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RISS 인기검색어
- 검색키워드
- 저자 : Hossein Mojaddadi Rizeei (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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Saharkhiz, Maryam Adel,Pradhan, Biswajeet,Rizeei, Hossein Mojaddadi,Jung, Hyung-Sup The Korean Society of Remote Sensing 2020 大韓遠隔探査學會誌 Vol.36 No.1
Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.
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Maryam Adel Saharkhiz,Biswajeet Pradhan,Hossein Mojaddadi Rizeei,정형섭 대한원격탐사학회 2020 大韓遠隔探査學會誌 Vol.36 No.1
Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster- Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.
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Ratiranjan Jena,Biswajeet Pradhan,정형섭,Abhishek Kumar Rai,Hossein Mojaddadi Rizeei 대한원격탐사학회 2020 大韓遠隔探査學會誌 Vol.36 No.1
Seasonal changes in river water vary seasonally as well as locationally, and the assessment is essential. In this study, we used the recent technique of post-classification by using the Google earth engine (GEE) to map the seasonal changes in Mahanadi river of Odisha. However, some fixed problems results during the rainy season that affects the livelihood system of Cuttack such as flooding, drowning of children and waste material deposit. Therefore, this study conducted 1) to map and analyse the water density changes and 2) to analyse the seasonal variation of river water to resolve and prevent problem shortcomings. Our results showed that nine types of variation can be found in the Mahanadi River each year. The increase and decrease of intensity of surface water analysed, and it varies in between -130 to 70 m3/nf. The highest frequency change is 2900 Hz near Cuttack city. The pi diagram provides the percentage of seasonal variation that can be observed as permanent water (30%), new seasonal (28%), ephemeral (12%), permanent to seasonal (7%) and seasonal (10%). The analysis is helpful and effective to assess the seasonal variation that can provide a platform for the development of Cuttack city that lies in Mahanadi delta.
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Jena, Ratiranjan,Pradhan, Biswajeet,Jung, Hyung-Sup,Rai, Abhishek Kumar,Rizeei, Hossein Mojaddadi The Korean Society of Remote Sensing 2020 大韓遠隔探査學會誌 Vol.36 No.1
Seasonal changes in river water vary seasonally as well as locationally, and the assessment is essential. In this study, we used the recent technique of post-classification by using the Google earth engine (GEE) to map the seasonal changes in Mahanadi river of Odisha. However,some fixed problems results during the rainy season that affects the livelihood system of Cuttack such as flooding, drowning of children and waste material deposit. Therefore, this study conducted 1) to map and analyse the water density changes and 2) to analyse the seasonal variation of river water to resolve and prevent problem shortcomings. Our results showed that nine types of variation can be found in the Mahanadi River each year. The increase and decrease of intensity of surface water analysed, and it varies in between -130 to 70 ㎥/nf. The highest frequency change is 2900 Hz near Cuttack city. The pi diagram provides the percentage of seasonal variation that can be observed as permanent water (30%), new seasonal (28%), ephemeral (12%), permanent to seasonal (7%) and seasonal (10%). The analysis is helpful and effective to assess the seasonal variation that can provide a platform for the development of Cuttack city that lies in Mahanadi delta.
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