Urban built-up land change detection with road density and spectral information from multi-temporal Landsat TM data

Zhang, Qiaofeng; Wang, J.; Peng, Xulong; Gong, Peng; Shi, Peijun

doi:10.1080/01431160110104728

Cited by 207 publications

(101 citation statements)

References 15 publications

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“…Indeed, conversion or modification of the landscape units is done at the expense (regression) or in favor of one class over another (progression) or the stability of class from one year to another. To this end, the positive values represent an increase in class surface during the period analyzed, negative values, loss and values close or equal to zero (0), relative stability [11]. We will conduct an analysis of changes between 1977-1988 series of set-processing; 1988-1999; 1999-2006; 2006-2014 and 1977-2014.…”

Section: Detection Of Land Use Changes Between 1977 and 2014mentioning

confidence: 99%

Using of Landsat Images for Land Use Changes Detection in the Ecosystem_ A Case Study of the Senegal River Delta

Toure¹,

Ndiaye²,

Traoré³

et al. 2016

IJEAB

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Section: Detection Of Land Use Changes Between 1977 and 2014mentioning

confidence: 99%

Using of Landsat Images for Land Use Changes Detection in the Ecosystem_ A Case Study of the Senegal River Delta

Toure¹,

Ndiaye²,

Traoré³

et al. 2016

IJEAB

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“…We test the performance of the automatic detection method on the test areas and calculate the resulting errors of omission (landslides not detected) E o,i and commission (false alarms) E c,i relative either to the area (i = a) or to the numbers of landslides (i = n) (e.g., [46]) :…”

Section: Sensitivity Analysismentioning

confidence: 99%

Supervised Method of Landslide Inventory Using Panchromatic SPOT5 Images and Application to the Earthquake-Triggered Landslides of Pisco (Peru, 2007, Mw8.0)

et al. 2013

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Earthquake is one of the dominant triggering factors of landslides. Given the wide areas covered by mega earthquake-triggered landslides, their inventory requires development of automatic or semi-automatic methods applied to satellite imagery. A detection method is here proposed for this purpose, to fit with simple datasets; SPOT5 panchromatic images of 5 m resolution coupled with a freely and globally available DEM. The method takes advantage of multi-temporal images to detect changes based on radiometric variations after precise coregistration/orthorectification. Removal of false alarms is then undertaken using shape, orientation and radiometric properties of connected pixels defining objects. 80% of the landslides and 93% of the landslide area are detected indicating small omission errors but 50% of false alarms remain. They are removed using expert based analysis of the inventory. The method is applied to realize the first comprehensive inventory of landslides triggered by the Pisco earthquake (Peru, 15/08/2007, Mw 8.0) over an area of 27,000 km 2 . 866 landslides larger than 100 m 2 are detected covering a total area of 1.29 km 2 . The area/number distribution follows a power-law with an exponent of 1.63, showing a very particular regime of triggering in this arid environment compared to other areas in the world. This specific triggering can be explained by the little soil cover in the coastal and forearc regions of Peru.Analysis of this database finally shows a major control of the topography (both orientation and inclination) on the repartition of the Pisco-triggered landslides.Remote Sens. 2013, 5 2591

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“…The classification of multi-spectral images has been a successful application that is used for classification of land cover maps (Lunetta and Balogh, 1999;Oettera et al, 2000;Yuan et al, 2005), urban growth (Yeh and Li, 1997;Zhang et al, 2002), forest change (Vogelmann and Rock, 1988;Hall et al, 1991;Coppin and Bauer, 1994), monitoring change in ecosystem condition (Lambin, 1998;Weng, 2002), monitoring assessing deforestation and burned forest areas (Potapov et al, 2008), agricultural expansion (Woodcock et al, 1993;Pax-Lenney et al, 1996), mapping corn (Maxwell et al, 2004), real time fire detection (Dennison and Roberts, 2009), estimating tornado damage areas (Myint et al, 2008), estimating water quality characteristics of lakes (Lillesand et al, 1983;Lathrop et al, 1991;Dekker and Peters, 1993), geological mapping (Mostafa and Bishta, 2004;Bishta, 2010), estimating crop acreage and production (Liu et al, 2005), monitoring of environmental pollution (Zhu and Basir, 2005), monitoring and mapping mangrove ecosystems (Kuenzer et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Using Landsat Satellite Imagery to Determine Land Use/Land Cover Changes in Međimurje County, Croatia

Horvat¹

2014

Hrv. geogr. glas.

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using Landsat satellite images. Spatial dynamics of LU/LC changes were quantified using three Landsat satellite images: MSS, TM and ETM+. Three series of the LU/LC maps of 1978, 1992 and 2007 were produced. Based on the Anderson classification system, LU/LC are classified as: water bodies, forest land, barren land, agricultural land and urban built-up land. Error matrices were used to assess classification accuracy. Significant buildings construction, construction of the reservoir lakes on the Drava River and construction of a highway were major drives of LU/ LC changes in Međimurje County over the study period. This study showed a continuous decrease in agricultural lands in Međimurje County. Consequently, the urban built-up area and the water area increased.Key words: land use/land cover, land use/land cover changes, satellite imageries, Međimurje County Upotreba satelitskih snimaka Landsat za utvrđivanje promjena u načinu upotrebe i pokrovu zemljišta u Međimurskoj županiji u Hrvatskoj U radu se procjenjuju promjene u načinu upotrebe i pokrovu zemljišta u Međimurskoj županiji u Hrvatskoj u razdobljima 1978Hrvatskoj u razdobljima . -1992Hrvatskoj u razdobljima ., 1992Hrvatskoj u razdobljima . -2007Hrvatskoj u razdobljima . i 1978Hrvatskoj u razdobljima . -2007. upotrebom satelitskih snimaka Landsat. Prostorna dinamika promjena načina upotrebe zemljišta i pokrova kvantificirana je upotrebom triju serija satelitskih snimaka Landsat. Izrađene su tri serije karata načina upotrebe i pokrova zemljišta, za 1978., 1992. i 2007. godinu. Na temelju Andersonova klasifikacijskog sustava način upotrebe i pokrov zemljišta klasificirani su kao vodene površine, šumske površine, golo tlo, poljoprivredne površine i urbano područje. Za ocjenu točnosti klasifikacije poslužila je matrica pogrešaka. Značajna izgradnja zgrada, izgradnja akumulacijskih jezera na rijeci Dravi i autoceste najznačajnije su promjene u načinu upotrebe i pokrovu zemljišta u Međimurskoj županiji tijekom promatranog razdoblja. Istraživanje pokazuje kontinuirano smanjenje poljoprivrednog zemljišta u Međimurskoj županiji, zbog čega su građevinsko zemljište i vodene površine povećani.Ključne riječi: upotreba zemljišta, promjene upotrebe zemljišta, satelitske snimke, Međimurska županija Preliminary communicationPrethodno priopćenje 6Hrvatski geografski glasnik 75/2 (2013.)

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Urban built-up land change detection with road density and spectral information from multi-temporal Landsat TM data

Cited by 207 publications

References 15 publications

Using of Landsat Images for Land Use Changes Detection in the Ecosystem_ A Case Study of the Senegal River Delta

Using of Landsat Images for Land Use Changes Detection in the Ecosystem_ A Case Study of the Senegal River Delta

Supervised Method of Landslide Inventory Using Panchromatic SPOT5 Images and Application to the Earthquake-Triggered Landslides of Pisco (Peru, 2007, Mw8.0)

Using Landsat Satellite Imagery to Determine Land Use/Land Cover Changes in Međimurje County, Croatia

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