UASea Toolbox

UASea toolbox ( identifies the optimal flight times in a given day for an efficient UAS survey and the acquisition of reliable aerial imagery in the coastal environment. It gives hourly positive or negative suggestions about the optimal or non-optimal UAS acquisition times to conduct UAS surveys in coastal areas. The suggestions are derived using weather forecast data of weather variables and adaptive thresholds in a ruleset.  The parameters that have been proven to affect the quality of UAS imagery and flight safety have been used as variables in the ruleset. The proposed thresholds are used to exclude inconsistent and outlier values that may affect the quality of the acquired images and the safety of the survey. Considering the above, the ruleset is designed in such a way that outlines the optimal weather conditions, suitable for reliable and accurate data acquisition as well as for efficient short-range flight scheduling.

Web application 

UASea toolbox has been developed as an interactive web application accessible through the internet from modern web browsers. It is designed using HTML and CSS scripts while JavaScript augments the user experience and user interactivity through mouse events (scroll, pan, click, etc). It consists of a Graphical User Interface (GUI) component augmented by an app logic component, both framed and distributed by a web server for public access. GUI is a visual representation of various interactive visual components that allows users to interact with the UASea toolbox and is responsible for data input and output operations. Moreover, JavaScript is also responsible for app logic and calculations as the main core of the UASea toolbox. The app logic component utilizes user data input and asynchronously asks for weather forecast data in JSON format from the weather services, and based on the forecast values, suggests the optimal flight times, suitable for marine applications. The results are presented in tabular format and additional figures for each forecast parameter, using Charts.js.

Weather forecast datasets

To identify the optimal flight times for marine mapping applications, the UASea toolbox uses short-range forecast data. In this context, we use a) Dark Sky (DS) API (Dark Sky by Apple, for two days of forecast data on an hourly basis and b) Open Weather Map (OWM) API (Open Weather Map, five days forecast with three-hour step. Both services provide a limited free-of-charge usage of their APIs; DS allows up to 1,000 free API calls per day and OWM provides 60 calls per minute. The forecast data are provided in lightweight and easy-to-handle JavaScript Object Notation (JSON) file format, on asynchronous API requests. DS API uses a great variety of data sources either globally such as NOAA’s GFS model, German Meteorological Office’s ICON model, or regionally such as NOAA's NAMM available in North America and aggregates them to provide a reliable and accurate forecast for any given location. OWM also uses several data sources such as NOAA GFS, ECMWF ERA, data from weather stations (companies, users, etc.) as well as satellite and weather radar data. Their numerical weather prediction (NWP) model was developed based on machine learning techniques.


A set of mathematical rules based on Logical Conjunction and Set Theory was created using the mentioned ruleset. Every weather variable obtained by the weather APIs constitutes a distinct set namely A for temperature, B for humidity, C for cloud coverage, D for the probability of precipitation, E for wind speed, F for the wave height, and G for sun elevation angle, while each one of the above sets is accompanied by an additional set (A’, B’, C’, D’, E’, F’, G’) which represents the adaptive thresholds. Optimal flight conditions necessitate the intersection between the former and the latter using Equation (1). The results of the equation imply two possible outcomes (0, 1) where 1 indicates optimal flight conditions while 0 stands for non-optimal flight conditions.

(A∩A’) ∧ (B∩B’) ∧ (C∩C’) ∧ (D∩D’) ∧ (E∩E’) ∧ (F∩F’) ∧ (G∩G’)    (1)

UASea screens

Users may navigate to the map element by zooming in/out and panning to the desired location and selecting the study area by clicking the map (a). After clicking the map, a leaflet marker is created that triggers the ‘Adjust Parameters’ panel and button (b). The ‘Adjust Parameters’ panel consists of an HTML form in which users can adjust the parameters and their thresholds and select one of the available weather forecast data providers. By hitting the submit button, the parameter adjustment panel disappears, and the decision panel becomes available at the bottom of the screen. At the top of the decision panel (c), there is a date menu that is used to address the range of the available forecast data, while on the bottom of the decision panel the results of the UASea toolbox are presented in tabular format (d). In the ‘Decisions’ row, the green colour indicates optimal weather conditions, while the red colour stands for non-optimal weather conditions. Finally, a set of figures for each one of the weather parameters is also available through the figures panel (e).


Doukari M., Batsaris M., Papakonstantinou A., Topouzelis K., (2019). “A Protocol for Aerial Survey in Coastal Areas Using UAS”, Remote Sensing. 11(16), 1913;. DOI: 10.3390/rs11161913

Doukari, M.; Katsanevakis, S.; Soulakellis, N.; Topouzelis, K. (2021). The Effect of Environmental Conditions on the Quality of UAS Orthophoto-Maps in the Coastal Environment. ISPRS Int. J. Geo-Inf. 2021, 10, 18. DOI: 10.3390/ijgi10010018