Estimation of forest parameters using CARABAS-II VHF SAR data

Fransson, Johan E. S.; Walter, F.; Ulander, Lars M. H.

doi:10.1109/36.842001

Cited by 88 publications

(51 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…SAR applies longer wavelength microwave energy, which has stronger penetration than the visible and near infrared bands used by ALS systems and avoids interference caused by cloud cover [46]. SAR data with appropriate wavelengths can detect tree trunks due to strong canopy penetration and the backscatter has a linear relationship with stocking volume even for dense forests [47,48]. The ability of SAR to penetrate the canopy and detect trunks allows lower spatial resolution to meet the requirements for mapping individual trees compared to that required by ALS or multispectral sensors [45].…”

Section: Active Data Sources For Itcdmentioning

confidence: 99%

Trends in Automatic Individual Tree Crown Detection and Delineation—Evolution of LiDAR Data

2016

View full text Add to dashboard Cite

Automated individual tree crown detection and delineation (ITCD) using remotely sensed data plays an increasingly significant role in efficiently, accurately, and completely monitoring forests. This paper reviews trends in ITCD research from 1990-2015 from several perspectives-data/forest type, method applied, accuracy assessment and research objective-with a focus on studies using LiDAR data. This review shows that active sources are becoming more prominent in ITCD studies. Studies using active data-LiDAR in particular-accounted for 80% of the total increase over the entire time period, those using passive data or fusion of passive and active data comprised relatively small proportions of the total increase (8% and 12%, respectively). Additionally, ITCD research has moved from incremental adaptations of algorithms developed for passive data sources to innovative approaches that take advantage of the novel characteristics of active datasets like LiDAR. These improvements make it possible to explore more complex forest conditions (e.g., closed hardwood forests, suburban/urban forests) rather than a single forest type although most published ITCD studies still focused on closed softwood (41%) or mixed forest (22%). Approximately one-third of studies applied individual tree level (30%) assessment, with only a quarter reporting more comprehensive multi-level assessment (23%). Almost one-third of studies (32%) that concentrated on forest parameter estimation based on ITCD results had no ITCD-specific evaluation. Comparison of methods continues to be complicated by both choice of reference data and assessment metric; it is imperative to establish a standardized two-level assessment framework to evaluate and compare ITCD algorithms in order to provide specific recommendations about suitable applications of particular algorithms. However, the evolution of active remotely sensed data and novel platforms implies that automated ITCD will continue to be a promising technology and an attractive research topic for both the forestry and remote sensing communities.

show abstract

Section: Active Data Sources For Itcdmentioning

confidence: 99%

Trends in Automatic Individual Tree Crown Detection and Delineation—Evolution of LiDAR Data

2016

View full text Add to dashboard Cite

show abstract

“…Studies using CARABAS, a radar sensor similar to BioSAR, have shown that the VHF backscatter mechanisms are mainly dominated by ground-trunk doublebounce scattering mechanisms for simple forest structures such as gently sloped coniferous forests (Fransson et al 2000;Hallberg et al 2005). The longer wavelength radar has good foliage penetration; hence, the foliage-floor and trunk-foliage double-bounce scattering can be considered negligible.…”

Section: Discussionmentioning

confidence: 99%

“…Studies utilizing SAR data have found that the sensitivity of the radar backscatter coefficient to biomass disappears in forests with biomass exceeding 100 tonnes/ha (Dobson et al 1992;Fransson et al 2000;Imhoff et al 2000;Imhoff 1995). The usual 1-to 10-GHz frequencies are often intercepted by the crown layer of the canopy in dense forests, and twigs, needles, and smaller branches in the top layers of the canopy are the major scatterers at these wavelengths (Fransson et al 2000). Using lower frequencies, e.g., the Pband (around 440 MHz), the sensitivity to biomass increases, but saturation still occurs at 100-200 tonnes/ha biomass.…”

Section: Introductionmentioning

confidence: 99%

Synergistic use of very high-frequency radar and discrete-return lidar for estimating biomass in temperate hardwood and mixed forests

Banskota

Wynne

Johnson

et al. 2011

Annals of Forest Science

View full text Add to dashboard Cite

Abstract• Introduction Accurate estimation of aboveground biomass is essential to better understand the carbon cycle in forest ecosystems.• Methods The objective of this study was to determine whether biomass in temperate hardwood forests is better estimated using very high-frequency radar data (from BioSAR) alone or in combination with small-footprint discrete-return lidar data (both profiling and scanning). The study area was in the Appomattox-Buckingham State Forest, Virginia, USA (78°41′W, 37°25′N). Aboveground biomass for 28 stands was estimated using 131 basal area factor 10 point samples. The resulting stand biomass estimates were used as the dependent variable in a multiple linear regression. Descriptors of the lidar distributions (both profiling and scanning) and averaged normalized radar cross-sections in each of these stands were used as independent variables.• Results Regression results revealed the following: (1) neither BioSAR nor scanning lidar data alone are good predictors of stand biomass (R 2 =0.57, root mean squared error (RMSE)= 31.0 tonnes/ha and R 2 =0.64, RMSE=28.5 tonnes/ha, respectively); (2) BioSAR data combined with small-footprint discrete lidar data (either profiling or scanning) are the best predictors of stand biomass (R 2 =0.80, RMSE=21.3 tonnes/ ha and R 2 =0.76, RMSE=24.2 tonnes/ha, respectively); and (3) when used with BioSAR data for stand biomass estimation, less costly profiling lidar data convey the same information as more costly scanning lidar data.• Conclusion Useful synergy can be realized by considering lidar and radar measurements jointly in estimating aboveground biomass in hardwood and mixed forests.

show abstract

“…Ongoing developments in active remote-sensing methods-so called because they involve the transmission of signal and measurement of the return signal-offer a promising source of additional information about the landscapes that animals inhabit. For example, light detection and ranging (lidar), can provide measurements of forest canopy height and vertical canopy structure (Dubayah and Drake 2000;Hyde et al 2006), and radio detection and ranging (radar) can provide measurements of aboveground biomass and basal area, and measurements of moisture levels in the canopy and in the soil (Fransson et al 2000;Quiñones and Hoekman 2004;Saatchi et al 2007;Treuhaft et al 2003;Treuhaft and Siqueira 2000). Another significant development is the increasing availability of remotely sensed imaging spectrometry, which yields a continuous reflectance spectrum for each pixel rather than reflectance values in a few specific wavelengths.…”

Section: Future Directionsmentioning

confidence: 99%

Feasibility of Using Proximity Tags to Locate Female Lion Panthera leo Kills

Tambling

Belton

2009

Wildlife Biology

View full text Add to dashboard Cite

Global positioning system (GPS) based telemetry studies are becoming more popular in large carnivore research. Recent advancements include detection and prediction of kill sites from GPS collar data. Thus far, the majority of models to detect kill sites focus on the patterns generated by a single focal individual. The prediction of kill sites helps increase sample sizes for diet studies of carnivores, especially when continuous observation methods cannot be employed. We propose and report on the feasibility of using the spatial association of multiple individuals from a social carnivore group to locate kill sites, using female lions Panthera leo in the Kruger National Park, South Africa, as an example. Our feasibility study suggests that lionesses cluster in space while at a GPS cluster with a kill. Clustering appeared most strongly in the first two hours of a kill, whereafter a more random association between individuals in space is observed. Additionally we found no difference in the initial spatial clustering pattern for kills of different sizes. When clusters are not associated with a kill (i.e. resting), female lions exhibit the random spatial association similar to the later hours found at kill sites. We feel that based on the initial results, association of social carnivores in space in combination with current spatio-temporal patterns of focal individuals can be used to improve kill-site models, but further research and larger sample sizes are required to validate our findings.

show abstract

Estimation of forest parameters using CARABAS-II VHF SAR data

Cited by 88 publications

References 14 publications

Trends in Automatic Individual Tree Crown Detection and Delineation—Evolution of LiDAR Data

Trends in Automatic Individual Tree Crown Detection and Delineation—Evolution of LiDAR Data

Synergistic use of very high-frequency radar and discrete-return lidar for estimating biomass in temperate hardwood and mixed forests

Feasibility of Using Proximity Tags to Locate Female Lion Panthera leo Kills

Contact Info

Product

Resources

About