Imaging IKONOS Research Articles

IMPLEMENTASI METODE MARR-HILDERTH OPERATOR UNTUK MENDETEKSI TEPI CITRA IKONOS

Ikonos imagery is a satellite image that has high spatial resolution with an accuracy of one meter pixels for panchromatic and four meters to multispektral. Ikonos imagery is often used to map the process, view, measure and memoniotring areas of work/activities on the Earth. Ikonos image of Government also often use it for things like national security evaluation against the occurrence of the disaster, city planning, mineral exploration and mine planning monitoring of agriculture, and others. Image digital imaging results over long distances using satellite is often there are disturbances in the form of light distortion, noise or other distractions that cause the object on the image less obvious or obscure. This discussion on the research being done is knowing the process of detection on image by calculating the difference between two dots are bertetanggan, and is in the process of smoothing and thresholding on image ikonos. The methods used in this research is a method of Marr-Hilderth. In addition, a process that is done on this research is conducting a testing method against Marr-Hilderth, which can be implemented to fix the blurry objects on images ikonos. The results of this research is to generate image ikonos with display clear object with the menerapakan method of the Marr-Hilderth and tested using the matlab application version 7.8 (r2009a).Keywords: Ikonos image, image processing, method of Marr-Hilderth, Matlab 7.8

Radiometric characterization of IKONOS multispectral imagery

A radiometric characterization of Space Imaging's IKONOS 4-m multispectral imagery has been performed by a National Aeronautics and Space Administration (NASA) funded team from NASA Stennis Space Center, the University of Arizona Remote Sensing Group (U of A RSG), and South Dakota State University (SDSU). Both intrinsic radiometry and the effects of Space Imaging processing on radiometry were investigated. Relative radiometry was examined with uniform Antarctic and Saharan sites. Absolute radiometric calibration was performed using reflectance-based vicarious calibration methods on several uniform sites imaged by IKONOS coincident with ground-based surface and atmospheric measurements. Ground-based data and the IKONOS spectral response function served as input to radiative transfer codes to generate a top-of-atmosphere (TOA) radiance estimate. Calibration coefficients derived from each vicarious calibration were combined to generate an IKONOS radiometric gain coefficient for each multispectral band assuming a linear response over the full dynamic range of the instrument. These calibration coefficients were made available to Space Imaging, which subsequently adopted them by updating its initial set of calibration coefficients. IKONOS imagery procured through the NASA Scientific Data Purchase was processed with or without a Modulation Transfer Function Compensation (MTFC) kernel. The radiometric effects of this kernel on various scene types were also investigated.

The Joint Agency Commercial Imagery Evaluation team: overview and IKONOS joint characterization approach

The Joint Agency Commercial Imagery Evaluation (JACIE) team was formed to leverage government agencies' capabilities for the characterization of commercial remote sensing data. The team is composed of staff from the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA), and the U.S. Geological Survey (USGS). Each JACIE agency has a vested interest in the purchase and use of commercial imagery to support its research and applications. It is critical that this imagery be assessed for its accuracy and utility. Through JACIE, NASA, NIMA, and USGS jointly characterized image products from Space Imaging's IKONOS satellite. The JACIE team acquired IKONOS imagery of several study sites to perform the assessments. Each JACIE agency performed an aspect of the characterization according to its area of expertise. NASA and its university partners performed a system characterization focusing on radiometric calibration, geopositional accuracy, and spatial resolution assessment; NIMA performed image interpretability and feature extraction evaluations; and the USGS assessed the geopositional accuracy of several IKONOS products. The results of the JACIE team's IKONOS effort, which were discussed with Space Imaging and then presented at an industry–government workshop, ensured and improved overall product quality and benefited both the commercial industry and the government. Additional JACIE activities include the characterization of other commercial products such as those from the DigitalGlobe QuickBird and the Orbital Imaging (Orbimage) OrbView-3 satellites.

Empirical comparison of Landsat 7 and IKONOS multispectral measurements for selected Earth Observation System (EOS) validation sites

The Space Imaging IKONOS observatory may provide an important benefit in terrestrial scientific research. The five-band, 1 m panchromatic and 4 m multispectral measurements have the potential to provide a source of measurements to evaluate subpixel land cover variability in measurements from observatories such as Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Terra MODIS sensor. The IKONOS observations are at a spatial scale equivalent to field measurements typically carried out in ecological and land cover research. As such, the IKONOS observations may serve as a source of “virtual” ground measurements, for the lower spatial resolution, global observatories. In this study we examine how well IKONOS sensor observations replicate Landsat 7 ETM+ visible/near infrared observations for selected Earth Observation System (EOS) validation sites in the United States. The sites examined—Beltsville, MD, Konza Prairie, KS, and Sevilleta, NM—sample the east–west moisture gradient across the United States. Observations for each site were acquired, as nearly time-coincident as possible, from ETM+ and the IKONOS sensor, several times over the growing season. This was done to insure that we compared these two sensors over the widest range of observing conditions possible. We also examined IKONOS imagery from Phoenix, AZ, where Space Imaging had and had not applied a modulation transfer function compensation (MTFC) process. The MTFC is their standard product. We found that this product, at the original 4 m spatial resolution, appears to have minor radiometric artifacts as a result of the process. When the IKONOS observations were aggregated to 30 m, this problem was essentially absent, allowing us to proceed with the remainder of our study. We processed the IKONOS sensor and ETM+ measurements to produce close approximates of each other. Our processing steps included ortho-rectification, calibration to planetary reflectance, pixel alignment and pixel aggregation. We initially found radiometric differences between the two sensors that increased with increasing wavelength. Space Imaging updated their calibration information, based on analyses from NASA Stennis Space Center staff, which removed much of this discrepancy. We now find that the IKONOS red and near infrared measurements differ between the two sensors, with IKONOS generally producing higher reflectance in the red band and lower reflectance in the near infrared band than the Landsat 7 ETM+ sensor. This results in the IKONOS sensor producing lower spectral vegetation index measurements, for the same target, than ETM+, a measurement variation that has been observed between other sensors. We also encountered far more cirrus cloud (and shadow) contamination in these paired observations that we had expected. After careful initial selection, we lost over half of our image pairs from the analysis because of cirrus cloud contamination. We do not know whether this is simply because of the paired, comparative design of this study or whether it relates to the increased spatial and radiometric resolution of the IKONOS sensor. The results of this study not only provide a baseline assessment of IKONOS versus Landsat 7 ETM+ visible and near infrared measurements but also suggest some of the issues that need more attention when comparing other sensor systems as well as developing the design of future land observatories.

Acquisition of earth science remote sensing observations from commercial sources: lessons learned from the Space Imaging IKONOS example

Over the last decade, NASA and other federal agencies have been increasingly encouraged to explore commercial sources of land remote sensing data rather than pursuing government-funded sources of these measurements (prior to U.S. Commercial Executive, 2003. U.S. Commercial Remote Sensing Policy. White House, Washington, DC). The science and applications users have been skeptical of this move to commercial sources of observations both because of uncertainty over the capabilities of the private sector and the unsatisfactory outcomes of previous efforts to commercialize satellite-acquired land remote sensing observations. In an effort to more fully explore the potential of commercial remotely sensed land data sources, the NASA Earth Science Enterprise (ESE) implemented an experimental Scientific Data Purchase (SDP) that solicited bids from the private sector to meet ESE-user data needs. The SDP activity spanned nearly 5 years and supplied many US and international researchers with sources of land remote sensing observations that had not been previously available. The images from the Space Imaging IKONOS system provided a particularly good match to the current ESE missions such as Terra and Landsat 7 and therefore serve as focal point in this analysis. Throughout the SDP process, there have been many lessons learned concerning interactions between US industry, government agencies and the science user community. The specifics of the Space Imaging IKONOS experience under the NASA SDP are most valuable with respect to possible future uses of commercial vendors to supply NASA ESE user needs for space-acquired land observations. Areas where valuable lessons were learned included the technical, scientific, proprietary and management aspects of the interactions. As this activity has evolved, user confidence in the technical and scientific qualities of the IKONOS measurements has increased substantially. There are still areas where further progress could be achieved, with respect to proprietary and management aspects of scientific commercial data buys. To date, the NASA scientific and applications users who have examined the IKONOS imagery have found the data to be of high quality, providing substantial value to their specific pursuits. They have found that the novel attributes of IKONOS, particularly in the spatiotemporal domain have introduced new analysis challenges not previously experienced with EOS sensors such as Landsat and MODIS. The technical qualities of the observations have been substantially improved during the SDP activity as a result of independent validation and verification by the Joint Agency Commercial Imagery Evaluation (JACIE) of the IKONOS observations. The experience gained from the Space Imaging IKONOS SDP activity, suggests that US private sector is technically capable of meeting the needs of NASA ESE science and application users. The future success of such interactions between industry, government and users appears to be far more dependent on the organizational and legal aspects of such arrangements than technical capabilities of the data providers.

Cross comparison of eo-1 sensors and other earth resources sensors to landsat-7 etm+ using railroad valley playa

The Remote Sensing Group at the University of Arizona has used ground-based test sites for the vicarious calibration of airborne and satellite-based sensors, of which the Railroad Valley Playa in north central Nevada has played a key role. This work presents a cross comparison of five satellite-based sensors that all imaged this playa on July 16, 2001. These sensors include the Advanced Land Imager and Hyperion on the Earth Observer-1 platform, the Landsat-7 Enhanced Thematic Mapper Plus (ETM+), Terra's Moderate Resolution Imaging Spectroradiometer, and Space Imaging's Ikonos. The approach atmospherically corrects the ETM+ data to derive surface reflectance for a 1 km /spl times/ 1 km area of the playa and then uses these reflectances to determine a hyperspectral at-sensor radiance for each of the sensors taking into account the changes in solar zenith angle due to any temporal differences in the overpass times as well as differences in the view angles between the sensors. Results show that all of the sensors agree with ETM+ to within 10% in the solar reflective for bands not affected by atmospheric absorption. ETM+, MODIS, and ALI agree in all bands to better than 4.4% with better agreement in the visible and near infrared. Poorer agreement between Hyperion and other sensors appears to be due partially to poorer signal to noise ratio in the narrowband Hyperion datasets.

Satellite image collection optimization

Imaging satellite systems represent a high capital cost. Optimizing the collection of images is critical for both satisfying customer orders and building a sustainable satellite operations business. We describe the functions of an operational, multivariable, time dynamic optimization system that maximizes the daily collection of satellite images. A graphical user interface allows the operator to quickly see the results of what if adjustments to an image collection plan. Used for both long range planning and daily collection scheduling of Space Imaging's IKONOS satellite, the satellite control and tasking (SCT) software allows collection commands to be altered up to 10 min before upload to the satellite.

Geopositioning Accuracy of Ikonos Imagery: Indications from Two Dimensional Transformations

Earth observation satellites with 1m resolution, such as Space Imaging's Ikonos system, offer the photogrammetric and remote sensing communities a significant new means for geospatial information collection. These satellites possess the potential for pixel‐level geopositioning precision and promise timely, highly automated generation of two dimensional (2D) and three dimensional (3D) spatial information products. This paper concentrates on the pursuit of optimal accuracy and considers an essential first step in the evaluation of the Ikonos imaging system, namely the metric integrity of the sensor system. In the absence of sensor calibration information (the camera model), an empirical evaluation approach has been adopted. This involves an assessment of 2D transformations between image and planar object space. It is shown that based on results obtained in the Melbourne Ikonos Testfield, 2D geopositioning to 0.5 m accuracy is possible from the base‐level “Geo”product when a modest amount of good quality ground control is available and sub‐pixel image mensuration is achieved. These findings are applicable to both near‐nadir imagery and oblique stereo images. Moreover, the results obtained suggest that there are no significant geometric perturbations in the sensor system and initial image processing, which augurs well for the successful application of non‐collinearity based 3D orientation and triangulation models for Ikonos imagery.