NDLI: Evaluating the impact of classification algorithms and spatial resolution on the accuracy of land cover mapping in a mountain environment in Pakistan

Please wait, while we are loading the content...

Gravity anomaly interpretation of 2D fault morphologies by means of nonplanar fault planes and exponential density contrast model: a space domain technique

Determination of zero difference GPS differential code biases for satellites and prominent receiver types

Shallow-water tidal analysis at Sharm Obhur, Jeddah, Red Sea

Evaluating the impact of classification algorithms and spatial resolution on the accuracy of land cover mapping in a mountain environment in Pakistan

An ARMA(1,1) model for monthly stream flows

Evolution of the transtensional structure in Huimin sag of Bohai Bay basin, eastern China

Hazard degree identification and coupling analysis of the influencing factors on goafs

Formation of hydrochemical composition and spatio-temporal evolution mechanism under mining-induced disturbance in the Linhuan coal-mining district

Dissolution sequestration mechanism of CO$_{2}$ at the Shiqianfeng saline aquifer in the Ordos Basin, northwestern China

Empirical equations for flood analysis in arid zones: the Ari-Zo model

Mineralogy, geochemistry, and ore formation of Nuwaifa bauxite deposit, western desert of Iraq

Aeromagnetic data over Harrat Lunayyir and surrounding areas, western Saudi Arabia

Evaluating the Baluti Formation at Sararu village, Ora Anticline, Iraqi Kurdistan: a stratigraphic and geochemical approach

Thermobarometry in the Sarvian Fe-skarn deposit (Central Iran) based on garnet–pyroxene chemistry and fluid inclusion studies

The Wajid Sandstone around Abha/Khamis Mushayt and in its type area: lithostratigraphic architecture and correlations

Hydrochemistry, multidimensional statistics, and rock mechanics investigations for Sanshandao Gold Mine, China

Sedimentological interpretation of coastal ditch cuttings: implications for subsurface geology and provenance in Dahomey Basin, Nigeria

Assessing the influence of watershed characteristics on soil erosion susceptibility of Jhelum basin in Kashmir Himalayas

Arabian Journal of Geosciences : Volume 10, Issue 2, January 2017

Arabian Journal of Geosciences : Volume 10, Issue 1, January 2017

Arabian Journal of Geosciences : Volume 9

Arabian Journal of Geosciences : Volume 8

Arabian Journal of Geosciences : Volume 7

Arabian Journal of Geosciences : Volume 6

Arabian Journal of Geosciences : Volume 5

Arabian Journal of Geosciences : Volume 4

Arabian Journal of Geosciences : Volume 3

Arabian Journal of Geosciences : Volume 2

Arabian Journal of Geosciences : Volume 1

Evaluating the impact of classification algorithms and spatial resolution on the accuracy of land cover mapping in a mountain environment in Pakistan

Content Provider	Springer Nature Link
Author	Ullah, Sami Shafique, Muhammad Farooq, Muhammad Zeeshan, Muhammad Dees, Matthias
Copyright Year	2017
Abstract	Satellite images of various spatial resolutions and different image classification techniques have been utilized for land cover (LC) mapping at local and regional scale studies. Mapping capabilities and achievable accuracies of LC classification in a mountain environment are, however, influenced by the spatial resolution of the utilized images and applied classification techniques. Hence, developing and characterizing regionally optimized methods are essential for the planning and monitoring of natural resources. In this study, the potential of four non-parametric image classification techniques, i.e., k-nearest neighbor (k-NN), support vector machine (SVM), random forest (RF), and neural network (NN) on the accuracy of LC classification was evaluated in the Hindu Kush mountains ranges of northern Pakistan. Moreover, we have assessed the impact of the spatial resolution of the utilized satellite imagery, i.e., SPOT-5 with 2.5 m and Landsat-8 with 30 m on the accuracy of the derived LC classification. For the classification of LC based on SPOT-5, we have achieved the highest overall classification accuracy (OCA) = 89% with kappa coefficient (KC = 0.86) using SVM followed by k-NN, RF, and NN. However, for LC classification derived from Landsat-8 imagery, we achieved the highest OCA = 71% with KC = 0.59 using RF and SVM followed by k-NN and NN. The higher accuracy derived from SPOT-5 versus Landsat-8 indicated that the results of LC classification based on SPOT-5 are more accurate and reliable than Landsat-8. The findings of the present study will be useful for the classification and mapping task of LC in a mountain environment using SPOT-5 and Landsat-8 at local and regional scale studies.
Starting Page	1
Ending Page	11
Page Count	11
File Format	PDF
ISSN	18667511
Journal	Arabian Journal of Geosciences
Volume Number	10
Issue Number	3
e-ISSN	18667538
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2017-02-01
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Land cover k-nearest neighbor Support vector machine Random forest Neural network Landsat-8 Spot-5 Earth Sciences
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Environmental Science

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Assessment of k-Nearest Neighbor and Random Forest Classifiers for Mapping Forest Fire Areas in Central Portugal Using Landsat-8, Sentinel-2, and Terra Imagery

Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery

MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP

HOW LANDSAT 9 IS SUPERIOR TO LANDSAT 8: COMPARATIVE ASSESSMENT OF LAND USE LAND COVER CLASSIFICATION AND LAND SURFACE TEMPERATURE

Landsat-comparable land cover maps using ASTER and SPOT images: a case study for large-area mapping programmes

Object-oriented land use cover classification of Landsat 8 OLI images in Sumatra

A Method to Determine Appropriate Spatial Resolution for Hard Image Classification

Evaluating the Performance of a Random Forest Kernel for Land Cover Classification

A Patch-Based Light Convolutional Neural Network for Land-Cover Mapping Using Landsat-8 Images

Evaluating the impact of classification algorithms and spatial resolution on the accuracy of land cover mapping in a mountain environment in Pakistan

Similar Documents

Assessment of k-Nearest Neighbor and Random Forest Classifiers for Mapping Forest Fire Areas in Central Portugal Using Landsat-8, Sentinel-2, and Terra Imagery

Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery

MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP

HOW LANDSAT 9 IS SUPERIOR TO LANDSAT 8: COMPARATIVE ASSESSMENT OF LAND USE LAND COVER CLASSIFICATION AND LAND SURFACE TEMPERATURE

Landsat-comparable land cover maps using ASTER and SPOT images: a case study for large-area mapping programmes

Object-oriented land use cover classification of Landsat 8 OLI images in Sumatra

A Method to Determine Appropriate Spatial Resolution for Hard Image Classification

Evaluating the Performance of a Random Forest Kernel for Land Cover Classification

A Patch-Based Light Convolutional Neural Network for Land-Cover Mapping Using Landsat-8 Images

Evaluating the impact of classification algorithms and spatial resolution on the accuracy of land cover mapping in a mountain environment in Pakistan