scholarly journals Assessment of Human Modification of Landscapes: Human Perceptions vs. Analytical Indices

2021 ◽  
Author(s):  
Stephen Trombulak ◽  
William Hegman
Keyword(s):  
Geographic Location ◽  
Human Perception ◽  
Aerial Images ◽  
Remotely Sensed Data ◽  
Web Based ◽  
Landscape Modification ◽  
Human Footprint ◽  
Human Modification ◽  
Human Perceptions ◽  
Analytical Index

We assessed how close human perceptions of landscape modification matched a multivariate index based on remotely sensed data of the same locations. Using a Human Footprint (HF) map of the continental U.S. (scaled 0-100), we created three series of aerial images, each with ten images distributed evenly across the 10 deciles of HF score. Using a web-based survey, 290 members of the global public ranked the images in one series based on their perception of the degree of human modification. Respondents also reported age, sex, and country. The degree of correspondence between rankings by respondents and by HF score was high, an average of 1.29 units of difference out of a maximum possible of 5.0. Differences among respondents were not explained by age, sex, or general geographic location. These results suggest that human perception of relative landscape modification conforms closely with the relative ranking made by a multivariate, analytical index.

A Web-Based Visualization Tool for 3D Spatial Coverage Measurement of Aerial Images

2019 ◽  
pp. 715-721
Author(s):  
Abdullah Alfarrarjeh ◽  
Zeyu Ma ◽  
Seon Ho Kim ◽  
Yeonsoo Park ◽  
Cyrus Shahabi
Keyword(s):  
Aerial Images ◽  
Visualization Tool ◽  
Web Based ◽  
Spatial Coverage ◽  
Coverage Measurement

scholarly journals Remote Sensing for Property Valuation: A Data Source Comparison in Support of Fair Land Taxation in Rwanda

2021 ◽  
Vol 13 (18) ◽  
pp. 3563
Author(s):  
Mila Koeva ◽  
Oscar Gasuku ◽  
Monica Lengoiboni ◽  
Kwabena Asiama ◽  
Rohan Mark Bennett ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Aerial Images ◽  
Primary Data ◽  
Structured Interviews ◽  
Remotely Sensed Data ◽  
Quality Of Data ◽  
New Approach ◽  
Property Valuation ◽  
Land Administration

Remotely sensed data is increasingly applied across many domains, including fit-for-purpose land administration (FFPLA), where the focus is on fast, affordable, and accurate property information collection. Property valuation, as one of the main functions of land administration systems, is influenced by locational, physical, legal, and economic factors. Despite the importance of property valuation to economic development, there are often no standardized rules or strict data requirements for property valuation for taxation in developing contexts, such as Rwanda. This study aims at assessing different remote sensing data in support of developing a new approach for property valuation for taxation in Rwanda; one that aligns with the FFPLA philosophy. Three different remote sensing technologies, (i) aerial images acquired with a digital camera, (ii) WorldView2 satellite images, and (iii) unmanned aerial vehicle (UAV) images obtained with a DJI Phantom 2 Vision Plus quadcopter, are compared and analyzed in terms of their fitness to fulfil the requirements for valuation for taxation purposes. Quantitative and qualitative methods are applied for the comparative analysis. Prior to the field visit, the fundamental concepts of property valuation for taxation and remote sensing were reviewed. In the field, reference data using high precision GNSS (Leica) was collected and used for quantitative assessment. Primary data was further collected via semi-structured interviews and focus group discussions. The results show that UAVs have the highest potential for collecting data to support property valuation for taxation. The main reasons are the prime need for accurate-enough and up-to-date information. The comparison of the different remote sensing techniques and the provided new approach can support land valuers and professionals in the field in bottom-up activities following the FFPLA principles and maintaining the temporal quality of data needed for fair taxation.

scholarly journals THE URBIS PROJECT: IDENTIFICATION AND CHARACTERIZATION OF POTENTIAL URBAN DEVELOPMENT AREAS AS A WEB-BASED SERVICE

2016 ◽  
Vol XLI-B4 ◽  
pp. 227-233
Author(s):  
Nina Manzke ◽  
Martin Kada ◽  
Thomas Kastler ◽  
Shaojuan Xu ◽  
Norbert de Lange ◽  
...  
Keyword(s):  
Urban Areas ◽  
Landscape Fragmentation ◽  
Urban Land ◽  
End Users ◽  
Information Services ◽  
Urban Land Use ◽  
Specific Information ◽  
Remotely Sensed Data ◽  
Web Based ◽  
Site Specific

Urban sprawl and the related landscape fragmentation is a Europe-wide challenge in the context of sustainable urban planning. The URBan land recycling Information services for Sustainable cities (URBIS) project aims for the development, implementation, and validation of web-based information services for urban vacant land in European functional urban areas in order to provide end-users with site specific characteristics and to facilitate the identification and evaluation of potential development areas. The URBIS services are developed based on open geospatial data. In particular, the Copernicus Urban Atlas thematic layers serve as the main data source for an initial inventory of sites. In combination with remotely sensed data like SPOT5 images and ancillary datasets like OpenStreetMap, detailed site specific information is extracted. Services are defined for three main categories: i) baseline services, which comprise an initial inventory and typology of urban land, ii) update services, which provide a regular inventory update as well as an analysis of urban land use dynamics and changes, and iii) thematic services, which deliver specific information tailored to end-users' needs.

Spatial Models, Cognitive Metrics, and Majority Rule Equilibria

2009 ◽  
Vol 40 (1) ◽  
pp. 11-30 ◽  
Author(s):  
Macartan Humphreys ◽  
Michael Laver
Keyword(s):  
Empirical Research ◽  
Majority Rule ◽  
Sufficient Conditions ◽  
Spatial Models ◽  
Human Perception ◽  
City Block ◽  
Human Perceptions ◽  
Smooth Preferences ◽  
Similarity And Difference ◽  
Necessary And Sufficient

Long-standing results demonstrate that, if policy choices are defined in spaces with more than one dimension, majority-rule equilibrium fails to exist for a general class of smooth preference profiles. This article shows that if agents perceive political similarity and difference in ‘city block’ terms, then the dimension-by-dimension median can be a majority-rule equilibrium even in spaces with an arbitrarily large number of dimensions and it provides necessary and sufficient conditions for the existence of such an equilibrium. This is important because city block preferences accord more closely with empirical research on human perception than do many smooth preferences. It implies that, if empirical research findings on human perceptions of similarity and difference extend also to perceptions ofpoliticalsimilarity and difference, then the possibility of equilibrium under majority rule re-emerges.

Abstract 205: Etiologic Ischemic Stroke Phenotypes in the NINDS Stroke Genetics Network

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Hakan Ay ◽  
Ethem M Arsava ◽  
Robert D. Brown ◽  
Steven J Kittner ◽  
Jin-Moo Lee ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Geographic Location ◽  
Quality Data ◽  
High Quality ◽  
Good Reliability ◽  
Web Based ◽  
Stroke Subtypes ◽  
Phenotype Data ◽  
Epidemiological Characteristics

Background and Purpose: NINDS Stroke Genetics Network (SiGN) is an international consortium of ischemic stroke studies that aims to generate high quality phenotype data to identify the genetic basis of ischemic stroke subtypes. The goal of this analysis is to characterize the etiopathogenetic basis of ischemic stroke in the consortium. Methods: This analysis included 16,954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries. 52 trained and certified adjudicators used the web-based Causative Classification of Stroke System for etiologic stroke classification through chart reviews to determine both phenotypic (abnormal test findings categorized in major etiologic groups without weighting towards the most likely cause in the presence of multiple etiologies) and causative subtypes in each subject. Classification reliability was assessed with blinded re-adjudication of 1509 randomly selected cases. Findings: The figure shows the distribution of etiologic categories. Overall, only 40% to 54% of cases with a given major ischemic stroke etiology (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (kappa 0·72, 95%CI:0·69-0·75) and phenotypic classifications (kappa 0·73, 95%CI:0·70-0·75). Conclusions: This study provides high quality data on etiologic stroke subtypes and demonstrates that etiologic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes suggests that the presence of an abnormality in a stroke patient does not necessarily mean that it is the cause of stroke.

Mobile Robot Navigation Utilizing the WEB Based Aerial Images Without Prior Teaching Run

2017 ◽  
Vol 29 (4) ◽  
pp. 697-705 ◽  
Author(s):  
Satoshi Muramatsu ◽  
Tetsuo Tomizawa ◽  
Shunsuke Kudoh ◽  
Takashi Suehiro ◽  
◽  
...  
Keyword(s):  
Image Data ◽  
Aerial Images ◽  
Mobile Robot Navigation ◽  
Aerial Image ◽  
Map Matching ◽  
Robot Localization ◽  
Web Based ◽  
Map Data ◽  
Component Map ◽  
Robot Position

In order to realize the work of goods conveyance etc. by robot, localization of robot position is fundamental technology component. Map matching methods is one of the localization technique. In map matching method, usually, to create the map data for localization, we have to operate the robot and measure the environment (teaching run). This operation requires a lot of time and work. In recent years, due to improved Internet services, aerial image data is easily obtained from Google Maps etc. Therefore, we utilize the aerial images as a map data to for mobile robots localization and navigation without teaching run. In this paper, we proposed the robot localization and navigation technique using aerial images. We verified the proposed technique by the localization and autonomous running experiment.

scholarly journals Hyperspace Geography: Visualizing Fitness Landscapes beyond 4D

2006 ◽  
Vol 12 (2) ◽  
pp. 211-216 ◽  
Author(s):  
Janet Wiles ◽  
Bradley Tonkes
Keyword(s):  
Cognitive Abilities ◽  
Human Perception ◽  
Continuous Functions ◽  
Basins Of Attraction ◽  
Search Algorithms ◽  
Fitness Landscapes ◽  
Neighborhood Structure ◽  
Web Based ◽  
Complex Spaces ◽  
Graph Paper

Human perception is finely tuned to extract structure about the 4D world of time and space as well as properties such as color and texture. Developing intuitions about spatial structure beyond 4D requires exploiting other perceptual and cognitive abilities. One of the most natural ways to explore complex spaces is for a user to actively navigate through them, using local explorations and global summaries to develop intuitions about structure, and then testing the developing ideas by further exploration. This article provides a brief overview of a technique for visualizing surfaces defined over moderate-dimensional binary spaces, by recursively unfolding them onto a 2D hypergraph. We briefly summarize the uses of a freely available Web-based visualization tool, Hyperspace Graph Paper (HSGP), for exploring fitness landscapes and search algorithms in evolutionary computation. HSGP provides a way for a user to actively explore a landscape, from simple tasks such as mapping the neighborhood structure of different points, to seeing global properties such as the size and distribution of basins of attraction or how different search algorithms interact with landscape structure. It has been most useful for exploring recursive and repetitive landscapes, and its strength is that it allows intuitions to be developed through active navigation by the user, and exploits the visual system's ability to detect pattern and texture. The technique is most effective when applied to continuous functions over Boolean variables using 4 to 16 dimensions.

scholarly journals ADVERSARIAL DOMAIN ADAPTATION FOR THE CLASSIFICATION OF AERIAL IMAGES AND HEIGHT DATA USING CONVOLUTIONAL NEURAL NETWORKS

2019 ◽  
Vol IV-2/W7 ◽  
pp. 197-204 ◽  
Author(s):  
D. Wittich ◽  
F. Rottensteiner
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Domain Adaptation ◽  
Feature Representation ◽  
Training Data ◽  
Aerial Images ◽  
Remotely Sensed Data ◽  
Target Domain ◽  
Deep Convolutional Neural Networks

<p><strong>Abstract.</strong> Domain adaptation (DA) can drastically decrease the amount of training data needed to obtain good classification models by leveraging available data from a source domain for the classification of a new (target) domains. In this paper, we address deep DA, i.e. DA with deep convolutional neural networks (CNN), a problem that has not been addressed frequently in remote sensing. We present a new method for semi-supervised DA for the task of pixel-based classification by a CNN. After proposing an encoder-decoder-based fully convolutional neural network (FCN), we adapt a method for adversarial discriminative DA to be applicable to the pixel-based classification of remotely sensed data based on this network. It tries to learn a feature representation that is domain invariant; domain-invariance is measured by a classifier’s incapability of predicting from which domain a sample was generated. We evaluate our FCN on the ISPRS labelling challenge, showing that it is close to the best-performing models. DA is evaluated on the basis of three domains. We compare different network configurations and perform the representation transfer at different layers of the network. We show that when using a proper layer for adaptation, our method achieves a positive transfer and thus an improved classification accuracy in the target domain for all evaluated combinations of source and target domains.</p>

scholarly journals Effects of Augmented Self-Reflections on Health Perceptions During the COVID-19 Pandemic: A Between-Subjects Web-Based Experiment (Preprint)

2021 ◽  
Author(s):  
Ayanna Seals ◽  
Monsurat Olaosebikan ◽  
Jennifer Otiono ◽  
Orit Shaer ◽  
Oded Nov
Keyword(s):  
Adverse Effects ◽  
Health Communication ◽  
Adverse Reactions ◽  
Human Perception ◽  
Communication Strategy ◽  
Health Perceptions ◽  
Perceived Threat ◽  
Web Based ◽  
Vicarious Reinforcement ◽  
The Impact

BACKGROUND Augmented Reality (A.R.) technologies with the potential for augmenting mirror and video self-reflections are growing in popularity. It is important to study how the use of these tools may impact human perception and emotion as it relates to health behavior. OBJECTIVE We aimed to examine the impact of mirror self-focus attention and vicarious reinforcement on psychological predictors of behavior change during the COVID-19 pandemic. In addition, our study included measures of fear and message minimization to assess potential adverse reactions to the design interventions. METHODS A web-based between-subjects experiment (n = 335) was conducted to compare the health perceptions of participants in different design conditions. Those who experienced mirror self-focus, vicarious reinforcement, or a combination of the two were compared to a control condition. RESULTS We found that participants who engaged in mirror self-focus, when combined with vicarious reinforcement displayed directly on the user, resulted in elevated scores of perceived threat severity (P = 0.03) and susceptibility (P = 0.01) when compared to the control. A significant indirect effect of direct mirror reinforcement on intention was found with perceived threat severity as a mediator (b = .06, 95% CI= [.02, .12], SE = .02). Direct mirror reinforcement did not result in higher levels of fear (P = 0.32) or message minimization (P = 0.42) when compared to the control. CONCLUSIONS Augmenting reflections with vicarious reinforcement may be an effective strategy for health communication designers. While our study’s results did not show adverse effects in regards to fear and message minimization, utilization of augmenting reflections should be done with care due to possible adverse effects of heightened levels of fear as a health communication strategy.

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