Tandem Coherence Research Articles

InSAR Study of Shoreline Change along the Damietta Promontory, Egypt

Aly, M.H.; Giardino, J.R.; Klein, A.G., and Zebker, H.A., 2012. InSAR study of shoreline change along the Damietta Promontory, Egypt. Shoreline erosion has been a major problem in the Nile Delta since the full damming of the Nile River in 1970, especially along the two Nile promontories (Rosetta and Damietta). Synthetic aperture radar interferometric (InSAR) data acquired by the European remote-sensing satellites (ERS-1 and ERS-2), spanning 1993–2000, were utilized in this study to (1) identify the erosion/accretion pattern along the Damietta Promontory shoreline, (2) monitor the evolution of the accretionary spit on the E side of the promontory, and (3) investigate the effect of protective structures established in multiple stages since 1991. The tandem coherence of InSAR was found to be a powerful tool for delineating the water/land boundary with very high precision. Four locations along the promontory shoreline experienced substantial erosion, with average rates of −9, −39, −17, and −11 m yr−1. Local accretion occurred at the W and E flanks of the promontory, with average rates of 12 and 36 m yr−1, respectively. The sandy spit increased in width by about 36 m yr−1 and migrated laterally to the SE at an average rate of 120 m yr−1. Shoreline instability during 1993–2000 implies that the established defensive structures have not been sufficient to cease erosion completely. As the promontory shoreline has not been armored with further protection since 2000, the identified erosional locations at the promontory flanks still require protection and monitoring to help mitigate the impact of shoreline retreat and its environmental consequences.

Large area forest stem volume mapping in the boreal zone using synergy of ERS-1/2 tandem coherence and MODIS vegetation continuous fields

ERS-1/2 tandem coherence was reported to have high potential for the mapping of boreal forest stem volume (e.g. Santoro et al., 2002, 2007a; Wagner et al., 2003; Askne & Santoro, 2005). Large-scale application of the data for forest stem volume mapping, however, is hindered by the variability of coherence with meteorological and environmental acquisition conditions. The traditional way of stem volume retrieval is based on the training of models, relating coherence to stem volume, with the aid of forest inventory data which is generally available for a few small test sites but not for large areas. In this paper a new approach is presented that allows model training using the MODIS Vegetation Continuous Fields canopy cover product (Hansen et al., 2003) without further need for ground data. A comparison of the new approach with the traditional regression-based and ground-data dependent model training is presented in this paper for a multi-seasonal ERS-1/2 tandem dataset covering several well known Central Siberian forest sites. As a test scenario for large-area application, the approach was applied to a multi-seasonal ERS-1/2 tandem dataset of 223 ERS-1 and ERS-2 image pairs covering Northeast China (~ 1.5 million km 2) to map four stem volume classes (0–20, 20–50, 50–80, and > 80 m 3/ha).

Satellite-based radar mapping of British forest age and Net Ecosystem Exchange using ERS tandem coherence

A method of mapping forest age structure using satellite remote sensing data in combination with ground data is used to form an age structure map of mainland Britain’s forests. Age structure is then used to demonstrate a method of calculating Net Ecosystem Exchange (NEE) for a region of forest. Synthetic Aperture Radar (SAR) coherence data provides an indication of forest biomass, which is related to forest age using forest management data at five independent locations. Coherence data is sensitive to time varying environmental effects and hence requires extensive calibration of the function relating coherence to forest age. The calibration approach appropriate in Britain makes use of the extensive ground GIS data available. Age structure information for nearly 3 million hectares of forest is generated, of which 70% is privately owned and age information is otherwise unavailable. The resulting map has a spatial resolution that can differentiate individual forest stands and provides detailed regional age and biomass estimates. Comparison of stand age estimates with ground data is has potential to provide growth rate and felling information. The age structure map is used in combination with an exemplary function relating forest age to NEE to estimate atmospheric carbon exchange for England, Scotland and Wales. This method predicts threefold higher (10.87 M t a −1) forest carbon uptake than national inventory figures. The remote sensing data also indicates age estimates that conflict with the ground data in Wales, which is explainable by the introduction of partial felling practices in this region during the time period of the coherence acquisitions.

Properties of ERS-1/2 coherence in the Siberian boreal forest and implications for stem volume retrieval

Properties of multi-temporal ERS-1/2 tandem coherence in boreal forests and retrieval accuracy of forest stem volume have been investigated mostly for small, managed forest areas. The clear seasonal trends and the high accuracy of the retrieval are therefore valid for specific types of forest and question is if these findings extend to large areas with different forest types in a similar manner. Using multi-temporal ERS-1/2 coherence data and extensive sets of inventory data at stand level at seven forest compartments in Central Siberia we confirm that the trend of coherence as a function of stem volume is mainly driven by the environmental conditions at acquisition. In addition, we have now found that the variability of the coherence for a given stem volume are due to spatial variations of the environmental conditions, strong topography (slope > 10°), small stand size (< 3–4 ha) and low relative stocking (< 50%). Further deviations can be related to errors in the ground data. Stem volume retrieval behaves consistently under stable winter frozen conditions. For stands larger than 3–4 ha and relative stocking of at least 50%, a relative RMSE of 20–25% can be considered the effective retrieval error achievable in Siberian boreal forest. Combined with previous experience from managed test forests in Sweden and Finland, C-band ERS-1/2 tandem coherence observations acquired under stable winter conditions with a snow cover and an at least moderate breeze can be considered so far the most suitable spaceborne remote sensing observable for the estimation of forest stem volume in homogeneous forest stands throughout the boreal zone.

Environmental effects on the interferometric repeat-pass coherence of forests

The variability of C-band one-day tandem coherence measurements of forest is analyzed both statistically and with the aid of a soil-vegetation-atmosphere transfer model coupled to models for dielectric, backscattering coefficient, and coherence. Coherence depends strongly on both moisture and wind conditions. The dependence between coherence and moisture fluctuations in the soil and canopy is simulated using a simplified coherence model neglecting canopy coherence; trends are similar to those observed in measured coherence, but the range of variability observed in the satellite data is underestimated. Improved consistency with the data is achieved by using empirical estimates of canopy coherence derived from mature forest, but still with underestimated variability. The canopy coherence values cannot be predicted from the environmental model, and anomalous observations prevent the formulation of a reliable empirical predictor based on weather data; this could potentially be improved if higher time resolution wind data were made available. The study also suggests that canopy dielectric can vary rapidly in daylight, and that current models for dielectric may be inadequate to capture the effect of this behavior on coherence.

Classification of forest volume resources using ERS tandem coherence and JERS backscatter data

Considering recent progress in the development of techniques and methods to achieve biomass estimates and full carbon accounting, remote sensing research of forested ecosystems needs to be aimed towards the retrieval of information at global scales. In this paper, an algorithm for the estimation of growing stock volume, an important parameter for the commercial forest community and a proxy for woody biomass density, from ERS and JERS synthetic aperture radar (SAR) data is described. The algorithm is based on the information content of both ERS tandem coherence and JERS backscatter images and was developed using ground data, made available by the Russian Forestry Services. It is tested on SAR datasets of boreal forests in Siberia, a managed, temperate forest plantation in the United Kingdom and a semi-natural boreal forest at Siggefora in Sweden. Comparisons of the classified products, comprising three growing stock interval classes and one non-forest class are made with ground data. The results of this accuracy assessment exercise show that the algorithm yields, in all cases, overall classification accuracies of greater than 70%. A visual comparison is made of the algorithm performance over a tropical forest region of Brazil. The results indicate that the algorithm has the potential to retrieve growing stock volume estimates in forest ecosystems throughout the globe.

Multitemporal repeat-pass sar interferometry of boreal forests

Multitemporal European Remote Sensing satellites 1 and 2 (ERS-1/2) and the Japanese Earth Resources Satellite 1 (JERS-1) interferometric synthetic aperture radar (InSAR) data from a boreal forest test site in Sweden (stem volumes up to 335 m/sup 3//ha, equivalent to above-ground dry biomass of /spl sim/200 tons/ha) are studied in order to estimate stem volume using coherence and backscatter. The changes of JERS-1 backscatter and ERS-1/2 tandem coherence between images are consistent over the area studied, in contrast to ERS-1/2 backscatter. A model-based regression analysis has been performed, and the use of the model for inversion is discussed and compared with other approaches found in the literature. The model parameters are discussed in terms of their relation to wind speed and temperature. Results from the different acquisitions are combined to improve the stem volume estimation. The accuracy in terms of rms error (RMSE) for standwise estimated stem volume is /spl ap/10 m/sup 3//ha using ERS-1/2 coherence. Using backscatter and coherence from JERS-1 we obtain an RMSE of /spl ap/30-35 m/sup 3//ha. Finally, conditions for accurate retrieval of stem volume using multitemporal InSAR observations are discussed. We conclude that C- and L-band repeat-pass InSAR can provide stem volume estimates in boreal forests with accuracies similar to those of standard in situ measurements.

Land-cover classification using multitemporal ERS-1/2 insar data

In this study the potential of ERS-1/2 Tandem InSAR data for land-cover classification was investigated at a 2500 km/sup 2/ study area around the Helsinki metropolitan area in Southern Finland. A time-series of 14 ERS-1/2 SAR Tandem image pairs was processed into 28 five-look intensity images, 14 Tandem coherence images and two coherence images with a longer temporal baseline (36 and 246 days). All image data was coregistered and orthorectified into map coordinates using an InSAR DEM. A two-stage hybrid classifier method was employed, where the water-class was classified separately in the first classifier stage, and the remaining classes were classified with an ISODATA classifier. Temporal averaging and Principal Components Transformation (PCT) were used to reduce the number of images fed into ISODATA. Classification accuracy was assessed using high-resolution aerial orthophotos, digital base maps and the Finnish National Forest Inventory (NFI). The overall accuracy for six classes (Field/Open Land, Dense Forest, Sparse Forest, Mixed Urban, Dense Urban, Water) was found to be 90% with kappa coefficient of 0.86. Interferometric coherence carries more land-cover related information than the backscattered intensity. This study confirms that the ERS-1/2 Tandem archives could be exploited for land-cover classification.

Large-scale mapping of boreal forest in SIBERIA using ERS tandem coherence and JERS backscatter data

Siberia's boreal forests represent an economically and ecologically precious resource, a significant part of which is not monitored on a regular basis. Synthetic aperture radars (SARs), with their sensitivity to forest biomass, offer mapping capabilities that could provide valuable up-to-date information, for example about fire damage or logging activity. The European Commission SIBERIA project had the aim of mapping an area of approximately 1 million km 2 in Siberia using SAR data from two satellite sources: the tandem mission of the European Remote Sensing Satellites ERS-1/2 and the Japanese Earth Resource Satellite JERS-1. Mosaics of ERS tandem interferometric coherence and JERS backscattering coefficient show the wealth of information contained in these data but they also show large differences in radar response between neighbouring images. To create one homogeneous forest map, adaptive methods which are able to account for brightness changes due to environmental effects were required. In this paper an adaptive empirical model to determine growing stock volume classes using the ERS tandem coherence and the JERS backscatter data is described. For growing stock volume classes up to 80 m 3/ha, accuracies of over 80% are achieved for over a hundred ERS frames at a spatial resolution of 50 m.

The use of ERS-1/2 Tandem interferometric coherence in the estimation of agricultural crop heights

In this study, the relationship between ERS-1/2 SAR Tandem interferometric coherence and the height of sugar beet, potato, and winter wheat is investigated using measurements of crop growth and coherence. The development of both coherence and crop height is observed to be approximately linear during the early growing season, and linear crop-specific relationships between Tandem coherence and the heights of the studied crops are derived. The coherence of all the studied crops decreases as the crop heights increase, a probable explanation for this is that as the crop grows, it screens the ground more effectively, and a greater part of the incident radar energy is backscattered from vegetation that decorrelates more rapidly than the more stable soil. The relatively dense canopies of the root crops sugar beet and potato screen the ground considerably more effectively than the cereal crop winter wheat. This study gives a strong indication that ERS-1/2 Tandem interferometric coherence is related to the height of agricultural crops, and that this relationship can be used to retrieve crop heights.