Environmental Entomology, Published 23 September 2017
By A G Garcia, M R Araujo, K Uramoto, J M M Walder, and R A Zucchi
“Fruit flies are among the most damaging insect pests of commercial fruit in Brazil. It is important to understand the landscape elements that may favor these flies. In the present study, spatial data from surveys of species of Anastrepha Schiner (Diptera: Tephritidae) in an urban area with forest fragments were analyzed, using geostatistics and Geographic Information System (GIS) to map the diversity of insects and evaluate how the forest fragments drive the spatial patterns.
“The results indicated a high diversity of species associated with large fragments, and a trend toward lower diversity in the more urbanized area, as the fragment sizes decreased. We concluded that the diversity of Anastrepha species is directly and positively related to large and continuous forest fragments in urbanized areas, and that combining geostatistics and GIS is a promising method for use in insect-pest management and sampling involving fruit flies.”
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Geographica Pannonica Volume 21, Issue 2, June 2017
By Uglješa Stankov, Tanja Armenski, Michal Klauco, Vanja Pavluković, Marija Cimbaljević, and Nataša Drakulić-Kovačević
“Spatial autocorrelation methodologies can be used to reveal patterns and temporal changes of different spatial variables, including tourism arrivals. The research adopts a GIS-based approach to spatially analyse tourist arrivals in Serbia, using Global Moran’s I and Anselin’s Local Moran’s I statistics applied on the level of municipalities. To assess feasibility of this approach the article discusses spatial changes of tourist arrivals in order to identify potentially significant trends of interest for tourism development policy in Serbia.
Moran significance map for international tourist arrivals in Serbia (without the territory of Kosovo and Metohija) in 2001 and 2013.
Metohija) in 2001 and 2013
“There is a significant spatial inequality in the distribution of tourism arrivals in Serbia that is not adequately addressed in tourism development plans. The results of global autocorrelation suggest the existence of low and decreasing spatial clustering for domestic tourist arrivals and high, relatively stable spatial clustering for international tourists. Local autocorrelation statistics revealed different of domestic and international tourism arrivals. In order to assess feasibility of this approach these results are discussed in their significance to tourism development policy in Serbia.”
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GIScience Research Sessions
Esri International Users Conference
July 9‐13, 2018
San Diego, California
Esri invites you to present a peer‐reviewed paper in a series of GIScience research sessions that will be scheduled as part of the 2018 Esri International Users Conference. Presentations in these special sessions will focus on cutting‐edge research in GIScience and full papers will be included in a special issue of Transactions in GIS that will be published a few weeks ahead of the conference itself. For your work to be considered for inclusion in these special GIScience research sessions, extended abstracts (≤ 1,500 words) must be submitted to Dr. John Wilson, University of Southern California, by Wednesday, November 15, 2017.
The three editors of Transactions in GIS will review these extended abstracts based on the novelty and likely impact of their GIScience content and select 9‐12 abstracts to become full papers. Notice of acceptance will occur by Friday, December 8, 2017. Full papers (maximum 6,000 words plus figures, tables, and references in appropriate format for publication) must be submitted via the journal’s Scholar One portal for peer review by Friday, January 19, 2018. Reviewed papers will be returned to authors by Wednesday, February 28, 2018 and final manuscripts must be returned by Friday, March 30, 2018, to be included in the special issue of Transactions in GIS.
For questions and/or additional guidance on these GIScience research sessions, contact Michael Gould at firstname.lastname@example.org.
Abstracts should be submitted via e‐mail with a subject line “Esri GIScience Abstract, Authors Last Name” no later than Wednesday, November 15, 2017 to:
Dr. John Wilson, email@example.com
Scientific Data, Published Online 31 January 2017
By Christopher T. Lloyd, Alessandro Sorichetta, and Andrew J. Tatem
“Recent years have seen substantial growth in openly available satellite and other geospatial data layers, which represent a range of metrics relevant to global human population mapping at fine spatial scales. The specifications of such data differ widely and therefore the harmonisation of data layers is a prerequisite to constructing detailed and contemporary spatial datasets which accurately describe population distributions. Such datasets are vital to measure impacts of population growth, monitor change, and plan interventions. To this end the WorldPop Project has produced an open access archive of 3 and 30 arc-second resolution gridded data.
An excerpt of selected WorldPop gridded datasets at 100 m resolution, in plan view and as pseudo 3d stacks.
“Four tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to Global ADMinistrative area (GADM) coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) and slope layer. Further layers include transport networks, landcover, nightlights, precipitation, travel time to major cities, and waterways. Datasets and production methodology are here described. The archive can be downloaded both from the WorldPop Dataverse Repository and the WorldPop Project website.”
Sustainability 2017, 9(3), 348
By Jinlang Zou and Qun Wu
“In the context of China’s food security, spatially explicit information on grain production is an important asset to achieve the sustainable management of cultivated land. Previous studies have shown that spatial mismatches exist between grain production and water and cultivated land resources. In this paper, county-level data are used to investigate the degree of spatial (mis)match between grain output and the geographical distribution patterns of plain, hill, and mountain counties.
County-level dominant landform classification into plain counties, hill counties, or mountain counties based on the China County Statistical Yearbook.
“We estimate the difference in grain output between these different types of counties with a Spatial Autoregression Model. The results indicate that plain counties have the highest grain output, followed by hill counties and mountain counties subsequently. The reasons for the higher production in plain counties lie in the presence of more cultivated land, as well as a higher degree of irrigation and agricultural mechanization. The current pattern of Chinese total grain production follows the law of substituting labor with mechanization. Improving efficiency in the use of water resources and chemical fertilizer is both urgent and crucial. In this paper, we propose that the future roles for total grain production in relation to landforms should be: increased production and competitiveness in plain counties, a stabilization of capacity in hill counties, and a decrease in grain production in mountain counties.”
PLOSone, published online March 18, 2016
By Samantha Hajna, Nancy A. Ross, Lawrence Joseph, Sam Harper, and Kaberi Dasgupta
“There is evidence that greater neighbourhood walkability (i.e., neighbourhoods with more amenities and well-connected streets) is associated with higher levels of total walking in Europe and in Asia, but it remains unclear if this association holds in the Canadian context and in chronic disease populations. We examined the relationships of different walkability measures to biosensor-assessed total walking (i.e., steps/day) in adults with type 2 diabetes living in Montreal (QC, Canada).
Materials and Methods
Participants (60.5±10.4 years; 48.1% women) were recruited through McGill University-affiliated clinics (June 2006 to May 2008). Steps/day were assessed once per season for one year with pedometers. Neighbourhood walkability was evaluated through participant reports, in-field audits, Geographic Information Systems (GIS)-derived measures, and the Walk Score®. Relationships between walkability and daily steps were estimated using Bayesian longitudinal hierarchical linear regression models (n = 131).
Participants who reported living in the most compared to the least walkable neighbourhoods completed 1345 more steps/day (95% Credible Interval: 718, 1976; Quartiles 4 versus 1). Those living in the most compared to the least walkable neighbourhoods (based on GIS-derived walkability) completed 606 more steps per day (95% CrI: 8, 1203). No statistically significant associations with steps were observed for audit-assessed walkability or the Walk Score®.
Adults with type 2 diabetes who perceived their neighbourhoods as more walkable accumulated more daily steps. This suggests that knowledge of local neighborhood features that enhance walking is a meaningful predictor of higher levels of walking and an important component of neighbourhood walkability.”