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At least 199 records · Page 11

Regional Rates of Young US Forest Growth Estimated From Annual Landsat Disturbance History and IKONOS Stereo Imagery

Forests of the Contiguous United States (CONUS) have been found to be a large contributor to the global atmospheric carbon sink. The magnitude and nature of this sink is still uncertain and recent studies have sought to define the dynamics that control its strength and longevity. The Landsat series of satellites has been a vital resource to understand the long-term changes in land cover that can impact ecosystem function and terrestrial carbonstock. We combine annual Landsat forest disturbance history from 1985 to 2011 with single date IKONOS stereoimagery to estimate the change in young forest canopy height and above ground live dry biomass accumulation for selected sites in the CONUS. Our approach follows an approximately linear growth rate following clearing over short intervals and does not estimate the distinct non-linear growth rate over longer intervals.We produced canopy height models by differencing digital surface models estimated from IKONOS stereo pairs with national elevation data (NED). Correlations between height and biomass were established independently using airborne LiDAR, and then applied to the IKONOS-estimated canopy height models. Graphing current biomass against time since disturbance provided biomass accumulation rates. For 20 study sites distributed across five regions of the CONUS, 19 showed statistically significant recovery trends (p is less than 0.001) with canopy growth from 0.26 m yr-1to 0.73 m yr-1. Above ground live dry biomass (AGB) density accumulation ranged from 1.31 t/ha yr-1 to 12.47 t/ha yr-1. Mean forest AGB accumulationwas 6.31 t/ha yr-1 among all sites with significant growth trends. We evaluated the accuracy of our estimates by comparing to field estimated site index curves of growth, airborne LiDAR data, and independent model predictions of C accumulation. Growth estimates found with this approach are consistent with site index curves and total biomass estimates fall within the range of field estimates. This is aviable approach to estimate forest biomass accumulation in regions with clear-cut harvest disturbances.

Neigh, Christopher S. R.↗

Colorado Front Range Disasters: Understanding the Impact of Forest Management on the Cameron Peak and CalWood Fire

Along the Colorado Front Range, forest management has gained significant attention due to uncharacteristically large fires that burned late in 2020. The Cameron Peak Fire (largest in Colorado recorded history) and the CalWood Fire collectively burned an estimated 219,019 acres from August through December of 2020. Project partners at the Coalition for the Poudre River Watershed, Colorado State Forest Service, Ben Delatour Scout Ranch, The Nature Conservancy, Colorado Forest Restoration Institute, and Colorado State University were interested in understanding the effectiveness of previous forest treatments in reducing burn severity within the Cameron Peak Fire and the CalWood Fire. We first collated a forest treatment dataset from pre-existing datasets by reclassifying over 29,000 treatments, which occurred across the Northern Colorado Front Range between 1970-2020. Secondly, we mapped three burn severity indices using Landsat 8 OLI and Sentinel-2 MSI Earth observations and compared them to soil burn severity field data. Thirdly, a total of 35 topographic, disturbance, forest structure, and treatment predictor variables were generated across the fires. Finally, we assessed relationships between these predictor variables and burn severity using the random forest algorithm. Model results indicate that the primary drivers of burn severity were elevation and distance to treatment edge for the Cameron Peak Fire and fire area and forest canopy cover for the CalWood Fire. Further analysis of these variables paired with field data is necessary to understand the relationship between burn severity and treatments to guide future restoration efforts, improve forest resiliency, and mitigate fire risks.

Neal Swayze↗

Development of SMAP Retrievals for Forested Regions: SMAPVEX19-22 and SMAPVEX22-Boreal

The retrieval of soil moisture (SM) under forest canopy has long been an important goal for low frequency remote sensing. The NASA Soil Moisture Active Passive (SMAP) mission is engaged at three separate experiment sites to improve its SM retrieval algorithm in forested areas. Two of the sites are located in the deciduous forest region in Massachusetts and New York, US and one is located in southern boreal forest zone in Saskatchewan, Canada. Each site has a SM measurement network of about 20 stations spread out over an area of about 30 km, which covers the SMAP radiometer footprint. In 2022, intensive observations will be carried out at each site which involve deployments of an airborne instrument, which is similar to the SMAP instrument, and intensive manual measurements of SM, surface and vegetation. The measurements also include tower-based radiometer observations with ground truth measurements within the instrument footprint. Here we show some early results using the networks and SMAP measurements to analyze the sensitivity of the SMAP L-band measurements to SM changes in forested area and the impact of the vegetation to the signal. The results suggest an upper limit for vegetation attenuation accounting for surface roughness effect and relate that to the values used in the current SMAP SM products.

Yueh, Simon H.↗

(abstract) Characterization of Tree Water Status and Dielectric Constant Changes of North American Boreal Forests in Combination with Synthetic Aperture Radar Remote Sensing

The occurrence and magnitude of temporal and spatial tree water status changes in the boreal environment were studied in a floodplain forest in Alaska and in four forest types of Central Canada. Under limited water supply conditions from the rooted soil zone in early spring (freeze/thaw transition) and during summer, trees show declining water potentials. Coincidental change in tree water potential, tree transpiration and tree dielectric constant had been observed in previous studies performed in Mediterranean ecotones. If radar is sensitive to chances in tree water status as reflected through changes in dielectric constant, then radar remote sensing could be used to monitor the water status of forests. The SAR imagery is examined to determine the response of the radar backscatter to the ground based observations of the water status of forest canopies. Comparisons are made between stands and also along the large North-South gradient between sites. Data from SAR are used to examine the radar response to canopy physiological state as related to vegetation freeze/thaw and growing season length.

remote sensing imaging↗

The atmospheric sulfur cycle over the Amazon Basin. II - Wet season

The fluxes and concentrations of atmospheric sulfur species were determined at ground level and from aircraft over the Amazon Basin during the 1987 wet season, providing a comprehensive description of the sulfur cycle over a remote tropical region. The vertical profile of dimethylsulfide (DMS) during the wet season was found to be very similar to that measured during the dry season, suggesting little seasonal variation in DMS fluxes. The concentrations of H2S were almost an order of magnitude higher than those of DMS, which makes H2S the most important biogenic source species in the atmosheric sulfur cycle over the Amazon Basin. Using the gradient-flux approach, the flux of DMS at the top of the tree canopy was estimated. The canopy was a source of DMS during the day, and a weak sink during the night. Measurements of sulfur gas emissions from soils, using the chamber method, showed very small fluxes, consistent with the hypothesis that the forest canopy is the major source of sulfur gases. The observed soil and canopy emission fluxes are similar to those measured in temperate regions. The concentrations of SO2 and sulfate aerosol in the wet season atmosphere were similar to dry season values.

Andreae, M. O.↗

Exploring the remote sensing of foliar biochemical concentrations with AVIRIS data

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data shows promise for the estimation of foliar biochemical concentrations at the scale of the canopy. There are, however, several problems associated with the use of AVIRIS data in this way and these are detailed in recent Plant Biochemical Workshop Report. The research reported was concentrated upon three of these problems: field sampling of forest canopies, wet laboratory assay of foliar chemicals, and the visualization of AVIRIS data.

Smith, Geoffrey M.↗

View Angle Effects on MODIS Snow Mapping in Forests

Binary snow maps and fractional snow cover data are provided routinely from MODIS (Moderate Resolution Imaging Spectroradiometer). This paper investigates how the wide observation angles of MODIS influence the current snow mapping algorithm in forested areas. Theoretical modeling results indicate that large view zenith angles (VZA) can lead to underestimation of fractional snow cover (FSC) by reducing the amount of the ground surface that is viewable through forest canopies, and by increasing uncertainties during the gridding of MODIS data. At the end of the MODIS scan line, the total modeled error can be as much as 50% for FSC. Empirical analysis of MODIS/Terra snow products in four forest sites shows high fluctuation in FSC estimates on consecutive days. In addition, the normalized difference snow index (NDSI) values, which are the primary input to the MODIS snow mapping algorithms, decrease as VZA increases at the site level. At the pixel level, NDSI values have higher variances, and are correlated with the normalized difference vegetation index (NDVI) in snow covered forests. These findings are consistent with our modeled results, and imply that consideration of view angle effects could improve MODIS snow monitoring in forested areas.

MODIS↗

Relationship of Thematic Mapper simulator data to leaf area index of temperate coniferous forests

Regional relationships between remote sensing data and the leaf area index (LAI) of coniferous forests were analyzed using data acquired by an Airborne Thematic Mapper. Eighteen coniferous forest stands with a range of projected leaf area index of 0.6-16.1 were sampled from an environmental gradient in moisture and temperature across west-central Oregon. Spectral radiance measurements to account for atmospheric effects were acquired above the canopies from a radiometer mounted on a helicopter. A strong positive relationship was observed between LAI of closed canopy forest stands and the ratio of near-infrared and red spectral bands. A linear regression based on LAI explained 83 percent of the variation in the ratio of the atmospherically corrected bands. A log-linear equation fit the asymptotic characteristic of the relationship better, explaining 91 percent of the variance. The positive relationship is explained by a strong asymptotic inverse relationship between LAI and red radiation and a relatively flat response between LAI and near-infrared radiation.

Peterson, David L.↗

Polarimetric radar measurements of a forested area near Mt. Shasta

The authors present the results of an experiment using the NASA/JPL DC-8 AIRSAR (aircraft synthetic-aperture radar) over a coniferous forest near Mt. Shasta (California) in 1989. Calibration devices were deployed in clearings and under the forest canopy and passes at 20, 40, and 55 deg incidence angles were made with the AIRSAR. A total of eight images at differing incidence angles have been processed and calibrated. The multipolarization, multifrequency data were examined, and it was found that the C-band cross section averaged over like and cross polarizations is the best parameter for distinguishing between two stands with differing forest biomass. The average cross section at P- and L-bands is useful only for smaller incidence angles. Parameters describing the polarization behavior of the scattering were primarily useful in identifying the dominant scattering mechanisms for forest backscatter. It was found that both branch scattering and ground/tree interactions are important at P-band. At L-band and C-bands, the return is primarily from the canopy. Comparison with model calculations verified this conclusion.

Durden, Stephen L.↗

Investigation of techniques for inventorying forested regions. Volume 2: Forestry information system requirements and joint use of remotely sensed and ancillary data

The author has identified the following significant results. Effects of terrain topography in mountainous forested regions on LANDSAT signals and classifier training were found to be significant. The aspect of sloping terrain relative to the sun's azimuth was the major cause of variability. A relative insolation factor could be defined which, in a single variable, represents the joint effects of slope and aspect and solar geometry on irradiance. Forest canopy reflectances were bound, both through simulation, and empirically, to have nondiffuse reflectance characteristics. Training procedures could be improved by stratifying in the space of ancillary variables and training in each stratum. Application of the Tasselled-Cap transformation for LANDSAT data acquired over forested terrain could provide a viable technique for data compression and convenient physical interpretations.

Nalepka, R. F.↗

Determining successional stage of temperate coniferous forests with Landsat satellite data

Thematic Mapper (TM) digital imagery was used to map forest successional stages and to evaluate spectral differences between old-growth and mature forests in the central Cascade Range of Oregon. Relative sun incidence values were incorporated into the successional stage classification to compensate for topographic induced variation. Relative sun incidence improved the classification accuracy of young successional stages, but did not improve the classification accuracy of older, closed canopy forest classes or overall accuracy. TM bands 1, 2, and 4; the normalized difference vegetation index; and TM 4/3, 4/5, and 4/7 band ratio values for o|d-growth forests were found to be significantly lower than the values of mature forests. The Tasseled Cap features of brightness, greenness, and wetness also had significantly lower old-growth values as compared to mature forest values .

Fiorella, Maria↗

Determining successional stage of temperate coniferous forests with Landsat satellite data

Thematic Mapper (TM) digital imagery was used to map forest successional stages and to evaluate spectral differences between old-growth and mature forests in the central Cascade Range of Oregon. Relative sun incidence values were incorporated into the successional stage classification to compensate for topographic induced variation. Relative sun incidence improved the classification accuracy of young successional stages, but did not improve the classification accuracy of older, closed canopy forest classes or overall accuracy. TM bands 1, 2, and 4; the normalized difference vegetation index (NDVI); and TM 4/3, 4/5, and 4/7 band ratio values for old-growth forests were found to be significantly lower than the values of mature forests (P less than or equal to 0.010). Wetness and the TM 4/5 and 4/7 band ratios all had low correlations to relative sun incidence (r(exp 2) less than or equal to 0.16). The TM 4/5 band ratio was named the 'structural index' (SI) because of its ability to distinguish between mature and old-growth forests and its simplicity.

Fiorella, Maria↗

Combining MODIS LAI with ICESat-Based Canopy Heights Improves Spaceborne Estimates of Vegetation Roughness Length for Momentum

Most land-surface models require parameterization of vertical wind profiles within the atmospheric boundary layer. For vegetated surfaces, it is common to assume a logarithmic profile in the surface layer, which includes estimates of vegetation roughness length for momentum (z0) and zero-plane displacement height (d0). This study finds that remotely-sensed forest canopy heights improve estimates of aerodynamic roughness length for momentum using a previously-developed representation of the roughness sublayer (Raupach 1992; Jasinski et al. 2005). Resulting roughness products consist of two datasets: 1) 14 years of 8-day snapshots of the global land surface at a nominal spatial resolution of 500-meters for users who wish to retain full temporal resolution and interannual variability; and 2) multiyear averages of the 8-day snapshots, here referred to as "climatologies" of roughness, which retain underlying seasonality. Both products are suitable for use in data assimilation and reanalyses such as the National Climate Assessment Land Data Assimilation System (NCA-LDAS), for which these products were initially developed.

Borak, Jordan S.↗

Identification of terrain cover using the optimum polarimetric classifier

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow-covered fields is developed using the optimum polarimetric classifier. The covariance matrices for various terrain cover are computed from theoretical models of random medium by evaluating the scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Analytical and Monte Carlo simulated classification errors using the fully polarimetric feature vector are compared with classification based on single features which include the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements.

Kong, J. A.↗

Remote sensing of earth terrain

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow covered fields is developed using the optimum polarimetric classifier. The covariance matrices for the various terrain cover are computed from theoretical models of random medium by evaluating the full polarimetric scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Theoretical probability of classification error using the full polarimetric matrix are compared with classification based on single features including the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements.

Kong, J. A.↗

Remote sensing of earth terrain

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow covered fields is developed using the optimum polarimetric classifier. The covariance matrices for the various terrain covers are computed from the theoretical models of random medium by evaluating the full polarimetric scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Theoretical probability of classification error using the full polarimetric matrix are compared with classification based on single features including the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements. A systematic approach is presented for obtaining the optimal polarimetric matched filter which produces maximum contrast between two scattering classes, each represented by its respective covariance matrix.

Kong, J. A.↗

Development of an L-, C-, and X-band radar for backscattering studies over vegetation

With the recent surge of interest in global change, the impact of different ecosystems on the Earth's carbon budget has become the focus of many scientific studies. Studies have been launched by NASA and other agencies to address this issue. One such study is the Boreal Ecosystem-Atmosphere Study (BOREAS). BOREAS focuses on the boreal ecosystem in Northern Canada. As a part of the BOREAS study, we have developed a helicopter-borne three-band radar system for measuring the scattering coefficient of various stands within the boreal forest. During the summer of 1994 the radar was used at the southern study area (SSA) in Saskatchewan over the young jack pine (YJP), old jack pine (OJP), old black spruce (OBS) and old aspen (OA) sites. The data collected will be used to study the interaction of microwaves with forest canopy. By making use of three different frequency bands the contribution to the backscatter from each of the layers within the canopy can be determined. Using the knowledge gained from these studies, we will develop algorithms to enable more accurate interpretation of SAR images of the boreal region. This report describes in detail the development of the L-, C- and X-band radar system. The first section provides background information and explains the objectives of the boreal forest experiment. The second section describes the design and implementation of the radar system. All of the subsystems of the radar are explained in this section. Next, problems that were encountered during system testing and the summer experiments are discussed. System performance and results are then presented followed by a section on conclusions and further work.

Lockhart, G. Lance↗

Forest discrimination with multipolarization imaging radar

The use of radar polarization diversity for discriminating forest canopy variables on airborne synthetic-aperture radar (SAR) images is evaluated. SAR images were acquired at L-Band (24.6 cm) simultaneously in four linear polarization states (HH, HV, VH, and VV) in South Carolina on March 1, 1984. In order to relate the polarization signatures to biophysical properties, false-color composite images were compared to maps of forest stands in the timber compartment. In decreasing order, the most useful correlative forest data are stand basal area, forest age, site condition index, and forest management type. It is found that multipolarization images discriminate variation in tree density and difference in the amount of understory, but do not discriminate between evergreen and deciduous forest types.

Ford, J. P.↗