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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Meng, Ran↗
NASA NTRS1985

Spatial-frequency spectrum of patterns changes the visibility of spatial-phase differences

It is shown that spatial-frequency components over a 4-octave range affected the visibility of spatial-phase differences. Contrast thresholds were measured for discrimination between two (+45- and -45-deg) spatial phases of a sinusoidal test grating added to a background grating. The background could contain one or several sinusoidal components, all in 0-deg phase. Phase differences between the test and the background were visible at lower contrasts when test and background frequencies were harmonically related than when they were not, when test and background frequencies were within 1 octave than when they were farther apart, when the fundamental frequency of the background was low than when it was high, and for some discriminations more than for others, after practice. The visibility of phase differences was not affected by additional components in the background if the fundamental and difference frequencies of the background remained unchanged. Observers' reports of their strategies gave information about the types of attentive processing that were used to discriminate phase differences. Attentive processing facilitated phase discrimination for multifrequency gratings spanning a much wider range of spatial frequencies than would be possible by using only local preattentive processing. These results were consistent with the visibility of phase differences being processed by some combination of even- and odd-symmetric simple cells tuned to a wide range of different spatial frequencies.

Lawton, T. B.↗
NASA NTRS1995

Spatial and Spatial Frequency Spreads of Masking: Measurements and A Contrast-Gain-Control Model

Masked pattern detection is affected by the mask's proximity to the target in both the spatial and the spatial frequency domains. We measured contrast thresholds for detection of a Gabor patch centered in a sample of static band-pass noise with a central noise-free aperture. To examine spatial spread, target and mask frequency were identical, at either 2, 4, or 8 cycles/degree (cpd), and the radius of the aperture was 0, 1/2 or 1 cycle of the noise band's center frequency. The results suggest that the spatial spread of masking is scale invariant, with the largest radius producing little masking. To examine spatial frequency spread, a radius of 0 (no aperture) was used with all pairings of 2, 4, and 8 cpd for target and mask. The results suggest that masking is asymmetrical over log frequency: 8 z 0 cpd noise masks a 2 cpd target, but 2 cpd noise does not mask an 8 cpd target. We have used these results to calibrate a model of contrast-gain-control.

Solomon, Joshua A.↗
NASA NTRS1995

Spatial and Spatial Frequency Spreads Of Masking: Measurements and a Contrast-Gain-Control Model

Masked pattern detection is affected by the mask's proximity to the target in both the spatial and the spatial frequency domains. We measured contrast thresholds for detection of a Gabor patch centered in a sample of static band-pass noise with a central noise-free aperture. To examine spatial spread, target and mask frequency were identical, at either 2, 4, or 8 cycles/degree (cpd), and the radius of the aperture was 0, 1/2 or 1 cycle of the noise band's center frequency. The results suggest that the spatial spread of masking is scale invariant, with the largest radius producing little masking. To examine spatial frequency spread, a radius of 0 (no aperture) was used with all pairings of 2,4, and 8 cpd for target and mask. The results suggest that masking is asymmetrical over log frequency: 8 cpd noise masks a 2 cpd target, but 2 cpd noise does not mask an 8 cpd target. We have used these results to calibrate a model of contrast-gain-control.

Solomon, J. A.↗
NASA NTRS2006

Comparisons of Temporal and Spatial Trends in the Spatially Complete Global Spectral Surface Albedos Products

Five years of spatially complete snow-free land surface albedo data have been prepared using high quality white-sky and black-sky land surface albedo observations (MOD43B3) from the MODIS instrument aboard NASA's Terra satellite platform. The data were generated using an updated ecosystem-dependent temporal interpolation technique. In this paper, we describe the refinements in the technique and the creation of a spatially complete snow-free five-year aggregate climatology product. This paper also describes an error analysis of the interpolation technique. The filled albedo products are examined through comparisons of temporal and spatial trends for pixels that have been filled versus pixels that have been retained in the original MOD43B3 values. The variability in the trends showcase how the filling technique maintains the pixel-level spatial, spectral, and temporal integrity of the MOD43B3 data. These comparisons are made for both a single-year of filled data, year 2002, and for the five-year aggregate climatology product.

Moody, Eric G.↗
NASA NTRS2018

Spatial Correlation Structures in SMAP Near-Surface Soil Moisture (How Spatially Correlated are the Temporal Variations of Soil Moisture at Different Locations? and Why Is This of Interest?)

Spatial correlation structures can describe the degree to which soil moisture at a specified location co-varies in time with that at other, remote locations. Using four years of warm season SMAP Level 2 near-surface soil moisture data, we compute these spatial correlation structures for points across North America. The character of these structures is seen to differ geographically; the structures found for the west-central US, for example, are significantly more spatially extensive. We then demonstrate how these structures can potentially be used to reconstruct soil moisture fields during the pre-SMAP era. In this exercise, we consider as "truth" the soil moistures produced in a long-term offline land surface model simulation (1980-2014) that utilizes precipitation forcing based on a high density of precipitation gauges. Then, for a given location within the continent, we construct an"estimated" soil moisture time series based solely on historical soil moisture information simulated at least 300 km distant from the location, using the SMAP-based spatial correlation structures to determine how to make best use of the remote information. The reconstructed soil moistures are found to have significant skill relative to the assumed truth, suggesting that the same approach, when applied in areas of low rain gauge density (i.e., in areas for which historically simulated soil moistures are necessarily inaccurate), could provide useful historical soil moisture estimates through the SMAP-guided extraction of relevant information from neighboring gauged regions.

Koster, Randal↗
NASA NTRS1986

The Sun at high spatial resolution: The physics of small spatial structures in a magnetized medium

An attempt is made to provide a perspective on the problem of spatial structuring on scales smaller than can presently be directly and regularly observed from the ground or with which current space-based instrumentation can be anticipated. There is abundant evidence from both observations and theory that such spatial structuring of the solar outer atmosphere is ubiquitous not only on the observed scales, but also on spatial scales down to (at least) the subarcsecond range. This is not to say that the results to be obtained from observations on these small scales can be anticipated: quite the opposite. What is clear instead is that many of the classic problems of coronal and chromospheric activity - involving the basic dissipative nature of magnetized plasmas - will be seen from a novel perspective at these scales, and that there are reasons for believing that dynamical processes of importance to activity on presently-resolved scales will themselves begin to be resolved on the sub-arcsecond level. Since the Sun is the only astrophysical laboratory for which there is any hope of studying these processes in any detail, this observatioinal opportunity is an exciting prospect for any student of magnetic activity in astrophysics.

Rosner, R. T.↗
NASA NTRS1989

Spatial Displays and Spatial Instruments

The conference proceedings topics are divided into two main areas: (1) issues of spatial and picture perception raised by graphical electronic displays of spatial information; and (2) design questions raised by the practical experience of designers actually defining new spatial instruments for use in new aircraft and spacecraft. Each topic is considered from both a theoretical and an applied direction. Emphasis is placed on discussion of phenomena and determination of design principles.

Ellis, Stephen R.↗
NASA NTRS2017

Obtaining and Using Planetary Spatial Data into the Future: The Role of the Mapping and Planetary Spatial Infrastructure Team (MAPSIT)

Planetary spatial data, which include any remote sensing data or derived products with sufficient positional information such that they can be projected onto a planetary body, continue to rapidly increase in volume and complexity. These data are the hard-earned fruits of decades of planetary exploration, and are the end result of mission planning and execution. Maintaining these data using accessible formats and standards for all scientists has been necessary for the success of past, present, and future planetary missions. The Mapping and Planetary Spatial Infrastructure Team (MAPSIT) is a group of planetary community members tasked by NASA Headquarters to work with the planetary science community to identify and prioritize their planetary spatial data needs to help determine the best pathways for new data acquisition, usable product derivation, and tools/capability development that supports NASA's planetary science missions.

Radebaugh, J.↗
NASA NTRS1986

Analysis of spatial inhomogeneities in cumulus clouds using high spatial resolution Landsat data

Aircraft observations and high resolution Landsat MSS digital data are used to determine the sizes of spatial inhomogeneities ('holes') in cumulus clouds. The majority of holes are found near cloud edges, but the larger holes tend to be found in cloud interiors. Aircraft measurements show these cloud spatial inhomogeneities in the range of 100 to 500 m, while Landsat data show them in the range of 100 m to 3 km. The number of holes per cloud decreases exponentially with increasing hole diameter. Small clouds not only have smaller holes, but also fewer holes than large clouds. Large clouds have large holes in them, as well as large numbers of the smaller holes. The total cloud area occupied by holes increases with increasing cloud size.

Parker, Lindsay↗
NASA NTRS2002

Radiometric and Spatial Characterization of High-Spatial Resolution Sensors

The development and improvement of commercial hyperspatial sensors in recent years has increased the breadth of information that can be retrieved from spaceborne and airborne imagery. NASA, through it's Scientific Data Purchases, has successfully provided such data sets to its user community. A key element to the usefulness of these data are an understanding of the radiometric and spatial response quality of the imagery. This proposal seeks funding to examine the absolute radiometric calibration of the Ikonos sensor operated by Space Imaging and the recently-launched Quickbird sensor from DigitalGlobe. In addition, we propose to evaluate the spatial response of the two sensors. The proposed methods rely on well-understood, ground-based targets that have been used by the University of Arizona for more than a decade.

Thome, Kurtis↗
NASA NTRS2024

Land Cover Change Analysis and Spatial Variations in Southeast Asian Nations: Insights on Spatial Scale Dynamics

Land cover type is a fundamental aspect of studies using remote sensing for environmental analysis such as monitoring deforestation, quantifying wildland fire emissions, and more. There are many land cover products available for varying time periods and spatial resolutions, each with different land cover class definitions and number of land cover classes. These differences yield inherent variation in land cover estimates. In this study, we explore the spatial and areal variation between two major datasets for their commonly available time of 2018 to 2022 (MODIS 500m Land Cover and Esri Sentinel-2 10m land cover) in the continental Southeast Asia countries of Cambodia, Laos, Myanmar, Thailand, and Vietnam. To enable comparison, we resampled the datasets and reclassified the land cover classes to a common scheme. Major disagreement was detected between Esri and MODIS, especially for the wetlands/flooded vegetation class in which only 3.6% of pixels were in agreement. In addition to quantifying variation between the datasets, we quantify land cover change at the decadal scale of 2001, 2011, and 2021 for each country and identified province-level hotspots of land cover change. Cambodia experienced the highest rate of land cover change with 67.8% of total land area changed, followed by Vietnam (58.6%), Laos (50.2%), Myanmar (46.9%), and Thailand (46.3%). The highest rate of land cover change was detected in Odtar Mean Chey, Cambodia, which had large swaths of forest area cleared for agricultural production, river damming, and more. Ultimately, many areas in the region experienced forest clearing for crop production (i.e. rice) which appeared to be classified as wetland in the MODIS product, and crop in the Esri product. Myanmar was the only country which did not experience net decline in forest area over the 2001 to 2021 time period.

Land Cover Change↗
NASA NTRS1990

Cumulus cloud field morphology and spatial patterns derived from high spatial resolution Landsat imagery

Using high-spatial-resolution Landsat MSS imagery, the cumulus cloud morphology, cloud nearest-neighbor distributions, and cloud clumping scales were investigated. It is shown that the cloud-size distribution can be represented by a mixture of two power laws; clouds of diameters less than 1 km have power-law slope range of 1.4-2.3, while larger clouds have slopes from 2.1 to 4.75. The break in power-law slope occurs at the cloud size that makes the largest contribution to cloud cover. Results suggest that larger clouds grow at the expense of smaller clouds. It was also found that the cloud inhomogeneities have significant impact on radiative fluxes.

Sengupta, S. K.↗