Unmanned Aerial Vehicles (UAVs) in environmental biology: A Review

Acquiring information about the environment is a key step during each study in the field of environmental biology at different levels, from an individual species to community and biome. However, obtaining information about the environment is frequently difficult because of, for example, the phenological timing, spatial distribution of a species or limited accessibility of a particular area for the field survey. Moreover, remote sensing technology, which enables the observation of the Earth’s surface and is currently very common in environmental research, has many limitations such as insufficient spatial, spectral and temporal resolution and a high cost of data acquisition. Since the 1990s, researchers have been exploring the potential of different types of unmanned aerial vehicles (UAVs) for monitoring Earth’s surface. The present study reviews recent scientific literature dealing with the use of UAV in environmental biology. Amongst numerous papers, short communications and conference abstracts, we selected 110 original studies of how UAVs can be used in environmental biology and which organisms can be studied in this manner. Most of these studies concerned the use of UAV to measure the vegetation parameters such as crown height, volume, number of individuals (14 studies) and quantification of the spatio-temporal dynamics of vegetation changes (12 studies). UAVs were also frequently applied to count birds and mammals, especially those living in the water. Generally, the analytical part of the present study was divided into following sections: (1) detecting, assessing and predicting threats on vegetation, (2) measuring the biophysical parameters of vegetation, (3) quantifying the dynamics of changes in plants and habitats and (4) population and behaviour studies of animals. At the end, we also synthesised all the information showing, amongst others, the advances in environmental biology because of UAV application. Considering that 33% of studies found and included in this review were published in 2017 and 2018, it is expected that the number and variety of applications of UAVs in environmental biology will increase in the future

Potential of remote sensing and open street data for flood mapping in poorly gauged areas: a case study in Gonaives, Haiti

The Hispaniola Island, in the Caribbean tropical zone, is prone to extreme flood events. Floods are caused by tropical springs and hurricanes and may lead to human losses, economical damages, and spreading of waterborne diseases. Flood studies based upon hydrological and hydraulic modelling are hampered by almost complete lack of hydro-meteorological data. Thenceforth, and given the cost and complexity in the organization of field measurement campaigns, the need for exploitation of remote sensing data, and open source data bases. We present here a feasibility study to explore the potential of (i) high-resolution of digital elevation models (DEMs) from remote imagery and (ii) remotely sensed precipitation data, to feed hydrological flow routing and hydraulic flood modelling, applied to the case study of river La Quinte closed to Gonaives (585 km2), Haiti. We studied one recent flood episode, namely hurricane Ike in 2008, when flood maps from remote sensing were available for validation. The atmospheric input given by hourly rainfall was taken from downscaled Tropical Rainfall Measuring Mission (TRMM) daily estimates, and subsequently fed to a semi-distributed DEM-based hydrological model, providing an hourly flood hydrograph. Then, flood modelling using Hydrologic Engineering Center River Analysis System (HEC-RAS 1D, one-dimensional model for unsteady open channel flow) was carried out under different scenarios of available digital elevation models. The DEMs were generated using optical remote sensing satellite WorldView-1 and Shuttle Radar Topography Mission (SRTM), combined with information from an open source database (OpenStreetMap). Observed flood extent and land use have been extracted using Système Pour l’Observation de la Terre-4 (SPOT-4) imagery. The hydraulic model was tuned for floodplain friction against the observed flooded area. We compared different scenarios of flood simulation and the predictive power given by model tuning. Our study provides acceptable results in depicting flooded areas, especially considering the tremendous lack of ground data, and shows the potential of hydrological modelling approach fed by remote sensing information in Haiti, and in similarly data-scarce areas. Our approach may be useful to provide depiction of flooded areas for the purpose of (i) flood design for urban planning under a frequency-driven approach and (ii) forecasting of flooded areas for warning procedures, pending availability of weather forecast with proper lead time

Arctic–CHAMP: A program to study Arctic hydrology and its role in global change

The Arctic constitutes a unique and important environment that is central to the dynamics and evolution of the Earth system. The Arctic water cycle, which controls countless physical, chemical, and biotic processes, is also unique and important. These processes, in turn, regulate the climate, habitat, and natural resources that are of great importance to both native and industrial societies. Comprehensive understanding of water cycling across the Arctic and its linkage to global biogeophysical dynamics is a scientific as well as strategic policy imperative

Arctic–CHAMP: A program to study Arctic hydrology and its role in global change

The Arctic constitutes a unique and important environment that is central to the dynamics and evolution of the Earth system. The Arctic water cycle, which controls countless physical, chemical, and biotic processes, is also unique and important. These processes, in turn, regulate the climate, habitat, and natural resources that are of great importance to both native and industrial societies. Comprehensive understanding of water cycling across the Arctic and its linkage to global biogeophysical dynamics is a scientific as well as strategic policy imperative

Using airborne LiDAR Survey to explore historic-era archaeological landscapes of Montserrat in the eastern Caribbean

This article describes what appears to be the first archaeological application of airborne LiDAR survey to historic-era landscapes in the Caribbean archipelago, on the island of Montserrat. LiDAR is proving invaluable in extending the reach of traditional pedestrian survey into less favorable areas, such as those covered by dense neotropical forest and by ashfall from the past two decades of active eruptions by the Soufrière Hills volcano, and to sites in localities that are inaccessible on account of volcanic dangers. Emphasis is placed on two aspects of the research: first, the importance of ongoing, real-time interaction between the LiDAR analyst and the archaeological team in the field; and second, the advantages of exploiting the full potential of the three-dimensional LiDAR point cloud data for purposes of the visualization of archaeological sites and features

Deep learning in remote sensing: a review

Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields. Shall we embrace deep learning as the key to all? Or, should we resist a 'black-box' solution? There are controversial opinions in the remote sensing community. In this article, we analyze the challenges of using deep learning for remote sensing data analysis, review the recent advances, and provide resources to make deep learning in remote sensing ridiculously simple to start with. More importantly, we advocate remote sensing scientists to bring their expertise into deep learning, and use it as an implicit general model to tackle unprecedented large-scale influential challenges, such as climate change and urbanization.Comment: Accepted for publication IEEE Geoscience and Remote Sensing Magazin