The relationship between the backscattering coefficient and the biomass of narrow and broad leaf crops

Macelloni, Giovanni; Paloscia, S.; Pampaloni, P.; Marliani, F.; Gai, Marco

doi:10.1109/36.917914

Cited by 204 publications

(115 citation statements)

References 27 publications

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“…It is well known that the accuracy of forest biometric parameter estimations is site-dependent [8,18] and affected by the forest structure [19,20], shape and dimensions of leaves and stems [21], and the ground conditions. Little is known about the backscattering characteristics of Acacia trees under a power decomposition scheme.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Decomposition Powers of L-Band Multi-Polarimetric SAR in Assessing Tree Growth of Industrial Plantation Forests in the Tropics

et al. 2012

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A decomposition scheme was applied to ALOS/PALSAR data obtained from a fast-growing tree plantation in Sumatra, Indonesia to extract tree stem information and then estimate the forest stand volume. The scattering power decomposition of the polarimetric SAR data was performed both with and without a rotation matrix and compared to the following field-measured forest biometric parameters: tree diameter, tree height and stand volume. The analytical results involving the rotation matrix correlated better than those without the rotation matrix even for natural scattering surfaces within the forests. Our primary finding was that all of the decomposition powers from the rotated matrix correlated significantly to the forest biometric parameters when divided by the total power. The surface scattering ratio of the total power markedly decreased with the forest growth, whereas the canopy and double-bounce scattering ratios increased. The observations of the OPEN ACCESS Remote Sens. 2012, 4 3059 decomposition powers were consistent with the tree growth characteristics. Consequently, we found a significant logarithmic relationship between the decomposition powers and the forest biometric parameters that can potentially be used to estimate the forest stand volume.

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Section: Introductionmentioning

confidence: 99%

Characteristics of Decomposition Powers of L-Band Multi-Polarimetric SAR in Assessing Tree Growth of Industrial Plantation Forests in the Tropics

et al. 2012

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“…Additionally, previous studies that used SAR data for crop mapping have distinguished between "broad leafed" and "fine/narrow leaf" crops and noted the usefulness of radar data in differentiating them based on their canopy architecture [24,25]. Broad-leaved crops have higher backscatter intensity than fine-leaved crops, due to a high absorption of the radar signal in the latter [75]. In this regard, yam, which can be categorized as broad leaf, will have higher backscatter intensities than rice, which can be considered as fine leaf.…”

Section: Contribution Of Tsx Data To Crop Mappingmentioning

confidence: 99%

Integration of Optical and Synthetic Aperture Radar Imagery for Improving Crop Mapping in Northwestern Benin, West Africa

et al. 2014

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Crop mapping in West Africa is challenging, due to the unavailability of adequate satellite images (as a result of excessive cloud cover), small agricultural fields and a heterogeneous landscape. To address this challenge, we integrated high spatial resolution multi-temporal optical (RapidEye) and dual polarized (VV/VH) SAR (TerraSAR-X) data to map crops and crop groups in northwestern Benin using the random forest classification algorithm. The overall goal was to ascertain the contribution of the SAR data to crop mapping in the region. A per-pixel classification result was overlaid with vector field boundaries derived from image segmentation, and a crop type was determined for each field based on the modal class within the field. A per-field accuracy assessment was conducted by comparing the final classification result with reference data derived from a field campaign. Results indicate that the integration of RapidEye and TerraSAR-X data improved classification accuracy by 10%-15% over the use of RapidEye only. The VV polarization was found to better discriminate crop types than the VH polarization. The research has shown that if optical and SAR data are available for the whole cropping season, classification accuracies of up to 75% are achievable.

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“…Among the possible electromagnetic models, an incoherent RTT model was selected that was originally developed at IFAC for the simulation of agricultural crops [Macelloni et al, 2001] [Ulaby et al, 1990], and then modified for forest vegetation [ESA, 2008]. This e.m. model was developed and tested during Phase-0 of the CoReH2O mission [ESA, 2008], and was recently improved.…”

Section: The Snow-vegetation Modelmentioning

confidence: 99%

Effect of forests on the retrieval of snow parameters from backscatter measurements

Macelloni

Brogioni

Montomoli

et al. 2012

European Journal of Remote Sensing

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In preparation for the CoReH2O satellite mission, one of the three missions selected for scientific and technical feasibility studies within the Earth Explorer Programme of the ESA, experimental and theoretical studies have been under way in order to improve methods for the retrieval of snow physical properties from SAR data. The aim of this paper is to investigate the impact of vegetation in the retrieval of snow parameters from microwave backscattering measurements. ARTT model capable of simulating scattering from a snowcovered vegetated terrain was developed and implemented to study the sensitivity to snow and vegetation parameters. A procedure for correcting the vegetation effect in the SWE retrieval algorithm has been suggested.

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The relationship between the backscattering coefficient and the biomass of narrow and broad leaf crops

Cited by 204 publications

References 27 publications

Characteristics of Decomposition Powers of L-Band Multi-Polarimetric SAR in Assessing Tree Growth of Industrial Plantation Forests in the Tropics

Characteristics of Decomposition Powers of L-Band Multi-Polarimetric SAR in Assessing Tree Growth of Industrial Plantation Forests in the Tropics

Integration of Optical and Synthetic Aperture Radar Imagery for Improving Crop Mapping in Northwestern Benin, West Africa

Effect of forests on the retrieval of snow parameters from backscatter measurements

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