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Results for “Photogrammetric Engineering & Remote Sensing”

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At least 37 records · Page 2Linked to original sources

Marsh canopy leaf area and orientation calculated for improved marsh structure mapping

An approach is presented for producing the spatiotemporal estimation of leaf area index (LAI) of a highly heterogeneous coastal marsh without reliance on user estimates of marsh leaf-stem orientation. The canopy LAI profile derivation used three years of field measured photosynthetically active radiation (PAR) vertical profiles at seven S. alterniflora marsh sites and iterative transform of those PAR attenuation profiles to best-fit light extinction coefficients (KM). KM sun zenith dependency was removed obtaining the leaf angle distribution (LAD) representing the average marsh orientation and the LAD used to calculate the LAI canopy profile. LAI and LAD reproduced measured PAR profiles with 99% accuracy and corresponded to field documented structures. LAI and LAD better reflect marsh structure and results substantiate the need to account for marsh orientation. The structure indexes are directly amenable to remote sensing spatiotemporal mapping and offer a more meaningful representation of wetland systems promoting biophysical function understanding.

Photogrammetric Engineering and Remote Sensing↗

An agreement coefficient for image comparison

Combination of datasets acquired from different sensor systems is necessary to construct a long time-series dataset for remotely sensed land-surface variables. Assessment of the agreement of the data derived from various sources is an important issue in understanding the data continuity through the time-series. Some traditional measures, including correlation coefficient, coefficient of determination, mean absolute error, and root mean square error, are not always optimal for evaluating the data agreement. For this reason, we developed a new agreement coefficient for comparing two different images. The agreement coefficient has the following properties: non-dimensional, bounded, symmetric, and distinguishable between systematic and unsystematic differences. The paper provides examples of agreement analyses for hypothetical data and actual remotely sensed data. The results demonstrate that the agreement coefficient does include the above properties, and therefore is a useful tool for image comparison.

Photogrammetric Engineering and Remote Sensing↗

College and university sources of remote sensing information

Research in remote-sensing applications has increased dramatically since the launch of the Earth Resources Technology Satellite-l (ERTS-l, renamed LANDSAT-I) and Skylab's Earth Resources Experiment Package (EREP). It is becoming increasingly more difficult to keep abreast of university research publications related to remote sensing. To assist researchers in locating those universities that are actively publishing research material in remote-sensing technology and applications, this paper lists major colleges by types of publications generated and by application oriented disciplines pursued, and includes a geographical index.

Photogrammetric Engineering and Remote Sensing↗

Evaluation of eelgrass beds mapping using a high-resolution airborne multispectral scanner

Eelgrass ( Zostera marina ) can provide vital ecological functions in stabilizing sediments, influencing current dynamics, and contributing significant amounts of biomass to numerous food webs in coastal ecosystems. Mapping eelgrass beds is important for coastal water and nearshore estuarine monitoring, management, and planning. This study demonstrated the possible use of high spatial (approximately 5 m) and temporal (maximum low tide) resolution airborne multispectral scanner on mapping eelgrass beds in Northern Puget Sound, Washington. A combination of supervised and unsupervised classification approaches were performed on the multispectral scanner imagery. A normalized difference vegetation index (NDVI) derived from the red and near-infrared bands and ancillary spatial information, were used to extract and mask eelgrass beds and other submerged aquatic vegetation (SAV) in the study area. We evaluated the resulting thematic map (geocoded, classified image) against a conventional aerial photograph interpretation using 260 point locations randomly stratified over five defined classes from the thematic map. We achieved an overall accuracy of 92 percent with 0.92 Kappa Coefficient in the study area. This study demonstrates that the airborne multispectral scanner can be useful for mapping eelgrass beds in a local or regional scale, especially in regions for which optical remote sensing from space is constrained by climatic and tidal conditions.

Photogrammetric Engineering and Remote Sensing↗

The evolving Alaska mapping program.

This paper describes the development of mapping in Alaska, the current status of the National Mapping Program, and future plans for expanding and improving the mapping coverage. Research projects with Landsat Multispectral Scanner and Return Vidicon imagery and real- and synthetic-aperture radar; image mapping programs; digital mapping; remote sensing projects; the Alaska National Interest Lands Conservation Act; and the Alaska High-Altitude Aerial Photography Program are also discussed.-from Authors

Photogrammetric Engineering and Remote Sensing↗

Leaf optical property changes associated with the occurrence of Spartina alterniflora dieback in Coastal Louisiana related to remote sensing mapping

In order to provide a remote sensing solution that would detect both the initial onset and monitor the early, as well as, the later stages of impact progression, changes in live leaf optical properties were compared along transects spanning impacted coastal Louisiana marsh sites. Green and red edge reflectance trends generally represented the early stages and fairly well the later stages of dieback progression, while blue and red reflectance and absorption trends represented the later stages of marsh impact that were most closely related to visible signs of marsh impact. Leaf reflectance in the near infrared (NIR) was not compatible with visual reflectance trends and did not co-vary with derived indicators of leaf water content, and thereby, water stress. Predicted from reflectance ratios, carotene tended to remain constant or increase relative to chlorophyll following noted changes in stressed plants at the two least impacted sites, while the pigments co-varied at the two most impacted sites. As an operational solution most amenable for satellite remote sensing, the NIR /red ratio followed blue and red reflectance trends while the NIR /green ratio mimicked the green and red edge reflectance trends indicating impact onset and progression, as well as, generally portraying blue and red reflectance trends indicating later stages of impact. The NIR/ green ratio magnitude and range generally increased from the most to least impacted site providing a convenient method to detect dieback onset and monitor dieback progression. This research demonstrated that remote sensing mapping at these sites could offer a more accurate perception of dieback severity distribution than offered by determinations relying on visible indicators of marsh changes.

Louisiana↗

Multitemporal Landsat multispectral scanner and thematic mapper data of the Hubbard Glacier region, southeast Alaska

In late May 1986, the advancing Hubbard Glacier blocked the entrance to Russell Fiord near Yakutat, Alaska, creating a large ice-dammed lake. Runoff from the surrounding glaciated mountains raised the level of the lake to about 25 m above sea level by 8 October, when the ice dam failed. Remote sensing offers one method to monitor this large tidal glacier system, particularly the glacier activity that would portend the re-closure of Russell Fiord. -Authors

Photogrammetric Engineering and Remote Sensing↗

Mapping Chinese tallow with color-infrared photography

Airborne color-infrared photography (CIR) (1:12,000 scale) was used to map localized occurrences of the widespread and aggressive Chinese tallow (Sapium sebiferum), an invasive species. Photography was collected during senescence when Chinese tallow's bright red leaves presented a high spectral contrast within the native bottomland hardwood and upland forests and marsh land-cover types. Mapped occurrences were conservative because not all senescing tallow leaves are bright red simultaneously. To simulate low spectral but high spatial resolution satellite/airborne image and digital video data, the CIR photography was transformed into raster images at spatial resolutions approximating 0.5 in and 1.0 m. The image data were then spectrally classified for the occurrence of bright red leaves associated with senescing Chinese tallow. Classification accuracies were greater than 95 percent at both spatial resolutions. There was no significant difference in either forest in the detection of tallow or inclusion of non-tallow trees associated with the two spatial resolutions. In marshes, slightly more tallow occurrences were mapped with the lower spatial resolution, but there were also more misclassifications of native land covers as tallow. Combining all land covers, there was no difference at detecting tallow occurrences (equal omission errors) between the two resolutions, but the higher spatial resolution was associated with less inclusion of non-tallow land covers as tallow (lower commission error). Overall, these results confirm that high spatial (???1 m) but low spectral resolution remote sensing data can be used for mapping Chinese tallow trees in dominant environments found in coastal and adjacent upland landscapes.

Photogrammetric Engineering and Remote Sensing↗

USGS aerial resolution targets.

It is necessary to measure the achievable resolution of any airborne sensor that is to be used for metric purposes. Laboratory calibration facilities may be inadequate or inappropriate for determining the resolution of non-photographic sensors such as optical-mechanical scanners, television imaging tubes, and linear arrays. However, large target arrays imaged in the field can be used in testing such systems. The USGS has constructed an array of resolution targets in order to permit field testing of a variety of airborne sensing systems. The target array permits any interested organization with an airborne sensing system to accurately determine the operational resolution of its system. -from Author

Photogrammetric Engineering and Remote Sensing↗

Landsat classification accuracy assessment procedures

A working conference was held in Sioux Falls, South Dakota, 12-14 November, 1980 dealing with Landsat classification Accuracy Assessment Procedures. Thirteen formal presentations were made on three general topics: (1) sampling procedures, (2) statistical analysis techniques, and (3) examples of projects which included accuracy assessment and the associated costs, logistical problems, and value of the accuracy data to the remote sensing specialist and the resource manager. Nearly twenty conference attendees participated in two discussion sessions addressing various issues associated with accuracy assessment. This paper presents an account of the accomplishments of the conference.

Photogrammetric Engineering and Remote Sensing↗

Aerodynamic roughness length estimation with lidar and imaging spectroscopy in a shrub-dominated dryland

The aerodynamic roughness length (Z 0 m ) serves an important role in the flux exchange between the land surface and atmosphere. In this study, airborne lidar ( ALS ), terrestrial lidar ( TLS ), and imaging spectroscopy data were integrated to develop and test two approaches to estimate Z 0 m over a shrub dominated dryland study area in south-central Idaho, USA. Sensitivity of the two parameterization methods to estimate Z 0 m was analyzed. The comparison of eddy covariance-derived Z 0 m and remote sensing-derived Z 0 m showed that the accuracy of the estimated Z 0 m heavily depends on the estimation model and the representation of shrub (e.g., Artemisia tridentata subsp. wyomingensis) height in the models. The geometrical method (RA1994) led to 9 percent (~0.5 cm) and 25% (~1.1 cm) errors at site 1 and site 2, respectively, which performed better than the height variability-based method (MR1994) with bias error of 20 percent and 48 percent at site 1 and site 2, respectively. The RA1994 model resulted in a larger range of Z 0 m than the MR1994 method. We also found that the mean, median and 75th percentiles of heights (H75) from ALS provides the best Z 0 m estimates in the MR1994 model, while the mean, median, and MLD (Median Absolute Deviation from Median Height), as well as AAD (Mean Absolute Deviation from Mean Height) heights from ALS provides the best Z 0 m estimates in the RA1994 model. In addition, the fractional cover of shrub and grass, distinguished with ALS and imaging spectroscopy data, provided the opportunity to estimate the frontal area index at the pixel-level to assess the influence of grass and shrub on Z 0 m estimates in the RA1994 method. Results indicate that grass had little effect on Z 0 m in the RA1994 method. The Z 0 m estimations were tightly coupled with vegetation height and its local variance for the shrubs. Overall, the results demonstrate that the use of height and fractional cover from remote sensing data are promising for estimating Z 0 m , and thus refining land surface models at regional scales in semiarid shrublands.

Photogrammetric Engineering and Remote Sensing↗

Detection of leaks in buried rural water pipelines using thermal infrared images

Leakage is a major problem in many pipelines. Minor leaks called 'seeper leaks', which generally range from 2 to 10 m 3 per day, are common and are difficult to detect using conventional ground surveys. The objective of this research was to determine whether airborne thermal-infrared remote sensing could be used in detecting leaks and monitoring rural water pipelines. This study indicates that such leaks can be detected using low-altitude 8.7- to 11.5. micrometer wavelength, thermal infrared images collected under proper conditions.

Photogrammetric Engineering and Remote Sensing↗

Lava flow surface textures: SIR-B radar image texture, field observations, and terrain measurements

Space Shuttle Imaging Radar (SIR-8) images, field observations, and small-scale (cm) terrain measurements are used to study lava flow surface textures related to emplacement processes of a single hawaiian lava flow. Although smooth pahoehoe textures are poorly characterized on the SIR-B data, rougher pahoehoe types and the a'a flow portion show image textures attributed to spatial variations in surface roughness. Field observations of six distinct lava flow textural units are described and used to interpret modes of emplacement. Terrain measurements of these units show that surface roughness differs across and along the flow, apparently due to shear during flow emplacement. The radar smooth/rough boundary between pahoehoe and a'a occurs at a vertical relief of -10 cm on this lava flow. While direct observation and measurement most readily yield information related to lava eruption and emplacement processes, analyses of remote sensing data such as those acquired by imaging radars and altimeters can provide a means of quantifying surface texture, identifying the size and distribution of flow components, and delineating textural unit boundaries.

Hawaii↗

Scaling field data to calibrate and validate moderate spatial resolution remote sensing models

Validation and calibration are essential components of nearly all remote sensing-based studies. In both cases, ground measurements are collected and then related to the remote sensing observations or model results. In many situations, and particularly in studies that use moderate resolution remote sensing, a mismatch exists between the sensor’s field of view and the scale at which in situ measurements are collected. The use of in situ measurements for model calibration and validation, therefore, requires a robust and defensible method to spatially aggregate ground measurements to the scale at which the remotely sensed data are acquired. This paper examines this challenge and specifically considers two different approaches for aggregating field measurements to match the spatial resolution of moderate spatial resolution remote sensing data: (a) landscape stratification; and (b) averaging of fine spatial resolution maps. The results show that an empirically estimated stratification based on a regression tree method provides a statistically defensible and operational basis for performing this type of procedure.

Photogrammetric Engineering and Remote Sensing↗

Institutional issues affecting the integration and use of remotely sensed data and geographic information systems

The developers as well as the users of remotely sensed data and geographic information system (GIS) techniques are associated with nearly all types of institutions in government, industry, and academia. Individuals in these various institutions often find the barriers to accepting remote sensing and GIS are not necessarily technical in nature, but can be attributed to the institutions themselves. Several major institutional issues that affect the technologies of remote sensing and GIS are data availability, data marketing and costs, equipment availability and costs, standards and practices, education and training, and organizational infrastructures. Not only are problems associated with these issues identified, but needs and opportunities also are discussed. -from Authors

Photogrammetric Engineering and Remote Sensing↗

Publication aspects of ethics in photogrammetry

According to the Code of Ethics of the American Society for Photogrammetry and Remote Sensing (ASPRS), the principles on which ethics are founded consist of honesty, justice, and courtesy, forming a moral philosophy associated with mutual interest among men. We will cover in particular the ethical problems of publication of photogrammetric material in the various media. There are many such problems, and we often face a dilemma in selecting a course which is the right thing to do.

Photogrammetric Engineering and Remote Sensing↗

Remote sensing investigations at a hazardous-waste landfill

In 1976 state licensed landfilling of industrial chemicals was begun above an abandoned, underground coal mine in Illinois. Five years later organic chemical pollutants were discovered in a monitoring well, suggesting migration 100 to 1000 times faster than predicted by laboratory tests. Remote sensing contributed to the determination of the causes of faster-than-predicted pollutant migration at the hazardous-waste landfill. Aerial and satellite imagery were employed to supplement field studies of local surface and groundwater hydrology, and to chronicle site history. Drainage impediments and depressions in the trench covers collected runoff, allowing rapid recharge of surface waters to some burial trenches. These features can be more effectively identified by photointerpretation than by conventional field reconnaissance. A ground-based, post-sunset survey of the trench covers that showed that a distinction between depressions which hold moisture at the surface from freely-draining depressions which permit rapid recharge to the burial trenches could be made using thermal infrared imagery.In 1976 state licensed landfilling of industrial chemicals was begun above an abandoned, underground coal mine in Illinois. Five years later organic chemical pollutants were discovered in a monitoring well, suggesting migration 100 to 1000 times faster than predicted by laboratory tests. Remote sensing contributed to the determination of the causes of faster-than-predicted pollutant migration at the hazardous-waste landfill. Aerial and satellite imagery were employed to supplement field studies of local surface and groundwater hydrology, and to chronicle site history. Drainage impediments and depressions in the trench covers collected runoff, allowing rapid recharge of surface waters to some burial trenches.

Photogrammetric Engineering and Remote Sensing↗