Mali is a country where little information is known about the circulation of avian influenza viruses (AIVs) in poultry. Implementing risk-based surveillance strategies would allow early detection and rapid control of AIVs outbreaks in the country. In this study, we implemented a multi-criteria decision analysis (MCDA) method coupled with geographic information systems (GIS) to identify risk areas for AIVs occurrence in domestic poultry in Mali. Five risk factors associated with AIVs occurrence were identified from the literature, and their relative weights were determined using the analytic hierarchy process (AHP). Spatial data were collected for each risk factor and processed to produce risk maps for AIVs outbreaks using a weighted linear combination (WLC). We identified the southeast regions (Bamako and Sikasso) and the central region (Mopti) as areas with the highest risk of AIVs occurrence. Conversely, northern regions were considered low-risk areas. The risk areas agree with the location of HPAI outbreaks in Mali. This study provides the first risk map using the GIS-MCDA approach to identify risk areas for AIVs occurrence in Mali. It should provide a basis for designing risk-based and more cost-effective surveillance strategies for the early detection of avian influenza outbreaks in Mali.

Cet article est une étude expérimentale menée sur le site archéologique de Gasr Chouline à Tataouine en utilisant la prospection archéologique et les systèmes d'informations géographiques (SIG) pour améliorer la gestion du site. Bien que cette étude n'ait pas prétendu à l'exhaustivité, elle a fourni de nouvelles données archéologiques par suite d'une prospection systématique.

Today, technological developments are ever-growing yet fragmented. Alongside inconsistent digital approaches and attitudes across city administrations, such developments have made it difficult to reap the benefits of city digital twins. Bringing together experiences from five research projects, this paper discusses these digital twins based on two digital integration methodologies—systems and semantic integration. We revisit the nature of the underlying technologies, and their implications for interoperability and compatibility in the context of planning processes and smart urbanism. Semantic approaches present a new opportunity for bidirectional data flows that can inform both governance processes and technological systems to co-create, cross-pollinate, and support optimal outcomes. Building on this opportunity, we suggest that considering the technological dimension as a new addition to the trifecta of economic, environmental, and social sustainability goals that guide planning processes, can aid governments to address this conundrum of fragmentation, interoperability, and compatibility.

Racial identification is a critical factor in understanding a multitude of important outcomes in many fields. However, inferring an individual’s race from ecological data is prone to bias and error. This process was only recently improved via Bayesian improved surname geocoding (BISG). With surname and geographic-based demographic data, it is possible to more accurately estimate individual racial identification than ever before. However, the level of geography used in this process varies widely. Whereas some existing work makes use of geocoding to place individuals in precise census blocks, a substantial portion either skips geocoding altogether or relies on estimation using surname or county-level analyses. Presently, the trade-offs of such variation are unknown. In this letter, we quantify those trade-offs through a validation of BISG on Georgia’s voter file using both geocoded and nongeocoded processes and introduce a new level of geography—ZIP codes—to this method. We find that when estimating the racial identification of White and Black voters, nongeocoded ZIP code-based estimates are acceptable alternatives. However, census blocks provide the most accurate estimations when imputing racial identification for Asian and Hispanic voters. Our results document the most efficient means to sequentially conduct BISG analysis to maximize racial identification estimation while simultaneously minimizing data missingness and bias.

The objective of this study is to determine the prevalence of Fasciola hepatica infection in cattle slaughterhouses, as well as its association with climatic/environmental factors (derived from satellite data), seasonality and climate regions in two states in Mexico. Condemned livers from slaughtered animals were obtained from three abattoirs in the states of Puebla and Veracruz. The overall prevalence of the parasite in cattle between January and December of 2017 was 20.6% (1407 out of 6834); the highest rate of condemnation was observed in Veracruz (26.3%; tropical climate), and the lowest rate was found in Puebla (15.5%; temperate climate). The seasonal prevalence of fluke infection was 18.6%, 14.8% and 28.4% during the wet season, and 17.1%, 12.4% and 22.8% during the dry season in the three abattoir sites, located in the districts of Zacatlán, Teziutlán and Ciudad Alemán, respectively. Liver condemnations due to bovine fasciolosis were prevalent in the Zacatlán, Teziutlán and Ciudad Alemán districts during summer, autumn and summer, respectively. Using generalized estimating equations analysis, we determined six variables – rainfall (wet/dry), land surface temperature day, land surface temperature night, normalized difference vegetation index, seasonality and climate regions (temperate/tropical) – to be significantly associated with the prevalence of condemned livers. Climate region was the variable most strongly associated with F. hepatica infection (odds ratio (OR) 266.59; 95% confidence interval (CI): 241.90–353.34), followed by wet and dry seasons (OR 25.56; 95% CI: 20.56–55.67).

Using a production function approach, we estimate that the economic value of biotic pollination to Georgia’s agriculture increased from $425 million in 2009 to $488 million in 2017 in real terms. We perform spatial analysis to reveal county-level spatial patterns and temporal trends in that value. Using a unique set of pollinator survey data, we also compare the locations of biotic pollinators to the areas they bring the most economic value to, which provides insights on the variation in the dependency of the crop mix to pollination services.

Evidence exists of an increasing prevalence of chronic conditions within developed and developing nations, notably for priority population groups. The need for the collection of geospatial data to monitor the health impact of rapid social-environmental and economic changes occurring in these countries is being increasingly recognized. Rigorous accuracy assessment of such geospatial data is required to enable error estimation, and ultimately, data utility for exploring population health. This research outlines findings from a field-based evaluation exercise of the SOMAARTH DDESS geospatial-health platform. Participatory-based mixed methods have been employed within Palwal-India to capture villager perspectives on built infrastructure across 51 villages. This study, conducted in 2013, included an assessment of data element position and attribute accuracy undertaken in six villages, documenting mapping errors and land parcel changes. Descriptive analyses of 5.1% (n = 455) of land parcels highlighted some discrepancies in position (6.4%) and attribute (4.2%) accuracy, and land parcel changes (17.4%). Furthermore, the evaluation led to a refinement of the existing geospatial health platform incorporating ground-truthed reflections from the participatory field exercise. The evaluation of geospatial data accuracies contributes to understandings on global public health surveillance systems, outlining the need to systematically consider assessment of environmental features in relation to lifestyle-related diseases.

A detailed, quantitative, multitemporal analysis of historical maps, aerial photos, and satellite images was performed to investigate the channel planform changes that occurred along the Scrivia River floodplain from 1878 to 2016. Various channel planform features, including channel length, area, width, braiding, sinuosity, lateral migration, activity, and stability, were computed through an innovative geographic information system–based procedure, starting from manually digitized active-channel polygons. Three active-channel morphological evolution stages are evident from: (1) 1878 to the 1950s; (2) the 1950s to the end of 1990s; and (3) the end of 1990s onward. In the first period, the river was generally able to migrate in its floodplain, shaping the riverscape. Active-channel narrowing and increasing channel stability characterize the second period. The most recent phase shows an inversion of the morphological evolutionary trend. This last phase is characterized by a slight generalized widening related to the reactivation of stabilized surfaces and to bank-erosion processes. Particularly from the 1950s to the 1990s, in-channel sediment mining and channelization with consequent occupation of riverine areas strongly affected the Scrivia River. These factors, together with floods, are thought to be the most likely causes of such consistent and fast morphological changes.

Ice cores from mid-latitude mountain glaciers provide detailed information on past climate conditions and regional environmental changes, which is essential for placing current climate change into a longer term perspective. In this context, it is important to define guidelines and create dedicated maps to identify suitable areas for future ice-core drillings. In this study, the suitability for ice-core drilling (SICD) of a mountain glacier is defined as the possibility of extracting an ice core with preserved stratigraphy suitable for reconstructing past climate. Morphometric and climatic variables related to SICD are selected through literature review and characterization of previously drilled sites. A quantitative Weight of Evidence method is proposed to combine selected variables (i.e. slope, local relief, temperature and direct solar radiation) to map the potential drilling sites in mid-latitude mountain glaciers. The method was first developed in the European Alps and then applied to the Asian High Mountains. Model performances and limitations are discussed and first indications of new potential drilling sites in the Asian High Mountains are provided. Results presented here can facilitate the selection of future drilling sites especially on unexplored Asian mountain glaciers towards the understanding of climate and environmental changes.

A screening procedure to minimize adverse water quality impacts of pesticide application is presented that matches pesticide parameters to site-specific soil ratings. The pesticide parameters include a Relative Leaching Potential Index (RLPI), a Relative Runoff Potential Index (RRPI), the U.S. Environ. Prot. Agency (USEPA) lifetime health advisory level (HAL), and aquatic toxicity (LC50). Criteria used in developing soil ratings are described. Pesticide selection is accomplished by matching pesticide parameters values for the array of pesticides that control the pest of interest to soil ratings at the application site using selection criteria. A worksheet is presented to facilitate organization of information for the selection procedure and to serve as a record of the pesticide applicator's decision. The linking of an environmental fate model to a geographic information system (GIS) to create thematic maps of pesticide leaching potentials in terms of probability of exceeding the HAL in groundwater is described. A cost vs. groundwater hazard index frontier is described that suggests a method to assess the economic consequences of alternative pesticide selections.

Leafy spurge is a troublesome, exotic weed in the northern Great Plains of the United States. Leafy spurge produces showy yellow bracts during June that give this weed a conspicuous appearance. A study was conducted to determine the feasibility of using remote sensing techniques to detect leafy spurge in this phenological stage. Study sites were located in North Dakota and Montana. Plant canopy reflectance measurements showed that leafy spurge had higher visible (0.63- to 0.69-μm) reflectance than several associated plant species. The conspicuous yellow bracts of leafy spurge gave it distinct yellow-green and pink images on conventional color and color-infrared aerial photographs, respectively. Leafy spurge also could be distinguished on conventional color video imagery where it had a golden yellow image response. Quantitative data obtained from digitized video images showed that leafy spurge had statistically different digital values from those of associated vegetation and soil. Computer analyses of video images showed/that light reflected from leafy spurge populations could be quantified from associated vegetation. This technique permits area estimates of leafy spurge populations. Large format conventional color photographs of Theodore Roosevelt National Park near Medora, ND were digitized and integrated with a geographic information system to produce a map of leafy spurge populations within the park that can be useful to monitor the spread or decline of leafy spurge.

This paper describes the application of airborne video data with global positioning system and geographic information system technologies for detecting and mapping Chinese tamarisk infestations in the southwestern United States. Study areas were along the Colorado River in southwestern Arizona, the Rio Grande River in extreme west Texas, and the Pecos River in west-central Texas. Chinese tamarisk could be readily distinguished on conventional color video imagery in late November when its foliage turned a yellow-orange to orange-brown color prior to leaf drop. The integration of the global positioning system with the video imagery permitted latitude/longitude coordinates of Chinese tamarisk infestations to be recorded on each image. The global positioning system latitude/longitude coordinates were entered into a geographic information system to map Chinese tamarisk populations along the three river systems.

The number of invasive exotic plant species establishing in the United States is continuing to rise. When prevention of exotic species from entering into a country fails at the national level and the species establishes, reproduces, spreads, and becomes invasive, the most successful action at a local level is early detection followed by eradication. We have developed a simple geographic information system (GIS) analysis for developing watch lists for early detection of invasive exotic plants that relies upon currently available species distribution data coupled with environmental data to aid in describing coarse-scale potential distributions. This GIS analysis tool develops environmental envelopes for species based upon the known distribution of a species thought to be invasive and represents the first approximation of its potential habitat while the necessary data are collected to perform more in-depth analyses. To validate this method we looked at a time series of species distributions for 66 species in Pacific Northwest and northern Rocky Mountain counties. The time series analysis presented here did select counties that the invasive exotic weeds invaded in subsequent years, showing that this technique could be useful in developing watch lists for the spread of particular exotic species. We applied this same habitat-matching model based upon bioclimatic envelopes to 100 invasive exotics with various levels of known distributions within continental U.S. counties. For species with climatically limited distributions, county watch lists describe county-specific vulnerability to invasion. Species with matching habitats in a county would be added to that county's list. These watch lists can influence management decisions for early warning, control prioritization, and targeted research to determine specific locations within vulnerable counties. This tool provides useful information for rapid assessment of the potential distribution based upon climate envelopes of current distributions for new invasive exotic species.