Determining the Extent of Market and Extent of Resource for Stated Preference Survey Design Using Mapping Methods

Determining the appropriate survey population and the commodity to be valued are among the most fundamental design decisions for stated preference (SP) surveys. However, often little information is available about who in the population holds measurable value for the resource (the extent of the market) and their perceptions regarding the scope of the resource to be valued (the extent of the resource). In this paper, we present a novel approach using cognitive mapping interview techniques to shed light on these design questions. The method also provides ancillary information that assists in the interpretation of information collected during focus groups and through SP survey administration. The approach was developed and tested as part of an ongoing study on environmental degradation associated with acidification in the Southern Appalachian Mountain region. Although damage from acidification in the study region is broad, it is not clear whether residents of this region care, in both a use and nonuse sense, about resources in their states of residence, in neighboring states, on public lands, or more broadly across the region. From a pilot study, we found that participants show a significant home-state preference in the number and size of natural areas that they value within the larger Southern Appalachian Mountain region. However, this preference is not strong enough to suggest that the market for improving these resources is solely constrained to residents of the state in which the resource is located.stated preference, cognitive mapping, extent of market, extent of resource, definition of commodity

The State of the Art in Cartograms

Cartograms combine statistical and geographical information in thematic maps, where areas of geographical regions (e.g., countries, states) are scaled in proportion to some statistic (e.g., population, income). Cartograms make it possible to gain insight into patterns and trends in the world around us and have been very popular visualizations for geo-referenced data for over a century. This work surveys cartogram research in visualization, cartography and geometry, covering a broad spectrum of different cartogram types: from the traditional rectangular and table cartograms, to Dorling and diffusion cartograms. A particular focus is the study of the major cartogram dimensions: statistical accuracy, geographical accuracy, and topological accuracy. We review the history of cartograms, describe the algorithms for generating them, and consider task taxonomies. We also review quantitative and qualitative evaluations, and we use these to arrive at design guidelines and research challenges

PolyTB: a genomic variation map for Mycobacterium tuberculosis

Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) is the second major cause of death from an infectious disease worldwide. Recent advances in DNA sequencing are leading to the ability to generate whole genome information in clinical isolates of M. tuberculosis complex (MTBC). The identification of informative genetic variants such as phylogenetic markers and those associated with drug resistance or virulence will help barcode Mtb in the context of epidemiological, diagnostic and clinical studies. Mtb genomic datasets are increasingly available as raw sequences, which are potentially difficult and computer intensive to process, and compare across studies. Here we have processed the raw sequence data (>1500 isolates, eight studies) to compile a catalogue of SNPs (n = 74,039, 63% non-synonymous, 51.1% in more than one isolate, i.e. non-private), small indels (n = 4810) and larger structural variants (n = 800). We have developed the PolyTB web-based tool (http://pathogenseq.lshtm.ac.uk/polytb) to visualise the resulting variation and important meta-data (e.g. in silico inferred strain-types, location) within geographical map and phylogenetic views. This resource will allow researchers to identify polymorphisms within candidate genes of interest, as well as examine the genomic diversity and distribution of strains. PolyTB source code is freely available to researchers wishing to develop similar tools for their pathogen of interest

Mapping the Space of Genomic Signatures

We propose a computational method to measure and visualize interrelationships among any number of DNA sequences allowing, for example, the examination of hundreds or thousands of complete mitochondrial genomes. An "image distance" is computed for each pair of graphical representations of DNA sequences, and the distances are visualized as a Molecular Distance Map: Each point on the map represents a DNA sequence, and the spatial proximity between any two points reflects the degree of structural similarity between the corresponding sequences. The graphical representation of DNA sequences utilized, Chaos Game Representation (CGR), is genome- and species-specific and can thus act as a genomic signature. Consequently, Molecular Distance Maps could inform species identification, taxonomic classifications and, to a certain extent, evolutionary history. The image distance employed, Structural Dissimilarity Index (DSSIM), implicitly compares the occurrences of oligomers of length up to $k$ (herein $k=9$) in DNA sequences. We computed DSSIM distances for more than 5 million pairs of complete mitochondrial genomes, and used Multi-Dimensional Scaling (MDS) to obtain Molecular Distance Maps that visually display the sequence relatedness in various subsets, at different taxonomic levels. This general-purpose method does not require DNA sequence homology and can thus be used to compare similar or vastly different DNA sequences, genomic or computer-generated, of the same or different lengths. We illustrate potential uses of this approach by applying it to several taxonomic subsets: phylum Vertebrata, (super)kingdom Protista, classes Amphibia-Insecta-Mammalia, class Amphibia, and order Primates. This analysis of an extensive dataset confirms that the oligomer composition of full mtDNA sequences can be a source of taxonomic information.Comment: 14 pages, 7 figures. arXiv admin note: substantial text overlap with arXiv:1307.375

From the cartographic gaze to contestatory cartographies

Rene Descartes declared in the 16th Century that the world was now dominated by the visual, a notion that would be seen as defining the Enlightenment (Descartes, cited in Potts, 2015). As the increased dominance of seeing and the desire to visualise the world cohered with the production of increasingly accurate tools of measurement and the advent of the printing press, cartography emerged as a discipline, often used as tool of oppression and dominance. Cartographic visualizations, afforded the creator, and user, a Gods eye view of the world. Following others (See Casas-Cortés et. al., 2013; Koch, 1998), this chapter refers to this way of seeing the world from above as the Cartographic Gaze. First, the chapter briefly examines the historical emergence of the Cartographic Gaze before turning to a discussion about how the proliferation of geographic imaging technologies and digital tools simultaneously further embedded this gaze into mapping practice, while also diffusing such practices of mapping to broader populations. Discussing the rise of participatory mapping and counter mapping under the rubric of contestatory cartographies, the chapter presents some of the challenges that face those attempting to create alternative maps of their worlds, and the ways in which they become entrapped by the pervasiveness of the Cartographic Gaze. We use the term participatory mapping to refer to methodologies for map-making based around the participation of those who the map will represent. And we employ the term counter mapping to reference those mapping practices that explicitly seek to expose and challenge power relations. In specific, we look at how the colonizing origins of the Cartographic Gaze limit what it is possible to do with these alternative mapping practices

A Weakly Supervised Approach for Estimating Spatial Density Functions from High-Resolution Satellite Imagery

We propose a neural network component, the regional aggregation layer, that makes it possible to train a pixel-level density estimator using only coarse-grained density aggregates, which reflect the number of objects in an image region. Our approach is simple to use and does not require domain-specific assumptions about the nature of the density function. We evaluate our approach on several synthetic datasets. In addition, we use this approach to learn to estimate high-resolution population and housing density from satellite imagery. In all cases, we find that our approach results in better density estimates than a commonly used baseline. We also show how our housing density estimator can be used to classify buildings as residential or non-residential.Comment: 10 pages, 8 figures. ACM SIGSPATIAL 2018, Seattle, US

Chromosomal-level assembly of the Asian Seabass genome using long sequence reads and multi-layered scaffolding

We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species' native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics