A contour matching approach for accurate NOAA-AVHRR image navigation

Although different methods for NOAA AVHRR image navigation have already been established, the multitemporal and multi-satellite character of most studies requires automatic and accurate methods for navigation of satellite images. In the proposed method, a simple Kepplerian orbital model for the NOAA satellites is considered as reference model, and mean orbital elements are given as input to the model from ephemeris data. In order to correct the errors caused by these simplifications, errors resulting from inaccuracies in the positioning of the satellite and failures in the satellite internal clock, an automatic global contour matching approach has been adopted. First, the sensed image is preprocessed to obtain a gradient energy map of the reliable areas (sea-land contours) using a cloud detection algorithm and a morphological gradient operator. An initial estimation of the reliable contour positions is automatically obtained. The final positions of the contours are obtained by means of an iterative local minimization procedure that allows a contour to converge on an area of high image energy (edge). Global transformation parameters are estimated based on the initial and final positions of all reliable contour points. Finally, the performance of this approach is assessed using NOAA 14 AVHRR images from different geographic areas.Postprint (published version

Accurate and automatic NOAA-AVHRR image navigation using a global contour matching approach

The problem of precise and automatic AVHRR image navigation is tractable in theory, but has proved to be somewhat difficult in practice. The authors' work has been motivated by the need for a fully automatic and operational navigation system capable of geo-referencing NOAA-AVHRR images with high accuracy and without operator supervision. The proposed method is based on the simultaneous use of an orbital model and a contour matching approach. This last process, relying on an affine transformation model, is used to correct the errors caused by inaccuracies in orbit modeling, nonzero value for the spacecraft's roll, pitch and yaw, errors due to inaccuracies in the satellite positioning and failures in the satellite internal clock. The automatic global contour matching process is summarized as follows: i) Estimation of the gradient energy map (edges) in the sensed image and detection of the cloudless (reliable) areas in this map. ii) Initialization of the affine model parameters by minimizing the Euclidean distance between the reference and sensed images objects. iii) Simultaneous optimization of all reference image contours on the sensed image by energy minimization in the domain of the global transformation parameters. The process is iterated in a hierarchical way, reducing the parameter searching space at each iteration. The proposed image navigation algorithm has proved to be capable of geo-referencing a satellite image within 1 pixel.Peer ReviewedPostprint (published version

Komponenta projekta ADRICOSM – sustav promatranja na velikoj skali – satelitski sustav

In the framework of the ADRICOSM project, the Satellite Oceanography Group (GOS) of Rome developed a Fast Delivery System (FDS) for providing the partner modeling centres with remotelysensed ocean colour and sea surface temperature (SST) data. Data are processed, mapped and binned on the Adriatic Sea area in order to be assimilated into both ecosystem models and circulation models for ocean forecasting. Further technological improvements permitted the building and optimization of a system suitable for meeting the increasing demand for near-real-time ocean colour and SST products for applications in operational oceanography. Real-Time Images of SeaWiFS chlorophyll concentration, clouds/case I/case II water flags and true colour images are obtained by processing the satellite passes using climatological ancillary data. These images are provided daily through an ad hoc automatic system that processes the raw satellite data and makes it available on the web within an hour of satellite overpass acquisition. All of the images are stored in a gallery web archive organized in a calendar chart. Accurate chlorophyll maps for assimilation are produced in near real time (typically after 4 days) as soon as daily meteorological ancillary data are made available on the NASA website. Each chlorophyll map is flagged for clouds or other contamination factors using the corresponding 24 quality flag maps. This implies that case-2 waters and spurious atmospheric effects have been removed from the pigment data set. This final product is binned on the Adriatic model grid and made available for the ADRICOSM project on the GOS web site. NOAA/AVHRR data are also acquired by the GOS ground station in Rome and managed by the FDS from their reception up to their distribution. Daily SST maps of the Adriatic Sea binned over the AREG model grid at 1/16° resolution are distributed weekly in Near-Real-Time along with the daily SST maps of the eastern Mediterranean Sea delivered at 1/8° resolution to the MFSTEP project. Real-Time SST maps of the Adriatic Sea at 1km resolution are posted daily in GIF format on the GOS website.U okviru projekta ADRISOSM, GOS (Grupa za satelitsku oceanografiju) iz Rima razvila je Sustav za brzu isporuku FDS, snabdijevanje partnerskih centara za modeliranje satelitskim snimcima boje mora i tem-peraturnim podacima površine mora (SST). Podaci za Jadran su obrađeni, pretvoreni u grafičke produkte i digitalizirani kako bi se mogli asimilirati u model strujanja i model ekosistema, te koristiti oceanografskoj prognozi. Daljnja tehnološka poboljšanja su omogućila izgradnju i optimalizaciju sustava, zbog rastućih potreba za produktima boje mora i površinske temperature za različite primjene u operativnoj oceanografiji. Slike koncentracije klorofila od senzora SeaWiFS, slike oblaka te Case1 i Case2 oznake, kao i slike prave boje dobivaju se procesiranjem satelitskih scena uz popratne klimatološke podatke. Slike se procesiraju dnevno kroz ad-hoc automatski sustav koji obrađuje sirove satelitske podatke i omogućuje njihovu isporuku na mrežu, sat vremena nakon prikupljanja satelitskih podataka tj. nakon prolaska satelita. Sve se slike spremaju u arihvu na mreži koja je organizirana prema datumima. Korigirane slike koncentracije klorofila za asimilaciju u model proizvode se u skoro realnom vremenu (tipično 4 dana kasnije) čim se dobiju popratni meteorološki podaci s mreže NASA-e. Na svakoj slici klorofila su označeni oblaci ili drugi kontaminirajući faktori, prema 24 kategorije kvalitete slika. To znači da su Case 2 slučajevi piksela uklonjeni iz snimaka kao i atmosferske sme-tnje. Konačni produkt se usklađuje s koordinatnom mrežom Jadrana i stavlja na raspolaganje na stranicama ADRICOSM-a preko GOS-ove Internet stranice. GOS zemaljska stanica u Rimu prikuplja i podatke NOAA/ AVHRR koji se procesiraju kroz FDS sustav, od prijema do konačne distribucije podataka. Dnevne se slike površinske temperature mora (SST), usklađene preko koordinatne mreže AREG-a pri prostornom razlučivanju od 1/16 stupnja, distribuiraju tjedno u skoro realnom vremenu, zajedno sa slikama istočnog Sredozemlja koje imaju razlučivanje od 1/8 stupnja prema MFSTEP projektu. Dnevno, u skoro realnom vremenu, isporučuju se slike SST za Jadran uz prostorno razlučivanje od 1 km u GIF formatu na Internet stranici GOS-a

Study of spacecraft direct readout meteorological systems

Characteristics are defined of the next generation direct readout meteorological satellite system with particular application to Tiros N. Both space and ground systems are included. The recommended space system is composed of four geosynchronous satellites and two low altitude satellites in sun-synchronous orbit. The goesynchronous satellites transmit to direct readout ground stations via a shared S-band link, relayed FOFAX satellite cloud cover pictures (visible and infrared) and weather charts (WEFAX). Basic sensor data is transmitted to regional Data Utilization Stations via the same S-band link. Basic sensor data consists of 0.5 n.m. sub-point resolution data in the 0.55 - 0.7 micron spectral region, and 4.0 n.m. resolution data in the 10.5 - 12.6 micron spectral region. The two low altitude satellites in sun-synchronous orbit provide data to direct readout ground stations via a 137 MHz link, a 400 Mhz link, and an S-band link

Monsoon Flooding Response: a Multi-scale Approach to Water-extent Change Detection

This paper has the aim of illustrating an automatic and speditive way for retrieving inundation extent from multispectral and multitemporal satellite data, together with land-cover changes caused by flooding events, which is a fundamental issue for managing a reconstruction plan after the event. A straightforward method to map inundated areas was applied in the North-Eastern region of Bangladesh, heavily struck by monsoonal rains in September 2000. This method in based on the Principal Components Transform (PCT) of multispectral satellite data, in its Spectral-Temporal implementation, followed by logical filtering and image segmentation, in order to reach the needed coherency of the results. The use of multiresolution data (28.5-meters ground resolution Landsat-7/ETM+ and 1,100-meters ground resolution NOAA-14/AVHRR) makes possible to evaluate hazard affected areas at different scales. Comparison to RADARSAT-derived water extension maps assessed an Overall Accuracy between 86.4% (for the flood map derived with NOAA-14/AVHRR data over the whole Bangladesh) and 90.6% (for the flood map derived with Landsat-7/ETM+ data over the North-East part of the country)

Near Real Time Processing of NOAA AVHRR Satellite Data

This thesis describes near real time processing of NOAA AVHRR satellite raw data which includes automatic geocoding approach followed by cloud masking techniques and sea surface temperature extraction algorithm implemented over South China Sea. For geocoding of the images an orbital model has been used followed by Earth location determination algorithms. Different models have been implemented based on radiative transfer equations for extracting sea surface temperature fro m satellite data, namely single channel, split-window, spatiotemporal split-window technique and multichannel sea surface temperature. There are five cloud masking techn iques namely gross cloud check, spatial coherence method, dynamic visible and near infrared method, ratio of near infrared reflectance to visible reflectance and channel difference method have been implemented. The accuracy of the geocoding is within 2-10 km. Sea surface temperature from satellite data has been compared with ground truth data and standard deviation for sea surface temperature is within 0.1 - 0.75 degree Celsius. The cloud masking techniques are capable to produce non contaminated pixels in the imagery. All the works have been carried out by customization of EASI/PACE environment of PCI software and the developed techniques are fully automatic in nature. These developments can be used for fish forecasting and monitoring of oil spill over Malaysian sea water

Estimation of Evapotranspiration Using Advanced Very Idgh Resolution Radiometer (Avhrr) Data

Biosystems Engineerin