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NASA NTRS2020

The bioclimatic extent and pattern of the cold edge of the boreal forest: the circumpolar taiga-tundra ecotone

Current configurations of forest structure at the cold edge of the boreal may help understand the future of ecosystem functioning in high northern latitudes. The circumpolar biome boundary at the boreal (taiga) forest and tundra interface is an ecological transition zone (taiga-tundra ecotone; TTE) experiencing changes that affect its forest structure. We accounted for the TTE's horizontal forest structure with an estimate of its extent and pattern as represented by tree canopy cover (TCC). We quantified TCC patterns with an algorithm that describes its spatial gradient, and summarized landscape patterns of structure to represent heterogeneity, capturing abrupt, diffuse, and uniform forest at mesoscales. We used these landscape patterns to constrain the spatial extent of sparse and open canopy forest, and non-forest (forest-adjacent) edge that defines the TTE extent. The resulting map of the TTE extent is based on forest structure spatial patterns resolved at 30 m, highlights structural variability across landscapes, and helps distinguish tundra from boreal domains. We classified 14 594 landscapes as those associated with the TTE within a circumpolar bioclimatic envelope (11.575 million km2), where 44.83% of the area of these landscapes were forest and non-forest edge, yet 36.43% contributed to the TTE extent. We report the overall extent of the TTE (3.032 million km2) across North America and Greenland (53%), and Eurasia (47%), where 0.697 million km2 is non-forest edge, 0.549 million km2 is sparse forest, and 1.787 million km2 is open canopy forest. Diffuse forest landscapes dominate the TTE (79%), and abrupt landscapes (~19%) indicate portions of the TTE where sparse forest and non-forest edge are the prevailing structural patterns. This account of the TTE quantifies the area of the cold edge of the boreal forest where previous global estimates show high discrepancies, and can help target monitoring and prediction of circumpolar dynamics.

Paul M Montesano↗

NASA NTRS2021

Simulation of Solar-Induced Chlorophyll Fluorescence from 3D Canopies with the Dart Model

The potential of solar-induced chlorophyll fluorescence (SIF) to monitor photosynthesis and plant stress has attracted considerable interest in SIF remote sensing (RS). However, canopy SIF and RS observations are impacted by topography, vegetation three dimension (3D) structure, leaf orientation, non foliar elements (e.g., tree woody skeleton), ... Physically based downscaling of canopy SIF RS data to leaf-level (i.e., to leaf photosynthesis) requires 3D radiative transfer (RT) models simulating canopy SIF and its observation. These models are necessary to better exploit the potential of SIF, by linking leaf SIF and SIF in RS observations as a function of canopy 3D architecture and experimental configurations (sun and viewing directions, etc.). The Discrete Anisotropic Radiative Transfer (DART) model is a comprehensive 3D radiative transfer (RT) model for urban and natural landscapes. This paper presents its SIF modeling for vegetation simulated with facets, its validation with the SCOPE/mSCOPE 1D models, and its recent extension to SIF modelling for landscapes simulated with 3D turbid medium.

radiative transfer↗

NASA NTRS2021

Simulation of Solar-Induced Chlorophyll Fluorescence from 3D Canopies with the Dart Model

Radiative transfer↗

NASA NTRS2016

Scaling Estimates of Vegetation Structure in Amazonian Tropical Forests Using Multi-Angle MODIS Observations

Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r(exp 2)= 0.54, RMSE= 0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy(0.52 less than or equal to r(exp 2) less than or equal to 0.61; p less than 0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (sigma(sup 0)) from SeaWinds/QuikSCAT presented an r(exp 2) of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon.

MODIS↗

NASA NTRS1981

Soybean canopy reflectance as a function of view and illumination geometry

Reflectances were calculated from measurements at four wavelength bands through eight view azimuth and seven view zenith directions, for various solar zenith and azimuth angles over portions of three days, in an experimental characterization of a soybean field by means of its reflectances and physical and agronomic attributes. Results indicate that the distribution of reflectance from a soybean field is a function of the solar illumination and viewing geometry, wavelength, and row direction, as well as the state of canopy development. Shadows between rows were found to affect visible wavelength band reflectance to a greater extent than near-IR reflectance. A model describing reflectance variation as a function of projected solar and viewing angles is proposed, which approximates the visible wavelength band reflectance variations of a canopy with a well-defined row structure.

Ranson, K. J.↗

NASA NTRS2023

Invasion in the Niger Delta: Remote Sensing of Mangrove Conversion to Invasive Nypa fruticans from 2015-2020

Invasive species are a leading threat to biodiversity worldwide. Nypa palm ( Nypa fruticans ) has emerged as the predominant invasive species in the Niger Delta region of Nigeria. While endemic mangroves have high rates of carbon sequestration, stabilize coastlines, and protect biodiversity, Nypa does not provide these services outside its native region of Southeast Asia. Oil exploration and urbanization in this region also exacerbates mangrove loss and Nypa spread. As Nypa is difficult to distinguish from endemic mangrove species in remotely sensed data, estimates of mangrove and ecosystem services losses in Nigeria are highly uncertain. Here, we analyze multisensor satellite data with machine learning to quantify the rapid expansion of Nypa from 2015-2020 in Nigeria. Using Landsat imagery and random forest classification, we quantify total potential Nypa extent in Nigeria in 2019. We then produced a Nypa extent map using iterative combinations of Sentinel-1 SAR, Sentinel-2 MSI, and ALOS PALSAR. Random forest classifications using SAR data from ALOS and Sentinel-1 were best suited for mapping Nypa extent with similar accuracies (78% and 75% respectively). Based on data availability and accuracy, we focused our change analysis on Sentinel-1 SAR. Our results show ~28,000 ha of mangroves were converted to Nypa in Nigeria by 2020 and covered a larger extent than endemic mangroves, compounding the effect of the existing degradation and deforestation in the region. We also compared forest height and complexity estimates from GEDI (Global Ecosystem Dynamics Investigation) LiDAR to further distinguish between endemic mangroves and Nypa in three dimensions. Nypa structural variability, measured by top-of-canopy height, vegetation cover, plant area index, and foliage height diversity, was lower than that of mangroves. At current rates of Nypa expansion, the entire area of study would be invaded by Nypa by 2028, with potentially detrimental consequences to the ecosystem services provided by mangroves.

GEE↗

NASA NTRS2014

Deciphering the Precision of Stereo IKONOS Canopy Height Models for U.S. Forests with G-LiHT Airborne LiDAR

Few studies have evaluated the precision of IKONOS stereo data for measuring forest canopy height. The high cost of airborne light detection and ranging (LiDAR) data collection for large area studies and the present lack of a spaceborne instrument lead to the need to explore other low cost options. The US Government currently has access to a large archive of commercial high-resolution imagery, which could be quite valuable to forest structure studies. At 1 m resolution, we here compared canopy height models (CHMs) and height data derived from Goddard's airborne LiDAR Hyper-spectral and Thermal Imager (G-LiHT) with three types of IKONOS stereo derived digital surface models (DSMs) that estimate CHMs by subtracting National Elevation Data (NED) digital terrain models (DTMs). We found the following in three different forested regions of the US after excluding heterogeneous and disturbed forest samples: (1) G-LiHT DTMs were highly correlated with NED DTMs with R (sup 2) greater than 0.98 and root mean square errors (RMSEs) less than 2.96 m; (2) when using one visually identifiable ground control point (GCP) from NED, G-LiHT DSMs and IKONOS DSMs had R (sup 2) greater than 0.84 and RMSEs of 2.7 to 4.1 m; and (3) one GCP CHMs for two study sites had R (sup 2) greater than 0.7 and RMSEs of 2.6 to 3 m where data were collected less than four years apart. Our results suggest that IKONOS stereo data are a useful LiDAR alternative where high-quality DTMs are available.

IKONOS↗

NASA NTRS2011

Measuring Effective Leaf Area Index, Foliage Profile, and Stand Height in New England Forest Stands Using a Full-Waveform Ground-Based Lidar

Effective leaf area index (LAI) retrievals from a scanning, ground-based, near-infrared (1064 nm) lidar that digitizes the full return waveform, the Echidna Validation Instrument (EVI), are in good agreement with those obtained from both hemispherical photography and the Li-Cor LAI-2000 Plant Canopy Analyzer. We conducted trials at 28 plots within six stands of hardwoods and conifers of varying height and stocking densities at Harvard Forest, Massachusetts, Bartlett Experimental Forest, New Hampshire, and Howland Experimental Forest, Maine, in July 2007. Effective LAI values retrieved by four methods, which ranged from 3.42 to 5.25 depending on the site and method, were not significantly different ( b0.1 among four methods). The LAI values also matched published values well. Foliage profiles (leaf area with height) retrieved from the lidar scans, although not independently validated, were consistent with stand structure as observed and as measured by conventional methods. Canopy mean top height, as determined from the foliage profiles, deviated from mean RH100 values obtained from the Lidar Vegetation Imaging Sensor (LVIS) airborne large-footprint lidar system at 27 plots by .0.91 m with RMSE=2.04 m, documenting the ability of the EVI to retrieve stand height. The Echidna Validation Instrument is the first realization of the Echidna lidar concept, devised by Australia's Commonwealth Scientific and Industrial Research Organization (CSIRO), for measuring forest structure using full-waveform, ground-based, scanning lidar.

Zhao, Feng↗

NASA NTRS1971

Leaf light reflectance, transmittance, absorptance, and optical and geometrical parameters for eleven plant genera with different leaf mesophyll arrangements.

Review of research on radiation interactions within plant canopies and communities and interactions of various leaf structures (mesophyll arrangements) with electromagnetic radiation involved in the interpretation of data sensed from air or spacecraft. The hypothesis underlying the research reported is that leaf mesophyll arrangements influence spectral energy measurements of leaves.

Gausman, H. W.↗

NASA NTRS1991

Relating the temporal change observed by AIRSAR to surface and canopy properties of mixed conifer and hardwood forests of northern Michigan

The mixed hardwood and conifer forests of northern Michigan were overflown by a 3-frequency airborne imaging radar in Apr. and Jul. 1990. A set of 10 x 10 km test sites near the University of Michigan Biological Station at Douglas Lake and within the Hiawatha National Forest in the upper peninsula of Michigan contained training stands representing the various forest species typical of forest communities across the ecotone between the coniferous boreal forest and mid-latitude hardwood and coniferous forests. The polarimetric radar data were externally calibrated to allow interdate comparisons. The Apr. flight was prior to bud-break of deciduous species and patchy snowcover was present. The Jul. flights occurred during and 2 days after heavy rain showers, and provide a unique opportunity to examine the differences in radar backscatter attributable to intercepted precipitation. Analyses show that there are significant changes in backscattering between biophysically dissimilar forest stands on any given date and also between dates for a given forest stand. These differences in backscattering can be related to moisture properties of the forest floor and the overlying canopy and also to the quantity and organizational structure of the above-ground biomass.

Dobson, M. Craig↗

NASA NTRS1992

Multitemporal diurnal AVIRIS images of a forested ecosystem

Both physiological and ecosystem structural information may be derived from diurnal images. Structural information may be inferred from changes in canopy shadows between images and from changes in spectral composition due to changes in proportions of subpixel mixing resulting from the differences in sun/view angles. Physiological processes having diurnal scales also may be measurable if a stable basis for spectral comparison can be established. Six diurnal images of an area east of Mt. Shasta, CA were acquired on 22 Sep. 1989. This unique diurnal data set provided an opportunity to test the consistency of endmember fractions and residuals. It was expected that shade endmember abundances would show the greatest change as lighting geometry changed and less change in the normalized fractional proportion of other endmembers. Diurnal changes in spectral features related to physiological characteristics may be identifiable as changes in wavelength specific residuals.

Ustin, Susan L.↗

NASA NTRS1986

Two-flow simulation of the natural light field within a canopy of submerged aquatic plants

A two-flow model is developed to simulate a light field composed of both collimated and diffuse irradiance within natural waters containing a canopy of bottom-adhering plants. To account for the effects of submerging a canopy, the transmittance and reflectance terms associated with each plant structure (leaves, stems, fruiting bodies, etc.) are expressed as functions of the ratio of the refractive index of the plant material to the refractive index of the surrounding media and the internal transmittance of the plant stucture. Algebraic solutions to the model are shown to yield plausible physical explanations for unanticipated variations in volume reflectance spectra. The effect of bottom reflectance on the near-bottom light field is also investigated. These indicate that within light-limited submerged aquatic plant canopies, substrate reflectance may play an important role in determining the amount of light available to the plants and, therefore, canopy productivity.

Ackleson, S. G.↗

NASA NTRS2007

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Al-Hamdan, Mohammad Z.↗

NASA NTRS1984

Geologic interpretation of Seasat SAR imagery near the Rio Lacantum, Mexico

A mosaic of the Seasat Synthetic Aperture Radar (SAR) optically processed images over Central America is presented. A SAR image of the Rio Lacantum area (southeastern Mexico) has been digitally processed and its interpretation is presented. The region is characterized by low relief and a dense vegetation canopy. Surface is believed to be indicative of subsurface structural features. The Seasat-SAR system had a steep imaging geometry (incidence angle 23 + or - 3 deg off-nadir) which is favorable for detection of subtle topographic variations. Subtle textural features in the image corresponding to surface topography were enhanced by image processing techniques. A structural and lithologic interpretation of the processed images is presented. Lineaments oriented NE-SW dominate and intersect broad folds trending NW-SE. Distinctive karst topography characterizes one high relief area

Rebillard, PH.↗

NASA NTRS1987

Atmospheric surface and boundary layers of the Amazon Basin

Three phases of work were performed: design of and preparation for the Amazon Boundary Layer Experiment (ABLE 2-A); execution of the ABLE 2-A field program; and analysis of the ABLE 2-A data. Three areas of experiment design were dealt with: surface based meteorological measurements; aircraft missions; and project meteorological support. The primary goal was to obtain a good description of the structure of the atmosphere immediately above the rain forest canopy (top of canopy to a few thousand meters), to describe this region during the growing daytime phase of the boundary layer; and to examine the nighttime stratified state. A secondary objective was to examine the role that deep convective storms play in the vertical transport of heat, water vapor, and other trace gases. While significant progress was made, much of the analysis remains to be done.

Garstang, Michael↗

NASA NTRS1988

Detecting air pollution stress in southern California vegetation using Landsat Thematic Mapper band data

Landsat Thematic Mapper (TM) and aircraft-borne Thematic Mapper simulator (TMS) data were collected over two areas of natural vegetation in southern California exposed to gradients of pollutant dose, particularly in photochemical oxidants: the coastal sage scrub of the Santa Monica Mountains in the Los Angeles basin, and the yellow pine forests in the southern Sierra Nevada. In both situations, natural variations in canopy closure, with subsequent exposure of understory elements (e.g.,rock or soil, chaparral, grasses, and herbs), were sufficient to cause changes in spectral variation that could obscure differences due to visible foliar injury symptoms observed in the field. TM or TMS data are therefore more likely to be successful in distinguishing pollution injury from background variation when homogeneous communities with closed canopies are subjected to more severe pollution-induced structural and/or compositional change. The present study helps to define the threshold level of vegetative injury detectable by TM data.

Westman, Walter E.↗

NASA NTRS2012

Demonstration of Repeat-Pass POLINSAR Using UAVSAR: The RMOG Model

In this paper we show our first POLINSAR results using the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) developed by the Jet Propulsion Laboratory (JPL). UAVSAR is a L-band repeat-pass polarimetric and interferometric system designed for measuring vegetation structure and monitoring crustal deformations. In order to extract canopy height from POLINSAR data and account for temporal decorrelation, we formulate a physical model of the temporal-volumetric coherence, random motion over ground (RMOG) model. Canopy height extracted from single-baseline UAVSAR data using the RMOG model is shown to be in agreement with canopy height measured by the Land, Vegetation, and Ice Sensor (LVIS) lidar.

polarimetry↗

NASA NTRS1983

Extension of a uniform canopy reflectance model to include row effects

The reflectance model for a uniform crop canopy is extended to include the effects of crops planted in rows. The effect of row structure is assumed to be caused by the variation in density of vegetation across rows rather than to a profile in canopy height. The calculation of crop reflectance using vegetation density modulation across rows follows a parallel procedure to that for a uniform canopy. Predictions using the row model for wheat show that the effect of changes in sun to row azimuth are greatest in Landsat Band 5 (red band) and can result in underestimation of crop biomass.

Suits, G. H.↗