K. Jon Ranson

The Boreal Ecosystem–Atmosphere Study (BOREAS): An Overview and Early Results from the 1994 Field Year

Abstract The Boreal Ecosystem Atmosphere Study (BOREAS) is large-scale international field experiment that has the goal of improving our understanding of the exchanges of radiative energy, heat water, CO2, and trace gases between the boreal forest and the lower atmosphere. An important objective of BORES is collect the data needed to improve computer simulation models of the processes controlling these exchanges so that scientists can anticipate the effects of global change. From August 1993 through September 1994, a continuous set of monitoring measurements—meteorology, hydrology, and satellite remote sensing—were gathered over the 1000 × 1000 km BOREAS study region that covers most of Saskatchewan and Manitoba, Canada. This monitoring program was punctuated by six campaigns that saw the deployment of some 300 scientists and aircrew into the field, supported by 11 research aircraft. The participants were drawn primarily from U.S. and Canadian agencies and universities, although there were also important ...

BOREAS in 1997: Experiment overview, scientific results, and future directions

The goal of the Boreal Ecosystem-Atmosphere Study (BOREAS) is to improve our understanding of the interactions between the boreal forest biome and the atmosphere in order to clarify their roles in global change. This overview paper describes the science background and motivations for BOREAS and the experimental design and operations of the BOREAS 1994 and BOREAS 1996 field years. The findings of the 83 papers in this journal special issue are reviewed. In section 7, important scientific results of the project to date are summarized and future research directions are identified.

Imaging radar for ecosystem studies

Recently a number of satellites have been launched with radar sensors, thus expanding opportunities for global assessment. In this article we focus on the applications of imaging radar, which is a type of sensor that actively generates pulses of microwaves and, in the interval between sending pulses, records the returning signals reflected back to an antenna.

Mapping of boreal forest biomass from spaceborne synthetic aperture radar

As part of the Boreal-Ecosystem Atmosphere Study (BOREAS), an investigation is being made of the use of satellite data including shuttle imaging radar-C (SIR-C), X-band synthetic aperture radar (XSAR), and Landsat-Thematic Mapper data for estimating total and component aboveground woody biomass in boreal forest study sites in Canada. The goal of this paper is to present progress in mapping above ground woody biomass over portions of the BOREAS southern study area using spaceborne sensor data. Relationships of backscatter to total biomass and total biomass to foliage, branch, and bole biomass are used to estimate biomass across the landscape. The procedure involves image classification with SAR and Landsat data and development of simple mapping techniques using combinations of SAR channels. The analysis uses measurements from forest stands representing a range of biomass and structures. Field measurements included plot level mensuration (species, stem diameter, height, density, and basal area) and tree geometry measurements (leaf, branch, bole size, and angle distributions). The results indicate that aboveground biomass can be estimated to within about 1.6 kg/m2 and up to about 15 kg/m2 across the SIR-C image evaluated. A general method produced equivalent results with those obtained by treating forest type (pine, spruce, and aspen) separately. The biomass mapping was extended to bole, branch, and foliage components from relationships with total aboveground biomass developed from detailed tree measurements. Average biomass within the imaged area was estimated to be about 7.3 kg/m2 with biomass components of bole, branch, and foliage comprising 83, 12, and 5% of the total. Examination of the scaling of biomass estimates from remote sensing images of varying resolution shows that information at scales useful for ecosystem models can be obtained. In addition, the biomass estimation technique provides similar information at different image resolutions.

An evaluation of AIRSAR and SIR-C/X-SAR images for mapping northern forest attributes in Maine, USA☆

Abstract In previous work by the authors, multifrequency, polarimetric airborne synthetic aperture radar (AIRSAR) data were used to characterize forest categories and biomass density of a forest area in Maine, USA. This study area was included as a test site for ecological studies during the Spaceborne Imaging Radar C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) missions in 1994. The SIR-C/X-SAR missions provided the first opportunity for Earth scientists to receive multifrequency and multipolarization SAR data from space from a single platform. During the Space Radar Laboratory missions in April and October 1994, images from AIRSAR and SIR-C/X-SAR were acquired for the same areas within a few days of each other. In this paper, the capabilities of AIRSAR and SIR-C/X-SAR images for characterizing a northern hardwood-boreal transitional forest were evaluated and compared. The use of multiple frequency, polarimetric information to produce forest-cover classification, biomass estimates, and forest spatial pattern analysis were investigated. The results from SIR-C/X-SAR compared with those from AIRSAR were generally similar despite different available frequencies (C-band, L-band, X-band vs. C-band, L-band, P-band) and resolution (25.0 m vs. 8.3 m). AIRSAR data better enabled the mapping of stands of hardwood and mixed forests than did SIR-C/X-SAR data. However, SIR-C/X-SAR produced better classification results for conifer forest stands. There was no great benefit from using higher resolution for classification except for forest stands in which there were mixtures of species (i.e., hardwood and softwood). A comparison of the image data also showed that both instruments could provide reasonable estimates of biomass density up to about 15 kg/m 2 . At higher biomass levels, both AIRSAR and SIR-C showed the well-known biomass saturation effect. The average biomass densities determined from the AIRSAR and SIR-C images were reasonably close at 9.7 kg/m 2 and 9.0 kg/m 2 , respectively. Finally, spatial character of the image data was examined by using perimeter and area relations and lacunarity analysis. The results were consistent between the two instruments and showed that the forest opening patterns were self-similar for openings greater than about 3 ha.

Multispectral bidirectional reflectance of northern forest canopies with the advanced solid-state array spectroradiometer (ASAS)

Abstract Understanding the bidirectional reflectance characteristics of forest canopies is important for relating remote sensing observations to biomass, species, stand structure, and albedo. Studies of the directional scattering of forest canopies have been limited in the past because of difficulties in suspending instruments over tall canopies or by being restricted to airborne scanning systems. In this article we discuss the use of the Advanced Solid-State Array Spectroradiometer (ASAS) to measure the bidirectional reflectance of several diverse forest canopies. ASAS data were acquired in 1989 and 1990 as part of an extensive field measurement campaign at International Papers Northern Experimental Forest (NEF) located near Howland, Maine. Multiangle data sets were acquired for several sites under clear sky conditions and at view azimuths parallel, oblique, and perpendicular to the principal plane of the sun. The sensor radiance data for several surface types including forest stands and openings were converted to bidirectional reflectance using an atmospheric correction algorithm and optical thickness measurements. In addition, photosynthetically active radiation (PAR) hemispherical reflectance (albedo) was calculated from the corrected ASAS data and compared to a vegetation index. Highest observed reflectance factors were recorded in or near the solar principal plane at viewing geometries approaching the antisolar direction. Minimum reflectances were also observed in the solar principal plane, but in the forward scattered direction. Bidirectional reflectance factors (BRFs) acquired in the backscatter direction at visible wavelengths showed larger percent differences between viewing angles of 45° in the forward and backscattered direction (up to 95%) than near-IR data (up to 60%). The normalized vegetation index (NDVI) also varied with view angle but to a lesser degree than single-band BRFs. Also in contrast to single-band BRFs, maximum NDVI was recorded in the forward scattered direction and minimum NDVI was observed in the backscattered direction. Estimated fraction of absorbed photosynthetically active radiation (FAPAR) was determined from the hemispherical PAR reflectance for several canopy types within the forest area. Examining the relationships with NDVI revealed a strong dependence of NDVI on FAPAR for nadir and 45° forward scattered data. A poor relationship was observed for data acquired at 45° in the backscattered direction and for NDVI derived from hemispherical reflectance. From these results, it is apparent that the sensor viewing geometry that minimizes the contribution of reflectance from branches and the ground will yield higher relationships between FAPAR and NDVI.

Northern forest classification using temporal multifrequency and multipolarimetric SAR images

Abstract Characterizing forest ecosystem dynamics for global change studies requires updated knowledge in terms of species composition, carbon storage, and biophysical functioning. Often, significant areas of forest are obscured by clouds or are under reduced solar illumination conditions, which limit acquisition of optical satellite data. Synthetic aperture radar (SAR) images, however, can be acquired under these conditions. Several SAR image data sets were acquired over the Northern Experimental Forest near Howland, Maine as part of the Forest Ecosystem Dynamics-Multisensor Aircraft Campaign. A SAR data processing and analysis sequence, from calibration through classification, is described. The usefulness of multifrequency temporal polarimetric SAR image data for identifying ecosystem classes is discussed. Our results show that with principal component analysis of temporal data sets (winter and late summer) SAR images can be classified into general forest categories such as softwood, hardwood, regeneration, and clearing with better than 80% accuracy. Other nonforest classes such as bogs, wetlands, grass, and water were also accurately classified. Classifications from single date images suffered in accuracy. The winter image had significant confusion of softwoods and hardwoods with a strong tendency to overestimate hardwoods. Modeling results suggest that increased double-bounce scattering of the radar beam from conifer stands because of lowered dielectric constant of frozen needles and branches was the contributing factor for the misclassifications.

Sensor-fusion field experiment in forest ecosystem dynamics

An extensive multisensor airborne and field campaign was conducted in the Northern Experimental Forest near Bangor, Maine, during September 1989 to acquire a data set to allow us to test various modeling hypotheses concerning the interaction of optical, thermal, and microwave electromagnetic radiation within northern coniferous forest canopies and their underlying backgrounds. This experiment represents a significant component of a Forest Ecosystem Dynamics project, which is concerned with the response of northern forests to climatic and other environmental changes. Extensive ground control information, basic remote-sensing measurements, and comprehensive calibration data were obtained to support the interpretation of numerous airborne sensor measurements and to provide both static and dynamic biophysical input parameters to electromagnetic scattering and absorption models. Aircraft instruments deployed included a multifrequency, quadpolarized synthetic aperture radar, a solid-state array bidirectional imager, and the Thematic Mapper Simulator. In addition, a suite of helicopter-borne nonimaging systems was utilized, consisting of a multifrequency laser polarimeter and both narrow- and broad-band spectrometers. This paper presents background on this first Forest Ecosystems Dynamics field campaign, provides a progress report on the analysis of the collected data and related modeling activities, and outlines plans for future experiments at different points in the phenological cycle.

The proposed DESDynI mission - From science to implementation

The proposed DESDynI mission is being planned by NASA to study earth change in three distinct disciplines - ecosystems, solid earth, and cryospheric sciences. DESDynI would provide unique and unprecedented capabilities to the science community, with an imaging L-band radar proposed to include new modes and observational techniques, and a first-of-a-kind multi-beam lidar for measuring canopy height metrics at fine spatial resolution. Under current planning scenarios, DESDynI could be ready to launch in 2017. In this paper, we describe the science objectives, how these lead to the measurements that achieve these objectives, and how these requirements lead to a mission design. The properties of the radar are then described, including a number of new radar modes and capabilities such as “SweepSAR” scan-on-receive techniques and split-spectrum acquisitions in single and multipol configurations.

Comparative analysis of data acquired by three narrow-band airborne spectroradiometers over subboreal vegetation

Abstract Calibrated radiance data were acquired with three airborne sensor systems on 8 September 1990 over a northern forest as part of the Forest Ecosystem Dynamics Multisensor Aircraft Campaign. The spectral data were acquired nearly simultaneously under extremely clear sky conditions with NASAs AVIRIS and ASAS imaging spectroradiometers, and an SE-590 spectroradiometer mounted on a NASA UH-1B helicopter. After atmospheric corrections were applied to these data, intercomparisons of nadir reflectance factor measurements from each of these sensors were made for four important vegetation communities including a bog and individual forest stands dominated by spruce ( Picea sp.), eastern hemlock ( Tsuga canadensis ), and mixed northern hardwoods (dominated by Acer sp., Populus sp., and Betula sp.), respectively. The reflectance factor spectra from the different instruments were comparable for each of these cover types, suggesting the possible interchangeable use of the three datasets over comparable wavelength regions. These comparisons also serve to graphically illustrate the importance of applying atmospheric corrections to such data, even if acquired under extremely clear sky conditions. This remote sensing data set appears suitable for assessing the applicability of multistage, multisensor data in largescale ecological research.