The use of the Thematic Mapper for the analysis of eutrophic lakes: a case study in the Netherlands.

Dekker, A.G.; Peters, Steef

doi:10.1080/01431169308904379

Cited by 249 publications

(162 citation statements)

References 5 publications

Supporting

Mentioning

152

Contrasting

Unclassified

Order By: Relevance

“…In this LMR model to predict SM, band TM4, TM5, and TM7 were not found significant (p < 0.05). These results support finding of Wang and Ma (2001) and Dekker and Peters (1993). Wang and Ma (2001) found that TM4 band had no significant relationship with water quality parameters.…”

Section: Statistical Modelssupporting

confidence: 81%

Artificial Neural Networks Application in Lake Water Quality Estimation Using Satellite Imagery

2004

View full text Add to dashboard Cite

ABSTRACT. Lake water quality monitoring using traditional water sampling and laboratory analyses is very expensive and time consuming. Application of neural networks to predict water quality using satellite imagery data has a potential to make the water quality determination process cost-effective, quick, and feasible. This paper includes an indirect method of determining the concentrations of chlorophyll-a (chl-a) and suspended matter (SM), two optically active parameters of lake water quality. Radial basis function neural (RBFN) network models are developed to predict the chl-a and SM concentrations in the lake. The low cost commercially available Landsat-TM imagery spectral information was used as the input with chl-a or SM concentrations as output. The model is trained and validated with data from the years 2001, 2002, 2003, and 2004. The model testing resulted in a coefficient of determination (R 2 ) of 0.55, and 0.90, respectively, for actual and predicted chl-a and SM concentrations. The root mean square error (RMSE), standard error of prediction (SEP), and average testing accuracy indicated the merit of the developed models.

show abstract

Section: Statistical Modelssupporting

confidence: 81%

Artificial Neural Networks Application in Lake Water Quality Estimation Using Satellite Imagery

2004

View full text Add to dashboard Cite

show abstract

“…For example, remote sensing methods have been developed for operational large-scale monitoring of chlorophyll concentration and suspended materials (Kloiber et al 2000, Harma et al 2001, Wiangwang et al 2006. Several studies have shown that imagery from Landsat sensors can be used in the estimation of Secchi depth (SD), chlorophyll-a (Chl-a) concentration, turbidity and total suspended solids (Tassan 1987, Harrington et al 1992, Dekker and Peters 1993, Pattiaratchi et al 1994, Keiner and Yan 1998, Nellis et al 1998, Allee and Johnson 1999, Roelfsema et al 2001. These remote sensing methods were shown to be effective in reducing the experimental cost and labour (Khorram andCheshire 1985, Lathrop 1992).…”

Section: Introductionmentioning

confidence: 99%

Empirical estimation of total phosphorus concentration in the mainstream of the Qiantang River in China using Landsat TM data

et al. 2010

International Journal of Remote Sensing

111

View full text Add to dashboard Cite

“…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.

View full text Add to dashboard Cite

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.)

show abstract

The use of the Thematic Mapper for the analysis of eutrophic lakes: a case study in the Netherlands.

Cited by 249 publications

References 5 publications

Artificial Neural Networks Application in Lake Water Quality Estimation Using Satellite Imagery

Artificial Neural Networks Application in Lake Water Quality Estimation Using Satellite Imagery

Empirical estimation of total phosphorus concentration in the mainstream of the Qiantang River in China using Landsat TM data

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

Contact Info

Product

Resources

About