Automated House Detection and Delineation using Optical Remote Sensing Technology for Informal Human Settlement

Asmat, Arnis; Zamzami, S.Z.

doi:10.1016/j.sbspro.2012.03.071

Cited by 11 publications

(7 citation statements)

References 3 publications

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“…The former class expanded to forest area following rapid urban expansion near to town center on croplands in 2002. However, a built-up area rapidly replaced agricultural land following massive constructions, This finding is in line with Asmat and Zamzami(2012) and Esayas ( 2013) which explain about increased built-up area due to rapid, unstructured and unplanned development. Extreme decline of grassland and agricultural land was occurred in the year 2002 to 2020.…”

Section: Land Use/cover Dynamicssupporting

confidence: 75%

Urban Expansion and Vegetation Cover Change in and Around Jimma Town Since 1990

Fufa¹

2021

JEES

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Urbanization is the renovation of rural society into an urban society as a result of socio-economic and political growth leading to foundation and expansion of urban agglomerations along with changing land use patterns. The main aims of this study was Investigating the extent of vegetation loss through urban expansion in and around Jimma Town over a 30 period of 6 years interval by using Geographic Information System (GIS) and Remote Sensing (RS) techniques. To achieve this objectives, Data was obtained from earth explorer (USGS) 6 years interval from1990 to 2020 of the study area. Downloaded image were extracted and each layer stacked together using the digital image-processing software ENVI 5.2. The Processed images were classified using supervised classification Algorithms into 5 hierarchical classes; Built-up area, Vegetation, Agricultural land, Grass land, and wetlands based on a modified classification scheme. Change analysis was also undertaken by applying postclassification change detection procedures. Accuracy of the image classification was assessed using error matrix, overall accuracy and kappa coefficient. The change analysis result revealed that the LULC have shown both positive and negative significant changes. Built-up were the top LULC that experienced positive change; whereas grass land, vegetation, agricultural land and wetlands have substantially declined. An important implication of the observed changes is that rapid urban expansion, compounded by poor urban planning is leading to enormous losses of key ecosystems such as wetlands and natural vegetation. The consequence of this rapid ecological degradation could potentially impact ecological functioning and environmental sustainability in and around Jimma city. Therefore, critical system thinking is required to address these complex problems in the study area and areas of rapid urbanization elsewhere in the country.

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Section: Land Use/cover Dynamicssupporting

confidence: 75%

Urban Expansion and Vegetation Cover Change in and Around Jimma Town Since 1990

Fufa¹

2021

JEES

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“…Only English-language papers are selected, and very similar publications by the same authors (e.g., journal and conference publication) were counted only once. In total, 87 key publications (Aminipouri et al, 2009;Asmat & Zamzami, 2012;Barros Filho & Sobreira, 2005;Biggs, Anderson, & Pombo, 2015;Dell'Acqua, Stasolla, & Gamba, 2006;Dell'Acqua, Lisini, & Gamba, 2011;Duque, Patino, Ruiz, & Pardo-Pascual, 2015;Eckert, 2010;Ella et al, 2008;Engstrom et al, 2013;Engstrom et al, 2015;Galeon, 2008;Gamba, Dell'Acqua, & Trianni, 2007;Giada, De Groeve, Ehrlich, & Soille, 2003b;Graesser et al, 2012;Gruebner et al, 2014;Gueguen, 2015;Gunter, 2009;Hassan, 2011;Hofmann, 2014;Hofmann et al, 2011; The analytical framework (Figure 2.2) for analysing the retrieved publications, inspired by the outcome of the expert meeting on slum mapping (Sliuzas, Mboup, et al, 2008), forms the skeleton for this review. Figure 2.2 shows that slum formation and development in global cities are impacted by several contextual factors, such as geographic location and climate, the topography of the city, the location within the city including proximity to services, and general socioeconomic and political factors (e.g., land governance).…”

Section: Methodology Of Reviewmentioning

confidence: 99%

Spatial patterns of deprivation in cities of the global south in very high resolution imagery

Kuffer

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“…Band Ratio Techniques: Compared to enhancement and band combination techniques, the band ratio method provided a more detailed image of the houses. Houses' spectral characteristics will be enhanced by the combinations of band ratios used (Asmat and Zamzami, 2011). Ratios between Red (Band4), Green (Band3), Near-infrared (NIR) (Band8), and C (Radar) were applied to the Sentinel1 and 2 images.…”

Section: 112mentioning

confidence: 99%

“…To optimize the image for analysis and visual interpretation, different enhancement types were applied to it, including linear, root, equal, adaptive, and infrequency functions. By stretching the maximum and minimum of the image digital values over the total dynamic range, linear enhancement optimizes the images' overall contrast (Asmat and Zamzami, 2011). As shown in Figure 4, by modifying certain components, different subbands can be created, and the contrast can be enhanced (Celik, 2012).…”

Section: Enhancement Techniquesmentioning

confidence: 99%

Remote Sensing Methods to Detect and Identify Clay-Made Houses

Khawary

Zeaieanfirouzabadi²,

Sadidi³

2023

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. One of the most important issues in urban management is the existence of clay-made houses in or around cities. By the hypothesis that these phenomena are spectrally and spatially behaviour differently from other land uses and land covers. This study attempts to detect and identify clay-made houses through different image processing methods. In this regard, Sentinel 1, 2, and Landsat 8 OLI thermal images of Yazd city have been analysed. After pre-processing, a number of image processing techniques, including optical and radar image composite generation, band ratio, image fusion, image filtering, and image classification (i.e. MLC and ANN), have been used. The result shows that RGB from a combination of Red=radar band C, Green=sentinel band 8, and Blue=sentinel band 4 are the best for visual interpretation of clay-made houses. Also, the most suitable band ratio is the ratio corresponding to radar C and NIR, the Red and Green bands, and the best fusion is derived with Sentinel 1 (band C) and Sentinel 2 (bands 4 and 8) images through the HSV algorithm, kappa coefficients of the agreement for MLC and ANN classifiers are 0.89 and 0.29 respectively. It is concluded that remote sensing image analysis can effectively be used to detect and identify clay-made houses.

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Automated House Detection and Delineation using Optical Remote Sensing Technology for Informal Human Settlement

Cited by 11 publications

References 3 publications

Urban Expansion and Vegetation Cover Change in and Around Jimma Town Since 1990

Urban Expansion and Vegetation Cover Change in and Around Jimma Town Since 1990

Spatial patterns of deprivation in cities of the global south in very high resolution imagery

Remote Sensing Methods to Detect and Identify Clay-Made Houses

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