GO AEI - Application of 3D LiDAR and satellite detection technologies in super intensive almond trees
Project information
Títol: Application of 3D LiDAR and satellite detection technologies for the development of a comprehensive model for monitoring and improving productive and economic performance in super-intensive almond trees.
The traditional system of training almond trees, in non irrigated scenarios, has been based on the classic vase, with normally severe pruning and wide planting frames due to the limitation in the availability of water. Currently, with the incorporation of irrigation, new improved plant materials, technology and the use of more fertile and better quality soils, it is possible to propose new productive models, with different systems for driving the plantation and collecting the almond
Among the new productive models, high density plantations stand out, which are possible thanks to the use of rootstocks of moderate or reduced vigor, which combined with new varieties can allow high and early production to be achieved. Unfortunately, there is still a considerable lack of knowledge about the proper management of these new cropping systems, particularly with regard to tree formation and pruning. This lack of knowledge results in an inefficient use of technology and the resources used, therefore reducing the previously mentioned expectations of timeliness and production. That is why it is necessary to dedicate resources to analyze which are the most suitable formations and the most suitable management to manage these crops in the most efficient and sustainable way possible.
Description of the project
The aim of this project is to define and establish a new comprehensive monitoring model for the new super-intensive almond crop, based on new technologies (LiDAR and satellite image analysis) that through the measurement of the leaf canopy and other parameters phenological conditions allow
establish the best management models for the initial formation of the crop and other maintenance strategies during the campaign (winter pruning, green pruning, fertilization, phytosanitary treatments, irrigation needs and use of plant covers) and their dimensioning towards productive surfaces larger In order to achieve this general objective, the following specific objectives are proposed:
- To determine the optimal dimensional parameters of leaf canopy in super-intensive almond plantations (height, width and density) in relation to the early entry into production and its performance.
- Optimizing the management of crop formation (winter pruning and green pruning) and other agricultural modifications that allow reaching the optimal dimensional parameters of the leaf canopy in super-intensive almond plantations.
- Evaluate the effect of different experimental training pruning systems on the development of the leaf canopy of new almond crops in super intensive, and determine the resource needs (manpower, fertilizer and phytosanitary treatments, plant covers, water needs, among others) associated with each pilot test.
- Reduce the use of resources, mainly phytosanitary, through new models of developing the leaf canopy of new super-intensive almond crops.
- Validate the monitoring parameters: leaf canopy (size and density), number of flowers, and percentage of curd, fruits and productive yield, as parameters with significance within the new models, arising from the correlation between two image processing technologies (satellite images and 3D LiDAR sensors).
- Define a comprehensive model for continuous crop monitoring based on the relationship established between the 3D measurements of a mobile ground scanner and satellite imagery.
- Establish a system of priorities in decision-making that will have to be implemented within the integral model of continuous monitoring of super-intensive almond cultivation.
- Carry out a transfer of the integral monitoring model for super-intensive almond cultivation, to validate it (continuous improvement of the model) and make it more robust, with data based on the heterogeneity of different productive plots.
