Building Change Detection Method to Support Register of Identified Changes on Buildings

Jovanović, Dušan; Gavrilović, Milan; Sladić, Dubravka; Radulović, Aleksandra; Govedarica, Miro

doi:10.3390/rs13163150

Cited by 5 publications

(4 citation statements)

References 39 publications

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“…Chang et al [25] have shown that using OBIA techniques can substantially overcome issues associated with the per-pixel method, and these are capable of more precisely defining a spatially complex urban area by successfully distinguishing between settlement types [20,24,26]. Several researchers, including Ghaffarian and Emtehani [27], Kohli et al [28] and Jovanović et al [29], have studied the use and effectiveness of OBIA. They concluded that OBIA produces highly accurate results.…”

Section: Literature Reviewmentioning

confidence: 99%

Using Local Knowledge and Remote Sensing in the Identification of Informal Settlements in Riyadh City, Saudi Arabia

2023

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Urban planning within Riyadh, the capital of Saudi Arabia, has been impacted by the presence of informal settlements. An understanding of the spatial distribution of these settlements is essential in developing urban policies. This study used remotely sensed imagery to evaluate and characterize informal settlements within the city, both with and without expert knowledge of the study area (defined as expert knowledge, EK). An informal settlement ontology for four study sites within Riyadh City was developed using an analytical hierarchy process (AHP). Local knowledge was translated into a ruleset to identify and map settlement areas using spatial, spectral, textural, and geometric techniques. These were combined with an object-based image analysis (OBIA) approach. The study demonstrated that combining expert knowledge and remotely sensed data can efficiently and accurately identify informal settlements. Two classified images were produced, one with EK, and one without EK, to investigate how a detailed understanding of local conditions could affect the final image classification. Overall accuracy when using EK was 94%, with a kappa coefficient of 89%, while without EK accuracy was 68% (kappa coefficient of 61%). The final OBIA classes included formal and informal settlements, road networks, vacant blocks, shaded areas, and vegetation. This study demonstrated that local expert knowledge and OBIA helpful in urban mapping. It also indicated the value of integrating a local ontological process during digital image classification. This work provided improved techniques for mapping informal settlements in Middle Eastern cities.

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Section: Literature Reviewmentioning

confidence: 99%

Using Local Knowledge and Remote Sensing in the Identification of Informal Settlements in Riyadh City, Saudi Arabia

2023

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“…Object-based machine learning algorithms are becoming an area of interest in feature extraction [41][42][43]. The RF classification algorithm is an ensemble of decision trees trained using a combination of learning models [44].…”

Section: Random Forest Classifiermentioning

confidence: 99%

Assessment of Spatial Patterns of Backyard Shacks Using Landscape Metrics

Mudau,

Mhangara

2023

Drones

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Urban informality in developing economies like South Africa takes two forms: freestanding shacks are built in informal settlements, and backyard shacks are built in the yard of a formal house. The latter is evident in established townships around South African cities. In contrast to freestanding shacks, the number of backyard shacks has increased significantly in recent years. The study assessed the spatial patterns of backyard shacks in a formal settlement containing low-cost government houses (LCHs) using Unmanned Aerial Vehicle (UAV) products and landscape metrics. The backyard shacks were mapped using Object-Based Image Analysis (OBIA), which uses height information, vegetation index, and radiometric values. We assessed the effectiveness of rule-based and Random Forest (RF) OBIA techniques in detecting formal and informal structures. Informal structures were further classified as backyard shacks using spatial analysis. The spatial patterns of backyard shacks were assessed using eight shapes, aggregation, and landscape metrics. The analysis of the shape metrics shows that the backyard shacks are primarily square, as confirmed by a higher shape index value and a lower fractional dimension index value. The contiguity index of backyard shack patches is 0.6. The values of the shape metrics of backyard shacks were almost the same as those of formal and informal dwelling structures. The values of the assessed aggregation metrics of backyard shacks were more distinct from formal and informal structures compared with the shape metrics. The aggregation metrics show that the backyard shacks are less connected, less dense, and more isolated from each other compared with formal and freestanding shacks. The Shannon’s Diversity Index and Simpson’s Evenness Index values of informal settlements and formal areas with backyard shacks are almost the same. The results achieved in this study can be used to understand and manage informality in formal settlements.

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“…This is the knowledge gap that the authors wanted to address. Some of the important objects, the disclosure of which in the cadastre database causes significant consequences for both their owner and the municipality, are buildings [27,28].…”

Section: Introductionmentioning

confidence: 99%

Active Collection of Data in the Real Estate Cadastre in Systems with a Different Pedigree and a Different Way of Building Development: Learning from Poland and Slovakia

et al. 2022

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A cadastre is a system of major importance for the economy and for management strategies in support of sustainable development. Thus, its modernisation process (especially in the case of buildings) is extremely important. This study compared the results from the cadastre modernisation process of Poland and Slovakia, that is, countries with a different way of building development and different historical cadastral traditions. It was certain that in countries with dispersed development—such as Poland—the modernisation process could significantly change the cadastre’s picture. However, the analysis of the number of buildings in the cadastre after modernisation revealed a change of 3.048% for scattered development and only 6% for compact development. Thus, the urgent need to perform retrofits in countries with a scattered pattern of development was demonstrated. In addition, a comparative analysis proved that excessively frequent changes in the law cause the cadastre base to lose its validity. The Polish building cadastre has become a victim of such frequent changes in the law. It happened that just after the cadastre had been modernised at a high financial cost, the data on buildings collected in the cadastre became outdated as a result of a change in the law. Research highlighted that frequent changes and inconsistencies in the law result in a state of affairs in which activities that should be systemic and technical instead become activities that depend on political aspects.

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Building Change Detection Method to Support Register of Identified Changes on Buildings

Cited by 5 publications

References 39 publications

Using Local Knowledge and Remote Sensing in the Identification of Informal Settlements in Riyadh City, Saudi Arabia

Using Local Knowledge and Remote Sensing in the Identification of Informal Settlements in Riyadh City, Saudi Arabia

Assessment of Spatial Patterns of Backyard Shacks Using Landscape Metrics

Active Collection of Data in the Real Estate Cadastre in Systems with a Different Pedigree and a Different Way of Building Development: Learning from Poland and Slovakia

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