A knowledge-based, transferable approach for block-based urban land-use classification

Novack, Tessio; Kux, Hermann Johann Heinrich; Feitosa, Raul Queiroz; Costa, Gilson Alexandre Ostwald Pedro da

doi:10.1080/01431161.2014.921943

Cited by 18 publications

(11 citation statements)

References 35 publications

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“…OBIA techniques have been extensively used to map urban features [21][22][23][24][25][26][27], to derive forest stand-level inventory information [28][29][30], to monitor biodiversity and wildlife habitat [31][32][33], and also to estimate relative abundance of wildlife [34]. For example, a high-resolution image can be first decomposed at coarser scales to delineate large image features, e.g., forest type.…”

Section: Introductionmentioning

confidence: 99%

An Object-Based Classification Method to Detect Methane Ebullition Bubbles in Early Winter Lake Ice

et al. 2019

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Thermokarst lakes in the Arctic and Subarctic release carbon from thawing permafrost in the form of methane and carbon dioxide with important implications for regional and global carbon cycles. Lake ice impedes the release of gas during the winter. For instance, bubbles released from lake sediments become trapped in downward growing lake ice, resulting in vertically-oriented bubble columns in the ice that are visible on the lake surface. We here describe a classification technique using an object-based image analysis (OBIA) framework to successfully map ebullition bubbles in airborne imagery of early winter ice on an interior Alaska thermokarst lake. Ebullition bubbles appear as white patches in high-resolution optical remote sensing images of snow-free lake ice acquired in early winter and, thus, can be mapped across whole lake areas. We used high-resolution (9–11 cm) aerial images acquired two and four days following freeze-up in the years 2011 and 2012, respectively. The design of multiresolution segmentation and region-specific classification rulesets allowed the identification of bubble features and separation from other confounding factors such as snow, submerged and floating vegetation, shadows, and open water. The OBIA technique had an accuracy of >95% for mapping ebullition bubble patches in early winter lake ice. Overall, we mapped 1195 and 1860 ebullition bubble patches in the 2011 and 2012 images, respectively. The percent surface area of lake ice covered with ebullition bubble patches for 2011 was 2.14% and for 2012 was 2.67%, representing a conservative whole lake estimate of bubble patches compared to ground surveys usually conducted on thicker ice 10 or more days after freeze-up. Our findings suggest that the information derived from high-resolution optical images of lake ice can supplement spatially limited field sampling methods to better estimate methane flux from individual lakes. The method can also be used to improve estimates of methane ebullition from numerous lakes within larger regions.

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Section: Introductionmentioning

confidence: 99%

An Object-Based Classification Method to Detect Methane Ebullition Bubbles in Early Winter Lake Ice

et al. 2019

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“…A interpretação visual de imagens de satélite Landsat 8 ocorre através da extração de padrões texturais nas bandas monocromáticas e nas composições coloridas. Para a realização de levantamentos quanto ao uso da terra e cobertura vegetal, a utilização das composições coloridas favorece a aquisição de melhores informações, já que o olho humano apresenta maior sensibilidade a cores do que aos tons de cinza (Nascimento et al, 2014).…”

Section: Methodsunclassified

Análise da degradação da vegetação nativa em área de preservação permanente na Paraíba

Silva

Pereira

Cosme³

et al. 2020

Rev. Bras. Geog. Fis.

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A supressão da vegetação nativa para a expansão agropecuária ou para outro tipo de uso, tem agravado o processo de degradação florestal, ocasionando impactos negativos. Assim, este estudo teve como objetivo o mapeamento da vegetação da APP no Horto Florestal Olho D´água da Bica, do município de Cuité – PB, quantificando as áreas alteradas da vegetação densa, vegetação rala e o solo exposto, através das mudanças espectrais em quatro anos (2015 a 2018), visando obter maior conhecimento sobre a sua preservação. Foram utilizadas imagens de satélite Landsat 8 que possuíam menores coberturas de nuvens. A interpretação visual de imagens de satélite ocorre através da extração de padrões texturais nas bandas monocromáticas e nas composições coloridas. A partir, dos resultados observou-se que a vegetação densa sofreu uma significativa redução ao longo dos anos e que a vegetação rala e o solo exposto obtiveram um maior crescimento no período analisado. Desta forma, conclui-se que a degradação da vegetação, ocorreu ao longo dos anos, sendo necessário uma intervenção e plano de recuperação da área. A vegetação densa teve redução significativa, enquanto houve elevação da vegetação rala. Assim, torna necessário a aplicação de projetos de educação ambiental na comunidade para incentivar a conscientização e preservação desta APP. Analysis of the degradation of native vegetation in a permanent preservation area in Paraíba A B S T R A C TThe removal of native vegetation to agricultural expansion or for other use, has aggravated the process of forest degradation, causing negative impacts. Thus, this study aimed to the mapping of the vegetation of the APP in the Horto Florestal Eye D ´ water da Bica, the municipality of Cuité-PB, quantifying the altered areas of dense vegetation, thin vegetation and soil exposed, through the spectral changes in four years (2015 to 2018), in order to gain greater knowledge of your preservation. Landsat satellite images were used 8 who had lower cloudiness. The visual interpretation of satellite imagery occurs through the extraction of textural patterns in monochrome and colored bands in the compositions. From the results, it was observed that the dense vegetation has suffered a significant reduction over the years and that the thin vegetation and exposed soil obtained a higher growth in the period analyzed. Thus, it is concluded that the degradation of vegetation, occurred over the years, requiring an intervention and recovery plan of the area. The dense vegetation had significant reduction, while there were thin vegetation elevation. So, makes necessary the implementation of environmental education projects in the community to encourage the awareness and preservation of this APP.Keywords: vegetation cover, permanent preservation area, environmental education.

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“…Moreover, either the rule sets or the objects' shape or even both need to be manually adapted in order to achieve acceptable results for a variety of images. Against this background, recent developments have paid more attention to the genericity of solutions (Novack et al 2014) and the reusability of knowledge that has been used to create the complex rule sets (Arvor et al 2014). However, in order to overcome the limited transferability of OBIA rule sets, we investigate the coupling, extension and integration of OBIA with principles and methods from the agent-based paradigm.…”

Section: Obia For Vhr Image Data Analysismentioning

confidence: 99%

Agent Based Image Analysis (ABIA): Preliminary Research Results from an implemented Framework

Hofmann¹,

Andrejchenko²,

Lettmayer³

et al. 2016

GEOBIA 2016: Solutions and Synergies

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Object Based Image Analysis (OBIA) has meanwhile been established as a paradigm for analyzing remotely sensed image data. Although the degree of automation for OBIA methods has increased for several applications, especially in the domain of remote sensing, robust and transferable object-based solutions for automated image analysis of sets of images or even large image archives are still rare. One of the reasons for this lack of robustness and transferability is the high complexity of remote sensing image contents: Especially in Very High Resolution (VHR) remote sensing data, under varying imaging conditions or sensor characteristics, the objects' properties can vary unpredictably. Although earlier work has demonstrated that OBIA rule sets bear a high potential of transferability these rule sets need to be adapted manually in order to receive acceptable results, or the classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering and robotics. The aims of such integration are a) rule sets which can be adapted autonomously according to varying imaging data, and b) image objects which can adapt and adjust themselves in order to best possibly represent the objects of interest in an image. This paper briefly introduces a framework for Agent Based Image Analysis (ABIA) and presents our first research results.

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A knowledge-based, transferable approach for block-based urban land-use classification

Cited by 18 publications

References 35 publications

An Object-Based Classification Method to Detect Methane Ebullition Bubbles in Early Winter Lake Ice

An Object-Based Classification Method to Detect Methane Ebullition Bubbles in Early Winter Lake Ice

Análise da degradação da vegetação nativa em área de preservação permanente na Paraíba

Agent Based Image Analysis (ABIA): Preliminary Research Results from an implemented Framework

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