Establishment of Parameterized Models for Estimation of the Possible Presence of Pollution and Soil Disease Using Drones

Project Details

Description

General objective Generate parameterized models through precision agriculture with geospatial technologies that determine the possible presence of contamination and soil diseases through the application of drones Justification Through research related to soil loss issues for agriculture, the same ones that are highly susceptible to being contaminated by anthropogenic activities, for the same reason it is intended to carry out a mathematical model that allows us to determine the quality of the soil of the areas affected by interrelated variables such as Nitrogen concentration, among other measurable soil parameters and different spectral indices such as the Normalized Vegetation Index (NDVI) (Variable generated by multispectral cameras) and thermography of the sector. Multispectral cameras, being highly technological equipment, allow us to know the state of health or growth of crops, the detection of diseases or pests, the estimation of fertilizers, vegetation index, among others; The adequate and correct use of this technology allows us to reduce costs and risks when exploring or monitoring several hectares of land. One of the main objectives of the research is to generate an empirical parameterized model that determines the possible presence of contamination and soil diseases through of the drone application. For which we will proceed to collect information in the field and correlate it with the information obtained from the drone to determine the mathematical formula that allows us to relate variables that the soils present in the areas to be studied and allow us to understand the state of the soil. The project will be generated during 12 months with the main objective of being able to expand it to the following years with greater detection of other possible contaminants.
StatusFinished
Effective start/end date8/03/198/03/19

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.