Mapping vegetation in a heterogeneous mountain rangeland using landsat data: an alternative method to define and classify land-cover units

Cingolani, Ana M.; Renison, Daniel; Zak, Marcelo Román; Cabido, Marcelo

doi:10.1016/j.rse.2004.05.008

Cited by 187 publications

(239 citation statements)

References 47 publications

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“…This contrasts with a value lower than 85 % in several other reported land use classification studies (Foody 2002;Wilkinson 2005). For example, Cingolani et al (2004) showed overall accuracy and kappa for maximum likelihood 78 % and 0.74, respectively. In the study of Rozenstein and Karnieli (2010), overall accuracy and kappa coefficient were 70.67 % and 0.65 for ISODATA, 60.53 % and 0.53 for maximum likelihood, 73.50 and 0.68 for synthetic method.…”

Section: Resultscontrasting

confidence: 77%

A comparison of supervised, unsupervised and synthetic land use classification methods in the north of Iran

Mohammady

Moradi

Zeinivand

et al. 2014

Int. J. Environ. Sci. Technol.

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Land use classification is often the first step in land use studies and thus forms the basis for many earth science studies. In this paper, we focus on low-cost techniques for combining Landsat images with geographic information system approaches to create a land use map. In the Golestan region of Iran, we show that traditional supervised and unsupervised methods do not result in sufficiently accurate land use maps. Therefore, we evaluated a synthetic approach combining supervised and unsupervised methods with decision rules based on easily accessible ancillary data. For accuracy assessment, confusion matrices and kappa coefficients were calculated for the maps created with the supervised, unsupervised and synthetic approaches. Overall accuracy of the synthetic approach was 98.2 %, which is over the 85 % level that is considered satisfactory for planning and management purposes. This shows that integration of remote sensing data, ancillary data and decision rules provides better classification accuracy than traditional methods, without significant additional use of resources.

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Section: Resultscontrasting

confidence: 77%

A comparison of supervised, unsupervised and synthetic land use classification methods in the north of Iran

Mohammady

Moradi

Zeinivand

et al. 2014

Int. J. Environ. Sci. Technol.

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“…The similar values of P at different criteria indicates that alleles in several loci are present in similar frequencies throughout the whole population, which is presumably promoted by a high degree of gene flow (Nm = 10.9). Moreover, levels of genetic variability of the most degraded P. australis populations of Mina Clavero and Yuspe, which were characterized by isolated trees or small forest patches (TORRES et al, 2008;RENISON et al, 2006;CINGOLANI et al, 2004), were similar or even higher than other well conserved populations. NEI, 1972) between five populations of Polylepis australis.…”

Section: Discussionmentioning

confidence: 89%

Genetic structure and diversity ofPolylepis australis(Rosaceae) tree populations from central Argentina: Implications for forest conservation

et al. 2011

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Worldwide, large areas of forest are being transformed to other land cover types and the resulting fragmented populations may suffer from restricted gene flow leading to genetic pauperization and increased inbreeding. To assess the genetic constitution of fragmented Polylepis australis mountain forests of central Argentina, analyses of the structure and diversity of ISSR markers were carried out for 90 trees distributed throughout five river basins with differing degrees of fragmentation. Overall, average polymorphism (P) ranged between 87.2 and 94.9% (95% criterion) while marker diversity index (M) varied between 0.35 and 0.39; values which are comparable with other wind-pollinated tree species. Analysis of molecular variance (AMOVA) revealed that most genetic variation occurred within river basins (97.8%), with only a little occurring between river basins (2.2%; ΦST = 0.02). In addition, Mantel’s test indicated that P. australis does not follow the usual pattern of isolation by distance; instead the UPGMA method showed that trees from the two most degraded river basins formed a group while trees from the three better preserved basins formed another. As such, either effective pollen flow has maintained high levels of genetic diversity, or present day genetic variability is a remnant of a recently fragmented ancestral panmictic population. We conclude that, at present, genetic degradation in P. australis populations of central Argentina is not as important as ecological degradation – such as soil loss, intensive browsing by livestock or increased frequencies of wildfires, and that genetic variability is still fully available for forest restoration.

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“…This approach uses separate classifications of images acquired at different times to produce difference maps from which ''from-to'' change information can be generated [17]. Among the several classifiers available, the Maximum Likelihood Classifier (MLC) has been widely used to classify RS data and successful results of applying this classifier for land-cover mapping have been numerous (e.g., [18][19][20]) despite the limitations due to its assumption of normal distribution of class signatures [21]. Its use has also been effective in a number of post-classification comparison change detection studies (e.g., [12,[22][23][24]).…”

Section: Rs Change Detectionmentioning

confidence: 99%

Integrated Landsat Image Analysis and Hydrologic Modeling to Detect Impacts of 25-Year Land-Cover Change on Surface Runoff in a Philippine Watershed

2011

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Landsat MSS and ETM+ images were analyzed to detect 25-year land-cover change in the critical Taguibo Watershed in Mindanao Island, Southern Philippines. This watershed has experienced historical modifications of its land-cover due to the presence of logging industries in the 1950s, and continuous deforestation due to illegal logging and slash-and-burn agriculture in the present time. To estimate the impacts of land-cover change on watershed runoff, land-cover information derived from the Landsat images was utilized to parameterize a GIS-based hydrologic model. The model was then calibrated with field-measured discharge data and used to simulate the responses of the watershed in its year 2001 and year 1976 land-cover conditions. The availability of land-cover information on the most recent state of the watershed from the Landsat ETM+ image made it possible to locate areas for rehabilitation such as barren and logged-over areas. We then created a "rehabilitated" land-cover condition map of the watershed (re-forestation of logged-over areas and agro-forestation of barren areas) and used it to parameterize the model and predict the runoff responses of the watershed. Model results showed that changes in land-cover from 1976 to 2001 were directly related to the significant increase in surface runoff. Runoff predictions showed that a full rehabilitation of the watershed, especially in barren and logged-over areas, will be likely to reduce the generation of a huge volume of runoff during rainfall events. The results of this study have OPEN ACCESSRemote Sens. 2011, 3 1068 demonstrated the usefulness of multi-temporal Landsat images in detecting land-cover change, in identifying areas for rehabilitation, and in evaluating rehabilitation strategies for management of tropical watersheds through its use in hydrologic modeling.

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Mapping vegetation in a heterogeneous mountain rangeland using landsat data: an alternative method to define and classify land-cover units

Cited by 187 publications

References 47 publications

A comparison of supervised, unsupervised and synthetic land use classification methods in the north of Iran

A comparison of supervised, unsupervised and synthetic land use classification methods in the north of Iran

Genetic structure and diversity ofPolylepis australis(Rosaceae) tree populations from central Argentina: Implications for forest conservation

Integrated Landsat Image Analysis and Hydrologic Modeling to Detect Impacts of 25-Year Land-Cover Change on Surface Runoff in a Philippine Watershed

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