Pub Date : 2021-01-01DOI: 10.35198/01-2021-004-0004
{"title":"Developing Curriculum for the Training of Non-Specialist in Addiction Studies in Nigerian Universities: The Journey of Nigerian ICUDDR Team","authors":"","doi":"10.35198/01-2021-004-0004","DOIUrl":"https://doi.org/10.35198/01-2021-004-0004","url":null,"abstract":"","PeriodicalId":23534,"journal":{"name":"Volume 5, Issue 4","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74741456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.46243/jst.2021.v6.i1.pp101-109
Land is becoming scarce resource due to population growth and industrialization. Rapid growth of human activities can also be attributed as one of the reasons. Thus, it becomes an important task to regulate land resource for sustainable development and environmental protection. LULC change studies have become a central component in current strategies for managing and planning land resources and monitoring environmental changes. In this paper an attempt has been made to bring out spatio-temporal dynamics of LULC patterns of NTPCRamagundam and its surrounding environment by using multi-temporal satellite data of Landsat-4, IRS P6 LISS-III and IRS 2 LISS-IV and GIS techniques for the years 1984, 2005, 2011, 2015, 2018. The methodology includes base map preparation having features like Road (SH), Rail, Canal, River, Stream, Tanks, Forest boundary and other administrative boundaries from SOI topo sheet and the features digitized are updated on satellite images. Interpretation of study area for LULC feature extraction on satellite imageries of respective years is carried with Nrsc’s standard LULC classification system. Change detection statistics can be generated out of 5 LULC thematic layers obtained and analysed specially with respect to NTPC environs. Results from this study shows the percentage of geographical area occupied by built-up land, agricultural land, forests, wasteland and waterbodies of level-I LULC features were 10.27%, 60.68%, 6.61%, 11.81%, 10.63% respectively in 1984 and were changed into 21.41%, 48.51%, 5.97%, 12.77%, 11.34% respectively in 2018. This analysis shows a rapid growth in built-up land and fall in agricultural land between 1984 and 2018. There is a considerable change in the remaining features from 1984 and 2018.
{"title":"Spatio-Temporal Dynamics of Landuse/Land Cover Around NTPC\u0000Using High Resolution Satellite Imagery","authors":"","doi":"10.46243/jst.2021.v6.i1.pp101-109","DOIUrl":"https://doi.org/10.46243/jst.2021.v6.i1.pp101-109","url":null,"abstract":"Land is becoming scarce resource due to population growth and industrialization. Rapid growth of\u0000human activities can also be attributed as one of the reasons. Thus, it becomes an important task to regulate land\u0000resource for sustainable development and environmental protection. LULC change studies have become a central\u0000component in current strategies for managing and planning land resources and monitoring environmental changes.\u0000In this paper an attempt has been made to bring out spatio-temporal dynamics of LULC patterns of NTPCRamagundam and its surrounding environment by using multi-temporal satellite data of Landsat-4, IRS P6 LISS-III\u0000and IRS 2 LISS-IV and GIS techniques for the years 1984, 2005, 2011, 2015, 2018. The methodology includes base\u0000map preparation having features like Road (SH), Rail, Canal, River, Stream, Tanks, Forest boundary and other\u0000administrative boundaries from SOI topo sheet and the features digitized are updated on satellite images.\u0000Interpretation of study area for LULC feature extraction on satellite imageries of respective years is carried with\u0000Nrsc’s standard LULC classification system. Change detection statistics can be generated out of 5 LULC thematic\u0000layers obtained and analysed specially with respect to NTPC environs. Results from this study shows the percentage\u0000of geographical area occupied by built-up land, agricultural land, forests, wasteland and waterbodies of level-I\u0000LULC features were 10.27%, 60.68%, 6.61%, 11.81%, 10.63% respectively in 1984 and were changed into 21.41%,\u000048.51%, 5.97%, 12.77%, 11.34% respectively in 2018. This analysis shows a rapid growth in built-up land and fall\u0000in agricultural land between 1984 and 2018. There is a considerable change in the remaining features from 1984\u0000and 2018.","PeriodicalId":23534,"journal":{"name":"Volume 5, Issue 4","volume":"78 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85924742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}