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Results for “Journal of Remote Sensing”

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At least 109 records · Page 6Linked to original sources
USGS2007

Monitoring flooding in coastal wetlands by using radar imagery and ground-based measurements

Satellite radar was used in a Florida Juncus roemerianus marsh to map tidal flooding, a critical control of coastal vegetation distribution. Radar images taken during a time of near-continuous recordings of ground-based hydrology measurements directly linked marsh flooding to lowered radar returns and indicated a negative covariation between flood frequency and radar return. Flood-extent contours extracted from the radar images and calibrated with point depth measurements showed marsh elevation could be estimated to about 8 cm compared to the 150 cm topographic contours currently available.

International Journal of Remote Sensing↗
USGS2007

Characteristics of the 1 km AVHRR data set for North America

The North America portion of a new global 1 km AVHRR time-series dataset was produced recently by the U.S. Geological Survey, EROS Data Center. Characteristics of the dataset were evaluated for scan-angle distribution, image area distortion as the result of map projection, distribution of high solar zenith angle, and cloud presence in image composites produced using maximum values of normalized difference vegetation index (NDVI). The evaluation showed that the compositing procedure exhibits a bias favouring off-nadir pixels, particularly at post-nadir (forward scanning) positions in the winter months. Results for scan angle distribution and image area distortion provide a basis for calculating the data's effective minimum mapping area for various geographical locations. The amount of missing data due to large solar zenith angle effect varies from 42 per cent in January to 1 per cent in July. Cloud contaminated pixels estimated for the thirty-six 10-day composites range from 7??5 per cent in May to 1??6 per cent in November. Recompositing the North America data set from 10-day cycles to monthly cycles can effectively reduce the amount of cloudy pixels in the data.

International Journal of Remote Sensing↗
USGS2007

Compression of the Global Land 1-km AVHRR dataset

Large datasets, such as the Global Land 1-km Advanced Very High Resolution Radiometer (AVHRR) Data Set (Eidenshink and Faundeen 1994), require compression methods that provide efficient storage and quick access to portions of the data. A method of lossless compression is described that provides multiresolution decompression within geographic subwindows of multi-spectral, global, 1-km, AVHRR images. The compression algorithm segments each image into blocks and compresses each block in a hierarchical format. Users can access the data by specifying either a geographic subwindow or the whole image and a resolution (1,2,4, 8, or 16 km). The Global Land 1-km AVHRR data are presented in the Interrupted Goode's Homolosine map projection. These images contain masked regions for non-land areas which comprise 80 per cent of the image. A quadtree algorithm is used to compress the masked regions. The compressed region data are stored separately from the compressed land data. Results show that the masked regions compress to 0·143 per cent of the bytes they occupy in the test image and the land areas are compressed to 33·2 per cent of their original size. The entire image is compressed hierarchically to 6·72 per cent of the original image size, reducing the data from 9·05 gigabytes to 623 megabytes. These results are compared to the first order entropy of the residual image produced with lossless Joint Photographic Experts Group predictors. Compression results are also given for Lempel-Ziv-Welch (LZW) and LZ77, the algorithms used by UNIX compress and GZIP respectively. In addition to providing multiresolution decompression of geographic subwindows of the data, the hierarchical approach and the use of quadtrees for storing the masked regions gives a marked improvement over these popular methods.

International Journal of Remote Sensing↗
USGS2007

Estimating the effective spatial resolution of an AVHRR time series

A method is proposed to estimate the spatial degradation of geometrically rectified AVHRR data resulting from misregistration and off-nadir viewing, and to infer the cumulative effect of these degradations over time. Misregistrations are measured using high resolution imagery as a geometric reference, and pixel sizes are computed directly from satellite zenith angles. The influence or neighbouring features on a nominal 1 km by 1 km pixel over a given site is estimated from the above information, and expressed as a spatial distribution whose spatial frequency response is used to define an effective field-of-view (EFOV) for a time series. In a demonstration of the technique applied to images from the Conterminous U.S. AVHRR data set, an EFOV of 3·1km in the east-west dimension and 19 km in the north-south dimension was estimated for a time series accumulated over a grasslands test site.

International Journal of Remote Sensing↗
USGS2010

The IGBP-DIS global 1 km land cover data set, DISCover: First results

The International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) is co-ordinating the development of global land data sets from Advanced Very High Resolution Radiometer (AVHRR) data. The first is a 1 km spatial resolution land cover product 'DISCover', based on monthly Normalized Difference Vegetation Index composites from 1992 and 1993. DISCover is a 17 class land cover dataset based on the science requirements of IGBP elements. Mapping uses unsupervised classification with post-classification refinement using ancillary data. Draft Africa, North America and South America products are now available for peer review.

International Journal of Remote Sensing↗
USGS2010

Surface phenology and satellite sensor-derived onset of greenness: An initial comparison

The objective of this work was to document the utility of phenological data derived from satellite sensors by comparing them with modelled phenology. Surface phenological model outputs (first leaf and first bloom dates) were correlated positively with satellite sensor-derived start of season (SOS) dates for 1991-1995 across the eastern United States. The correlation was highest for forest (r 0.62 for deciduous trees and 0.64 for mixed woodland) and tall grass (r 0.46) and lowest for short grass (r 0.37). The average correlation over all land cover types was 0.61. Average SOS dates were consistently earlier than Spring Index dates across all land cover types. This finding and limited native tree phenology data suggest that the SOS technique detects understorey green-up in the forest rather than overstorey species. The biweekly temporal resolution of the satellite sensor data placed an upper limit on prediction accuracy; thus, year-to-year variations at individual sites were typically small. Nevertheless, the correct biweek SOS could be identified from the surface models 61% of the time, and 1 biweek 96% of the time. Further temporal refinement of the satellite sensor measurements is necessary in order to connect them with surface phenology adequately and to develop links among 'green wave' components in selected biomes.

International Journal of Remote Sensing↗
USGS2010

Exploring the correlation between Southern Africa NDVI and Pacific sea surface temperatures: Results for the 1998 maize growing season

Several studies have identified statistically significant correlations between Pacific sea surface temperature anomalies and NDVI anomalies in Southern Africa. The potential predictive value of the relationship was explored for the 1998 maize growing season. Cross-validation techniques suggested a more useful relationship for regions of wet anomaly than for regions of dry anomaly. Observed 1998 NDVI anomaly patterns were consistent with this result. Wet anomalies were observed as expected, but wide areas of expected dry anomalies exhibited average or above-average greeness.

International Journal of Remote Sensing↗
USGS2007

A whole image approach using field measurements for transforming EO1 Hyperion hyperspectral data into canopy reflectance spectra

To maximize the spectral distinctiveness (information) of the canopy reflectance, an atmospheric correction strategy was implemented to provide accurate estimates of the intrinsic reflectance from the Earth Observing 1 (EO1) satellite Hyperion sensor signal. In rendering the canopy reflectance, an estimate of optical depth derived from a measurement of downwelling irradiance was used to drive a radiative transfer simulation of atmospheric scattering and attenuation. During the atmospheric model simulation, the input whole-terrain background reflectance estimate was changed to minimize the differences between the model predicted and the observed canopy reflectance spectra at 34 sites. Lacking appropriate spectrally invariant scene targets, inclusion of the field and predicted comparison maximized the model accuracy and, thereby, the detail and precision in the canopy reflectance necessary to detect low percentage occurrences of invasive plants. After accounting for artifacts surrounding prominent absorption features from about 400nm to 1000nm, the atmospheric adjustment strategy correctly explained 99% of the observed canopy reflectance spectra variance. Separately, model simulation explained an average of 88%??9% of the observed variance in the visible and 98% ?? 1% in the near-infrared wavelengths. In the 34 model simulations, maximum differences between the observed and predicted reflectances were typically less than ?? 1% in the visible; however, maximum reflectance differences higher than ?? 1.6% (<??2.3%) at more than a few wavelengths were observed at three sites. In the near-infrared wavelengths, maximum reflectance differences remained less than ??3% for 68% of the comparisons (??1 standard deviation) and less than ??6% for 95% of the comparisons (??2 standard deviation). Higher reflectance differences in the visible and near-infrared wavelengths were most likely associated with problems in the comparison, not in the model generation. ?? 2005 US Government.

International Journal of Remote Sensing↗
USGS2014

Landsat TM memory effect characterization and correction

Before radiometric calibration of Landsat Thematic Mapper (TM) data can be done accurately, it is necessary to minimize the effects of artifacts present in the data that originate in the instrument's signal processing path. These artifacts have been observed in downlinked image data since shortly after launch of Landsat 4 and 5. However, no comprehensive work has been done to characterize all the artifacts and develop methods for their correction. In this paper, the most problematic artifact is discussed: memory effect (ME). Characterization of this artifact is presented, including the parameters necessary for its correction. In addition, a correction algorithm is described that removes the artifact from TM imagery. It will be shown that this artifact causes significant radiometry errors, but the effect can be removed in a straightforward manner.

Canadian Journal of Remote Sensing↗
USGS2013

Classification of freshwater ice conditions on the Alaskan Arctic Coastal Plain using ground penetrating radar and TerraSAR-X satellite data

Arctic freshwater ecosystems have responded rapidly to climatic changes over the last half century. Lakes and rivers are experiencing a thinning of the seasonal ice cover, which may increase potential over-wintering freshwater habitat, winter water supply for industrial withdrawal, and permafrost degradation. Here, we combined the use of ground penetrating radar (GPR) and high-resolution (HR) spotlight TerraSAR-X (TSX) satellite data (1.25 m resolution) to identify and characterize floating ice and grounded ice conditions in lakes, ponds, beaded stream pools, and an alluvial river channel. Classified ice conditions from the GPR and the TSX data showed excellent agreement: 90.6% for a predominantly floating ice lake, 99.7% for a grounded ice lake, 79.0% for a beaded stream course, and 92.1% for the alluvial river channel. A GIS-based analysis of 890 surface water features larger than 0.01 ha showed that 42% of the total surface water area potentially provided over-wintering habitat during the 2012/2013 winter. Lakes accounted for 89% of this area, whereas the alluvial river channel accounted for 10% and ponds and beaded stream pools each accounted for <1%. Identification of smaller landscape features such as beaded stream pools may be important because of their distribution and role in connecting other water bodies on the landscape. These findings advance techniques for detecting and knowledge associated with potential winter habitat distribution for fish and invertebrates at the local scale in a region of the Arctic with increasing stressors related to climate and land use change.

Alaska↗
USGS2018

Sentinel-2A MSI and Landsat-8 OLI radiometric cross comparison over desert sites

The Sentinel-2A and Landsat-8 satellites carry on-board moderate resolution multispectral imagers for the purpose of documenting the Earth’s changing surface. Though they are independently built and managed, users will certainly take advantage of the opportunity to have higher temporal coverage by combining the datasets. Thus it is important for the radiometric and geometric calibration of the MultiSpectral Instrument (MSI) and the Operational Land Imager (OLI) to be compatible. Cross-calibration of MSI to OLI has been accomplished using multiple techniques involving the use of pseudo-invariant calibration sites (PICS) using direct comparisons as well as through use of PICS models predicting top-of-atmosphere reflectance. A team from the University of Arizona is acquiring field data under both instruments for vicarious calibration of the sensors. This paper shows that the work done to date by the Landsat and Sentinel-2 calibration teams has resulted in stable radiometric calibration for each instrument and consistency to ~2.5% between the instruments for all the spectral bands that the instruments have in common.

European Journal of Remote Sensing↗
USGS2009

An automated imagery orthorectification pilot

Automated orthorectification of raw image products is now possible based on the comprehensive metadata collected by Global Positioning Systems and Inertial Measurement Unit technology aboard aircraft and satellite digital imaging systems, and based on emerging pattern-matching and automated image-to-image and control point selection capabilities in many advanced image processing systems. Automated orthorectification of standard aerial photography is also possible if a camera calibration report and sufficient metadata is available. Orthorectification of historical imagery, for which only limited metadata was available, was also attempted and found to require some user input, creating a semi-automated process that still has significant potential to reduce processing time and expense for the conversion of archival historical imagery into geospatially enabled, digital formats, facilitating preservation and utilization of a vast archive of historical imagery. Over 90 percent of the frames of historical aerial photos used in this experiment were successfully orthorectified to the accuracy of the USGS 100K base map series utilized for the geospatial reference of the archive. The accuracy standard for the 100K series maps is approximately 167 feet (51 meters). The main problems associated with orthorectification failure were cloud cover, shadow and historical landscape change which confused automated image-to-image matching processes. Further research is recommended to optimize automated orthorectification methods and enable broad operational use, especially as related to historical imagery archives.

Journal of Remote Sensing↗
USGS2023

National Land Cover Database 2019: A comprehensive strategy for creating the 1986-2019 forest disturbance product

The National Land Cover Database (NLCD) 2016 products show that, between 2001 and 2016, nearly half of the land cover change in the conterminous United States (CONUS) involved forested areas. To ensure the quality of NLCD land cover and land cover change products, it is important to accurately detect the location and time of forest disturbance. We designed a comprehensive strategy to integrate a continuous time series forest change detection method and a discrete 2-date forest change detection method to produce the NLCD 1986–2019 forest disturbance product, which shows the most recent forest disturbance date between the years 1986 and 2019 for every 2- to 3-year interval. This method, the Time-Series method Using Normalized Spectral Distance (NSD) index (TSUN), uses NSD to detect multi-date forest land cover changes and was shown to be easily extended to a new date even when new images were processed in a different way than previous date images. The discrete 2-date method uses the Multi-Index Integrated Change Analysis (MIICA) method to detect changes between 2-date images. A method based on confidence and object grouping was designed to combine the multiple MIICA outputs to improve change detection accuracy. Finally, an aggregation scheme was implemented to combine the TSUN output, the integrated MIICA results, and ancillary data to produce the NLCD 2019 forest disturbance 1986–2019 product. The initial accuracy assessments from 1,600 samples over 4 Landsat path/rows show that the producer’s and user’s accuracies of the 2001–2019 forest disturbance map are 76% and 74%, respectively. The final CONUS-wide forest disturbance product is provided at https://www.mrlc.gov/nlcd-2019-science-research-products .

conterminous United States↗
USGS2023

A web-based application for exploring potential changes in design peak flow of U.S. urban areas driven by land cover change

Floods have become increasingly prominent in recent decades, especially in urban areas causing devastating effects on lives and livelihoods worldwide. Efficient tools to assess the drivers of floods, such as increasing urbanization could help to minimize flood hazards. A Google Earth Engine (GEE) application was developed to explore the potential changes (1985-2020) in design peak-flow of urban areas across the conterminous United States driven by land cover change. The results indicate a potential increase in peak-flow in urban areas up to 126.6% in 2020 compared to 1985. Out of the total 3535 study urban areas, about 80% (2840) urban areas increased peak-flow and about 19% (654) decreased peak-flow. A general pattern of increasing peak-flow was observed during 1985-2010 and decreasing pattern during 2010-2020, primarily driven by respective increasing (decreasing) and decreasing (increasing) developed areas (croplands). The GEE application pro-vides crucial information by visualizing both spatial and temporal data that could be useful for decision-makers in developing and improving urban stormwater management plans and policies for efficient resource allocations and reducing flood risks.

Journal of Remote Sensing↗
USGS2014

Landsat TM and ETM+ thermal band calibration

Landsat-5 has been imaging the Earth since March 1984, and Landsat-7 was added to the series of Landsat instruments in April 1999. The Landsat Project Science Office and the Landsat-7 Image Assessment System have been monitoring the on-board calibration of Landsat-7 since launch. Additionally, two separate university teams have been evaluating the on-board thermal calibration of Landsat-7 through ground-based measurements since launch. Although not monitored as closely over its lifetime, a new effort is currently being made to validate the calibration of Landsat-5. Two university teams are beginning to collect ground truth under Landsat-5, along with using other vicarious calibration methods to go back into the archive to validate the history of the calibration of Landsat-5. This paper considers the calibration efforts for the thermal band, band 6, of both the Landsat-5 and Landsat-7 instruments. Though stable since launch, Landsat-7 had an initial calibration error of about 3 K, and changes were made to correct for this beginning 1 October 2000 for data processed with the National Landsat Archive Production System (NLAPS) and beginning 20 December 2000 for data processed with the Landsat Product Generation System (LPGS). Recent results from Landsat-5 vicarious calibration efforts show an offset of –0.7 K over the lifetime of the instrument. This suggests that historical calibration efforts may have been detecting errors in processing systems rather than changes in the instrument. A correction to the Landsat-5 processing has not yet been implemented but will be in the near future.

Canadian Journal of Remote Sensing↗
USGS2014

Characterization of intra-annual reflectance properties of land cover classes in southeastern South Dakota using Landsat TM and ETM+ data

Landsat-7 and Landsat-5 have orbits that are offset from each other by 8 days. During the time that the sensors on both satellites are operational, there is an opportunity for conducting analyses that incorporate multiple intra-annual high spatial resolution data sets for characterizing the Earth's land surface. In the current study, nine Landsat thematic mapper (TM) and enhanced thematic mapper plus (ETM+) data sets, covering the same path and row on different dates, were acquired during a 1-year time interval for a region in southeastern South Dakota and analyzed. Scenes were normalized using pseudoinvariant objects, and digital data from a series of test sites were extracted from the imagery and converted to surface reflectance. Sunphotometer data acquired on site were used to atmospherically correct the data. Ground observations that were made throughout the growing season by a large group of volunteers were used to help interpret spectroradiometric patterns and trends. Normalized images were found to be very effective in portraying the seasonal patterns of reflectance change that occurred throughout the region. Many of the radiometric patterns related to plant growth and development, but some also related to different background properties. The different kinds of land cover in the region were spectrally and radiometrically characterized and were found to have different seasonal patterns of reflectance. The degree to which the land cover classes could be separated spectrally and radiometrically, however, depended on the time of year during which the data sets were acquired, and no single data set appeared to be adequate for separating all types of land cover. This has practical implications for classification studies because known patterns of seasonal reflectance properties for the different types of land cover within a region will facilitate selection of the most appropriate data sets for producing land cover classifications.

Canadian Journal of Remote Sensing↗
USGS2014

An approach for mapping large-area impervious surfaces: Synergistic use of Landsat-7 ETM+ and high spatial resolution imagery

A wide range of urban ecosystem studies, including urban hydrology, urban climate, land use planning, and resource management, require current and accurate geospatial data of urban impervious surfaces. We developed an approach to quantify urban impervious surfaces as a continuous variable by using multisensor and multisource datasets. Subpixel percent impervious surfaces at 30-m resolution were mapped using a regression tree model. The utility, practicality, and affordability of the proposed method for large-area imperviousness mapping were tested over three spatial scales (Sioux Falls, South Dakota, Richmond, Virginia, and the Chesapeake Bay areas of the United States). Average error of predicted versus actual percent impervious surface ranged from 8.8 to 11.4%, with correlation coefficients from 0.82 to 0.91. The approach is being implemented to map impervious surfaces for the entire United States as one of the major components of the circa 2000 national land cover database.

Canadian Journal of Remote Sensing↗
USGS2014

Surface deformation associated with the March 1996 earthquake swarm at Akutan Island, Alaska, revealed by C-band ERS and L-band JERS radar interferometry

In March 1996, an intense earthquake swarm beneath Akutan Island, Alaska, was accompanied by extensive ground cracking but no eruption of Akutan volcano. Radar interferograms produced from L-band JERS-1 and C-band ERS-1/2 images show uplift associated with the swarm by as much as 60 cm on the western part of the island. The JERS-1 interferogram has greater coherence, especially in areas with loose surface material or thick vegetation. It also shows subsidence of similar magnitude on the eastern part of the island and displacements along faults reactivated during the swarm. The axis of uplift and subsidence strikes about N70°W, which is roughly parallel to a zone of fresh cracks on the northwest flank of the volcano, to normal faults that cut the island and to the inferred maximum compressive stress direction. A common feature of models that fit the deformation is the emplacement of a shallow dike along this trend beneath the northwest flank of the volcano. Both before and after the swarm, the northwest flank was uplifted 5–20 mm/year relative to the southwest flank, probably by magma intrusion. The zone of fresh cracks subsided about 20 mm during 1996–1997 and at lesser rates thereafter, possibly because of cooling and degassing of the intrusion.

Alaska↗