Comparative assessment of the measures of thematic classification accuracy

Liu, Canran; Frazier, Paul; Kumar, Lalit

doi:10.1016/j.rse.2006.10.010

Cited by 367 publications

(235 citation statements)

References 26 publications

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“…11. Karta promjena u načinu upotrebe i pokrovu zemljišta 1978. -2007 decrease by 5 % was from 1992-2007.…”

Section: Discussionmentioning

confidence: 99%

“…The error matrix is the most widely used approach for image classification accuracy assessment and can be used to derive a series of descriptive and analytical statistics (Congalton and Mead;Congalton, 1991;Congalton and Green, 1999;Smits et al, 1999;Congalton and Plourde, 2002;Foody, 2002;Liu et al, 2007). In this study, accuracy assessment was performed for the classified maps of all three time steps.…”

Section: Forestmentioning

confidence: 99%

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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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“…11. Karta promjena u načinu upotrebe i pokrovu zemljišta 1978. -2007 decrease by 5 % was from 1992-2007.…”

Section: Discussionmentioning

confidence: 99%

Section: Forestmentioning

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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“…However, even in this context, kappa does not provide a measure of the model's predictive ability, and alternatives to kappa should be considered for this purpose (DeMast, 2007). Liu et al (2007) provide a comprehensive review and analysis of other proposed accuracy measures.…”

Section: Discussionmentioning

confidence: 99%

Using remotely sensed data to construct and assess forest attribute maps and related spatial products

McRoberts

Cohen

Næsset

et al. 2010

Scandinavian Journal of Forest Research

112

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Tremendous advances in the construction and assessment of forest attribute maps and related spatial products have been realized in recent years, partly as a result of the use of remotely sensed data as an information source. This review focuses on the current state of techniques for the construction and assessment of remote sensing-based maps and addresses five topic areas: statistical classification and prediction techniques used to construct maps and related spatial products, accuracy assessment methods, map-based statistical inference, and two emerging topics, change detection and use of lidar data. Multiple general conclusions were drawn from the review: (1) remotely sensed data greatly contribute to the construction of forest attribute maps and related spatial products and to the reduction of inventory costs; (2) parametric prediction techniques, accuracy assessment methods and probability-based (design-based) inferential methods are generally familiar and mature, although inference is surprisingly seldom addressed; (3) non-parametric prediction techniques and modelbased inferential methods lack maturity and merit additional research; (4) change detection methods, with their great potential for adding a spatial component to change estimates, will mature rapidly; and (5) lidar applications, although currently immature, add an entirely new dimension to remote sensing research and will also mature rapidly. Crucial forest sustainability and climate change applications will continue to push all aspects of remote sensing to the forefront of forest research and operations.

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“…It should be also noticed that the same ROIs were used for Accuracy assessment has been a topic of considerable debate and research in remote sensing for many years. This is in part because the promoted standard methods such as the Kappa coefficient are not always appropriate [45]. Several researchers have worked on the problems relative to accuracy assessment of classification uncertainty [46][47][48].…”

Section: Case Study Area 2: Mironikitas Areamentioning

confidence: 99%

Detection of olive oil mill waste (OOMW) disposal areas using high resolution GeoEye’s OrbView-3 and Google Earth images

2016

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Abstract:The olive oil industry is considered to be as one of the driving sectors of the agricultural economy of the Mediterranean basin. The extraction of olive oil generates huge quantities of wastes that may have a great impact on land and water environments due to high concentrations in phenolic compounds that could cause ophytotoxicity. This paper aims to examine the potential use of freely distributed satellite images for the detection of olive oil mil waste (OOMW) areas in the island of Crete through the use of two cases studies. In the first case study an archive GeoEye OrbView-3 image was used to detect OOMW areas using the Spectral Angle Mapper detection algorithm and other geometric and topographic parameters. In the second case study, Google Earth images were examined through different classification algorithms at different scales. The overall results demonstrate that remote sensing techniques can be used as an alternative to field observations so as to detect and monitor OOMW areas Furthermore, freely distributed RGB images from digital globes (such as Google Earth) can be sufficiently and effectively used for this purpose.

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Comparative assessment of the measures of thematic classification accuracy

Cited by 367 publications

References 26 publications

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

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

Using remotely sensed data to construct and assess forest attribute maps and related spatial products

Detection of olive oil mill waste (OOMW) disposal areas using high resolution GeoEye’s OrbView-3 and Google Earth images

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