Synthetic aperture radar and optical remote sensing image fusion for flood monitoring in the Vietnam lower Mekong basin: a prototype application for the Vietnam Open Data Cube

Flood monitoring systems are crucial for flood management and consequence mitigation in flood prone regions. Different remote sensing techniques are increasingly used for this purpose. However, the different approaches suffer various limitations, including cloud and weather effects (optical data), and low spatial resolution and poor colour presentation (synthetic aperture radar data). This study fuses two data types (Landsat and Sentinel-1) to overcome these limitations and produce better quality images for a prototype flood application in the Vietnam Open Data Cube (VODC). Visual and quantitative evaluation of fused image quality revealed improvement in the images compared with the original scenes. Ground-truth data was used to develop the study flood extraction algorithm and we found a good agreement between our results and SERVIR Mekong (a joint initiative by the US agency for International Development (USAID), National Aeronautics and Space Administration (NASA), Myanmar, Thailand, Cambodia, Laos and Vietnam) maps. While the algorithm is run on a personal computer (PC), it has a clear potential to be developed for application on a big data system

Mobile Laser Scanning accuracy assessment for the purpose of base-map updating

The aim of the research was to analyze the possibility of using mobile laser scanning systems to acquire information for production and/or updating of a basic map and to propose a no-reference index of this accuracy assessment. Point clouds have been analyzed in terms of content of interpretation and geometric potential. For this purpose, the accuracy of point clouds with a georeference assigned to the base map objects was examined. In order to conduct reference measurements, a geodetic network was designed and also additional static laser scanning data has been used. The analysis of mobile laser scanning (MLS) data accuracy was conducted with the use of 395 check points. In the paper, application of the total Error of Position of the base-map Objects acquired with the use of MLS was proposed. Research results were related to reference total station measurements. The resulting error values indicate the possibility to use an MLS point cloud in order to accurately determine coordinates for individual objects for the purposes of standard surveying studies, e.g. for updating some elements of the base map content. Nevertheless, acquiring MLS point clouds with satisfying accuracy not always is possible, unless specific resolution condition is fulfilled. The paper presents results of accuracy evaluation in different classes of base-map elements and objects

ASSESMENT OF THE INFLUENCE OF UAV IMAGE QUALITY ON THE ORTHOPHOTO PRODUCTION

Over the past years a noticeable increase of interest in using Unmanned Aerial Vehicles (UAV) for acquiring low altitude images has been observed. This method creates new possibilities of using geodata captured from low altitudes to generate large scale orthophotos. Because of comparatively low costs, UAV aerial surveying systems find many applications in photogrammetry and remote sensing. One of the most significant problems with automation of processing of image data acquired with this method is its low accuracy. This paper presents the following stages of acquisition and processing of images collected in various weather and lighting conditions: aerotriangulation, generating of Digital Terrain Models (DTMs), orthorectification and mosaicking. In the research a compact, non-metric camera, mounted on a fuselage powered by an electric motor was used. The tested area covered flat, agricultural and woodland terrains. Aerotriangulation and point cloud accuracy as well as generated digital terrain model and mosaic exactness were examined. Dense multiple image matching was used as a benchmark. The processing and analysis were carried out with INPHO UASMaster programme. Based on performed accuracy analysis it was stated that images acquired in poor weather conditions (cloudy, precipitation) degrade the final quality and accuracy of a photogrammetric product by an average of 25%

ANALYSIS OF THE POSSIBILITIES OF USING LOW-COST SCANNING SYSTEM IN 3D MODELING

The laser scanning technique is still a very popular and fast growing method of obtaining information on modeling 3D objects. The use of low-cost miniature scanners creates new opportunities for small objects of 3D modeling based on point clouds acquired from the scan. The same, the development of accuracy and methods of automatic processing of this data type is noticeable. The article presents methods of collecting raw datasets in the form of a point-cloud using a low-cost ground-based laser scanner FabScan. As part of the research work 3D scanner from an open source FabLab project was constructed. In addition, the results for the analysis of the geometry of the point clouds obtained by using a low-cost laser scanner were presented. Also, some analysis of collecting data of different structures (made of various materials such as: glass, wood, paper, gum, plastic, plaster, ceramics, stoneware clay etc. and of different shapes: oval and similar to oval and prism shaped) have been done. The article presents two methods used for analysis: the first one - visual (general comparison between the 3D model and the real object) and the second one - comparative method (comparison between measurements on models and scanned objects using the mean error of a single sample of observations). The analysis showed, that the low-budget ground-based laser scanner FabScan has difficulties with collecting data of non-oval objects. Items built of glass painted black also caused problems for the scanner. In addition, the more details scanned object contains, the lower the accuracy of the collected point-cloud is. Nevertheless, the accuracy of collected data (using oval-straight shaped objects) is satisfactory. The accuracy, in this case, fluctuates between ± 0,4 mm and ± 1,0 mm whereas when using more detailed objects or a rectangular shaped prism the accuracy is much more lower, between 2,9 mm and ± 9,0 mm. Finally, the publication presents the possibility (for the future expansion of research) of modernization FabScan by the implementation of a larger amount of camera-laser units. This will enable spots the registration , that are less visible

INTEGRATION OF POINT CLOUDS AND IMAGES ACQUIRED FROM A LOW-COST NIR CAMERA SENSOR FOR CULTURAL HERITAGE PURPOSES

Terrestrial Laser Scanning is currently one of the most common techniques for modelling and documenting structures of cultural heritage. However, only geometric information on its own, without the addition of imagery data is insufficient when formulating a precise statement about the status of studies structure, for feature extraction or indicating the sites to be restored. Therefore, the Authors propose the integration of spatial data from terrestrial laser scanning with imaging data from low-cost cameras. The use of images from low-cost cameras makes it possible to limit the costs needed to complete such a study, and thus, increasing the possibility of intensifying the frequency of photographing and monitoring of the given structure. As a result, the analysed cultural heritage structures can be monitored more closely and in more detail, meaning that the technical documentation concerning this structure is also more precise. To supplement the laser scanning information, the Authors propose using both images taken both in the near-infrared range and in the visible range. This choice is motivated by the fact that not all important features of historical structures are always visible RGB, but they can be identified in NIR imagery, which, with the additional merging with a three-dimensional point cloud, gives full spatial information about the cultural heritage structure in question. The Authors proposed an algorithm that automates the process of integrating NIR images with a point cloud using parameters, which had been calculated during the transformation of RGB images. A number of conditions affecting the accuracy of the texturing had been studies, in particular, the impact of the geometry of the distribution of adjustment points and their amount on the accuracy of the integration process, the correlation between the intensity value and the error on specific points using images in different ranges of the electromagnetic spectrum and the selection of the optimal method of transforming the acquired imagery. As a result of the research, an innovative solution was achieved, giving high accuracy results and taking into account a number of factors important in the creation of the documentation of historical structures. In addition, thanks to the designed algorithm, the final result can be obtained in a very short time at a high level of automation, in relation to similar types of studies, meaning that it would be possible to obtain a significant data set for further analyses and more detailed monitoring of the state of the historical structures

CALIBRATION OF LOW COST RGB AND NIR UAV CAMERAS

Non-metric digital cameras are being widely used for photogrammetric studies. The increase in resolution and quality of images obtained by non-metric cameras, allows to use it in low-cost UAV and terrestrial photogrammetry. Imagery acquired with non-metric cameras can be used in 3D modeling of objects or landscapes, reconstructing of historical sites, generating digital elevation models (DTM), orthophotos, or in the assessment of accidents. Non-metric digital camcorders are characterized by instability and ignorance of the interior orientation parameters. Therefore, the use of these devices requires prior calibration. Calibration research was conducted using non-metric camera, different calibration tests and various software. The first part of the paper contains a brief theoretical introduction including the basic definitions, like the construction of non-metric cameras or description of different optical distortions. The second part of the paper contains cameras calibration process, details of the calibration methods and models that have been used. Sony Nex 5 camera calibration has been done using software: Image Master Calib, Matlab - Camera Calibrator application and Agisoft Lens. For the study 2D test fields has been used. As a part of the research a comparative analysis of the results have been done

SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8

The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands). Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5‐0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of Landsat 8 with data from the new high resolution panchromatic EROS B satellite are analyzed. The range of panchromatic band for EROS B is 0.4‐0.9 μm and spatial resolution is 0.7 m. Research relied on improving the spatial resolution of natural color band combinations (bands: 4,3,2) and of desired false color band composition of Landsat 8 satellite imagery. For this purpose, six algorithms have been tested: Brovey’s, Mulitplicative, PCA, IHS, Ehler's, HPF. On the basis of the visual assessment, it was concluded that the best results of multispectral and panchromatic image integration, regardless land cover, are obtained for the multiplicative method. These conclusions were confirmed by statistical analysis using correlation coefficient, ERGAS and R-RMSE indicators

Examining the possibility of correcting imagery acquired for the purpose of obtaining spectral reflectance coefficients in the infrared range using photometric measurements

The purpose of this paper is to determine the possibility of using photometric measurements in order to correct imagery acquired in the 900–1700 nm range. This imagery is acquired for the purpose of acquiring spectral reflectance coefficients in variable lighting conditions. This paper will present a series of experiments, the problems encountered and obtained results. The main aim of this research was to determine a link between these two quantities (luminance and irradiance) in order to be able to eliminate the need of using such a spectroradiometer (a large, heavy and costly instrument) when acquiring spectral reflectance data from a XEVA XS-1.7.320 camera mounted on an UAV without using a reference panel

Pre-processing of Xeva-XS imagery for determining spectral reflectance coefficients in laboratory conditions

There are two different methodologies which can be used to acquire imagery from which it would be possible to obtain spectral reflectance characteristics – the first based on images of a scene in which a reference panel had been included, and the second based on precisely selected exposure parameters. This paper is concerned with the first of these two methods based on experiments conducted using a 14bit XEVA XS-1.7.320 infrared sensor. The paper firstly describes the effect of different exposure settings on the accuracy with which we can later determine the spectral reflectance coefficients. The next step when working with such imagery in laboratory conditions is to eliminate the effect of the uneven distribution of illumination. In the paper we present two proposed methods for eliminating the uneven distribution of illumination – an additive method and a quotient method. After that it is essential to stretch the DN values. Once again we investigated two possible methods of doing this – firstly, by stretching the data using only the white reference panel, adjusting the maxDN value of the image of the surface of the reference panel to 95%. The second method additionally adds a second reference point – a black reference panel which reflects 5% of incident radiation. The spectral reflectance coefficients of chosen samples acquired using all of the above mentioned methods are compared with reference data obtained using a spectroradiometer. Establishing the most optimal methodologies will greatly increase the accuracy of obtained spectral response coefficients, which at the same time will increase the accuracy with which, in this case, water pollutants will be identified

CHOSEN ASPECTS OF THE PRODUCTION OF THE BASIC MAP USING UAV IMAGERY

For several years there has been an increasing interest in the use of unmanned aerial vehicles in acquiring image data from a low altitude. Considering the cost-effectiveness of the flight time of UAVs vs. conventional airplanes, the use of the former is advantageous when generating large scale accurate ortophotos. Through the development of UAV imagery, we can update large-scale basic maps. These maps are cartographic products which are used for registration, economic, and strategic planning. On the basis of these maps other cartographic maps are produced, for example maps used building planning. The article presents an assessesment of the usefulness of orthophotos based on UAV imagery to upgrade the basic map. In the research a compact, non-metric camera, mounted on a fixed wing powered by an electric motor was used. The tested area covered flat, agricultural and woodland terrains. The processing and analysis of orthorectification were carried out with the INPHO UASMaster programme. Due to the effect of UAV instability on low-altitude imagery, the use of non-metric digital cameras and the low-accuracy GPS-INS sensors, the geometry of images is visibly lower were compared to conventional digital aerial photos (large values of phi and kappa angles). Therefore, typically, low-altitude images require large along- and across-track direction overlap – usually above 70 %. As a result of the research orthoimages were obtained with a resolution of 0.06 meters and a horizontal accuracy of 0.10m. Digitized basic maps were used as the reference data. The accuracy of orthoimages vs. basic maps was estimated based on the study and on the available reference sources. As a result, it was found that the geometric accuracy and interpretative advantages of the final orthoimages allow the updating of basic maps. It is estimated that such an update of basic maps based on UAV imagery reduces processing time by approx. 40%