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At least 37 records · Page 2

The use of four band multispectral photography to identify forest cover types

Four-band multispectral aerial photography and a color additive viewer were employed to identify forest cover types in Northern Alabama. The multispectral photography utilized the blue, green, red and near-infrared spectral regions and was made with black and white infrared film. On the basis of color differences alone, a differentiation between conifers and hardwoods was possible; however, supplementary information related to forest ecology proved necessary for the differentiation of various species of pines and hardwoods.

Downs, S. W., Jr.↗

Nationwide forestry applications program. Ten-Ecosystem Study (TES) site 6, Fort Yukon, Alaska

The author has identified the following significant results. Analysis of the processing results has led to the following conclusions: (1) LANDSAT imagery was a reliable resource for the stratification of level 2 forest features (softwood, hardwood, tundra, and water). These features can be classified with an accuracy of 72.4 percent + or - 5.9 percent at the 90 percent confidence level. (2) Training fields selected for signature development from only 10 percent of the area did not adequately and efficiently cover the class variability for the entire area. (3) Derived regression transformations were ineffective in recovering the loss of level 1 forest proportions and level 2 softwood and hardwood proportions.

Ward, J. F.↗

Ten-Ecosystem Study (TES) site 9, Washington County, Missouri

The author has identified the following significant results. Sufficient spectral separability exists among softwood, hardwood, grassland, and water to develop a level 2 classification and inventory. Using the tested automatic data processing technology, softwood and grassland signatures can be extended across the county with acceptable accuracy; with more dense sampling, the hardwood signature probably could also be extended. Fall was found to be the best season for mapping this ecosystem.

Echert, W. H.↗

Using Landsat MSS data with soils information to identify wetland habitats

A previous study showed that certain fresh water wetland vegetation types can be spectrally separated when a maximum likelihood classification procedure is applied to Landsat spectral data. However, wetland and upland types which have similar vegetative life forms (e.g., upland hardwoods and hardwood swamps) are often confused because of spectral similarity. Therefore, the current investigation attempts to differentiate similar wetland and upland types by combining Landsat multispectral scanner (MSS) data with soils information. The Pigeon River area in northern Indiana used in the earlier study was also employed in this investigation. A layered classification algorithm which combined soils and spectral data was used to generate a wetland classification. The results of the spectral/soils wetland classification are compared to the previous classification that had been based on spectral data alone. The results indicate wetland habitat mapping can be improved by combining soils and other ancillary data with Landsat spectral data.

Ernst, C. L.↗

Discrimination of unique biological communities in the Mississippi lignite belt

Small scale hardcopy LANDSAT prints were manually interpreted and color infrared aerial photography was obtained in an effort to identify and map large contiguous areas of old growth hardwood stands within Mississippi's lignite belt which do not exhibit signs of recent disturbance by agriculture, grazing, timber harvesting, fire, or any natural catastrophe, and which may, therefore, contain unique or historical ecological habitat types. An information system using land cover classes derived from digital LANDSAT data and containing information on geology, hydrology, soils, and cultural activities was developed. Using computer-assisted land cover classifications, all hardwood remnants in the study area which are subject to possible disturbance from surface mining were determined. Twelve rare plants were also identified by botanists.

Miller, W. F.↗

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Supervised and cluster block training statistics were used to analyze the thematic mapper simulation MSS data (both 1979 and 1980 data sets). Cover information classes identified on SAR imagery include: hardwood, pine, mixed pine hardwood, clearcut, pasture, crops, emergent crops, bare soil, urban, and water. Preliminary analysis of the HH and HV polarized SAR data indicate a high variance associated with each information class except for water and bare soil. The large variance for most spectral classes suggests that while the means might be statistically separable, an overlap may exist between the classes which could introduce a significant classification error. The quantitative values of many cover types are much larger on the HV polarization than on the HH, thereby indicating the relative nature of the digitized data values. The mean values of the spectral classes in the areas with larger look angles are greater than the means of the same cover type in other areas having steeper look angles. Difficulty in accurately overlaying the dual polarization of the SAR data was resolved.

Hoffer, R. M.↗

Early remote laser detection of vegetation damage caused by certain environmental stress factors

The fluorescence spectra of plants excited with a pulsed nitrogen laser beam emitting at 337 nm were found to be related to plant type, as well as with changes in the physiology of the plant as the result of various kinds of environmental stress. The plant types which were studied included herbaceous dicots, monocots, hardwoods, and conifers. These plant types could be identified on the basis of differences in either the number of fluorescent bands, or the relative intensity of the bands. The dicots and monocots had fluorescent maxima at 440, 685, and 740 nm. The monocots could be distinguished from the dicots by virtue of having a much higher 440 nm/685 nm ratio. Hardwoods and conifers had an additional fluorescence band at 525 nm, but healthy conifers did not have a band at 685 nm.

Chappelle, Emmett W.↗

AVHRR-LAC estimates of forest area in Madagascar, 1990

Three AVHRR-LAC data sets acquired in September 1990 and January 1991 were used to map the forest resources of Madagascar. The island was partitioned into four strata to include: (1) the western hardwoods, (2) the central grasslands, (3) the eastern rainforest, and (4) spiny forest. Each stratum was classified separately using AVHRR-LAC data in conjunction with 1984-1988 Landsat-MSS photoproducts. The results of AVHRR classification indicate that approximately 11 percent of the island is covered by forest. Estimates of forest area, by stratum, are as follows: western hardwoods, 6697 sq km; central grasslands, 2830 sq km; eastern rainforest 34,167 sq km; and spiny forest, 17,224 sq km. The total forest area on the 587,041 sq km island is estimated to be 60,918 sq km. The AVHRR forest map was compared to a mid-1970s land cover map which was developed using Landsat-MSS photoproducts. The average class agreement between the mid 1970s ground reference map and the 1990 AVHRR-LAC map was 78.2 percent, the overall accuracy was 81.1 percent. Much of the per-pixel disagreement between the ground reference and AVHRR maps involved areas identified as forest in the 1970s and as nonforest in 1990.

Nelson, R.↗

Combined Use of Airborne Lidar and DBInSAR Data to Estimate LAI in Temperate Mixed Forests

The objective of this study was to determine whether leaf area index (LAI) in temperate mixed forests is best estimated using multiple-return airborne laser scanning (lidar) data or dual-band, single-pass interferometric synthetic aperture radar data (from GeoSAR) alone, or both in combination. In situ measurements of LAI were made using the LiCor LAI-2000 Plant Canopy Analyzer on 61 plots (21 hardwood, 36 pine, 4 mixed pine hardwood; stand age ranging from 12-164 years; mean height ranging from 0.4 to 41.2 m) in the Appomattox-Buckingham State Forest, Virginia, USA. Lidar distributional metrics were calculated for all returns and for ten one meter deep crown density slices (a new metric), five above and five below the mode of the vegetation returns for each plot. GeoSAR metrics were calculated from the X-band backscatter coefficients (four looks) as well as both X- and P-band interferometric heights and magnitudes for each plot. Lidar metrics alone explained 69% of the variability in LAI, while GeoSAR metrics alone explained 52%. However, combining the lidar and GeoSAR metrics increased the R2 to 0.77 with a CV-RMSE of 0.42. This study indicates the clear potential for X-band backscatter and interferometric height (both now available from spaceborne sensors), when combined with small-footprint lidar data, to improve LAI estimation in temperate mixed forests.

leaf area index↗

Information content of simulated space photographs as a function of various levels of image resolution.

The results of research are reported on the information content in simulated space photographs derivable as a function of various levels of image resolution. Whenever certain resource features could not be consistently identified on simulated low-resolution imagery, attempts were made to define the required level of image resolution that would allow a skilled interpreter to discriminate one feature from another. The results of this research, conducted within a chaparral-hardwood-grassland environment in California, indicate that simulated ERTS data contain sufficient information to allow an interpreter to discriminate between woody vegetation, grassland, and water bodies. However, if more detailed information is desired, the imagery must have a ground resolution of at least 50 ft, showing shape, size, texture, and shadow characteristics within each vegetation type. Spaceborne data, therefore, often will have to be supplemented by higher resolution aircraft imagery, depending on the types of resource information being sought.

Lauer, D. T.↗

Phenology satellite experiment

The author has identified the following significant results. The detection of a phenological event (the Brown Wave-vegetation sensescence) for specific forest and crop types using ERTS-1 imagery is described. Data handling techniques including computer analysis and photointerpretation procedures are explained. Computer analysis of multspectral scanner digital tapes in all bands was used to give the relative changes of spectral reflectance with time of forests and specified crops. These data were obtained for a number of the twenty-four sites located within four north-south corridors across the United States. Analysis of ground observation photography and ERTS-1 imagery for sites in the Appalachian Corridor and Mississippi Valley Corridor indicates that the recession of vegetation development can be detected very well. Tentative conclusions are that specific phenological events such as crop maturity or leaf fall can be mapped for specific sites and possible for different regions. Preliminary analysis based on a number of samples in mixed deciduous hardwood stands indicates that as senescence proceeds both the rate of change and differences in color among species can be detected. The results to data show the feasibility of the development and refinement of phenoclimatic models.

Dethier, B. E.↗

The use of multispectral sensing techniques to detect ponderosa pines trees under stress from insects or diseases

The detection of stress induced by bark beetles in conifers is reviewed in two sections: (1) the analysis of very small scale aerial photographs taken by NASA's RB-57F aircraft on August 10, 1969, and (2) the analysis of multispectral imagery obtained by the optical-mechanical line scanner. Underexposure of all films taken from the RB-57 aircraft and inadequate flight coverage prevented drawing definitive conclusions regarding optimum scales and film combinations to detect the discolored infestations. Preprocessing of the scanner signals by both analog and digital computers improved the accuracy of target recognition. Selection and ranking of the best channels for signature recognition was the greatest contribution of digital processing. Improvements were made in separating hardwoods from conifers and old-kill pine trees from recent discolored trees and from healthy trees, but accuracy of detecting the green infested trees is still not acceptable on either the SPARC or thermal-contouring processor. From six years of experience in processing line scan data it is clear that the greatest gain in previsual detection of stress will occur when registered multispectral data from a single aperture or common instantaneous field of view scanner system can be collected and processed.

Heller, R. C.↗

Unsupervised classification and areal measurement of land and water coastal features on the Texas coast

Multispectral scanner (MSS) digital data from ERTS-1 was used to delineate coastal land, vegetative, and water features in two portions of the Texas Coastal Zone. Data (Scene ID's 1037-16244 and 1037-16251) acquired on August 29, 1972, were analyzed on NASA Johnson Space Center systems through the use of two clustering algorithms. Seventeen to 30 spectrally homogeneous classes were so defined. Many classes were identified as being pure features such as water masses, salt marsh, beaches, pine, hardwoods, and exposed soil or construction materials. Most classes were identified to be mixtures of the pure class types. Using an objective technique for measuring the percentage of wetland along salt marsh boundaries, an analysis was made of the accuracy of areal measurement of salt marshes. Accuracies ranged from 89 to 99 percent. Aircraft photography was used as the basis for determining the true areal size of salt marshes in the study sites.

Flores, L. M.↗

Automatic photointerpretation for land use management in Minnesota

The author has identified the following significant results. The Minnesota Iron Range area was selected as one of the land use areas to be evaluated. Six classes were selected: (1) hardwood; (2) conifer; (3) water (including in mines); (4) mines, tailings and wet areas; (5) open area; and (6) urban. Initial classification results show a correct classification of 70.1 to 95.4% for the six classes. This is extremely good. It can be further improved since there were some incorrect classifications in the ground truth.

Swanlund, G. D.↗

Vegetation boundaries on ERTS-1 imagery

Comparison of systems corrected ERTS-1 imagery and microdensitometer scan printouts derived from them with base vegetation maps and current 1:120,000 and 1:60,000 scale imagery of the Great Smoky Mountains is in progress. It reveals good separation of the spruce-fir forest from the other forest areas but band seven does not distinguish between hardwood and heath dominated vegetation.

Deselm, H. R.↗

Timber type separability in Southeastern United States on LANDSAT-1 MSS data

A quantitative, computer-aided study was made on the spectral separability of timber types and condition classes in the Southeastern United States, using LANDSAT-1 multispectral scanner data. It was concluded that LANDSAT-1 could be used effectively to discriminate the gross forest features of softwood, hardwood, and regeneration. The only significant detectable age difference would be between an established forest versus a young (or denuded) forest. The red or near infrared bands would be better for discrimination; phenological early and late spring data would be better than winter. And a temporal analysis would be superior to single-season analysis. Lastly, two spectral bands would be most cost effective for computer analysis. The study site was Sam Houston National Forest of East Texas, a typical forest in the Flatwoods Zone, Southern Region, U. S. Forest Service.

Kan, E. P.↗