Calibration of the Thermal Infrared Sensor on the Landsat Data Continuity Mission

The Landsat series of satellites provides the longest running continuous data set of moderate-spatial-resolution imagery beginning with the launch of Landsat 1 in 1972 and continuing with the 1999 launch of Landsat 7 and current operation of Landsats 5 and 7. The Landsat Data Continuity Mission (LDCM) will continue this program into a fourth decade providing data that are keys to understanding changes in land-use changes and resource management. LDCM consists of a two-sensor platform comprised of the Operational Land Imager (OLI) and Thermal Infrared Sensors (TIRS). A description of the applications and design of the TIRS instrument is given as well as the plans for calibration and characterization. Included are early results from preflight calibration and a description of the inflight validation

Applications of ISES for vegetation and land use

Remote sensing relative to applications involving vegetation cover and land use is reviewed to consider the potential benefits to the Earth Observing System (Eos) of a proposed Information Sciences Experiment System (ISES). The ISES concept has been proposed as an onboard experiment and computational resource to support advanced experiments and demonstrations in the information and earth sciences. Embedded in the concept is potential for relieving the data glut problem, enhancing capabilities to meet real-time needs of data users and in-situ researchers, and introducing emerging technology to Eos as the technology matures. These potential benefits are examined in the context of state-of-the-art research activities in image/data processing and management

Report of Optical Radiometric Instruments and Calibration Panel

Measurement and accuracy needs for remote sensing are analyzed. Topics discussed include: (1) in orbit performance degradation due to contamination; (2) increased radiometric accuracy required for detecting small changes over long periods of time in environmental parameters; (3) references for verifying calibration in orbit; (4) high attenuation neutral density filters; (5) the sun as a radiation source for testing; (6) rejection of stray light; (7) development of spectrally flat detectors for flight sensors; and (8) long term stability of sensor components

Landsat Program

Landsat initiated the revolution in moderate resolution Earth remote sensing in the 1970s. With seven successful missions over 40+ years, Landsat has documented - and continues to document - the global Earth land surface and its evolution. The Landsat missions and sensors have evolved along with the technology from a demonstration project in the analog world of visual interpretation to an operational mission in the digital world, with incremental improvements along the way in terms of spectral, spatial, radiometric and geometric performance as well as acquisition strategy, data availability, and products

Downscaling landsat land surface temperature over the urban area of Florence

A new downscaling algorithm for land surface temperature (LST) images retrieved from Landsat Thematic Mapper (TM) was developed over the city of Florence and the results assessed against a high-resolution aerial image. The Landsat TM thermal band has a spatial resolution of 120 m, resampled at 30 m by the US Geological Survey (USGS) agency, whilst the airborne ground spatial resolution was 1 m. Substantial differences between Landsat USGS and airborne thermal data were observed on a 30 m grid: therefore a new statistical downscaling method at 30 m was developed. The overall root mean square error with respect to aircraft data improved from 3.3 °C (USGS) to 3.0 °C with the new method, that also showed better results with respect to other regressive downscaling techniques frequently used in literature. Such improvements can be ascribed to the selection of independent variables capable of representing the heterogeneous urban landscape

HIRIS (High-Resolution Imaging Spectrometer: Science opportunities for the 1990s. Earth observing system. Volume 2C: Instrument panel report

The high-resolution imaging spectrometer (HIRIS) is an Earth Observing System (EOS) sensor developed for high spatial and spectral resolution. It can acquire more information in the 0.4 to 2.5 micrometer spectral region than any other sensor yet envisioned. Its capability for critical sampling at high spatial resolution makes it an ideal complement to the MODIS (moderate-resolution imaging spectrometer) and HMMR (high-resolution multifrequency microwave radiometer), lower resolution sensors designed for repetitive coverage. With HIRIS it is possible to observe transient processes in a multistage remote sensing strategy for Earth observations on a global scale. The objectives, science requirements, and current sensor design of the HIRIS are discussed along with the synergism of the sensor with other EOS instruments and data handling and processing requirements

An Evaluation of Unmanned Aerial System Multispectral and Thermal Infrared Data as Information for Agricultural Crop and Irrigation Management

Spatial irrigation management has been steadily advancing over the last several years. A current issue with managing irrigation spatially on sub-field scale is the inability to readily collect the spatial field data necessary to properly manage irrigation. Multispectral and thermal infrared imagery used in informing irrigation management decisions was previously collected by satellite and manned aircraft remote sensing platforms. These remote sensing platforms pose issues concerning economic feasibility, revisit intervals, and weather factors that inhibit the collection of data. Recent developments in unmanned aerial systems, which provide an additional means of collecting multispectral and thermal infrared data, have the potential to provide supplemental data during periods of missing satellite data or to completely replace satellite and manned aircraft remote sensing platforms. As unmanned aerial system remote sensing platforms are a relatively new technology, there are uncertainties regarding how these systems compare to previous and more well-known remote sensing platforms. Some of these uncertainties include how to properly collect, process, and calibrate data acquired by these systems so that the end products are accurate and can by used in scientific applications. This work evaluated two different unmanned aerial systems with integrated multispectral and thermal infrared cameras to determine the best methods of collecting, processing, and calibrating data. Three different multispectral image calibration methods were evaluated and compared against Landsat satellite reflectance products and ground-based reflectance tarps. The thermal infrared image calibration consisted of correcting for emissivity and atmospheric effects, and was compared to in-field infrared thermometers. Relationships for estimating maize leaf area index, crop height, and fraction of vegetation cover were redefined and evaluated based on various vegetation indices derived from the unmanned aerial system calibrated multispectral imagery. This work also addressed some of the challenges and obstacles related to deploying unmanned aerial systems for remote sensing in agricultural applications. Advisors: Wayne E. Woldt and Christopher M.U. Neal

Overview of Intercalibration of Satellite Instruments

Intercalibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be interoperable, the instruments must be cross-calibrated. To meet the stringent needs of such applications, instruments must provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d’unités traceable calibration and validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stabilitymonitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Intercalibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Intercalibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated intercalibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms of change. This paper summarizes the state-of-the-art of postlaunch radiometric calibration of remote sensing satellite instruments through intercalibration

Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors

This paper provides a summary of the current equations and rescaling factors for converting calibrated Digital Numbers (DNs) to absolute units of at-sensor spectral radiance, Top-Of- Atmosphere (TOA) reflectance, and at-sensor brightness temperature. It tabulates the necessary constants for the Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Advanced Land Imager (ALI) sensors. These conversions provide a basis for standardized comparison of data in a single scene or between images acquired on different dates or by different sensors. This paper forms a needed guide for Landsat data users who now have access to the entire Landsat archive at no cost