The application of UAV and photogrammetry for supporting precision agriculture and monitoring environmental problems
Author(s)
Capolupo, Alessandra
Date Issued
June 27, 2016
Type
Doctoral Thesis
Abstract
Currently, the earth surface is damaged by natural disaster and any human activities, that causes seriously problems to the well-being of humans and the balance of our ecosystem. Therefore, in order to conserve the human health and protect the environment, the detection and the monitoring of the environmental problems are necessary. In particular, two different examples of environmental problems are explored. The first is focused on the development of an innovative method for detecting copper contaminated soils while the second is related to the choice of the best statistical method for estimating grassland traits in order to conserve the different grassland ecosystems.
The knowledge of pollutants concentration and distribution should be a priority for the community since they strongly affect the human health. Indeed, the pollutants presented in soils are commonly absorbed by crops that are usually eaten by human. The health problems are different according to the pollutant taken into account (Oliver, 1997; Muchuweti et al., 2006). This problem has been selected because it is one of the most widespread Italian criticality, due to the combination of geogenic and anthropogenic elements (Cicchella et al., 2005). The heterogeneity of Italian territory has generated an extremely diverse and complex situation (Vito et al., 2009), whereby also difficult to detect. Indeed, Campania region, known for the beauty of its territory, is currently involved in the area with more environmental problems since 6 of the 55 sites of national interest (NIPS) have been selected in this area. For this reason, it is essential to develop a new technique able to replace the method commonly used to detect pollutants accumulated in agricultural soils too expensive and time consumive. Thus, in the present work, approaches commonly applied in other research sectors and at other scales have been merged and transferred to field scale in order to predict copper accumulation in agricultural soils. The proposed technique is based on photogrammetry using UAVs, the indices for predicting wetland and geostatistics. In addition, to validate this method, an experimental field in Trentola Ducenta, in NIPS Agro-Aversano, has been selected as test field. So, in order to know the amount of the pollutants in the soil, the field was sampled using a regular grid of 5*5 m.
By comparing the map of the real distribution of copper and the map of predicted values, it is clear that 5 areas on 7, characterized by a value greater than legal limit, were identified. Consequently, the results of the method appear promising and the information extracted from this method have to be integrated in the sampling activity.
Grassland ecosystem has been selected because it covers 40% of the earth surface and because its features are affected by the geographical position and human activities. Therefore, it is required the development of a new grassland management plans able to integrate the qualitative information, due to farmers experience, with the quantitative data. Thus, the goal of this method is to test the different statistical approaches and identify the most performant approach for predicting the structural and biochemical grassland traits from hyperspectral images acquired by UAVs. Both tested methods show promising results, even if PLSR is the best.
The explored examples show a lot of advantages introduced by photogrammetric technique from UAVs in the field of environmental monitoring and precision agriculture supporting.
Additional information
Dottorato di ricerca in Scienze e tecnologie per la gestione forestale e ambientale
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