Terra Populus’ architecture for integrated big geospatial services

Big geospatial data is an emerging sub‐area of geographic information science, big data, and cyberinfrastructure. Big geospatial data poses two unique challenges. First, raster and vector data structures and analyses have developed on largely separate paths for the last 20 years. This is creating an impediment to geospatial researchers seeking to utilize big data platforms that do not promote heterogeneous data types. Second, big spatial data repositories have yet to be integrated with big data computation platforms in ways that allow researchers to spatio‐temporally analyze big geospatial datasets. IPUMS‐Terra, a National Science Foundation cyberInfrastructure project, addresses these challenges by providing a unified framework of integrated geospatial services which access, analyze, and transform big heterogeneous spatio‐temporal data. As IPUMS‐Terra's data volume grows, we seek to integrate geospatial platforms that will scale geospatial analyses and address current bottlenecks within our system. However, our work shows that there are still unresolved challenges for big geospatial analysis. The most pertinent is that there is a lack of a unified framework for conducting scalable integrated vector and raster data analysis. We conducted a comparative analysis between PostgreSQL with PostGIS and SciDB and concluded that SciDB is the superior platform for scalable raster zonal analyses.     

Annual cycle of radionuclide contamination on tide-washed pasture in the Mersey Estuary, NW England

The radionuclide burden of vegetation comprising a tide-washed pasture at Ince Marsh in the Mersey Estuary, U.K., derives mainly from adhered external particulates originating as suspended sediments in estuarine water. Radionuclide concentrations are dominated by the growth cycle of the vegetation, with the highest winter levels of contamination activity an order of magnitude greater than the lowest levels in mid-summer. A secondary effect due to sediment transfer during periods of severe flooding produces subsidiary features on this dominant seasonal profile. Radionuclide concentrations on vegetation are in the range¹³⁷Cs=8–191,¹³⁴Cs=0.3–0.9,²⁴¹Am=0.6–46,²³⁸Pu=0.1–1.5, and^239/240Pu=0.8–44 Bq kg⁻¹. These ranges reflect the relative concentrations of radionuclides in estuarine sediment (¹³⁷Cs=615,²⁴¹Am=202, and^239/240Pu=104 Bq kg⁻¹) rather than the values in filtered estuary water (¹³⁷Cs=0.4,²⁴¹Am=0.001, and^239/240Pu=0.001 Bq 1⁻¹). Median K_d values for these radionuclide species are Cs=1,400, Am=200,000, and Pu=80,000 1 kg⁻¹).     

Territoriality and the Police

Despite widespread interest in the relationship between the exercise of power and control of space, few current works in geography make explicit use of the concept of territoriality. This paper does so by considering the means by which the Los Angeles Police Department pursues its law enforcement and order maintenance functions through regulating space. I draw upon fieldwork observations of a single LAPD patrol division to demonstrate that officers regularly seek to govern the citizenry through controlling the spatial parameters of permissible action. The imperative toward effective territorial control is given further impetus within the subcultural world that officers construct; indeed, officers evaluate each other's competence in large part on their ability to manage activity within the spaces for which they are responsible.     

Improving deep decarbonization modelling capacity for developed and developing country contexts

Energy models are essential for the development of national or regional deep decarbonization pathways (DDPs), providing the necessary analytical framework to systematically explore the system transitions that are required. However, this is challenging due to the long time horizon, the numerous data requirements and the need for transparent, credible approaches that can provide insights into complex transitions.

This article explores how this challenge has been met to date, based on a review of the literature and the experiences of practitioners, drawing in particular on the Deep Decarbonization Pathways Project (DDPP), a collaborative effort by 16 national modelling teams. The article finds that there are a range of modelling approaches that have been used across different country contexts, chosen for different reasons, with recognized strengths and weaknesses. The key motivations for use of a given approach include being fit-for-purpose, having in-country capacity and the intertwined goals of transparency, communicability and policy credibility.

From the review, a conceptual decision framework for DDP analysis is proposed. This three step process incorporates policy priorities, national characteristics and the model-agnostic principles that drive model choices, considering the needs and capabilities of developed and developing countries, and subject to data and analytical practicalities. Finally an agenda for the further development of modelling approaches is proposed, which is vital for strengthening capacity. These include a focus on model linking, incorporating behaviour and policy impacts, the flexibility to handle distinctive energy systems, incorporating wider environmental constraints and the development of entry-level tools. The latter three are critical for application in developing countries.

Policy relevance

Following the Paris Agreement, it is essential that modelling approaches are available to enable governments to plan how to decarbonize their economies in the long term. This article takes stock of current practices, identifies the strengths and weaknesses of existing approaches and proposes how capacity can be strengthened. It also provides some practical guidance on the process of choosing modelling approaches, given national priorities and circumstances. This is particularly relevant as countries revisit their Nationally Determined Contributions to meet the global objective of remaining well below a 2°C average global temperature increase.     

The impact of oestrogenic and androgenic contamination on marine organisms in the United Kingdom--summary of the EDMAR programme. Endocrine Disruption in the Marine Environment

This paper summarises results of the EDMAR programme which is investigating oestrogenic and androgenic endocrine disruption in UK coastal waters. Most of the data concern fish. Four species (flounder, viviparous blenny and two sand gobies) are experiencing feminisation in industrialised estuaries. In males this includes vitellogenin (VTG) synthesis, ovotestis induction and/or feminised sexual characteristics. Although reproductive success may be impaired in some cases, implications for fish populations are still unclear. Suspected causative contaminants include natural oestrogenic substances and synthetic oestrogen mimics. The majority of the oestrogenic activity is adsorbed to sediments, and routes of exposure may include benthic food chain transfer. Some natural androgenic substances are also being discharged to estuaries, but their activity appears low.     

Developments in budget remote sensing for the geosciences

Acquiring outcrop, landform or other surface topography data in the field for the geosciences has always been challenging. Accessibility is often a problem, time is usually limited and an ideal spatial and temporal coverage often has to be compromised to be more manageable. However, emerging technologies, and some re-inventions of rather older ones, can overcome many of these constraints in a very exciting and budget-friendly manner. This article briefly introduces and reviews four major recent developments in budget remote sensing, specifically the use of blimps, kites, drones or UAVs (including quadcopters), and structure from motion (SFM) software. Both scientific and applied case studies are given and some possibilities for future studies are highlighted. Overall, the potential for these technologies to revolutionise the geosciences is clear and should be opportunistically embraced by scientists, resource and hazard managers and educators alike.