Könyv Accuracy Analysis of Satellite Image Classification Techniques Nagarajan Sureshkumar

Accuracy Analysis of Satellite Image Classification Techniques

Land Cover Changes using Combined LANDSAT and ENVISAT Images

Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
16 871 Ft
Recent monsoon failures and reduced rain falls urge the environmental and ecology researchers to con...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2016
oldal
112
EAN
9783330013827
ISBN
3330013826
Enbook ID
15664895
Súly
183
Méretek
150 x 220 x 7

Teljes leírás

Recent monsoon failures and reduced rain falls urge the environmental and ecology researchers to concentrate on the land cover changes. Significant and efficient way to monitor the land cover changes is satellite image classification. Classification of land cover changes of the study area are identified as used land, unused land, forest and vegetation. Using different kinds of remote sensing data like LANDSAT and ENVISAT, is an important research area for improving the classification performance. This work describes the combination of remotely sensed data, LANDSAT and ENVISAT images, to improve the classification accuracy. Classification algorithms KNN (K-Nearest Neighborhood) and SVM (Support Vector Machine) are tested for the accuracy and KNN in Embedding Space (KNNES) and SVM in Embedding Space (SVMES) are proposed and tested for the improved accuracy. Accuracy is quantified by reporting standard errors i.e., producer accuracy, user accuracy, omission error and commission error.

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