Estimations for Percentage of Impervious Area by the Use of Satellite Remote Sensing Imagery

Deguchi, Chikashi; Sugio, Satoru

doi:10.2166/wst.1994.0659

Cited by 27 publications

(10 citation statements)

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“…Kite et al (1992) apply semi-distributed watershed modelling, which requires prior knowledge about land cover classes (bare ground, forests and grass). Deguchi and Sugio (1994) evaluate the applicability of satellite imagery for estimating the percentage of impervious area in a scene with the goal of using it for runoff simulation in urban areas. In their work, land cover classification is achieved by clustering algorithms.…”

Section: Related Workmentioning

confidence: 99%

Automatic Classification of Aerial Imagery for Urban Hydrological Applications

Paul¹,

Chun²,

Breitkopf³

et al. 2018

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

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ABSTRACT:In this paper we investigate the potential of automatic supervised classification for urban hydrological applications. In particular, we contribute to runoff simulations using hydrodynamic urban drainage models. In order to assess whether the capacity of the sewers is sufficient to avoid surcharge within certain return periods, precipitation is transformed into runoff. The transformation of precipitation into runoff requires knowledge about the proportion of drainage-effective areas and their spatial distribution in the catchment area. Common simulation methods use the coefficient of imperviousness as an important parameter to estimate the overland flow, which subsequently contributes to the pipe flow. The coefficient of imperviousness is the percentage of area covered by impervious surfaces such as roofs or road surfaces. It is still common practice to assign the coefficient of imperviousness for each particular land parcel manually by visual interpretation of aerial images. Based on classification results of these imagery we contribute to an objective automatic determination of the coefficient of imperviousness. In this context we compare two classification techniques: Random Forests (RF) and Conditional Random Fields (CRF). Experimental results performed on an urban test area show good results and confirm that the automated derivation of the coefficient of imperviousness, apart from being more objective and, thus, reproducible, delivers more accurate results than the interactive estimation. We achieve an overall accuracy of about 85% for both classifiers. The root mean square error of the differences of the coefficient of imperviousness compared to the reference is 4.4% for the CRF-based classification, and 3.8% for the RF-based classification.

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Section: Related Workmentioning

confidence: 99%

Automatic Classification of Aerial Imagery for Urban Hydrological Applications

Paul¹,

Chun²,

Breitkopf³

et al. 2018

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

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“…On the other hand aerial photographs have previously been used as ancillary data to validate the accuracy of land cover maps generated from remotely sensed satellite imagery (Mas, 2003;Rembold et al, 2000;Wentz et al, 2006;Deguchi and Sugio, 1994). Deguchi and Sugio (1994).…”

Section: Introductionmentioning

confidence: 99%

“…They further noted that differences in levels of accuracy using the three methods arise from positional errors, incorrect ground observations, or discrepancies between the sizes of sampling unit in the ground versus classes generated. Hara et al, (2005) used aerial photographs to determine transformation on the urban fringe of Bangkok, Thailand, while Deguchi and Sugio (1994) cited by Wentz et al, (2006) compared aerial photography and a variety of satellite datasets for impervious areas and the density of urbanized area of Wake County in the state of North Carolina, USA. The two studies concluded that both aerial photography and satellite data returned results of similar accuracy.…”

Section: Introductionmentioning

confidence: 99%

Use of GIS and Orthophotos In Spatio-Temporal Assessment of Land Uses And City Expansion: A Case of Pietermaritzburg, Kwazulu-Natal, South Africa

Hlatywayo¹,

Masvosve²

2015

SA J of Geomatics

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“…[5][6][7][8] Remote sensing has long been used for land use/land cover (LULC) classification, and it allows up-to-date, spatially explicit estimates of urban surface imperviousness over large areas. [9][10][11] Ridd proposed the classic vegetation-impervious surface-soil model to parameterize biophysical composition of urban environments. 12 Carlson and Arthur retrieved the fraction impervious surface of Chester Country based on the inverse relationship between impervious surfaces and vegetation.…”

Section: Introductionmentioning

confidence: 99%

Using long time series of Landsat data to monitor impervious surface dynamics: a case study in the Zhoushan Islands

Zhang

Pan

Chen

et al. 2013

J. Appl. Remote Sens

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Abstract. Islands are an important part of the marine ecosystem. Increasing impervious surfaces in the Zhoushan Islands due to new development and increased population have an ecological impact on the runoff and water quality. Based on time-series classification and the complement of vegetation fraction in urban regions, Landsat thematic mapper and other high-resolution satellite images were applied to monitor the dynamics of impervious surface area (ISA) in the Zhoushan Islands from 1986 to 2011. Landsat-derived ISA results were validated by the high-resolution Worldview-2 and aerial photographs. The validation shows that mean relative errors of these ISA maps are < 15 %. The results reveal that the ISA in the Zhoushan Islands increased from 19.2 km 2 in 1986 to 86.5 km 2 in 2011, and the period from 2006 to 2011 had the fastest expansion rate of 5.59 km 2 per year. The major land conversions to high densities of ISA were from the tidal zone and arable lands. The expansions of ISA were unevenly distributed and most of them were located along the periphery of these islands. Time-series maps revealed that ISA expansions happened continuously over the last 25 years. Our analysis indicated that the policy and the topography were the dominant factors controlling the spatial patterns of ISA and its expansions in the Zhoushan Islands. With continuous urbanization processes, the rapid ISA expansions may not be stopped in the near feature.

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Estimations for Percentage of Impervious Area by the Use of Satellite Remote Sensing Imagery

Cited by 27 publications

References 0 publications

Automatic Classification of Aerial Imagery for Urban Hydrological Applications

Automatic Classification of Aerial Imagery for Urban Hydrological Applications

Use of GIS and Orthophotos In Spatio-Temporal Assessment of Land Uses And City Expansion: A Case of Pietermaritzburg, Kwazulu-Natal, South Africa

Using long time series of Landsat data to monitor impervious surface dynamics: a case study in the Zhoushan Islands

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