Estimating the global distribution of field size using crowdsourcing

There is an increasing evidence that smallholder farms contribute substantially to food production globally, yet spatially explicit data on agricultural field sizes are currently lacking. Automated field size delineation using remote sensing or the estimation of average farm size at subnational level using census data are two approaches that have been used. However, both have limitations, for example, automatic field size delineation using remote sensing has not yet been implemented at a global scale while the spatial resolution is very coarse when using census data. This paper demonstrates a unique approach to quantifying and mapping agricultural field size globally using crowdsourcing. A campaign was run in June 2017, where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo-Wiki application. During the campaign, participants collected field size data for 130 K unique locations around the globe. Using this sample, we have produced the most accurate global field size map to date and estimated the percentage of different field sizes, ranging from very small to very large, in agricultural areas at global, continental, and national levels. The results show that smallholder farms occupy up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modeling, comparative studies of agricultural dynamics across different contexts, for training and validation of remote sensing field size delineation, and potential contributions to the Sustainable Development Goal of Ending hunger, achieve food security and improved nutrition and promote sustainable agriculture.

A global reference database of crowdsourced cropland data collected using the Geo-Wiki platform

A global reference data set on cropland was collected through a crowdsourcing campaign using the Geo-Wiki crowdsourcing tool. The campaign lasted three weeks, with over 80 participants from around the world reviewing almost 36,000 sample units, focussing on cropland identification. For quality assessment purposes, two additional data sets are provided. The first is a control set of 1,793 sample locations validated by students trained in satellite image interpretation. This data set was used to assess the quality of the crowd as the campaign progressed. The second data set contains 60 expert validations for additional evaluation of the quality of the contributions. All data sets are split into two parts: the first part shows all areas classified as cropland and the second part shows cropland average per location and user. After further processing, the data presented here might be suitable to validate and compare medium and high resolution cropland maps generated using remote sensing. These could also be used to train classification algorithms for developing new maps of land cover and cropland extent.

Co-inheritance of α0 -thalassemia elevates Hb A2 level in homozygous Hb E: Diagnostic implications

INTRODUCTION

Differentiation of homozygous hemoglobin (Hb) E with and without α⁰ -thalassemia is subtle on routine hematological ground. We examined in a large cohort of homozygous Hb E if the level of Hb A₂ is helpful.

METHODS

A total of 592 subjects with homozygous Hb E were recruited from ongoing thalassemia screening program. Additionally, five couples at risk of having fetuses with Hb Bart's hydrops fetalis who were homozygous Hb E were also investigated. Hb analysis was performed using capillary electrophoresis system. Globin genotypes were defined by DNA analysis.

RESULTS

Subjects were classified into four groups including pure homozygous Hb E (n=532), homozygous Hb E/α⁰ -thalassemia (n=48), Hb Constant Spring EE Bart's disease (n=8), and Hb EE Bart's disease (n=4). The levels of Hb A₂ were found, respectively, to be 4.97±0.69, 6.64±1.02, 4.86±0.87, and 7.60±1.04%. Among five couples at risk, α⁰ -thalassemia was identified in three subjects with Hb A₂ >6.0%.

CONCLUSIONS

Increased Hb A₂ level is a useful marker for differentiation of homozygous Hb E with and without α⁰ -thalassemia. This should lead to a significant reduction in number of referral cases of homozygous Hb E for molecular testing of α⁰ -thalassemia in routine practice.

Geophysical imaging reveals topographic stress control of bedrock weathering

Bedrock fracture systems facilitate weathering, allowing fresh mineral surfaces to interact with corrosive waters and biota from Earth's surface, while simultaneously promoting drainage of chemically equilibrated fluids. We show that topographic perturbations to regional stress fields explain bedrock fracture distributions, as revealed by seismic velocity and electrical resistivity surveys from three landscapes. The base of the fracture-rich zone mirrors surface topography where the ratio of horizontal compressive tectonic stresses to near-surface gravitational stresses is relatively large, and it parallels the surface topography where the ratio is relatively small. Three-dimensional stress calculations predict these results, suggesting that tectonic stresses interact with topography to influence bedrock disaggregation, groundwater flow, chemical weathering, and the depth of the "critical zone" in which many biogeochemical processes occur.

Downgrading recent estimates of land available for biofuel production

Recent estimates of additional land available for bioenergy production range from 320 to 1411 million ha. These estimates were generated from four scenarios regarding the types of land suitable for bioenergy production using coarse-resolution inputs of soil productivity, slope, climate, and land cover. In this paper, these maps of land availability were assessed using high-resolution satellite imagery. Samples from these maps were selected and crowdsourcing of Google Earth images was used to determine the type of land cover and the degree of human impact. Based on this sample, a set of rules was formulated to downward adjust the original estimates for each of the four scenarios that were previously used to generate the maps of land availability for bioenergy production. The adjusted land availability estimates range from 56 to 1035 million ha depending upon the scenario and the ruleset used when the sample is corrected for bias. Large forest areas not intended for biofuel production purposes were present in all scenarios. However, these numbers should not be considered as definitive estimates but should be used to highlight the uncertainty in attempting to quantify land availability for biofuel production when using coarse-resolution inputs with implications for further policy development.