Open AccessGEOMATIC TECHNIQUES APPLIED FOR REMOTE DETERMINATION OF THE HAY QUANTITY IN AGROSILVOPASTORAL SYSTEMS
Author(s) -
L. Copăcean,
L. Cojocariu,
Mihai Simon,
Ionuţ-Dan Zisu,
Cosmin Popescu
Publication year - 2020
Publication title -
present environment and sustainable development
Language(s) - English
Resource type - Journals
eISSN - 2284-7820
pISSN - 1843-5971
DOI - 10.15551/pesd2020142006
Subject(s) - hay , geomatics , geospatial analysis , drone , remote sensing , volume (thermodynamics) , agricultural engineering , computer science , total station , hay fever , environmental science , geography , engineering , agronomy , cartography , allergy , physics , quantum mechanics , biology , immunology , genetics
The paper presents a descriptive model, applicable in agricultural theory and practice, for determining the quantity of alfalfa hay obtained from a land surface, using remote investigations, by geospatial methods and means. The working algorithm was tested in a rural area located in the northern part of Romania, in the Humor Depression, and the data acquisition was made with DJI Phantom 4 Pro - Unmanned Aerial Vehicle equipment. For the automated calculation of the amount of alfalfa hay harvested from a certain surface and stored as haystacks, the following steps were carried out: processing the images acquired with the drone to obtain the point clouds, determining the 3D model of the haystacks, calculating the volume of hay stored in the stacks and converting the volume in quantity of hay/surface. As a result of the measurements and calculations carried out, a quantity of hay of 11.96 tons/ha was obtained, data verified and validated by the researches from the specialized literature. Compared with the agronomic methods, the use of the geomatics techniques, to determine the quantity of hay harvested from an agricultural area, presents a series of practical and economic advantages: they exclude the manual measurements in the field and, therefore, the displacements on extended surfaces; reduce the working time; have high precision because, for the estimation of the haystacks volume, three-dimensional models are used, instead of the traditional mathematical formulas. At the same time, geospatial data is acquired through drone flying, which can be used in other types of analysis. The working algorithm can also be applied to other studied objectives or research topics.