A hybrid land-use mapping approach based on multi-scale spatial context

Jingbo  Chen; Hichem Sahli; Jiansheng  Chen; Wang Chengyin; Dongxu  He; Anzhi  Yue

A hybrid land-use mapping approach based on multi-scale spatial context

Jingbo Chen, Hichem Sahli, Jiansheng Chen, Wang Chengyin, Dongxu He, Anzhi Yue

Electronics and Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

1 Citation (Scopus)

Abstract

Multi-scale spatial context which integrates spatial metrics and textural metrics is used to characterize land-use parcel and a hybrid land-use mapping approach is proposed in this paper. In terms of land-use characterization, the contributions of textural and spatial metrics are evaluated quantitatively. In terms of land-use categorization, a hybrid land-use classification scheme which combines Pairwise Decision Tree based Support Vector Machine (PDTSVM) and rule based decision tree is designed to classify parcels into construction, cultivated and uncultivated agricultural parcels. Experiment show that applying the presented technique can facilitate land-use mapping.

Original language	English
Title of host publication	IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
Publisher	IEEE
Pages	771-774
ISBN (Electronic)	2153-7003
Publication status	Published - 2016
Event	IEEE International Geoscience and Remote Sensing Symposium - IEEE, Beijing, China Duration: 10 Jul 2016 → 15 Jul 2016 http://www.igarss2016.org/

Conference

Conference	IEEE International Geoscience and Remote Sensing Symposium
Abbreviated title	IGARSS 2016
Country/Territory	China
City	Beijing
Period	10/07/16 → 15/07/16
Internet address	http://www.igarss2016.org/

Keywords

remote sensing
Classification
decsion trees

IRP5: Objectifying Assessment of Human Emotional Processing and Expression of Clinical and Psychotherapy Applications (EMO-App)
Sahli, H., Vandekerckhove, M. & Kerckhofs, E.
1/04/13 → 31/03/18
Project: Fundamental
SRP11: Strategic Research Programme: Processing of large scale multi-dimensional, multi-spectral, multi-sensorial and distributed data (M³D²)
Schelkens, P., Deligiannis, N., Jansen, B., Kuijk, M., Munteanu, A., Sahli, H., Steenhaut, K., Stiens, J., Schelkens, P., Cornelis, J. P., Kuijk, M., Munteanu, A., Sahli, H., Stiens, J. & Vounckx, R.
1/11/12 → 31/12/23
Project: Fundamental

Cite this

@inproceedings{a3922e792cc441f880ad2370841a2c13,

title = "A hybrid land-use mapping approach based on multi-scale spatial context",

abstract = "Multi-scale spatial context which integrates spatial metrics and textural metrics is used to characterize land-use parcel and a hybrid land-use mapping approach is proposed in this paper. In terms of land-use characterization, the contributions of textural and spatial metrics are evaluated quantitatively. In terms of land-use categorization, a hybrid land-use classification scheme which combines Pairwise Decision Tree based Support Vector Machine (PDTSVM) and rule based decision tree is designed to classify parcels into construction, cultivated and uncultivated agricultural parcels. Experiment show that applying the presented technique can facilitate land-use mapping.",

keywords = "remote sensing, Classification, decsion trees",

author = "Jingbo Chen and Hichem Sahli and Jiansheng Chen and Wang Chengyin and Dongxu He and Anzhi Yue",

year = "2016",

language = "English",

pages = "771--774",

booktitle = "IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016",

publisher = "IEEE",

note = "IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 ; Conference date: 10-07-2016 Through 15-07-2016",

url = "http://www.igarss2016.org/",

}

TY - GEN

T1 - A hybrid land-use mapping approach based on multi-scale spatial context

AU - Chen, Jingbo

AU - Sahli, Hichem

AU - Chen, Jiansheng

AU - Chengyin, Wang

AU - He, Dongxu

AU - Yue, Anzhi

PY - 2016

Y1 - 2016

N2 - Multi-scale spatial context which integrates spatial metrics and textural metrics is used to characterize land-use parcel and a hybrid land-use mapping approach is proposed in this paper. In terms of land-use characterization, the contributions of textural and spatial metrics are evaluated quantitatively. In terms of land-use categorization, a hybrid land-use classification scheme which combines Pairwise Decision Tree based Support Vector Machine (PDTSVM) and rule based decision tree is designed to classify parcels into construction, cultivated and uncultivated agricultural parcels. Experiment show that applying the presented technique can facilitate land-use mapping.

AB - Multi-scale spatial context which integrates spatial metrics and textural metrics is used to characterize land-use parcel and a hybrid land-use mapping approach is proposed in this paper. In terms of land-use characterization, the contributions of textural and spatial metrics are evaluated quantitatively. In terms of land-use categorization, a hybrid land-use classification scheme which combines Pairwise Decision Tree based Support Vector Machine (PDTSVM) and rule based decision tree is designed to classify parcels into construction, cultivated and uncultivated agricultural parcels. Experiment show that applying the presented technique can facilitate land-use mapping.

KW - remote sensing

KW - Classification

KW - decsion trees

M3 - Conference paper

SP - 771

EP - 774

BT - IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016

PB - IEEE

T2 - IEEE International Geoscience and Remote Sensing Symposium

Y2 - 10 July 2016 through 15 July 2016

ER -

A hybrid land-use mapping approach based on multi-scale spatial context

Abstract

Conference

Keywords

Fingerprint

Projects

IRP5: Objectifying Assessment of Human Emotional Processing and Expression of Clinical and Psychotherapy Applications (EMO-App)

SRP11: Strategic Research Programme: Processing of large scale multi-dimensional, multi-spectral, multi-sensorial and distributed data (M³D²)

Cite this