Radar backscatter change from an ash in relation to its hydrological properties

Jong, J.J.M. de; Groot, H.W. de; Klaassen, Wim; Kuiper, P. J. C.

doi:10.1109/igarss.2000.860293

Cited by 2 publications

(2 citation statements)

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“…Considering the relationship between radar backscatter and the dielectric constant of tree tissues [21], it may be expected that TerraSAR-X imagery can be used for identifying trees infested by bark beetles. Healthy trees should result in a higher SAR backscatter than dry (infested) or dead trees [22].…”

Section: Introductionmentioning

confidence: 99%

Early Detection of Bark Beetle Green Attack Using TerraSAR-X and RapidEye Data

Ortiz¹,

Breidenbach²,

Kändler³

2013

Remote Sensing

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Bark beetles cause widespread damages in the coniferous-dominated forests of central Europe and North America. In the future, areas affected by bark beetles may further increase due to climate change. However, the early detection of the bark beetle green attack can guide management decisions to prevent larger damages. For this reason, a field-based bark beetle monitoring program is currently implemented in Germany. The combination of remote sensing and field data may help minimizing the reaction time and reducing costs of monitoring programs covering large forested areas. In this case study, RapidEye and TerraSAR-X data were analyzed separately and in combination to detect bark beetle green attack. The remote sensing data were acquired in May 2009 for a study site in south-west Germany. In order to distinguish healthy areas and areas affected by bark beetle green attack, three statistical approaches were compared: generalized linear models (GLM), maximum entropy (ME) and random forest (RF). The spatial scale (minimum mapping unit) was 78.5 m 2 .TerraSAR-X data resulted in fair classification accuracy with a cross-validated Cohen's Kappa Coefficient (kappa) of 0.23. RapidEye data resulted in moderate classification accuracy with a kappa of 0.51. The highest classification accuracy was obtained by combining the TerraSAR-X and RapidEye data, resulting in a kappa of 0.74. The accuracy of ME models was considerably higher than the accuracy of GLM and RF models. OPEN ACCESSRemote Sens. 2013, 5 1913

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Section: Introductionmentioning

confidence: 99%

Early Detection of Bark Beetle Green Attack Using TerraSAR-X and RapidEye Data

Ortiz¹,

Breidenbach²,

Kändler³

2013

Remote Sensing

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“…First, the radar measurements. These measurements are only briefly described as details can be found elsewhere [33], [34]. The next paragraph is about the collection of input data in order to run the models.…”

Section: Validationmentioning

confidence: 99%

Monitoring of rain water storage in forests with satellite radar

Jong

Klaassen²,

Kuiper

2002

IEEE Trans. Geosci. Remote Sensing

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The sensitivity of radar backscatter to the amount of intercepted rain in temperate deciduous forests is analyzed to determine the feasibility of retrieval of this parameter from satellite radar data. A backscatter model is validated with X-band radar measurements of a single tree exposed to rain. A good agreement between simulation and measurements is observed and this demonstrates the ability of radar to measure the amount of intercepted rain. The backscatter model is next applied to simulate different satellite radar configurations. To account for forest variability, the backscatter difference between a wet and dry forest canopy is calculated for four deciduous tree species, above a wet and a dry soil. On average, the simulated backscatter of a wet forest canopy is 1 dB higher than the backscatter of a dry forest canopy at co-polarized L-band and 2 dB at co-polarized C and X-band. The simulated sensitivity is in agreement with observations. It is argued that current satellites can retrieve the amount of intercepted rain at best with a reliability of 50%, due to the variability in soil moisture, species composition and system noise. We expect that the reliability will improve with the launch of the next generation radar satellites. The results of this analysis may also be used to assess the influence of rain, fog or dew upon other radar applications for temperate deciduous forests.

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Radar backscatter change from an ash in relation to its hydrological properties

Cited by 2 publications

References 4 publications

Early Detection of Bark Beetle Green Attack Using TerraSAR-X and RapidEye Data

Early Detection of Bark Beetle Green Attack Using TerraSAR-X and RapidEye Data

Monitoring of rain water storage in forests with satellite radar

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