Restoration of micro data of John Lossing Buck's survey and analysis of the inverse relationship between yield and farm size in rural China in the 1930's

A large scale Chinese agricultural survey was conducted at the direction of John Lossing Buck from 1929 through 1933. At the end of the 1990’s, some parts of the original micro data of Buck’s survey were discovered at Nanjing Agricultural University. An international joint study was begun to restore micro data of Buck’s survey and construct parts of the micro database on both the crop yield survey and special expenditure survey. This paper includes a summary of the characteristics of farmlands and cropping patterns in crop yield micro data that covered 2,102 farmers in 20 counties of 9 provinces. In order to test the classical hypothesis of whether or not an inverse relationship between land productivity and cultivated area may be observed in developing countries, a Box-Cox transformation test was conducted for functional forms on five main crops of Buck’s crop yield survey. The result of the test shows that the relationship between land productivity and cultivated areas of wheat and barley is linear and somewhat negative; those of rice, rapeseed, and seed cotton appear to be slightly positive. It can be tentatively concluded that the relationship between cultivated area and land productivity are not the same among crops, and the difference of labor intensity and the level of commercialization of each crop may be strongly related to the existence or non-existence of inverse relationships.

Precision Agriculture without borders: Practical issues and improvements in farmland coverage with aerial vehicles.

This work presents a solution for the aerial coverage of a field by using a fleet of aerial vehicles. The use of Unmanned Aerial Vehicles allows to obtain high resolution mosaics to be used in Precision Agriculture techniques. This report is focus on providing a solution for the full simultaneous coverage problem taking into account restrictions as the required spatial resolution and overlap while maintaining similar light conditions and safety operation of the drones. Results obtained from real field tests are finally reported

A waypoint-based mission planner for a farmland coverage with an aerial robot - a precision farming tool

Remote sensing (RS) with aerial robots is becoming more usual in every day time in Precision Agriculture (PA) practices, do to their advantages over conventional methods. Usually, available commercial platforms providing off-the-shelf waypoint navigation are adopted to perform visual surveys over crop fields, with the purpose to acquire specific image samples. The way in which a waypoint list is computed and dispatched to the aerial robot when mapping non empty agricultural workspaces has not been yet discussed. In this paper we propose an offline mission planner approach that computes an efficient coverage path subject to some constraints by decomposing the environment approximately into cells. Therefore, the aim of this work is contributing with a feasible waypoints-based tool to support PA practices