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A forest inventory project employing computerized classification of LANDSAT data to inventory vegetation types in western Nevada is described. The methodology and applicability of the resulting survey are summarized.
The author has identified the following significant results. The annotation system produced a RMSE of about 200 m ground distance in the MSS data system with the control data used. All the analytical MSS interpretation models tried were highly significant. However, the gains in forest sampling efficiency that can be achieved by using the models vary from zero to over 50 percent depending on the area to which they are applied and the sampling method used. Among the sampling methods tried, regression sampling yielded substantial and the most consistent gains. The single most significant variable in the interpretation model was the difference between bands 5 and 7. The contrast variable, computed by the Hadamard transform was significant but did not contribute much to the interpretation model. Forest areas containing very large timber volumes because of large tree sizes were not separable from areas of similar crown cover but containing smaller trees using ERTS image interpretation only. All correlations between space derived timber volume predictions and estimates obtained from aerial and ground sampling were relatively low but significant and stable. There was a much stronger relationship between variables derived from MSS and U2 data than between U2 and ground data.
In three sites of boreal and temperate forests, P band HH, HV, and VV polarization data combined estimate total aboveground dry woody biomass within 12 to 27% of the values derived from allometric equations, depending on forest complexity. Biomass estimates derived from HV-polarization data only are 2 to 14% less accurate. When the radar operates at circular polarization, the errors exceed 100% over flooded forests, wet or damaged trees and sparse open tall forests because double-bounce reflections of the radar signals yield radar signatures similar to that of tall and massive forests. Circular polarizations, which minimize the effect of Faraday rotation in spaceborne applications, are therefore of limited use for measuring forest biomass. In the tropical rain forest of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 50 kg/sq m in old, undisturbed floodplain stands, the P band horizontal and vertical polarization data combined separate biomass classes in good agreement with forest inventory estimates. The worldwide need for large scale, updated, biomass estimates, achieved with a uniformly applied method, justifies a more in-depth exploration of multi-polarization long wavelength imaging radar applications for tropical forests inventories.
Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse-scale imagery in the heterogeneous aspen parkland was limited. Longer-term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems.
The author has identified the following significant results. At the Atlanta site (226B) it was found that bulk color composites for October 15, 1972, and April 13, 1973, can be interpreted together to disclose the location of the perennial Kudzu vine (Pyeraria lobata). Land managers concerned with Kudzu eradication could use ERTS-1 to inventory locations over 200 meters (660 feet) square. Microdensitometer data collected on ERTS-1 Bulk photographic products for the Manitou test site (226C) have shown that the 15-step gray-scale tablets are not of systematic equal values corresponding to 1/14 the maximum radiant energy incident on the MSS sensor. The gray-scale values present a third-order polynomial function rather than a direct linear relationship. Although data collected on step tablets for precision photographic products appear more discrete, the density variation within blocks in almost as great as variations between blocks. These system errors will cause problems when attempting to analyze radiometric variances among vegetation and land use classes.
Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. The biggest deficiency of the existing ground based forest inventories is the uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse, lacking, and often decades old. Remote sensing methods can help overcome these problems. In this joint US and Russian study, we used the moderate resolution imaging spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) and produced a map of timber volume for a 10degx12deg area in Central Siberia. Using these methods, the mean timber volume for the forested area in the total study area was 203 m3/ ha. The new remote sensing methods used in this study provide a truly independent estimate of forest structure, which is not dependent on traditional ground forest inventory methods.
The author has identified the following significant results. Some current beetle-killed ponderosa pine can be detected on S190-B photography imaged over the Bear Lodge mountains in the Black Hills National Forest. Detections were made on SL-3 imagery (September 13, 1973) using a zoom lens microscope to view the photography. At this time correlations have not been made to all of the known infestation spots in the Bear Lodge mountains; rather, known infestations have been located on the SL-3 imagery. It was determined that the beetle-killed trees were current kills by stereo viewing of SL-3 imagery on one side and SL-2 on the other. A successful technique was developed for mapping current beetle-killed pine using MSS imagery from mission 247 flown by the C-130 over the Black Hills test site in September 1973. Color enhancement processing on the NASA/JSC, DAS system using three MSS channels produced an excellent quality detection map for current kill pine. More importantly it provides a way to inventory the dead trees by relating PCM counts to actual numbers of dead trees.
The author has identified the following significant results. Seventy-two ground sensors were interfaced with three DCP'S at the Black Hills test site. Unfortunately, the transmitters had to be returned for modification and forestry sensed data is not available. The DCP's did operate properly from the Berkeley laboratory and data were recovered from the Goldstone and Alaska stations via Goddard. Replicated training sets and test sets have been selected from all three test site areas in preparation for the receipt of ERTS imagery and digital tapes. From 600 and 800 points have been selected at each site location and UTM coordinates determined. Templates are being made of these sets. As of September 1, ERTS-generated data had not been received and no statements can be made regarding quality or suitability for forest and range experiments. Aerial photography (scale 1:32,000) of the Manitou (226 C) and Black Hills (226 A) sites was taken with CIR in June. Various scales (1:2,000; 1:10,000; 1:20,000; and 1:40,000) of 70 mm photographs were obtained at Manitou with normal color, CIR, and panchromatic in August.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report. Some ERTS-1 imagery has been received for each of the test sites: Black Hills, Atlanta, and Manitou. Only small portions of each site are covered and clouds have precluded capturing good imagery over the center of each site. Discoloration infestations of ponderosa pine are being located and sized on CIR transparencies. A computer program was completed from microdensitometer scans of CIR photos which maps areas of an image which are spectrally similar. Decided differences between forest types are present as well as differences between forest and other vegetative and nonvegetative land classes.
There are no author-identified significant results in this report.
The author has identified the following significant results. Three small scales of CIR photography were interpreted to determine the number of bark beetle-killed trees detected in each of six spot size categories. A procedure was developed to predict the probability of detecting spots in each spot size category and in turn to estimate the number of infestations and dead trees even on the smallest scale. Statistical tests of the data indicated that the linear model did not fit the data and that other models should be tested. As a result of daily monitoring of Black Hills radiometric instruments it was possible to show the spectral energy relationships in the ponderosa pine ecosystems over time. These data have been helpful for comparison with radiance signatures extracted from ERTS-1 bulk 70mm using precision microdensitometry. Effects of atmospheric interference were shown by a 30 percent increase in scene radiance on channel 4 of the satellite imagery. A calibration and scaling technique was developed and tested to enable interpretation of ERTS-1 bulk and precision data for the Atlanta test site. The technique includes calibration of a photographic copy system for the I2S image combiner and the production of scaled overlays of grid coordinate systems, study area locations, and outline maps of county boundaries.
The author has identified the following significant results. Two strips of U-2 RC-10 images were analytically triangulated and adjusted. Control points and pass points were marked on glass plates made from B&W copy negatives of IR color transparencies. A wild PUG-3 and TA1/p monocomparator were used to mark and measure the points on the glass plates. Each plate was measured twice in the same orientation for a check on accuracy and operator error. The 22 photographs were adjusted to 41 ground control and tie points and the block adjustment was performed in a secant plane coordinate system to eliminate the effect of earth curvature. Standard deviations of the residuals of the control and tie points were 12.8 m, 10.8 m, and 4.5 m for the X, Y, and Z coordinates respectively. The 12.8 m and 10.8 m figures correspond to an identification accuracy of 0.1 mm on the U-2 RC-10 plates. The standard deviations of the residuals encountered in the ERTS-1 resectioning were: (1) 0.16 mm assuming uncorrected perspective geometry and (2) 0.12 mm when the polynomial adjustment was added in. These results indicate a reduction of 0.11 in the square error due to the polynomial adjustment.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report.