Earth Sensing Imaging Research Articles

Look-up table approach for uncertainty determination for operational vicarious calibration of Earth imaging sensors.

Understanding the uncertainty of a vicarious calibration is essential for any application to Earth imaging sensors. The Radiometric Calibration Network provides SI-traceable spectral top-of-atmosphere (TOA) reflectance from a network of ground sites and uses a look-up table (LUT) approach for uncertainty determination. The uncertainty LUT was derived using Monte Carlo techniques applied to the relevant solar geometry, surface, and atmospheric variables. While surface reflectance is typically the dominant uncertainty source, atmospheric contributions do play an important role, depending upon the exact scenario and conditions. This approach allows knowledge of TOA reflectance uncertainty to within 0.5%.

A Content-Based Image Retrieval Method Using Neural Network-Based Prediction Technique

Satellite images are vital nowadays, and it is used in remote sensing, weather forecasting, monitor day to day national security issues, etc. Due to large capacity, resolution of the earth imaging sensors and image acquisition techniques, image storage, and retrieval of images are becoming a problem nowadays. Images are retrieved using text-based image retrieval that was unable to provide accurate results. Content-based image retrieval (CBIR) for remote information system provides the solution for the retrieval problem. Existing CBIR system based on the low-level feature extraction techniques such as color, shape, and texture remains an open problem. In this research, we proposed and implemented a new fusion technique for extracting the features of the images, based on the hybrid model of the extraction, which includes sparse auto-encoding of gray-level co-occurrence matrix-based features from principal component analysis and discrete wavelet transform derived coefficients, with prediction of information using neural network by applying the fuzzy inference system approach for the classification of the retrieved data. Results obtained from the proposed technique are compared with the existing techniques gray-level co-occurrence matrix, scale invariant feature transform, and speeded up robust features. The experimental results show that the performance of the proposed system is better in terms of accuracy, precision, and error in comparison with previous techniques.

Ultra-portable field transfer radiometer for vicarious calibration of earth imaging sensors

A small portable transfer radiometer has been developed as part of an effort to ensure the quality of upwelling radiance from test sites used for vicarious calibration in the solar reflective. The test sites are used to predict top-of-atmosphere reflectance relying on ground-based measurements of the atmosphere and surface. The portable transfer radiometer is designed for one-person operation for on-site field calibration of instrumentation used to determine ground-leaving radiance. The current work describes the detector- and source-based radiometric calibration of the transfer radiometer highlighting the expected accuracy and SI-traceability. The results indicate differences between the detector-based and source-based results greater than the combined uncertainties of the approaches. Results from recent field deployments of the transfer radiometer using a solar radiation based calibration agree with the source-based laboratory calibration within the combined uncertainties of the methods. The detector-based results show a significant difference to the solar-based calibration. The source-based calibration is used as the basis for a radiance-based calibration of the Landsat-8 Operational Land Imager that agrees with the OLI calibration to within the uncertainties of the methods.

Landsat-8 Sensor Characterization and Calibration

Landsat-8 was launched on 11 February 2013 with two new Earth Imaging sensors to provide a continued data record with the previous Landsats. For Landsat-8, pushbroom technology was adopted, and the reflective bands and thermal bands were split into two instruments. The Operational Land Imager (OLI) is the reflective band sensor and the Thermal Infrared Sensor (TIRS), the thermal. In addition to these fundamental changes, bands were added, spectral bandpasses were refined, dynamic range and data quantization were improved, and numerous other enhancements were implemented. As in previous Landsat missions, the National Aeronautics and Space Administration (NASA) and United States Geological Survey (USGS) cooperated in the development, launch and operation of the Landsat-8 mission. One key aspect of this cooperation was in the characterization and calibration of the instruments and their data. This Special Issue documents the efforts of the joint USGS and NASA calibration team and affiliates to characterize the new sensors and their data for the benefit of the scientific and application users of the Landsat archive. A key scientific use of Landsat data is to assess changes in the land-use and land cover of the Earth’s surface over the now 43-year record. [...]