The Water Frame Directive dictates that aquatic environments in Denmark have to achieve good ecological status and prevent further reduction of the water quality. The Danish Environmental Law (Miljømålsloven), which legally implements the Water Frame Directive in Denmark, divides the country into major catchment areas. The catchment areas are covered by individual water plans that seek to ensure good ecological quality on a regional basis. (Naturstyrelsen, 2014)
The water plans use chlorophyll a concentrations in evaluation of ecological quality in Danish lakes. Chlorophyll a is dependent on the phosphorus and nitrogen contents, which thus describes the ecological quality.
This study acknowledges the need for monitoring Danish lakes with regard to chlorophyll a-contents. A recent study from Closter, et al., (Upubliceret) establishes a chlorophyll algorithm made from Landsat 8 imagery. The algorithm reaches a coefficient of determination of 47 % (Closter, et al., Upubliceret). The Danish Environmental Law covers lakes larger than five hectares, which pose a challenge when attempting to map the smallest of lakes using the 30x30 m grid that Landsat 8 uses. This challenge leads the argument for discovering a more refined tool for data collection.
Drones are becoming more and more established in monitoring of the Danish environment. It is the goal of this project to test how drones can contribute to monitoring of Danish lakes by establishing a chlorophyll algorithm. The algorithm is based upon pictures shot with a multispectral camera. Data has been gathered from two Danish lakes in near proximity of the city of Silkeborg. Initially the two lakes were chosen due to the assumption that they represented different ecological classes. Through the analyses carried out during the project, however, it has been established that the lakes are classified as moderate and good ecological quality for Hummelsø and Velling Igelsø respectively, during the course of this project.
The lakes have been investigated on three levels specifically through in situ measurements, drone imagery and satellite imagery. It has been the goal to verify the drones’ ability to aptly estimate chlorophyll contents in the two lakes. The verification process has been done utilizing the in situ measurements as the actual state of chlorophyll contents. Satellite imagery was included in order to compare the two methods of remote sensing. Technical issues regarding the drones has left the project with a distinct lack of drone data.
Therefore, the project is mainly focused on how the used methods can be improved and how other methods can contribute to monitoring of the Danish environment, instead of the results representing a short interval of time. In fact, the additional thoughts section of this report deals entirely with recent articles on how drones can be applied in a Danish context.
The projects’ research question cannot solely, be answered by the investigations carried out during the project. Because of this, the additional thoughts section deals with answering the part where the results of this project falls short.
Data gathered using the drones is used to construct a chlorophyll algorithm. The algorithm stems from a regression analysis, which examines the relationship between reflectance from multispectral imagery and in situ measured chlorophyll. The regression analysis reveals a coefficient of determination of 52 % that should, however, not be viewed as completely truthful for lake chlorophyll contents. The algorithm is compared with an established method for determining the relationship between reflectance and measured chlorophyll using Landsat 8 imagery. It is found that the uncertainty of the algorithm established in this project can be ascribed to the lack of a substantial data quantity.
The additional thought section includes methodologies and experiences using drones around the world. In the section it is discussed how the experience with drones can be applied in a Danish context when monitoring aquatic environments.