Stratigraphic correlations between targets observed in the Glen Torridon trough and at the Pettegrove Point‐Jura member contact of Vera Rubin ridge (VRR) constrain dips to be between 3°SE and 2°NW, consistent with nearly flat strata deposited horizontally on an equipotential surface. The Jura member is determined to be stratigraphically equivalent to the northern portion of the Glen Torridon trough. Rover‐based dip magnitudes are generally significantly shallower than the orientation of VRR member contacts measured from High Resolution Imaging Science Experiment‐based traces, suggesting the sedimentary strata and VRR member contacts may be discordant

National Aeronautics and Space Administration fundamental research program. Information utilization and evaluation, appendices

Important points presented and recommendations made at an information and decision processes workshop held in Asilomar, California; at a data and information performance workshop held in Houston, Texas; and at a data base use and management workshop held near San Jose, California are summarized. Issues raised at a special session of the Soil Conservation Society of America's remote sensing for resource management conference in Kansas City, Missouri are also highlighted. The goals, status and activities of the NASA program definition study of basic research requirements, the necessity of making the computer science community aware of user needs with respect to information related to renewable resources, performance parameters and criteria for judging federal information systems, and the requirements and characteristics of scientific data bases are among the topics reported

Guidance for benthic habitat mapping: an aerial photographic approach

This document, Guidance for Benthic Habitat Mapping: An Aerial Photographic Approach, describes proven technology that can be applied in an operational manner by state-level scientists and resource managers. This information is based on the experience gained by NOAA Coastal Services Center staff and state-level cooperators in the production of a series of benthic habitat data sets in Delaware, Florida, Maine, Massachusetts, New York, Rhode Island, the Virgin Islands, and Washington, as well as during Center-sponsored workshops on coral remote sensing and seagrass and aquatic habitat assessment. (PDF contains 39 pages) The original benthic habitat document, NOAA Coastal Change Analysis Program (C-CAP): Guidance for Regional Implementation (Dobson et al.), was published by the Department of Commerce in 1995. That document summarized procedures that were to be used by scientists throughout the United States to develop consistent and reliable coastal land cover and benthic habitat information. Advances in technology and new methodologies for generating these data created the need for this updated report, which builds upon the foundation of its predecessor