A novel algorithm for land use and land cover classification using RADARSAT-2 polarimetric SAR data

Qi, Zhixin; Yeh, Ago; Xia, Li; Zheng, Lin

doi:10.1016/j.rse.2011.11.001

Cited by 245 publications

(152 citation statements)

References 43 publications

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“…Based on physical assumptions, polarimetric decomposition procedures aim to separate these different backscatter types [54,55]. As dual-pol SAR imagery was available for this study, the H/α decomposition proposed by Cloude and Pottier [40] was applied.…”

Section: Polarimetric Decompositionmentioning

confidence: 99%

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

2016

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Abstract:Mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response, i.e., to support rescue and humanitarian operations. Most synthetic aperture radar (SAR) data-based landslide detection approaches reported in the literature use change detection techniques, requiring very high resolution (VHR) SAR imagery acquired shortly before the landslide event, which is commonly not available. Modern VHR SAR missions, e.g., Radarsat-2, TerraSAR-X, or COSMO-SkyMed, do not systematically cover the entire world, due to limitations in onboard disk space and downlink transmission rates. Here, we present a fast and transferable procedure for mapping of landslides, based on change detection between pre-event optical imagery and the polarimetric entropy derived from post-event VHR polarimetric SAR data. Pre-event information is derived from high resolution optical imagery of Landsat-8 or Sentinel-2, which are freely available and systematically acquired over the entire Earth's landmass. The landslide mapping is refined by slope information from a digital elevation model generated from bi-static TanDEM-X imagery. The methodology was successfully applied to two landslide events of different characteristics: A rotational slide near Charleston, West Virginia, USA and a mining waste earthflow near Bolshaya Talda, Russia.

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Section: Polarimetric Decompositionmentioning

confidence: 99%

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

2016

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“…Two comprehensive reviews of this group of techniques can be found in [1,2]. The decomposition results have been used for a number of applications, such as target detection [3][4][5], land cover classification [6][7][8][9][10][11][12][13], and geophysical parameter inversion [14][15][16]. Freeman-Durden decomposition [17] is the pioneering work on model-based decompositions.…”

Section: Introductionmentioning

confidence: 99%

On the Use of Generalized Volume Scattering Models for the Improvement of General Polarimetric Model-Based Decomposition

et al. 2017

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Abstract:Recently, a general polarimetric model-based decomposition framework was proposed by Chen et al., which addresses several well-known limitations in previous decomposition methods and implements a simultaneous full-parameter inversion by using complete polarimetric information. However, it only employs four typical models to characterize the volume scattering component, which limits the parameter inversion performance. To overcome this issue, this paper presents two general polarimetric model-based decomposition methods by incorporating the generalized volume scattering model (GVSM) or simplified adaptive volume scattering model, (SAVSM) proposed by Antropov et al. and Huang et al., respectively, into the general decomposition framework proposed by Chen et al. By doing so, the final volume coherency matrix structure is selected from a wide range of volume scattering models within a continuous interval according to the data itself without adding unknowns. Moreover, the new approaches rely on one nonlinear optimization stage instead of four as in the previous method proposed by Chen et al. In addition, the parameter inversion procedure adopts the modified algorithm proposed by Xie et al. which leads to higher accuracy and more physically reliable output parameters. A number of Monte Carlo simulations of polarimetric synthetic aperture radar (PolSAR) data are carried out and show that the proposed method with GVSM yields an overall improvement in the final accuracy of estimated parameters and outperforms both the version using SAVSM and the original approach. In addition, C-band Radarsat-2 and L-band AIRSAR fully polarimetric images over the San Francisco region are also used for testing purposes. A detailed comparison and analysis of decomposition results over different land-cover types are conducted. According to this study, the use of general decomposition models leads to a more accurate quantitative retrieval of target parameters. However, there exists a trade-off between parameter accuracy and model complexity which constrains the physical validity of solutions and must be further investigated.

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“…Wang et al [19] prepared a LULC map of muddy tidal flat wetlands based on DTC and achieved an OA value of 95.84%, a 4.44% increase compared with MLC. Qi et al [26] obtained a LULC map of the Panyu district in Guanzhou city, China using DTC combined with object-oriented classification (DTC-OOC) and RADRSAR-2 Polarimetric ASR (PolSAR) data. They estimated an OA of 86.64% and KC of 0.84, which corresponded to increases of 16.98% and 0.19 in comparison to respective values obtained with MLC.…”

Section: Analysis Of Classification Accuracy and Other Similar Studiesmentioning

confidence: 99%

A Feature-Based Approach of Decision Tree Classification to Map Time Series Urban Land Use and Land Cover with Landsat 5 TM and Landsat 8 OLI in a Coastal City, China

Hua

Zhang

Chen

et al. 2017

IJGI

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Accurate mapping of temporal changes in urban land use and land cover (LULC) is important for monitoring urban expansion and changes in LULC, urban planning, environmental management, and environmental modeling. In this study, we present a feature-based approach of the decision tree classification (FBA-DTC) method for mapping LULC based on spectral and topographic information. Landsat 5 TM and Land 8 OLI images were employed, and the technique was applied to the coastal city of Xiamen, China. The method integrates multi-spectral features such as SAVI (soil adjustment vegetation index), NDWI (normalized water index), MNDBaI (modified normalized difference barren index), BI (brightness index), and WI (wetness index), with topographic features including DEM and slope. In addition, the new approach distinguishes between fallow land and cropland, and separates high-rise buildings from beaches and water bodies. Several of the FBA-DTC parameters (or rules) from 1997 to 2015 remained constant (i.e., DEM and slope), whereas others changed slightly. WI was negatively related to percent area of beach land, and BI was negatively related to percent area of arable land. The FBA-DTC method had an average user's accuracy (UA) of 91.36% for built-up land, an average overall accuracy (OA) of 92.13%, and a Kappa coefficient (KC) of 0.90 for the period from 2003 to 2015, representing respective increases of 15.87%, 10.17%, and 0.13, compared with values calculated using maximum likelihood classification (MLC). Over the past 12 years, built-up land increased from 23.67% to 43.17% owing to occupation of coastal reclamation, arable land, and forest land. The FBA-DTC method presented here is a valuable technique for evaluating urban growth and changes in LULC classification for coastal cities.

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A novel algorithm for land use and land cover classification using RADARSAT-2 polarimetric SAR data

Cited by 245 publications

References 43 publications

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

On the Use of Generalized Volume Scattering Models for the Improvement of General Polarimetric Model-Based Decomposition

A Feature-Based Approach of Decision Tree Classification to Map Time Series Urban Land Use and Land Cover with Landsat 5 TM and Landsat 8 OLI in a Coastal City, China

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