A5063489914- Remote Sensing in Agriculture
- Remote Sensing and LiDAR Applications
- Smart Agriculture and AI
- Plant Parasitism and Resistance
- Spectroscopy and Chemometric Analyses
- Land Use and Ecosystem Services
- 3D Surveying and Cultural Heritage
- Horticultural and Viticultural Research
- Plant and soil sciences
- Agronomic Practices and Intercropping Systems
- Remote-Sensing Image Classification
- Weed Control and Herbicide Applications
- Allelopathy and phytotoxic interactions
- Botanical Research and Chemistry
- Plant Pathogens and Fungal Diseases
- Potato Plant Research
- Remote Sensing and Land Use
- Sunflower and Safflower Cultivation
- Biological Control of Invasive Species
- Mediterranean and Iberian flora and fauna
- Environmental and Ecological Studies
- Adaptive optics and wavefront sensing
- Soil Geostatistics and Mapping
- Agricultural and Food Production Studies
- Leaf Properties and Growth Measurement
Instituto de Agricultura Sostenible
2015-2024
Consejo Superior de Investigaciones Científicas
2011-2024
Instituto de Ciencias Agrarias
2018
Centre for Automation and Robotics
2018
National Institute of Astrophysics, Optics and Electronics
2007-2016
National Research Council
2009
Unidades Centrales Científico-Técnicas
2008
Universidad Nacional Autónoma de México
2008
University of Córdoba
2007
Cordoba University
1998
The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series UAV images using six-band multispectral camera (visible near-infrared range) the ultimate objective generating map an experimental...
L ópez ‐G ranados F (2011). Weed detection for site‐specific weed management: mapping and real‐time approaches. Research 51 , 1–11. Summary This work describes the current status of remote proximal (on‐ground) systems management discusses limitations opportunities these technologies. Remote sensing based on multispectral aerial imagery can provide accurate maps, especially at late phenological stages, whereas images from high spatial resolution satellite unmanned vehicles must still be...
A new aerial platform has risen recently for image acquisition, the Unmanned Aerial Vehicle (UAV). This article describes technical specifications and configuration of a UAV used to capture remote images early season site- specific weed management (ESSWM). Image spatial spectral properties required seedling discrimination were also evaluated. Two different sensors, still visible camera six-band multispectral camera, three flight altitudes (30, 60 100 m) tested over naturally infested...
Accurate and timely detection of weeds between within crop rows in the early growth stage is considered one main challenges site-specific weed management (SSWM). In this context, a robust innovative automatic object-based image analysis (OBIA) algorithm was developed on Unmanned Aerial Vehicle (UAV) images to design post-emergence prescription maps. This novel makes major contribution. The OBIA combined Digital Surface Models (DSMs), orthomosaics machine learning techniques (Random Forest,...
The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status crop production. However, these variables are mostly estimated after a time-consuming hard field work applying equations that treat the solids, which produce inconsistent results. As an alternative, this presents innovative procedure for computing 3-dimensional individual tree-rows by two consecutive phases: 1) generation Digital Surface Models...
Feeding the growing global population requires an annual increase in food production. This requirement suggests use of pesticides, which represents unsustainable chemical load for environment. To reduce pesticide input and preserve environment while maintaining necessary level production, efficiency relevant processes must be drastically improved. Within this context, research strived to design, develop, test assess a new generation automatic robotic systems effective weed pest control aimed...
The strategic management of agricultural lands involves crop field monitoring each year. Crop discrimination via remote sensing is a complex task, especially if different crops have similar spectral response and cropping pattern. In such cases, identification could be improved by combining object-based image analysis advanced machine learning methods. this investigation, we evaluated the C4.5 decision tree, logistic regression (LR), support vector (SVM) multilayer perceptron (MLP) neural...
In order to optimize the application of herbicides in weed-crop systems, accurate and timely weed maps crop-field are required. this context, investigation quantified efficacy limitations remote images collected with an unmanned aerial vehicle (UAV) for early detection seedlings. The ability discriminate weeds was significantly affected by imagery spectral (type camera), spatial (flight altitude) temporal (the date study) resolutions. colour-infrared captured at 40 m 50 days after sowing...
This article describes the technical specifications and configuration of a multirotor unmanned aerial vehicle (UAV) to acquire remote images using six-band multispectral sensor. Several flight missions were programmed as follows: three altitudes (60, 80 100 m), two modes (stop cruising modes) ground control point (GCP) settings considered analyze influence these parameters on spatial resolution spectral discrimination orthomosaicked obtained Pix4Dmapper. Moreover, it is also necessary...
Summary Weed monitoring is the first step in any site‐specific weed management programme. A relatively large variety of platforms, cameras, sensors and image analysis procedures are available to detect map presence/abundance at various times spatial scales. Remote sensing from satellites or aircraft can provide accurate maps when images obtained late phenological stages. Cameras located on unmanned aerial vehicles (UAVs) have been shown be adequate for early‐season detection a wide‐row...
Tree pruning is a costly practice with important implications for crop harvest and nutrition, pest disease control, soil protection irrigation strategies. Investigations on tree usually involve tedious on-ground measurements of the primary crown dimensions, which also might generate inconsistent results due to irregular geometry trees. As an alternative intensive field-work, this study shows innovative procedure based combining unmanned aerial vehicle (UAV) technology advanced object-based...
Precision viticulture has arisen in recent years as a new approach grape production. It is based on assessing field spatial variability and implementing site-specific management strategies, which can require georeferenced information of the three dimensional (3D) grapevine canopy structure one input data. The 3D vineyard fields be generated applying photogrammetric techniques to aerial images collected with Unmanned Aerial Vehicles (UAVs), although processing large amount crop data embedded...