Thermal and multispectral images from Unmanned Aerial Vehicles (UAVs) for water presence detection in temporary streams: first results

2021 ◽  
Author(s):  
Massimo Micieli ◽  
Gianluca Botter ◽  
Giuseppe Mendicino ◽  
Alfonso Senatore
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Near Infrared ◽  
Infrared Band ◽  
Temporary Streams ◽  
Water Index ◽  
Long Wavelength ◽  
Research Activities ◽  
Aerial Vehicles ◽  
Normalized Difference Water Index ◽  
First Results

<p>UAVs (Unmanned Aerial Vehicles) are increasingly used for monitoring river networks with a broad range of purposes. In this contribution, we focus on the use of multispectral sensors, either in the thermal infrared band LWIR (Long-wavelength infrared, 8-15 µm) or in the infrared band NIR (Near-infrared, 0.75-1.4 µm) to map network dynamics in temporary streams. Specifically, we discuss the first results of a set of surveys carried out in 2020 within a small river catchment located in northern Calabria (southern Italy), as part of the research activities of the ERC-funded DyNET project. Preliminary, a rigorous methodology was identified to perform on-site surveys and to process and analyse the acquired images. Experimental results show that the combined use of LWIR and NIR sensors is a suitable solution for detecting water presence in channels characterized by different hydraulic and morphologic conditions. LWIR sensors alone allow one to discriminate water presence only when the thermal contrast with the surrounding environment is high. On the other hand, NIR sensors permit to detect the presence of water in most of the analyzed settings through the estimate of the Normalized Difference Water Index (NDWI). However, NIR sensors can be misled in case of shallow water depth, due to the NIR radiation emitted by the riverbed merging with that of the water. Overall, the study demonstrates that a combined LWIR/NIR approach allows addressing a broader range of conditions. Moreover, the information provided can be further enhanced by combining it with geomorphologic information and basic hydraulic concepts.</p>

scholarly journals Brief Communication "The use of UAV in rock fall emergency scenario"

2014 ◽  
Vol 2 (6) ◽  
pp. 4011-4029 ◽  
Author(s):  
D. Giordan ◽  
A. Manconi ◽  
A. Facello ◽  
M. Baldo ◽  
F. dell'Anese ◽  
...  
Keyword(s):  
Natural Disasters ◽  
Unmanned Aerial Vehicles ◽  
Rock Fall ◽  
Aerial Vehicles ◽  
Emergency Scenario ◽  
Study Results ◽  
First Results ◽  
Emergency Scenarios ◽  
North Western

Abstract. In recent years, the use of Unmanned Aerial Vehicles (UAVs) in operations in civilian/commercial contexts is becoming increasingly common also for the applications concerning the anthropic and natural disasters. In this paper, we present the first results of a research project aimed at defining a possible methodology for the use of micro-UAVs in emergency scenarios relevant to rock fall phenomena. To develop and support the presented method, the case study results relative to a rock fall emergency occurred on 7 March 2014 in the San Germano municipality (north-western Italy) are presented and discussed.

scholarly journals SUAS Based Multispectral Imagery for Monitoring Wetland Inundation and Vegetation

2019 ◽  
Author(s):  
Dustin Dehm ◽  
Richard Becker ◽  
Alexandra Godre
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Correction Method ◽  
Water Levels ◽  
Water Volume ◽  
Unmanned Aerial Systems ◽  
Short Term ◽  
Water Index ◽  
Normalized Difference Water Index

Mapping short-term wetland vegetation and water storage changes is valuable for monitoring the biogeochemical processes of wetland systems. Old Woman Creek National Estuarine Research Reserve is a dynamic freshwater estuary which experiences intermittent changes in water level over the course of a year. Small unmanned aerial systems (sUAS) are useful tools in monitoring changes as they are rapidly deployed, repeatable, and high-resolution. In this study, commercial quadcopters were paired with a red/green/near-infrared MAPIR Survey 3W camera to produce normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) maps to observe short-term changes at OWC. Orthomosaics were produced for flights on 8 days throughout 2018 and early 2019. The orthomosaics were calibrated to bottom-of-atmosphere reflectance using the Empirical Line Correction method, after which NDVI and NDWI maps were created. The NDVI maps allowed vegetation extent and density changes over time and for National Estuarine Reserve System (NERRS) Classification Codes to be applied to zones of interest. NDWI provided water extent at different water levels and when paired with LiDAR and bathymetric data yielded water volume and residence time estimates.

scholarly journals Measuring Landscape Albedo Using Unmanned Aerial Vehicles

2018 ◽  
Vol 10 (11) ◽  
pp. 1812 ◽  
Author(s):  
Chang Cao ◽  
Xuhui Lee ◽  
Joseph Muhlhausen ◽  
Laurent Bonneau ◽  
Jiaping Xu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Surface Albedo ◽  
Near Infrared ◽  
Surface Energy Balance ◽  
Landsat Image ◽  
Local Climate ◽  
Clear Sky ◽  
Aerial Vehicles ◽  
Albedo Change ◽  
Sky Conditions

Surface albedo is a critical parameter in surface energy balance, and albedo change is an important driver of changes in local climate. In this study, we developed a workflow for landscape albedo estimation using images acquired with a consumer-grade camera on board unmanned aerial vehicles (UAVs). Flight experiments were conducted at two sites in Connecticut, USA and the UAV-derived albedo was compared with the albedo obtained from a Landsat image acquired at about the same time as the UAV experiments. We find that the UAV estimate of the visibleband albedo of an urban playground (0.037 ± 0.063, mean ± standard deviation of pixel values) under clear sky conditions agrees reasonably well with the estimates based on the Landsat image (0.047 ± 0.012). However, because the cameras could only measure reflectance in three visible bands (blue, green, and red), the agreement is poor for shortwave albedo. We suggest that the deployment of a camera that is capable of detecting reflectance at a near-infrared waveband should improve the accuracy of the shortwave albedo estimation.

scholarly journals Overview of the Development of the Maritime Search and Rescue System in Croatia

2019 ◽  
Vol 31 (2) ◽  
pp. 205-212
Author(s):  
Dario Medić ◽  
Anita Gudelj ◽  
Natalija Kavran
Keyword(s):  
Response Time ◽  
Unmanned Aerial Vehicles ◽  
Search And Rescue ◽  
Future Research ◽  
Search System ◽  
International Convention ◽  
Research Activities ◽  
Aerial Vehicles ◽  
Rescue System ◽  
Maritime Search And Rescue

According to the Convention for the Safety of Life at Sea and International Convention on Maritime Search and Rescue, saving human lives at sea is the duty of all signatory states. This paper analyzes and gives an overview of previous research activities in search and rescue system at sea and how the use of unmanned aerial vehicles (UAV) can improve search and rescue actions at sea. Research activities include development of the search system and placement of resources that are used in search and rescue actions (ships, planes etc.). Previous research is mainly related to minimizing response time when accidents at sea are detected in relation to search and rescue missions. Implementation of unmanned aerial vehicles into the search and rescue system enables improvement of these actions due to earlier detection and verification of accidents at sea and prevents unnecessary search and rescue units engagement in cases when an accident did not occur. The results of previous research point to the fact that future research should aim to explore the synthesis of unmanned aerial vehicles with the existing search and rescue system at sea in Croatia.

scholarly journals Brief Communication: The use of an unmanned aerial vehicle in a rockfall emergency scenario

2015 ◽  
Vol 15 (1) ◽  
pp. 163-169 ◽  
Author(s):  
D. Giordan ◽  
A. Manconi ◽  
A. Facello ◽  
M. Baldo ◽  
F. dell'Anese ◽  
...  
Keyword(s):  
Natural Disasters ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Research Project ◽  
Aerial Vehicles ◽  
Emergency Scenario ◽  
First Results ◽  
Aerial Vehicle ◽  
Emergency Scenarios ◽  
North Western

Abstract. In recent years, the use of unmanned aerial vehicles (UAVs) in civilian/commercial contexts are becoming increasingly common, as well as for applications concerning anthropic and natural disasters. In this paper, we present the first results of a research project aimed at defining a possible methodology for the use of micro-UAVs in emergency scenarios relevant to rockfall phenomena. To develop and support the method presented herein, the results relevant to a rockfall emergency occurred on 7 March 2014 in the San Germano municipality (north-western Italy) are presented and discussed.

scholarly journals Fusarium Wilt of Radish Detection Using RGB and Near Infrared Images from Unmanned Aerial Vehicles

2020 ◽  
Vol 12 (17) ◽  
pp. 2863 ◽  
Author(s):  
L. Minh Dang ◽  
Hanxiang Wang ◽  
Yanfen Li ◽  
Kyungbok Min ◽  
Jin Tae Kwak ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Fusarium Wilt ◽  
Near Infrared ◽  
Wilt Disease ◽  
Pollinator Decline ◽  
Main Research ◽  
Aerial Vehicles ◽  
Segmented Images ◽  
Rgb Images ◽  
Side Dishes

The radish is a delicious, healthy vegetable and an important ingredient to many side dishes and main recipes. However, climate change, pollinator decline, and especially Fusarium wilt cause a significant reduction in the cultivation area and the quality of the radish yield. Previous studies on plant disease identification have relied heavily on extracting features manually from images, which is time-consuming and inefficient. In addition to Red-Green-Blue (RGB) images, the development of near-infrared (NIR) sensors has enabled a more effective way to monitor the diseases and evaluate plant health based on multispectral imagery. Thus, this study compares two distinct approaches in detecting radish wilt using RGB images and NIR images taken by unmanned aerial vehicles (UAV). The main research contributions include (1) a high-resolution RGB and NIR radish field dataset captured by drone from low to high altitudes, which can serve several research purposes; (2) implementation of a superpixel segmentation method to segment captured radish field images into separated segments; (3) a customized deep learning-based radish identification framework for the extracted segmented images, which achieved remarkable performance in terms of accuracy and robustness with the highest accuracy of 96%; (4) the proposal for a disease severity analysis that can detect different stages of the wilt disease; (5) showing that the approach based on NIR images is more straightforward and effective in detecting wilt disease than the learning approach based on the RGB dataset.

scholarly journals A Method for Reflectance Index Wavelength Selection from Moisture-Controlled Soil and Crop Residue Samples

2017 ◽  
Vol 60 (5) ◽  
pp. 1479-1487 ◽  
Author(s):  
Ali Hamidisepehr ◽  
Michael P. Sama ◽  
Aaron P. Turner ◽  
Ole O. Wendroth
Keyword(s):  
Remote Sensing ◽  
Moisture Content ◽  
Near Infrared ◽  
Statistical Significance ◽  
Coefficient Of Determination ◽  
Near Infrared Reflectance ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Agricultural Materials ◽  
Reflectance Measurements

Abstract. Reflectance indices are a method for reducing the dimensionality of spectral measurements used to quantify material properties. Choosing the optimal wavelengths for developing an index based on a given material and property of interest is made difficult by the large number of wavelengths typically available to choose from and the lack of homogeneity when remotely sensing agricultural materials. This study aimed to determine the feasibility of using a low-cost method for sensing the moisture content of background materials in traditional crop remote sensing. Moisture-controlled soil and wheat stalk residue samples were measured at varying heights using a reflectance probe connected to visible and near-infrared spectrometers. A program was written that used reflectance data to determine the optimal pair of narrowband wavelengths to calculate a normalized difference water index (NDWI). Wavelengths were selected to maximize the slope of the linear index function (i.e., sensitivity to moisture) and either maximize the coefficient of determination (R2) or minimize the root mean squared error (RMSE) of the index. Results showed that wavelengths centered near 1300 nm and 1500 nm, within the range of 400 to 1700 nm, produced the best index for individual samples. Probe height above samples and moisture content were examined for statistical significance using the selected wavelengths. The effect of moisture was significant for both bare soil and wheat stalks, but probe height was only significant for wheat stalk samples. The index, when applied to all samples, performed well for soil samples but poorly for wheat stalk samples. Index calculations from soil reflectance measurements were highly linear (R2 > 0.95) and exhibited small variability between samples at a given moisture content, regardless of probe height. Index calculations from wheat stalk reflectance measurements were highly variable, which limited the usefulness of the index for this material. Based on these results, it is expected that crop residues, such as wheat stalks, will reduce the accuracy of remotely sensed soil surface moisture measurements. Keywords: Near-infrared reflectance, Normalized difference water index, Remote sensing, Soil moisture, Spectroscopy.

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