We address the problem of inferring road maps from largescale GPS traces that have relatively low resolution and sampling frequency. Unlike past published work that requires high-resolution traces with dense sampling, we focus on situations with coarse granularity data, such as that obtained from thousands of taxis in Shanghai, which transmit their location as seldom as once per minute. Such data sources can be made available inexpensively as byproducts of existing processes, rather than having to drive every road with high-quality GPS instrumentation just for map buildingand having to re-drive roads for periodic updates. Although the challenges in using opportunistic probe data are significant, successful mining algorithms could potentially enable the creation of continuously updated maps at very low cost.In this paper, we compare representative algorithms from two approaches: working with individual reported locations vs. segments between consecutive locations. We assess their trade-offs and effectiveness in both qualitative and quantitative comparisons for regions of Shanghai and Chicago.

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Family farms in populated countries must produce sufficient quantities of food to meet the ever-growing population needs. It is unknown whether innovated farming systems can alleviate this issue. Here, we carried out field experiments in arid northwest China from 2009 to 2012 to determine the response of water use, grain yield, and water use efficiency. We integrated crop intensification via relay-planting and straw mulching in the same system. Straw mulching included stubble standing, straw covering, or straw incorporation to the soil. Results show that wheat and maize relay-planting with straw mulching increased yields by up to 153 % versus monoplanting of maize and wheat. Straw covering approached the highest yield. Relay-planting with stubble standing or straw covering decreased water consumption by 4.6 %. The integrated systems increased water use efficiency by up to 46 % compared to conventional mono-planting maize and wheat.

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