Using control data to determine the reliability of volunteered geographic information about land cover

There is much interest in using volunteered geographic information (VGI) in formal scientific analyses. This analysis uses VGI describing land cover that was captured using a web-based interface, linked to Google Earth. A number of control points, for which the land cover had been determined by experts allowed measures of the reliability of each volunteer in relation to each land cover class to be calculated. Geographically weighted kernels were used to estimate surfaces of volunteered land cover information accuracy and then to develop spatially distributed correspondences between the volunteer land cover class and land cover from 3 contemporary global datasets (GLC-2000, GlobCover and MODIS v.5). Specifically, a geographically weighted approach calculated local confusion matrices (correspondences) at each location in a central African study area and generated spatial distributions of user's, producer's, portmanteau, and partial portmanteau accuracies. These were used to evaluate the global datasets and to infer which of them was ‘best’ at describing Tree cover at each location in the study area. The resulting maps show where specific global datasets are recommended for analyses requiring Tree cover information. The methods presented in this research suggest that some of the concerns about the quality of VGI can be addressed through careful data collection, the use of control points to evaluate volunteer performance and spatially explicit analyses. A research agenda for the use and analysis of VGI about land cover is outlined

Food Security Monitoring via Mobile Data Collection and Remote Sensing: Results from the Central African Republic

<div><p>The Central African Republic is one of the world’s most vulnerable countries, suffering from chronic poverty, violent conflicts and weak disaster resilience. In collaboration with Doctors without Borders/Médecins Sans Frontières (MSF), this study presents a novel approach to collect information about socio-economic vulnerabilities related to malnutrition, access to resources and coping capacities. The first technical test was carried out in the North of the country (sub-prefecture Kabo) in May 2015. All activities were aimed at the investigation of technical feasibility, not at operational data collection, which requires a random sampling strategy. At the core of the study is an open-source Android application named SATIDA COLLECT that facilitates rapid and simple data collection. All assessments were carried out by local MSF staff after they had been trained for one day. Once a mobile network is available, all assessments can easily be uploaded to a database for further processing and trend analysis via MSF in-house software. On one hand, regularly updated food security assessments can complement traditional large-scale surveys, whose completion can take up to eight months. Ideally, this leads to a gain in time for disaster logistics. On the other hand, recording the location of every assessment via the smart phones’ GPS receiver helps to analyze and display the coupling between drought risk and impacts over many years. Although the current situation in the Central African Republic is mostly related to violent conflict it is necessary to consider information about drought risk, because climatic shocks can further disrupt the already vulnerable system. SATIDA COLLECT can easily be adapted to local conditions or other applications, such as the evaluation of vaccination campaigns. Most importantly, it facilitates the standardized collection of information without pen and paper, as well as straightforward sharing of collected data with the MSF headquarters or other aid organizations.</p></div

Technical Set-up of SATIDA COLLECT.

<p>Technical Set-up of SATIDA COLLECT.</p

Cost of the proposed scenarios expressed as the percentage of Agricultural GDP.

<p>Cost of the proposed scenarios expressed as the percentage of Agricultural GDP.</p

Illustration of the Region of Interest (Kabo) in the Central African Republic (Kabo) and Population Density based on the Worldpop Project (http://www.worldpop.org.uk/).

<p>Illustration of the Region of Interest (Kabo) in the Central African Republic (Kabo) and Population Density based on the Worldpop Project (<a href="http://www.worldpop.org.uk/" target="_blank">http://www.worldpop.org.uk/</a>).</p

Selected Screenshots of SATIDA COLLECT (start screen, GPS localisation, MUAC measurement, food consumed during last 24 hours) in French and English.

<p>Selected Screenshots of SATIDA COLLECT (start screen, GPS localisation, MUAC measurement, food consumed during last 24 hours) in French and English.</p

Satellite-derived time series of rainfall (blue) and soil moisture (brown) for the location of Kabo (18.61E/7.69N), covering January 2010 to May 2015 (the green rectangle highlights 2014).

<p>Satellite-derived time series of rainfall (blue) and soil moisture (brown) for the location of Kabo (18.61E/7.69N), covering January 2010 to May 2015 (the green rectangle highlights 2014).</p

Affordable Nutrient Solutions for Improved Food Security as Evidenced by Crop Trials

<div><p>The continuing depletion of nutrients from agricultural soils in Sub-Saharan African is accompanied by a lack of substantial progress in crop yield improvement. In this paper we investigate yield gaps for corn under two scenarios: a micro-dosing scenario with marginal increases in nitrogen (N) and phosphorus (P) of 10 kg ha⁻¹ and a larger yet still conservative scenario with proposed N and P applications of 80 and 20 kg ha⁻¹ respectively. The yield gaps are calculated from a database of historical FAO crop fertilizer trials at 1358 locations for Sub-Saharan Africa and South America. Our approach allows connecting experimental field scale data with continental policy recommendations. Two critical findings emerged from the analysis. The first is the degree to which P limits increases in corn yields. For example, under a micro-dosing scenario, in Africa, the addition of small amounts of N alone resulted in mean yield increases of 8% while the addition of only P increased mean yields by 26%, with implications for designing better balanced fertilizer distribution schemes. The second finding was the relatively large amount of yield increase possible for a small, yet affordable amount of fertilizer application. Using African and South American fertilizer prices we show that the level of investment needed to achieve these results is considerably less than 1% of Agricultural GDP for both a micro-dosing scenario and for the scenario involving higher yet still conservative fertilizer application rates. In the latter scenario realistic mean yield increases ranged between 28 to 85% in South America and 71 to 190% in Africa (mean plus one standard deviation). External investment in this low technology solution has the potential to kick start development and could complement other interventions such as better crop varieties and improved economic instruments to support farmers.</p> </div

Crosses indicate locations of 1358 historic FAO corn field trials with at least five N and P input combinations in Africa and South America carried out between 1969 and 1993.

<p>Colors indicate (subnational) maize (corn) yields (ton/ha) as collected by <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060075#pone.0060075-IFPRI1" target="_blank">[23]</a>.</p

A typical example of a fitted crop response trial with experimental (blue line with circles) and modeled data (black line with squares) with eight N and P input combinations and resulting yields.

<p>A typical example of a fitted crop response trial with experimental (blue line with circles) and modeled data (black line with squares) with eight N and P input combinations and resulting yields.</p