Estimating The Distribution of Livestock In Space And Time: A Time-Series Contribution To Livestock Density Mapping

More than one billion people rely on livestock for income, nutrition, and social cohesion, however livestock keeping can facilitate disease transmission and contribute to climate change. While data on the distribution of livestock thus have broad utility across a range of applications, efforts to map the distribution of livestock on a large scale are limited to the Gridded Livestock of the World (GLW) project. We present a complimentary effort to map the distribution of cattle and pigs in Malawi, Uganda, Democratic Republic of Congo (DRC), and South Sudan. In contrast to GLW, which uses dasymmetric modeling applied to census data to produce time-stratified estimates of livestock counts and spatial density, our work uses complex survey data and distinct modeling methods to generate a time-series of livestock distribution, defining livestock density as the ratio of animals to humans. In addition to favorable cross-validation results and general agreement with national density estimates derived from external data on national human and livestock populations, our results demonstrate extremely good agreement with GLW-3 estimates, supporting the validity of both efforts. Our results furthermore offer a high-resolution time series result and employ a definition of density which is particularly well-suited to the study of livestock-origin zoonoses.

Ecoregional and temporal dynamics of dugong habitat use in a complex coral reef lagoon ecosystem

Mobile marine species display complex and nonstationary habitat use patterns that require understanding to design effective management measures. In this study, the spatio-temporal habitat use dynamics of the vulnerable dugong (Dugong dugon) were modelled from 16 satellite-tagged individuals in the coral reef lagoonal ecosystems of New Caledonia, South Pacific. Dugong residence time was calculated along the interpolated tracks (9371 hourly positions) to estimate intensity of use in three contrasting ecoregions, previously identified through hierarchical clustering of lagoon topographic characteristics. Across ecoregions, differences were identified in dugong spatial intensity of use of shallow waters, deeper lagoon waters and the fore-reef shelf outside the barrier reef. Maps of dugong intensity of use were predicted from these ecological relationships and validated with spatial density estimates derived from aerial surveys conducted for population assessment. While high correlation was found between the two datasets, our study extended the spatial patterns of dugong distribution obtained from aerial surveys across the diel cycle, especially in shallow waters preferentially used by dugongs at night/dusk during high tide. This study has important implications for dugong conservation and illustrates the potential benefits of satellite tracking and dynamic habitat use modelling to inform spatial management of elusive and mobile marine mammals.

A Pricing Model for Urban Rental Housing Based on Convolutional Neural Networks and Spatial Density: A Case Study of Wuhan, China

With the development of urbanization and the expansion of floating populations, rental housing has become an increasingly common living choice for many people, and housing rental prices have attracted great attention from individuals, enterprises and the government. The housing rental prices are principally estimated based on structural, locational and neighborhood variables, among which the relationships are complicated and can hardly be captured entirely by simple one-dimensional models; in addition, the influence of the geographic objects on the price may vary with the increase in their quantities. However, existing pricing models usually take those structural, locational and neighborhood variables as one-dimensional inputs into neural networks, and often neglect the aggregated effects of geographical objects, which may lead to fluctuating rental price estimations. Therefore, this paper proposes a rental housing price model based on the convolutional neural network (CNN) and the synthetic spatial density of points of interest (POIs). The CNN can efficiently extract the complex characteristics among the relevant variables of housing, and the two-dimensional locational and neighborhood variables, based on the synthetic spatial density, effectively reflect the aggregated effects of the urban facilities on rental housing prices, thereby improving the accuracy of the model. Taking Wuhan, China, as the study area, the proposed method achieves satisfactory and accurate rental price estimations (coefficient of determination (R2) = 0.9097, root mean square error (RMSE) = 3.5126) in comparison with other commonly used pricing models.

Distribution and phenology of monarch butterfly larvae and their milkweed hosts in the South Central US

South Central US milkweeds (Asclepias) are critical adult nectar and larval food resources for producing the first spring and last summer/fall generations of declining eastern migratory monarch butterflies (Danaus plexippus). This study addresses multiple gaps in assessment of monarch conservation priorities for the South Central US through analyses of monarch larval host selectivity, phenology, and spatial density, as well as the phenology, niche modeled distribution, and land cover selectivity of important milkweed hosts. Results are synthesized to estimate seasonal milkweed resource areas. About 70% of monarch larval activity occurred from mid-March to mid-July (early season) and 30% from mid-August to late November (late season). Twenty-six wild milkweed (Apocynaceae) hosts were mapped, including four new records for North America. Important hosts included Asclepias a. ssp. capricornu, A. viridis, and A. oenotheroides, that were utilized more frequently during early season, and Asclepias latifolia, utilized more frequently during late season. Landscape host selectivity was positive for A. viridis and A. a. ssp. capricornu in late and early seasons, respectively, and negative for A. oenotheroides in late season. Milkweed land cover selectivity was positive for Developed-Open Space and Grassland Herbaceous, and negative for Cultivated Crops and Shrub/Scrub. Seasonal milkweed resource areas and larval spatial densities resolved interior and coastal corridors providing functional connectivity for monarch spring and fall migrations. A potential gap in milkweed land cover benefit was identified in South Texas. The novel merging of milkweed niche models with larval phenology, host selectivity, milkweed phenology, and land cover selectivity informs conservation assessment.

Monitoring deformations of infrastructure networks: A fully automated GIS integration and analysis of InSAR time-series

Ageing stock and extreme weather events pose a threat to the safety of infrastructure networks. In most countries, funding allocated to infrastructure management is insufficient to perform systematic inspections over large transport networks. As a result, early signs of distress can develop unnoticed, potentially leading to catastrophic structural failures. Over the past 20 years, a wealth of literature has demonstrated the capability of satellite-based Synthetic Aperture Radar Interferometry (InSAR) to accurately detect surface deformations of different types of assets. Thanks to the high accuracy and spatial density of measurements, and a short revisit time, space-borne remote-sensing techniques have the potential to provide a cost-effective and near real-time monitoring tool. Whilst InSAR techniques offer an effective approach for structural health monitoring, they also provide a large amount of data. For civil engineering procedures, these need to be analysed in combination with large infrastructure inventories. Over a regional scale, the manual extraction of InSAR-derived displacements from individual assets is extremely time-consuming and an automated integration of the two datasets is essential to effectively assess infrastructure systems. This paper presents a new methodology based on the fully automated integration of InSAR-based measurements and Geographic Information System-infrastructure inventories to detect potential warnings over extensive transport networks. A Sentinel dataset from 2016 to 2019 is used to analyse the Los Angeles highway and freeway network, while the Italian motorway network is evaluated by using open access ERS/Envisat datasets between 1992 and 2010, COSMO-SkyMed datasets between 2008 and 2014 and Sentinel datasets between 2014 and 2020. To demonstrate the flexibility of the proposed methodology to different SAR sensors and infrastructure classes, the analysis of bridges and viaducts in the two test areas is also performed. The outcomes highlight the potential of the proposed methodology to be integrated into structural health monitoring systems and improve current procedures for transport network management.

The Warm Gas in the Milky Way: The Kinematical Model of C iv and Its Connection to Si iv

We compose a 265-sight-line Milky Way C iv line-shape sample using the Hubble Space Telescope/Cosmic Origins Spectrograph archive, which is complementary to the existing Si iv samples. C iv has a higher ionization potential (47–64 eV) than Si iv (33–45 eV), so it also traces warm gas, which is roughly cospatial with Si iv. The spatial density distribution and kinematics of C iv are identical to those Si iv within ≈2σ. C iv is more sensitive to the warm gas density distribution at large radii with a higher element abundance. Applying the kinematical model to the C iv sample, we find two possible solutions of the density distribution, which are distinguished by the relative extension along the disk midplane and the normal-line direction. Both solutions can reproduce the existing sample and suggest a warm gas disk mass of log M ( M ⊙ ) ≈ 8 and an upper limit of log M ( M ⊙ ) < 9.3 within 250 kpc, which is consistent with Si iv. There is a decrease in the C iv/Si iv column density ratio from the Galactic center to the outskirts by 0.2–0.3 dex, which may suggest a phase transition or different ionization mechanisms for C iv and Si iv. Also, we find that the difference between C iv and Si iv is an excellent tracer of small-scale features, and we find a typical size of 5°–10° for possible turbulence within individual clouds (≈1 kpc).

The Dynamic Relationship between Air and Land Surface Temperature within the Madison, Wisconsin Urban Heat Island

The urban heat island (UHI) effect, the phenomenon by which cities are warmer than rural surroundings, is increasingly important in a rapidly urbanizing and warming world, but fine-scale differences in temperature within cities are difficult to observe accurately. Networks of air temperature (Tair) sensors rarely offer the spatial density needed to capture neighborhood-level disparities in warming, while satellite measures of land surface temperature (LST) do not reflect the air temperatures that people physically experience. This analysis combines both Tair measurements recorded by a spatially-dense stationary sensor network in Dane County, Wisconsin, and remotely-sensed measurements of LST over the same area—to improve the use and interpretation of LST in UHI studies. The data analyzed span three summer months (June, July, and August) and eight years (2012–2019). Overall, Tair and LST displayed greater agreement in spatial distribution than in magnitude. The relationship between day of the year and correlation was fit to a parabolic curve (R2 = 0.76, p = 0.0002) that peaked in late July. The seasonal evolution in the relationship between Tair and LST, along with particularly high variability in LST across agricultural land cover suggest that plant phenology contributes to a seasonally varying relationship between Tair and LST measurements of the UHI.

Landscape Evolution and Simulation of Rural Settlements around Wetland Park Based on MCCA Model and Landscape Theory: A Case Study of Chaohu Peninsula, China

As a transitional zone between urban and rural areas, the peri-urban areas are the areas with the most intense urban expansion and the most frequent spatial reconfiguration, and in this context, it is particularly important to reveal the evolution pattern of rural settlements in the peri-urban areas to provide reference for the rearrangement of rural settlements. The study takes five townships in the urban suburbs, and explores the scale, shape, spatial layout, and spatial characteristics of the urban suburbs of Hefei from 1980 to 2030 under the influence of urban-lake symbiosis based on spatial mathematical analysis and geographical simulation software. The study shows that: (1) the overall layout of rural settlements in the study area is randomly distributed due to the hilly terrain, but in small areas there is a high and low clustering phenomenon, and the spatial density shows the distribution characteristics of “high in the east and low in the west”; (2) since the reform and opening up, there are large spatial differences in the scale of rural settlements in the study area. (3) Different development scenarios have a strong impact on the future spatial pattern of rural settlement land use within the study area, which is a strong reflection of policy.

EFFECT OF THE SPANWISE DISCRETISATION ON TURBULENT FLOW PAST A CIRCULAR CYLINDER

The effect of the spanwise discretisation on numerical calculations of the turbulent flow around a circular cylinder is systematically assessed at a subcritical Reynolds number of 10000 in the frame of three-dimensional large-eddy simulation. The eddy-viscosity k-equation subgrid scale model is implemented to evaluate unsteady turbulent flow field. Large-eddy simulation is known to be a reliable method to resolve such a challenging flow field, however, the high computational efforts restrict to low Reynolds number flow or two-dimensional calculations. Therefore, minimum spatial density in the spanwise direction or cylinder axis direction needs to be carefully evaluated in order to reduce high computational resources. In the present study, the influence of the spanwise resolutions to satisfactorily represent three- dimensional complex flow features is discussed in detail and minimum spatial density for high Reynolds flow is suggested.