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Pixel Purity Index Applied to the Mapping of Degraded Soils by the Presence of Cangahuas in the Ilaló Volcano, Ecuador

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@article{IJASEIT14684,
   author = {Iván Palacios and Dennis Ushiña and David Carrera},
   title = {Pixel Purity Index Applied to the Mapping of Degraded Soils  by the Presence of Cangahuas in the Ilaló Volcano, Ecuador},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {11},
   number = {5},
   year = {2021},
   pages = {2121--2127},
   keywords = {Endmembers; remote sensing; physicochemical characterization.},
   abstract = {Soil degradation is a severe problem in the northern region of Ecuador. Due to deforestation, expansion of the agricultural frontier, and poor tillage practices, the outcrop of cangahuas further aggravates. Remote Sensing allows mapping this type of subsoil, which is often related to eroded areas; the spatial resolution of free multispectral images contains more than one coverage. This means that techniques to discern the pure spectral signature of the object of interest are required. Pixel Purity Index (PPI) is an endmember extraction algorithm capable of selecting the pure pixel and classifying it better than object-oriented techniques. The study's objective was to map soils with outcrops of cangahua, by PPI applied to Landsat 8 images in Ilaló volcano and later performed a physicochemical characterization to know the magnitude of the soil degradation in the mapped areas. We used two models with PPI: SAM and LSU; both were compared with classifications based on three vegetation indexes. LSU obtained the best result (91.2% accuracy and 0.81 Kappa coefficient). The mapped cangahua was approximately 806.85 ha. The soil had an average porosity of 45%, a relative density of 2.271 g/cm3, low concentrations of nitrates, phosphates, and sulfates, electrical conductivity <500 µS/cm, and alkaline pH, this means there is soil degradation. The PPI method had good accuracy and was achieved in identifying cangahua outcrops, which demonstrated its potentiality in mapping land cover.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14684},
   doi = {10.18517/ijaseit.11.5.14684}
}

EndNote

%A Palacios, Iván
%A Ushiña, Dennis
%A Carrera, David
%D 2021
%T Pixel Purity Index Applied to the Mapping of Degraded Soils  by the Presence of Cangahuas in the Ilaló Volcano, Ecuador
%B 2021
%9 Endmembers; remote sensing; physicochemical characterization.
%! Pixel Purity Index Applied to the Mapping of Degraded Soils  by the Presence of Cangahuas in the Ilaló Volcano, Ecuador
%K Endmembers; remote sensing; physicochemical characterization.
%X Soil degradation is a severe problem in the northern region of Ecuador. Due to deforestation, expansion of the agricultural frontier, and poor tillage practices, the outcrop of cangahuas further aggravates. Remote Sensing allows mapping this type of subsoil, which is often related to eroded areas; the spatial resolution of free multispectral images contains more than one coverage. This means that techniques to discern the pure spectral signature of the object of interest are required. Pixel Purity Index (PPI) is an endmember extraction algorithm capable of selecting the pure pixel and classifying it better than object-oriented techniques. The study's objective was to map soils with outcrops of cangahua, by PPI applied to Landsat 8 images in Ilaló volcano and later performed a physicochemical characterization to know the magnitude of the soil degradation in the mapped areas. We used two models with PPI: SAM and LSU; both were compared with classifications based on three vegetation indexes. LSU obtained the best result (91.2% accuracy and 0.81 Kappa coefficient). The mapped cangahua was approximately 806.85 ha. The soil had an average porosity of 45%, a relative density of 2.271 g/cm3, low concentrations of nitrates, phosphates, and sulfates, electrical conductivity <500 µS/cm, and alkaline pH, this means there is soil degradation. The PPI method had good accuracy and was achieved in identifying cangahua outcrops, which demonstrated its potentiality in mapping land cover.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14684
%R doi:10.18517/ijaseit.11.5.14684
%J International Journal on Advanced Science, Engineering and Information Technology
%V 11
%N 5
%@ 2088-5334

IEEE

Iván Palacios,Dennis Ushiña and David Carrera,"Pixel Purity Index Applied to the Mapping of Degraded Soils  by the Presence of Cangahuas in the Ilaló Volcano, Ecuador," International Journal on Advanced Science, Engineering and Information Technology, vol. 11, no. 5, pp. 2121-2127, 2021. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.11.5.14684.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Palacios, Iván
AU  - Ushiña, Dennis
AU  - Carrera, David
PY  - 2021
TI  - Pixel Purity Index Applied to the Mapping of Degraded Soils  by the Presence of Cangahuas in the Ilaló Volcano, Ecuador
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 11 (2021) No. 5
Y2  - 2021
SP  - 2121
EP  - 2127
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - Endmembers; remote sensing; physicochemical characterization.
N2  - Soil degradation is a severe problem in the northern region of Ecuador. Due to deforestation, expansion of the agricultural frontier, and poor tillage practices, the outcrop of cangahuas further aggravates. Remote Sensing allows mapping this type of subsoil, which is often related to eroded areas; the spatial resolution of free multispectral images contains more than one coverage. This means that techniques to discern the pure spectral signature of the object of interest are required. Pixel Purity Index (PPI) is an endmember extraction algorithm capable of selecting the pure pixel and classifying it better than object-oriented techniques. The study's objective was to map soils with outcrops of cangahua, by PPI applied to Landsat 8 images in Ilaló volcano and later performed a physicochemical characterization to know the magnitude of the soil degradation in the mapped areas. We used two models with PPI: SAM and LSU; both were compared with classifications based on three vegetation indexes. LSU obtained the best result (91.2% accuracy and 0.81 Kappa coefficient). The mapped cangahua was approximately 806.85 ha. The soil had an average porosity of 45%, a relative density of 2.271 g/cm3, low concentrations of nitrates, phosphates, and sulfates, electrical conductivity <500 µS/cm, and alkaline pH, this means there is soil degradation. The PPI method had good accuracy and was achieved in identifying cangahua outcrops, which demonstrated its potentiality in mapping land cover.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14684
DO  - 10.18517/ijaseit.11.5.14684

RefWorks

RT Journal Article
ID 14684
A1 Palacios, Iván
A1 Ushiña, Dennis
A1 Carrera, David
T1 Pixel Purity Index Applied to the Mapping of Degraded Soils  by the Presence of Cangahuas in the Ilaló Volcano, Ecuador
JF International Journal on Advanced Science, Engineering and Information Technology
VO 11
IS 5
YR 2021
SP 2121
OP 2127
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 Endmembers; remote sensing; physicochemical characterization.
AB Soil degradation is a severe problem in the northern region of Ecuador. Due to deforestation, expansion of the agricultural frontier, and poor tillage practices, the outcrop of cangahuas further aggravates. Remote Sensing allows mapping this type of subsoil, which is often related to eroded areas; the spatial resolution of free multispectral images contains more than one coverage. This means that techniques to discern the pure spectral signature of the object of interest are required. Pixel Purity Index (PPI) is an endmember extraction algorithm capable of selecting the pure pixel and classifying it better than object-oriented techniques. The study's objective was to map soils with outcrops of cangahua, by PPI applied to Landsat 8 images in Ilaló volcano and later performed a physicochemical characterization to know the magnitude of the soil degradation in the mapped areas. We used two models with PPI: SAM and LSU; both were compared with classifications based on three vegetation indexes. LSU obtained the best result (91.2% accuracy and 0.81 Kappa coefficient). The mapped cangahua was approximately 806.85 ha. The soil had an average porosity of 45%, a relative density of 2.271 g/cm3, low concentrations of nitrates, phosphates, and sulfates, electrical conductivity <500 µS/cm, and alkaline pH, this means there is soil degradation. The PPI method had good accuracy and was achieved in identifying cangahua outcrops, which demonstrated its potentiality in mapping land cover.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14684
DO  - 10.18517/ijaseit.11.5.14684