Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh
Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future l...
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creator | Rahman, M. Tauhid Ur Tabassum, Faheemah Rasheduzzaman, Md Saba, Humayra Sarkar, Lina Ferdous, Jannatul Uddin, Syed Zia Zahedul Islam, A. Z. M. |
description | Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future land use policy. The southwest coastal region of Bangladesh, especially Assasuni Upazila of Satkhira District, is the most vulnerable to natural disasters and has faced notable changes in its LULC due to the combined effects of natural and anthropogenic causes. The objectives of this study are to illustrate the temporal dynamics of LULC change in Assasuni Upazila over the last 27 years (i.e., between 1989 and 2015) and also to predict future land use change using CA-ANN (cellular automata and artificial neural network) model for the year 2028. Temporal dynamics of LULC change was analyzed, employing supervised classification of multi-temporal Landsat images. Then, prediction of future LULC was carried out by CA-ANN model using MOLUSCE plugin of QGIS. The analysis of LULC change revealed that the LULC of Assasuni had changed notably during 1989 to 2015. “Bare lands” decreased by 21% being occupied by other land uses, especially by “shrimp farms.” Shrimp farm area increased by 25.9% during this period, indicating a major occupational transformation from agriculture to shrimp aquaculture in the study area during the period under study. Reduction in “settlement” area revealed the trend of migration from the Upazila. The predicted LULC for the year 2028 showed that reduction in bare land area would continue and 1595.97 ha bare land would transform into shrimp farm during 2015 to 2028. Also, the impacts of the changing LULC on the livelihood of local people and migration status of the Upazila were analyzed from the data collected through focus group discussions and questionnaire surveys. The analysis revealed that the changing LULC and the occupational shift from paddy cultivation to shrimp farming were related to each other. Around 31.3% of the total respondents stated that at least one of their family members had migrated. Climate-driven southwestern coastal people usually migrate from the vulnerable rural areas towards the nearest relatively safe city due to adverse effects of natural disasters. To control the unplanned development and reduce the internal migration in Assasuni and other coastal areas, a comprehensive land use management plan was suggested that would |
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Tauhid Ur ; Tabassum, Faheemah ; Rasheduzzaman, Md ; Saba, Humayra ; Sarkar, Lina ; Ferdous, Jannatul ; Uddin, Syed Zia ; Zahedul Islam, A. Z. M.</creator><creatorcontrib>Rahman, M. Tauhid Ur ; Tabassum, Faheemah ; Rasheduzzaman, Md ; Saba, Humayra ; Sarkar, Lina ; Ferdous, Jannatul ; Uddin, Syed Zia ; Zahedul Islam, A. Z. M.</creatorcontrib><description>Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future land use policy. The southwest coastal region of Bangladesh, especially Assasuni Upazila of Satkhira District, is the most vulnerable to natural disasters and has faced notable changes in its LULC due to the combined effects of natural and anthropogenic causes. The objectives of this study are to illustrate the temporal dynamics of LULC change in Assasuni Upazila over the last 27 years (i.e., between 1989 and 2015) and also to predict future land use change using CA-ANN (cellular automata and artificial neural network) model for the year 2028. Temporal dynamics of LULC change was analyzed, employing supervised classification of multi-temporal Landsat images. Then, prediction of future LULC was carried out by CA-ANN model using MOLUSCE plugin of QGIS. The analysis of LULC change revealed that the LULC of Assasuni had changed notably during 1989 to 2015. “Bare lands” decreased by 21% being occupied by other land uses, especially by “shrimp farms.” Shrimp farm area increased by 25.9% during this period, indicating a major occupational transformation from agriculture to shrimp aquaculture in the study area during the period under study. Reduction in “settlement” area revealed the trend of migration from the Upazila. The predicted LULC for the year 2028 showed that reduction in bare land area would continue and 1595.97 ha bare land would transform into shrimp farm during 2015 to 2028. Also, the impacts of the changing LULC on the livelihood of local people and migration status of the Upazila were analyzed from the data collected through focus group discussions and questionnaire surveys. The analysis revealed that the changing LULC and the occupational shift from paddy cultivation to shrimp farming were related to each other. Around 31.3% of the total respondents stated that at least one of their family members had migrated. Climate-driven southwestern coastal people usually migrate from the vulnerable rural areas towards the nearest relatively safe city due to adverse effects of natural disasters. To control the unplanned development and reduce the internal migration in Assasuni and other coastal areas, a comprehensive land use management plan was suggested that would accommodate the diversified uses of coastal lands and eventually lessen the threats to the life and livelihood of the local people.</description><identifier>ISSN: 0167-6369</identifier><identifier>EISSN: 1573-2959</identifier><identifier>DOI: 10.1007/s10661-017-6272-0</identifier><identifier>PMID: 29039035</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Agricultural management ; Agriculture ; Agriculture - methods ; Anthropogenic factors ; Aquaculture ; Area ; Artificial neural networks ; Atmospheric Protection/Air Quality Control/Air Pollution ; Bangladesh ; Cellular automata ; Cities ; Climate ; Coastal zone ; Conservation of Natural Resources - methods ; Cultivation ; Data processing ; Disasters ; Dynamics ; Earth and Environmental Science ; Ecology ; Ecotoxicology ; Environment ; Environmental degradation ; Environmental Management ; Environmental monitoring ; Environmental Monitoring - methods ; Environmental science ; Farms ; Fisheries ; Human influences ; Image classification ; Internal migration ; Land cover ; Land management ; Land use ; Land use management ; Landsat ; Landsat satellites ; Livelihood ; Marine crustaceans ; Mathematical models ; Modelling ; Monitoring/Environmental Analysis ; Natural disasters ; Neural networks ; Policies ; Population Growth ; Predictions ; Reduction ; Remote sensing ; Rural areas ; Rural land use ; Satellite Imagery ; Shellfish farming ; Shrimp culture ; Surveys</subject><ispartof>Environmental monitoring and assessment, 2017-11, Vol.189 (11), p.565-565, Article 565</ispartof><rights>Springer International Publishing AG 2017</rights><rights>Environmental Monitoring and Assessment is a copyright of Springer, 2017.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c438t-2ff851e17279b1ec0e917a6cde358dc43e050a823877fa9a4d5cbd8c7dcee55c3</citedby><cites>FETCH-LOGICAL-c438t-2ff851e17279b1ec0e917a6cde358dc43e050a823877fa9a4d5cbd8c7dcee55c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10661-017-6272-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10661-017-6272-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29039035$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rahman, M. Tauhid Ur</creatorcontrib><creatorcontrib>Tabassum, Faheemah</creatorcontrib><creatorcontrib>Rasheduzzaman, Md</creatorcontrib><creatorcontrib>Saba, Humayra</creatorcontrib><creatorcontrib>Sarkar, Lina</creatorcontrib><creatorcontrib>Ferdous, Jannatul</creatorcontrib><creatorcontrib>Uddin, Syed Zia</creatorcontrib><creatorcontrib>Zahedul Islam, A. Z. M.</creatorcontrib><title>Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh</title><title>Environmental monitoring and assessment</title><addtitle>Environ Monit Assess</addtitle><addtitle>Environ Monit Assess</addtitle><description>Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future land use policy. The southwest coastal region of Bangladesh, especially Assasuni Upazila of Satkhira District, is the most vulnerable to natural disasters and has faced notable changes in its LULC due to the combined effects of natural and anthropogenic causes. The objectives of this study are to illustrate the temporal dynamics of LULC change in Assasuni Upazila over the last 27 years (i.e., between 1989 and 2015) and also to predict future land use change using CA-ANN (cellular automata and artificial neural network) model for the year 2028. Temporal dynamics of LULC change was analyzed, employing supervised classification of multi-temporal Landsat images. Then, prediction of future LULC was carried out by CA-ANN model using MOLUSCE plugin of QGIS. The analysis of LULC change revealed that the LULC of Assasuni had changed notably during 1989 to 2015. “Bare lands” decreased by 21% being occupied by other land uses, especially by “shrimp farms.” Shrimp farm area increased by 25.9% during this period, indicating a major occupational transformation from agriculture to shrimp aquaculture in the study area during the period under study. Reduction in “settlement” area revealed the trend of migration from the Upazila. The predicted LULC for the year 2028 showed that reduction in bare land area would continue and 1595.97 ha bare land would transform into shrimp farm during 2015 to 2028. Also, the impacts of the changing LULC on the livelihood of local people and migration status of the Upazila were analyzed from the data collected through focus group discussions and questionnaire surveys. The analysis revealed that the changing LULC and the occupational shift from paddy cultivation to shrimp farming were related to each other. Around 31.3% of the total respondents stated that at least one of their family members had migrated. Climate-driven southwestern coastal people usually migrate from the vulnerable rural areas towards the nearest relatively safe city due to adverse effects of natural disasters. To control the unplanned development and reduce the internal migration in Assasuni and other coastal areas, a comprehensive land use management plan was suggested that would accommodate the diversified uses of coastal lands and eventually lessen the threats to the life and livelihood of the local people.</description><subject>Agricultural management</subject><subject>Agriculture</subject><subject>Agriculture - methods</subject><subject>Anthropogenic factors</subject><subject>Aquaculture</subject><subject>Area</subject><subject>Artificial neural networks</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Bangladesh</subject><subject>Cellular automata</subject><subject>Cities</subject><subject>Climate</subject><subject>Coastal zone</subject><subject>Conservation of Natural Resources - methods</subject><subject>Cultivation</subject><subject>Data processing</subject><subject>Disasters</subject><subject>Dynamics</subject><subject>Earth and Environmental Science</subject><subject>Ecology</subject><subject>Ecotoxicology</subject><subject>Environment</subject><subject>Environmental degradation</subject><subject>Environmental Management</subject><subject>Environmental monitoring</subject><subject>Environmental Monitoring - methods</subject><subject>Environmental science</subject><subject>Farms</subject><subject>Fisheries</subject><subject>Human influences</subject><subject>Image classification</subject><subject>Internal migration</subject><subject>Land cover</subject><subject>Land management</subject><subject>Land use</subject><subject>Land use management</subject><subject>Landsat</subject><subject>Landsat satellites</subject><subject>Livelihood</subject><subject>Marine crustaceans</subject><subject>Mathematical models</subject><subject>Modelling</subject><subject>Monitoring/Environmental Analysis</subject><subject>Natural disasters</subject><subject>Neural networks</subject><subject>Policies</subject><subject>Population Growth</subject><subject>Predictions</subject><subject>Reduction</subject><subject>Remote sensing</subject><subject>Rural areas</subject><subject>Rural land use</subject><subject>Satellite Imagery</subject><subject>Shellfish farming</subject><subject>Shrimp culture</subject><subject>Surveys</subject><issn>0167-6369</issn><issn>1573-2959</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp1kU1rGzEQhkVpaVy3PyCXIOill21GWmslHR3TLwjpJT0LWZqNN-yuHGm3xf--4zoNoVAQjNA8885oXsbOBXwUAPqyCGgaUYHQVSO1rOAFWwil60paZV-yBYiGMnVjz9ibUu4BwOqVfc3OpIWajlqwwy0O-5R9z-Nh9EMXCk8t7_0Y-Vzw8s8lpJ-Yedj58Q758aGbCt9njF2YujQS2I13fLOu1jc3fEgRe96mzEuap90vLBPmkTR8majLFYn0PmLZvWWvWt8XfPcYl-zH50-3m6_V9fcv3zbr6yqsajNVsm2NEii01HYrMABaoX0TItbKRGIQFHgja6N1661fRRW20QQdA6JSoV6yDyfdfU4PM43jhq4E7OlrmObihFUSrDFWEPr-H_Q-zXmk6Y6UUNBIa4gSJyrkVErG1u1zN_h8cALc0Rd38sWRL-7oiwOquXhUnrcDxqeKv0YQIE9AoRTtOT9r_V_V3xHUmSA</recordid><startdate>20171101</startdate><enddate>20171101</enddate><creator>Rahman, M. 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Tauhid Ur ; Tabassum, Faheemah ; Rasheduzzaman, Md ; Saba, Humayra ; Sarkar, Lina ; Ferdous, Jannatul ; Uddin, Syed Zia ; Zahedul Islam, A. Z. 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Tauhid Ur</au><au>Tabassum, Faheemah</au><au>Rasheduzzaman, Md</au><au>Saba, Humayra</au><au>Sarkar, Lina</au><au>Ferdous, Jannatul</au><au>Uddin, Syed Zia</au><au>Zahedul Islam, A. Z. M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh</atitle><jtitle>Environmental monitoring and assessment</jtitle><stitle>Environ Monit Assess</stitle><addtitle>Environ Monit Assess</addtitle><date>2017-11-01</date><risdate>2017</risdate><volume>189</volume><issue>11</issue><spage>565</spage><epage>565</epage><pages>565-565</pages><artnum>565</artnum><issn>0167-6369</issn><eissn>1573-2959</eissn><abstract>Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future land use policy. The southwest coastal region of Bangladesh, especially Assasuni Upazila of Satkhira District, is the most vulnerable to natural disasters and has faced notable changes in its LULC due to the combined effects of natural and anthropogenic causes. The objectives of this study are to illustrate the temporal dynamics of LULC change in Assasuni Upazila over the last 27 years (i.e., between 1989 and 2015) and also to predict future land use change using CA-ANN (cellular automata and artificial neural network) model for the year 2028. Temporal dynamics of LULC change was analyzed, employing supervised classification of multi-temporal Landsat images. Then, prediction of future LULC was carried out by CA-ANN model using MOLUSCE plugin of QGIS. The analysis of LULC change revealed that the LULC of Assasuni had changed notably during 1989 to 2015. “Bare lands” decreased by 21% being occupied by other land uses, especially by “shrimp farms.” Shrimp farm area increased by 25.9% during this period, indicating a major occupational transformation from agriculture to shrimp aquaculture in the study area during the period under study. Reduction in “settlement” area revealed the trend of migration from the Upazila. The predicted LULC for the year 2028 showed that reduction in bare land area would continue and 1595.97 ha bare land would transform into shrimp farm during 2015 to 2028. Also, the impacts of the changing LULC on the livelihood of local people and migration status of the Upazila were analyzed from the data collected through focus group discussions and questionnaire surveys. The analysis revealed that the changing LULC and the occupational shift from paddy cultivation to shrimp farming were related to each other. Around 31.3% of the total respondents stated that at least one of their family members had migrated. Climate-driven southwestern coastal people usually migrate from the vulnerable rural areas towards the nearest relatively safe city due to adverse effects of natural disasters. To control the unplanned development and reduce the internal migration in Assasuni and other coastal areas, a comprehensive land use management plan was suggested that would accommodate the diversified uses of coastal lands and eventually lessen the threats to the life and livelihood of the local people.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>29039035</pmid><doi>10.1007/s10661-017-6272-0</doi><tpages>1</tpages></addata></record> |
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recordid | cdi_proquest_miscellaneous_1952098891 |
source | MEDLINE; Springer Nature - Complete Springer Journals |
subjects | Agricultural management Agriculture Agriculture - methods Anthropogenic factors Aquaculture Area Artificial neural networks Atmospheric Protection/Air Quality Control/Air Pollution Bangladesh Cellular automata Cities Climate Coastal zone Conservation of Natural Resources - methods Cultivation Data processing Disasters Dynamics Earth and Environmental Science Ecology Ecotoxicology Environment Environmental degradation Environmental Management Environmental monitoring Environmental Monitoring - methods Environmental science Farms Fisheries Human influences Image classification Internal migration Land cover Land management Land use Land use management Landsat Landsat satellites Livelihood Marine crustaceans Mathematical models Modelling Monitoring/Environmental Analysis Natural disasters Neural networks Policies Population Growth Predictions Reduction Remote sensing Rural areas Rural land use Satellite Imagery Shellfish farming Shrimp culture Surveys |
title | Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T13%3A37%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Temporal%20dynamics%20of%20land%20use/land%20cover%20change%20and%20its%20prediction%20using%20CA-ANN%20model%20for%20southwestern%20coastal%20Bangladesh&rft.jtitle=Environmental%20monitoring%20and%20assessment&rft.au=Rahman,%20M.%20Tauhid%20Ur&rft.date=2017-11-01&rft.volume=189&rft.issue=11&rft.spage=565&rft.epage=565&rft.pages=565-565&rft.artnum=565&rft.issn=0167-6369&rft.eissn=1573-2959&rft_id=info:doi/10.1007/s10661-017-6272-0&rft_dat=%3Cproquest_cross%3E1952098891%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1951506298&rft_id=info:pmid/29039035&rfr_iscdi=true |