MACHINE LEARNING FOR CLASSIFICATION OF AN ERODING SCARP SURFACE USING TERRESTRIAL PHOTOGRAMMETRY WITH NIR AND RGB IMAGERY

Abstract. Increasingly advanced and affordable close-range sensing techniques are employed by an ever-broadening range of users, with varying competence and experience. In this context a method was tested that uses photogrammetry and classification by machine learning to divide a point cloud into different surface type classes. The study site is a peat scarp 20 metres long in the actively eroding river bank of the Rotmoos valley near Obergurgl, Austria. Imagery from near-infra red (NIR) and conventional (RGB) sensors, georeferenced with coordinates of targets surveyed with a total station, was used to create a point cloud using structure from motion and dense image matching. NIR and RGB information were merged into a single point cloud and 18 geometric features were extracted using three different radii (0.02 m, 0.05 m and 0.1 m) totalling 58 variables on which to apply the machine learning classification. Segments representing six classes, dry grass, green grass, peat, rock, snow and target, were extracted from the point cloud and split into a training set and a testing set. A Random Forest machine learning model was trained using machine learning packages in the R-CRAN environment. The overall classification accuracy and Kappa Index were 98% and 97% respectively. Rock, snow and target classes had the highest producer and user accuracies. Dry and green grass had the highest omission (1.9% and 5.6% respectively) and commission errors (3.3% and 3.4% respectively). Analysis of feature importance revealed that the spectral descriptors (NIR, R, G, B) were by far the most important determinants followed by verticality at 0.1 m radius

Agricultural Insurance and Bounded Rationality

Bounded rationality influences the individuals making decisions. Rationality of decisions is limited by the complexity of the decision problem, the cognitive limitations of decision makers, and the time available to make the decision. One specific case of this situation is decision on the agricultural insurance. The success of agricultural activity is highly dependent on environmental influences in the region. These risks can destroy entire harvest or exterminate a whole herd of livestock. The Czech Republic, through the Support and Guarantee Fund for Farmers and Forestry, provides farmers and forest managers with a contribution to cover the costs of the payment of insurance against unforeseen damage for already several years by which it affects decision-making about insurance. The article discusses the rationality of decision on the agricultural insurance using decision model under risk

Continuity of Demarcation Process of the Regions for Concentrated State Support

The paper analyses the continuity of the demarcation process of Czech regions for the state support. This support aims to reduce negative disparities among the regions. The process of demarcation of the region includes criteria as an unemployment rate, number of applicants per one job vacancy, income tax rate, number of private entrepreneurs and purchasing power. These criteria and weights of these criteria have been changed during the last 20 years. The main aim of this paper is the analysis of the criteria set and the criteria weights modification during the years 1991 – 2010 and the examination of the modification of values of the criteria weights using two different methods - Analytic Hierarchy Process and Analytic Network Process. These methods are used for synthesis of the criteria weights, which shows the continuity of the region demarcation process during its modification in time

Semantic Network in Information Processing for the Pork Market

The main aim of this paper is to capture the elements of individual information frames and their relations using semantic network; and to express the loss of information and information asymmetry in the market environment. Preferences of elements in the network are evaluated by the Analytical network process. The benefits of applying semantic networks in the market environment are in increasing consumer information and reducing information asymmetry. The use of semantic networks will be shown in the analysis of the information frames of the producer, distributor and consumer in the pork market. The consumer’s frame expresses expectations and preferences, according to which decisions are made. Producer operates with greater range of information about the product than is available to the consumer. Distributor receives information from both the producer and from the consumer, but this information is not usually fully shared to the consumers or producers. This creates information asymmetry

Selection of Communication Routes in Agriculture Equipment Company

Many publications describe problems in businesses and project management that are caused by communication. Team communication is a very complicated process full of soft aspects. One of basic problems represents a choice of an appropriate communication route kind useful for messages transmission between the team members as sources and recipients. It is a complex issue because of necessity to evaluate individual communication routes from many different perspectives. Therefore the suitable communication route of team members can be selected by a multicriterial mathematical model. Since communication can be understood as a distribution of messages, the appropriate model form can be based on the distribution model. The proposed model is derived from the three-dimensional transportation problem. The article discusses the possibility of this approach on the case study of communication modelling in the field of agriculture. Specifically, it is constructed and solved a model of communication problem for small team of agriculture equipment dealers

Near-infrared spectroscopy patterns of cortical activity during gait in Parkinson’s disease patients treated with DBS STN

Disorders of gait seriously affect the functional state and quality of life of patients with Parkinson’s disease (PD). Impaired brain function underlies disorders of movement control in PD, however functional brain imaging with magnetic resonance (fMRI) is not feasible during gait. Near-Infrared Spectroscopy (NIRS) is a portable imaging method for measuring brain activity. It uses low-energy optical radiation to detect local changes of (de)oxyhemoglobin concentration in the cerebral cortex, like a fMRI. We included 8 patients with advanced PD chronically treated with DBS STN. Brain activity was recorded with the NIRSport. Gait was examined in 10 cycles, during which the active and resting phases alternated. Changes in oxyhemoglobin concentration were calculated from the native NIRS signal using a modified transformation of the Lambert-Beer Law. The signals were filtered in the 0.015–0.3 Hz band and the least-squares algorithm was fitted with the HRF function for each cycle separately, from which the median was finally calculated. The activity of the motor cortex was significantly higher during gait in the OFF compared to ON state (p = 0.02). In contrast, in other regions no differences were found. A higher motor cortex activity shown in the DBS OFF compared to ON state may reflect the impairment of gait control in PD. In general terms, the present study demonstrates the potential utility of the NIRS method in detecting functional changes of the brain during gait in patients with PD

PROMETHEE-GAIA Method as a Support of the Decision-Making Process in Evaluating Technical Facilities

Part 1: Environmental Application in the Scope of the Future InternetInternational audienceThis paper describes the application of PROMETHEE-GAIA methodology in a multiple criteria analysis to rank potential environmental investments in mineral-processing companies. The intent of the paper is to identify best technical facilities on the basis of preferential relations between a set of variants. The method of Total Cost Analysis (TCA) was chosen to define the criteria. The economic and environmental costs, as well as the benefits of these technical facilities, were determined by means of this method. PROMETHEE is one of the methods in the Multi Criteria Analysis (MCA) category. The MCA, as the name implies, deals with the evaluation of a number of variants by several criteria. The technical facility was selected by a comparative analysis involving five influential parameters (Investment Costs, Annual Operating Costs, Operating Income, Administrative Costs and Disposal Fees, Economic and Environmental Benefits). As expected, the analysis resulted in a preferential ranking of these technical facilities