Jean Paul Nkundabose, Félix Nshimiyimana, Gratien Twagirayezu, Olivier Irumva
{"title":"利用遥感工具评估卢旺达东部省土地利用/土地覆盖变化","authors":"Jean Paul Nkundabose, Félix Nshimiyimana, Gratien Twagirayezu, Olivier Irumva","doi":"10.11648/J.AJRS.20210901.13","DOIUrl":null,"url":null,"abstract":"The present paper attempted to study land use/land cover (LULC) changes in a rural region of Eastern Province, Rwanda. The particular study area consists of part of Ngoma, Rwamagana, Kayonza, Bugesera districts of Eastern province, Rwanda, and a tiny part of Burundi. The study considered LULC changes that happened in 15 years from 2005 to 2020. By means of Remote Sensing and GIS tools, Land use/Land cover (LULC) changes were detected. Possible causes linked to historical changes were highlighted accordingly. Multi-temporal remote sensing images (Landsat imagery) were used to generate land use/land cover (LULC) maps. Two temporal satellite images were collected, preprocessed, and classified through supervised Image classification stages in ENVI 5.1. Corresponding maps were exported by ArcGIS 10.7. Seven important classes including water, bare land, wetlands, agriculture, vegetation, forest, and built-up area were classified and detected for changes using both Image change workflow and Thematic change workflow tools in ENVI 5.1. Among seven classes of land use/land cover (LULC), four experienced gains while built-up area, forest, and bare land witnessed decrease/losses over the last 15 years period (2005-2020). Like Forest diminished from 197.8821 km2 in 2005 to 56.9304 km2 in 2020. Several factors including government policies and regulations, population growth, and economic development can be attributed to these changes. The present work can provide important insights on land use planning and management for the area under consideration and we believe this work to contribute to the literature on the application of ENVI and related remote sensing tools.","PeriodicalId":417484,"journal":{"name":"American Journal of Remote Sensing","volume":"442 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Employing Remote Sensing Tools for Assessment of Land Use/Land Cover (LULC) Changes in Eastern Province, Rwanda\",\"authors\":\"Jean Paul Nkundabose, Félix Nshimiyimana, Gratien Twagirayezu, Olivier Irumva\",\"doi\":\"10.11648/J.AJRS.20210901.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The present paper attempted to study land use/land cover (LULC) changes in a rural region of Eastern Province, Rwanda. The particular study area consists of part of Ngoma, Rwamagana, Kayonza, Bugesera districts of Eastern province, Rwanda, and a tiny part of Burundi. The study considered LULC changes that happened in 15 years from 2005 to 2020. By means of Remote Sensing and GIS tools, Land use/Land cover (LULC) changes were detected. Possible causes linked to historical changes were highlighted accordingly. Multi-temporal remote sensing images (Landsat imagery) were used to generate land use/land cover (LULC) maps. Two temporal satellite images were collected, preprocessed, and classified through supervised Image classification stages in ENVI 5.1. Corresponding maps were exported by ArcGIS 10.7. Seven important classes including water, bare land, wetlands, agriculture, vegetation, forest, and built-up area were classified and detected for changes using both Image change workflow and Thematic change workflow tools in ENVI 5.1. Among seven classes of land use/land cover (LULC), four experienced gains while built-up area, forest, and bare land witnessed decrease/losses over the last 15 years period (2005-2020). Like Forest diminished from 197.8821 km2 in 2005 to 56.9304 km2 in 2020. Several factors including government policies and regulations, population growth, and economic development can be attributed to these changes. The present work can provide important insights on land use planning and management for the area under consideration and we believe this work to contribute to the literature on the application of ENVI and related remote sensing tools.\",\"PeriodicalId\":417484,\"journal\":{\"name\":\"American Journal of Remote Sensing\",\"volume\":\"442 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11648/J.AJRS.20210901.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/J.AJRS.20210901.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Employing Remote Sensing Tools for Assessment of Land Use/Land Cover (LULC) Changes in Eastern Province, Rwanda
The present paper attempted to study land use/land cover (LULC) changes in a rural region of Eastern Province, Rwanda. The particular study area consists of part of Ngoma, Rwamagana, Kayonza, Bugesera districts of Eastern province, Rwanda, and a tiny part of Burundi. The study considered LULC changes that happened in 15 years from 2005 to 2020. By means of Remote Sensing and GIS tools, Land use/Land cover (LULC) changes were detected. Possible causes linked to historical changes were highlighted accordingly. Multi-temporal remote sensing images (Landsat imagery) were used to generate land use/land cover (LULC) maps. Two temporal satellite images were collected, preprocessed, and classified through supervised Image classification stages in ENVI 5.1. Corresponding maps were exported by ArcGIS 10.7. Seven important classes including water, bare land, wetlands, agriculture, vegetation, forest, and built-up area were classified and detected for changes using both Image change workflow and Thematic change workflow tools in ENVI 5.1. Among seven classes of land use/land cover (LULC), four experienced gains while built-up area, forest, and bare land witnessed decrease/losses over the last 15 years period (2005-2020). Like Forest diminished from 197.8821 km2 in 2005 to 56.9304 km2 in 2020. Several factors including government policies and regulations, population growth, and economic development can be attributed to these changes. The present work can provide important insights on land use planning and management for the area under consideration and we believe this work to contribute to the literature on the application of ENVI and related remote sensing tools.