Method for an automatic alignment of imagery and vector data applied to cadastral information in Poland

Ruiz-Lendínez, Juan José; Maćkiewicz, B.; Motek, Paweł; Stryjakiewicz, T.

doi:10.1080/00396265.2017.1388959

Cited by 10 publications

(8 citation statements)

References 28 publications

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“…As mentioned in the Introduction section, our approach to texture characterization was already successfully tested in other studies [19,20]. Although both their purpose and the features used differed from those addressed here, these studies were very useful when the relationship between computation time, image resolution, and threshold "U" was analyzed because the results obtained could be extrapolated to other types of segmentation processes.…”

Section: Discussionmentioning

confidence: 93%

“…LBP has become a really powerful measure of image texture, showing excellent results in terms of accuracy and computational complexity in many empirical studies [18]. This approach to texture characterization has already been successfully tested in many conflation processes between vector data and imagery in which road intersections are automatically extracted from imagery and then used as control points in order to accomplish the matching procedure [19,20]. After obtaining the map of abandoned land, we assessed the effectiveness of the proposed methodology from two different focuses: (i) the accuracy of the segmentation results (from a positional point of view) and (ii) the efficiency for locating abandoned land (as a specific type of land use) in urban areas particularly affected by rapid urbanization.…”

Section: Research Approachmentioning

confidence: 99%

“…However, this uniform statistical behavior is not usual in the majority of real imagery regions. Consequently, the use of pixel tone to segment imagery does not seem to be the best option [20]. To overcome this challenge, we developed an algorithm for extracting pixels from images based on a local-nonparametric approach to texture analysis.…”

Section: Abandoned Farmland Extraction Algorithmmentioning

confidence: 99%

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Abandoned Farmland Location in Areas Affected by Rapid Urbanization Using Textural Characterization of High Resolution Aerial Imagery

Ruiz-Lendínez

2020

IJGI

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Several studies have demonstrated that farmland abandonment occurs not only in rural areas, but is also closely interlinked with urbanization processes. Therefore, the location of abandoned land and the registration of the spatial information referring to it play important roles in urban land management. However, mapping abandoned land or land in the process of abandonment is not an easy task because the limits between the different land uses are not clear and precise. It is therefore necessary to develop methods that allow estimating and mapping this type of land as accurately as possible. As an alternative to other geomatics methods such as satellite remote sensing, our approach proposes a framework for automatically locating abandoned farmland in urban landscapes using the textural characterization and segmentation of aerial imagery. Using the city of Poznań (Poland) as a case study, results demonstrated the feasibility of applying our approach, reducing processing time and workforce resources. Specifically and by comparing the results obtained with the data provided by CORINE Land Cover, 2275 ha (40.3%) of arable land within the city limits were abandoned, and the area of abandoned arable land was almost 9.2% of the city’s area. Finally, the reliability of the proposed methodology was assessed from two different focuses: (i) the accuracy of the segmentation results (from a positional point of view) and (ii) the efficiency of locating abandoned land (as a specific type of land use) in urban areas particularly affected by rapid urbanization.

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Section: Discussionmentioning

confidence: 93%

Section: Research Approachmentioning

confidence: 99%

Section: Abandoned Farmland Extraction Algorithmmentioning

confidence: 99%

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Abandoned Farmland Location in Areas Affected by Rapid Urbanization Using Textural Characterization of High Resolution Aerial Imagery

Ruiz-Lendínez

2020

IJGI

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“…The relative errors after the geometric transformation were almost always below 2%, but the errors before the transformation were not reported. Srinivas et al (2012) build a brand new land parcel map using an orthoimage at scale 1:10.000 and they reported the resulting accuracy in terms of length. The relative error of the image was of the order of 0.07%.…”

Section: State Of the Artmentioning

confidence: 99%

Admissible relative errors of the parcel area while creating a land parcel map base using an orthoimage as a reference

Balado¹,

López-Vázquez²

2020

rcarto

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Currently the official land parcel map of Uruguay does not allow a suitable interoperability with other available geographic information. We are considering using a national high accuracy and high resolution orthomosaic in two ways: either to support the creation of a brand new land parcel map or to allow amending the existing one. In particular, the present work is part of a set of experiments which considers different techniques to amend the existing land parcel map. In order to perform a fair comparison it is necessary to have test cases produced with a reference procedure properly and objectively evaluated. The metric of success will be used as attainable goal for any other alternative. Using the orthomosaic in order to identify the apparent limits of parcels in the land parcel map we were able to modify its location, thus making the map interoperable with the image. In order to measure the accuracy of the fit, we used the relative difference between the area declared at the parcel map (taken as the reference value) respect to the one computed from the GIS. We found that the discrepancy between the areas computed from the initial and the final dataset w.r.t. the declared area decreases, but not up to expected level. Once filtered for outliers the remaining discrepancies follow a normal distribution, where its bias and standard deviation varies from (-0.65%, 11.24%) before editing to (‑1.72%, 8.59%) later. Despite the drastic change in planimetric accuracy the improvement of the area accuracy is marginal. Considering the admissibility criteria of the Uruguayan National Cadastral Office, for the legacy dataset only 39.4% parcel maps could be accepted, a value which improves up to 49.7% after the manual edition. It is still far from the goal of 100%, and the reasons for such pessimistic finding will be discussed.

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“…The first phase of map conflation is looking for the correspondences between the datasets (Ruiz et al, 2011), a process known as matching. Recent studies published show that this topic has raised open issues for the geospatial data science community (Wang et al, 2019, Ruiz-Lendínez et al, 2019.…”

Section: Introductionmentioning

confidence: 99%

A New Geographic Context Measure to Similarity Assessment Based on the Shape Context Descriptor

Xavier¹,

Ureña-Cámara

López

2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Nowadays there are many geospatial datasets available for the same area. This large availability is derivative from the advances in remote sensing processes, which includes the popularization of drones and the increasing number of satellite platforms. These data are built by distinct producers, with different requirements. It is fair presume that a more complete version of these datasets can be created using data integration techniques. Among them we can find the map conflation methods, in which the first phase often begins with an alignment between the datasets assessed. The procedure of find these correspondences between geospatial datasets is called matching. In this study we present a new geographic context measure that can be used to implement a new matching method at the feature level. This new measure is based on the shape context descriptor proposed by Belongie. The experiments showed that our approach is a feasible solution, which is less sensible to data disturbance then other traditional methods.

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Method for an automatic alignment of imagery and vector data applied to cadastral information in Poland

Cited by 10 publications

References 28 publications

Abandoned Farmland Location in Areas Affected by Rapid Urbanization Using Textural Characterization of High Resolution Aerial Imagery

Abandoned Farmland Location in Areas Affected by Rapid Urbanization Using Textural Characterization of High Resolution Aerial Imagery

Admissible relative errors of the parcel area while creating a land parcel map base using an orthoimage as a reference

A New Geographic Context Measure to Similarity Assessment Based on the Shape Context Descriptor

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