A morphology-stitching method to improve Landsat SLC-off images with stripes

Aghamohamadnia, Milad; Abedini, A.

doi:10.3724/sp.j.1246.2014.01027

Cited by 12 publications

(7 citation statements)

References 8 publications

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“…Before carrying out image classification of the image for 2018, it was necessary to remove the stripes caused by the Landsat ETM+ sensor malfunction after May 31, 2003 [44]. Several authors have proposed methods for dealing with this issue [44,45]. In this paper, we followed the approach described in [46] since this method was available in QGIS 3.8.…”

Section: Methodsmentioning

confidence: 99%

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Ecological Risk Assessment Based on Land Cover Changes: A Case of Zanzibar (Tanzania)

Omar

Cabral

2020

Remote Sensing

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Land use and land cover (LULC) under improper land management is a major challenge in sub-Saharan Africa and has drastically affected ecological security. Addressing environmental impacts related to this challenge requires efficient planning strategies based on the measured information of land use patterns. This study assessed the ecological risk index (ERI) of Zanzibar based on LULC. A random forest classifier was used to classify three Landsat images of Zanzibar for the years 2003, 2009, and 2018. Then, a land change model was employed to simulate the LULC changes for 2027 under a business-as-usual (BAU), conservation, and extreme scenarios. Results showed that the built-up areas and farmland of Zanzibar Island have increased constantly, while the natural grassland and forest cover have decreased. The forest, agricultural, and grassland were highly fragmented into several small patches. The ERI of Zanzibar Island increased at a constant rate and, if the current trend continues, this index will increase by up to 8.9% in 2027 under an extreme scenario. If a conservation scenario is adopted, the ERI will increase by 4.6% whereas if a BAU policy is followed, this value will increase by 6.2%. This study provides authorities with useful information to understand better the ecological processes and LULC dynamics and prevent unmanaged growth and haphazard development of informal housing and infrastructure.

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Section: Methodsmentioning

confidence: 99%

“…proposed methods for dealing with this issue [44,45]. In this paper, we followed the approach described in [46] since this method was available in QGIS 3.8.…”

Section: Methodsmentioning

confidence: 99%

Ecological Risk Assessment Based on Land Cover Changes: A Case of Zanzibar (Tanzania)

Omar

Cabral

2020

Remote Sensing

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“…A general constraint to bi-temporal change detection methods such as the IR-MAD is the loss of data due to a number of contaminations or errors such as SLC-off data gaps [57] and cloud cover [70]. Although well-performing correction approaches have been proposed for data gaps with information derived from neighboring pixels [71] or even other sensors [72], interpolation or the inclusion of extraneous data can introduce additional errors [73,74]. For this, SLC-off acquisitions as well as clouded scenes are discarded.…”

Section: Remote Sensing Change Detection Analysesmentioning

confidence: 99%

Analyses of Recent Sediment Surface Dynamic of a Namibian Kalahari Salt Pan Based on Multitemporal Landsat and Hyperspectral Hyperion Data

2017

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This study combines spaceborne multitemporal and hyperspectral data to analyze the spatial distribution of surface evaporite minerals and changes in a semi-arid depositional environment associated with episodic flooding events, the Omongwa salt pan (Kalahari, Namibia). The dynamic of the surface crust is evaluated by a change-detection approach using the Iterative-reweighted Multivariate Alteration Detection (IR-MAD) based on the Landsat archive imagery from 1984 to 2015. The results show that the salt pan is a highly dynamic and heterogeneous landform. A change gradient is observed from very stable pan border to a highly dynamic central pan. On the basis of hyperspectral EO-1 Hyperion images, the current distribution of surface evaporite minerals is characterized using Spectral Mixture Analysis (SMA). Assessment of field and image endmembers revealed that the pan surface can be categorized into three major crust types based on diagnostic absorption features and mineralogical ground truth data. The mineralogical crust types are related to different zones of surface change as well as pan morphology that influences brine flow during the pan inundation and desiccation cycles. These combined information are used to spatially map depositional environments where the more dynamic halite crust concentrates in lower areas although stable gypsum and calcite/sepiolite crusts appear in higher elevated areas.

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“…There are various methods for seamless mosaic of UAV remote sensing images have been investigated [ 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. Among them, seam-line based methods are intended to reduce grayscale and geometric differences.…”

Section: Related Workmentioning

confidence: 99%

“…The ant colony method in [ 14 ] is also based on dynamic programming, which can evade the areas where the color contrast is larger between images, while it will easily lead the search processing to the local optimum due to its sensitivity to the number of ants. Furthermore, there are some other methods based on the snake model [ 15 ], and some based on a morphological model [ 16 , 17 ]. Although these methods can almost ensure the consistence of the geometric structure and evade the phenomenon of ghosting in the overlapping regions under some conditions, they are still unable to ensure that ghosting and seams can be overcame at the same time—especially when there is a significant brightness difference between adjacent images.…”

Section: Related Workmentioning

confidence: 99%

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow

Guo

Liao

et al. 2018

Sensors

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Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images.

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A morphology-stitching method to improve Landsat SLC-off images with stripes

Cited by 12 publications

References 8 publications

Ecological Risk Assessment Based on Land Cover Changes: A Case of Zanzibar (Tanzania)

Ecological Risk Assessment Based on Land Cover Changes: A Case of Zanzibar (Tanzania)

Analyses of Recent Sediment Surface Dynamic of a Namibian Kalahari Salt Pan Based on Multitemporal Landsat and Hyperspectral Hyperion Data

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow

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