New sensors benchmark report on Kompsat-3

The following document has been drawn up as a follow up to the Quality Control Record L [i] on the commissioning phase of the Kompsat-3 imagery, planned benchmarking tests as well as the methodology used in the tests. Benchmarking is necessary to be performed in order to estimate the usability of the imagery collected by particular sensor in The Common Agricultural Policy (CAP) image acquisition Campaign. The main requirement that should be fulfilled concerns the planimetric accuracy of the orthoimagery which should not exceed particular thresholds given in VHR Specifications [iii]. The methodologies used in the benchmarking tests were performed based on Guidelines for Best Practice and Quality Checking of Ortho Imagery [ii]. However, in addition the tests were performed according to alternative methodology, described in [i], which differs from the standard one, the GCPs selection/measurement phase i.e. image to image correlation techniques are used.JRC.H.6-Digital Earth and Reference Dat

Digital surface modelling and 3D information extraction from spaceborne very high resolution stereo pairs

This report discusses the potentials of VHR stereo imagery for automatic digital surface modelling (DSM) and 3D information extraction on large metropolitan cities. Stereo images acquired by GeoEye-1 on Dakar and Guatemala City and by WorldView-2 on Panama City, Constitucion (Chile), Kabul, Teheran, Kathmandu and San Salvador were processed following a rigorous photogrammetric approach. The work focusing on evaluating the quality of the DSMs in relation to the image and terrain characteristics and, among the possible DSM’s application, present a solution for buildings height estimation. The size of the datasets, the variety of case studies and the complexity of the scenarios allow to critically analyzing the potentials of VHR stereo imagery for 3D landscape modeling for natural hazards assessment.JRC.G.2-Global security and crisis managemen

Image Simulation in Remote Sensing

Remote sensing is being actively researched in the fields of environment, military and urban planning through technologies such as monitoring of natural climate phenomena on the earth, land cover classification, and object detection. Recently, satellites equipped with observation cameras of various resolutions were launched, and remote sensing images are acquired by various observation methods including cluster satellites. However, the atmospheric and environmental conditions present in the observed scene degrade the quality of images or interrupt the capture of the Earth's surface information. One method to overcome this is by generating synthetic images through image simulation. Synthetic images can be generated by using statistical or knowledge-based models or by using spectral and optic-based models to create a simulated image in place of the unobtained image at a required time. Various proposed methodologies will provide economical utility in the generation of image learning materials and time series data through image simulation. The 6 published articles cover various topics and applications central to Remote sensing image simulation. Although submission to this Special Issue is now closed, the need for further in-depth research and development related to image simulation of High-spatial and spectral resolution, sensor fusion and colorization remains.I would like to take this opportunity to express my most profound appreciation to the MDPI Book staff, the editorial team of Applied Sciences journal, especially Ms. Nimo Lang, the assistant editor of this Special Issue, talented authors, and professional reviewers

An Introduction to the Geostationary-NASA Earth Exchange (GeoNEX) Products: 1. Top-of-Atmosphere Reflectance and Brightness Temperature

GeoNEX is a collaborative project led by scientists from NASA, NOAA, and many other institutes around the world to generate Earth monitoring products using data streams from the latest Geostationary (GEO) sensors including the GOES-16/17 Advanced Baseline Imager (ABI), the Himawari-8/9 Advanced Himawari Imager (AHI), and more. An accurate and consistent product of the Top-Of-Atmosphere (TOA) reflectance and brightness temperature is the starting point in the scientific processing pipeline and has significant influences on the downstream products. This paper describes the main steps and the algorithms in generating the GeoNEX TOA products, starting from the conversion of digital numbers to physical quantities with the latest radiometric calibration information. We implement algorithms to detect and remove residual georegistration uncertainties automatically in both GOES and Himawari L1bdata, adjust the data for topographic relief, estimate the pixelwise data-acquisition time, and accurately calculate the solar illumination angles for each pixel in the domain at every time step. Finally, we reproject the TOA products to a globally tiled common grid in geographic coordinates in order to facilitate intercomparisons and/or synergies between the GeoNEX products and existing Earth observation datasets from polar-orbiting satellites

Which Satellite Image should be used for Mapping

Today, topographical mapping based on satellite images is a standard method. With the large number of very high-resolution optical satellites, it only a question of the Ground Sampling Distance (GSD) and the map scale to be generated. But the classical large-format satellite images are expensive. With the today's variety of the classical small satellites (601kg to 1200kg) to Nano-satellites (1.1kg to 10kg) of 3U (10cm x 10cm x 30cm), various options are available that influence the economic solutions. An overview of the accessible optical satellites is given, with some specific information on the mini-satellites that offer new economical solutions for topographic mapping. Significantly more optical satellites are currently in operation, but their images are used only for military purposes or they are restricted for national use due to lack of image storage and limited download possibilities

Fusion of Interferometric SAR and Photogrammetric Elevation Data

Neurology & clinical neurophysiolog

Geometric Accuracy Assessment of Deimos-2 Panchromatic Stereo Pairs: Sensor Orientation and Digital Surface Model Production

Accurate elevation data, which can be extracted from very high-resolution (VHR) satellite images, are vital for many engineering and land planning applications. In this way, the main goal of this work is to evaluate the capabilities of VHR Deimos-2 panchromatic stereo pairs to obtain digital surface models (DSM) over different land covers (bare soil, urban and agricultural greenhouse areas). As a step prior to extracting the DSM, different orientation models based on refined rational polynomial coefficients (RPC) and a variable number of very accurate ground control points (GCPs) were tested. The best sensor orientation model for Deimos-2 L1B satellite images was the RPC model refined by a first-order polynomial adjustment (RPC1) supported on 12 accurate and evenly spatially distributed GCPs. Regarding the Deimos-2 based DSM, its completeness and vertical accuracy were compared with those obtained from a WorldView-2 panchromatic stereo pair by using exactly the same methodology and semiglobal matching (SGM) algorithm. The Deimos-2 showed worse completeness values (about 6% worse) and vertical accuracy results (RMSEZ 42.4% worse) than those computed from WorldView-2 imagery over the three land covers tested, although only urban areas yielded statistically significant differences (p < 0.05)

Review and critical analysis on digital elevation models

Nowadays, digital elevation model (DEM) acts as an inevitable component in the field of remote sensing and GIS. DEM reflects the physical surface of the earth helps to understand the nature of terrain by means of interpreting the landscape using modern techniques and high-resolution satellite images. To understand and analyze the nature of the terrain, DEM is required in many fields in the improvement of developing the product and decision making, mapping purpose, preparing 3D simulations, estimating river channel and creating contour maps to extract the elevation and so on. DEM in various applications will be useful to replicate the overall importance of the availability of worldwide, consistent, high-quality digital elevation models. The present article represents the overall review of DEMs, its generation, development using various techniques derived from topographic maps and high-resolution satellite images over a decade to present. It is useful to understand the nature of topography, address the practical problems and fix them by applying innovative ideas, upcoming high-resolution satellite images and techniques.Danas, digitalni model uzdizanja (DEM) djeluje kao neizbježna komponenta u području daljinskog istraživanja i GIS-a. DEM reflektira fizičku površinu zemlje pomaže pri razumijevanju prirode terena pomoću tumačenja krajolika pomoću suvremenih tehnika i satelitskih slika visoke razlučivosti. Za razumijevanje i analizu prirode terena, DEM je potreban u mnogim područjima poboljšanja razvoja proizvoda i odlučivanja, svrhe mapiranja, pripreme 3D simulacija, procjene riječnog kanala i stvaranja konturnih karata za izdvajanje visine i tako dalje. DEM u raznim aplikacijama bit će korisno za repliciranje sveukupne važnosti dostupnosti svjetskih, dosljednih i visokokvalitetnih modela digitalnih elevacija. Ovaj članak predstavlja cjelokupni pregled DEM-ova, njegovog stvaranja, razvoja pomoću različitih tehnika izvedenih iz topografskih karata i satelitskih snimaka visoke razlučivosti tijekom desetljeća do danas. Korisno je razumjeti prirodu topografije, rješavati praktične probleme i popraviti ih primjenom inovativnih ideja, nadolazećih satelitskih slika i tehnika visoke razlučivosti