{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/16712"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/16712","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Impacts of climate change on global agricultural land availability","abstract":"This thesis uses several global databases, including soil properties, slope, temperature and precipitation to simulate agricultural land suitability under both current and projected climate from thirteen general circulation models (GCMs) and two emission scenarios, A1B & B1, which represent relatively high and low emission, respectively. Two ensemble methods, Simple Average Method (SAM) and Root Mean Square Error Ensemble Method (RMSEMM), are employed to assemble the regional climate change which attempts to abate the uncertainty involved in global GCM projections. Fuzzy logic, which handles land classification in an approximate yet efficient way, is adopted to estimate the land suitability through empirically determined membership functions of soil properties, slope, air temperature and Humidity Index, and fuzzy rules chosen through a learning process based on remote sensed crop land products. Land suitability under five scenarios, which are the baseline scenario with the present climate and four climate change projections, A1B-SAM, A1B-RMSEMM, B1-SAM, and B1-RMSEMM, is assessed for both global and seven important agricultural regions in the world. The change patterns of climatic factors and land suitability are explored and analyzed. It is found that countries at the high latitudes of north hemisphere are more likely to benefit from climate change, while countries at mid- and low latitudes may suffer different levels of loss of potential arable land. Expansions of the gross potential arable land are likely to occur in regions at the north high latitudes, like Russia, North China and U.S., while shrinking can be expected in South America, Africa, India and Europe. Although the greatest potential for agricultural expansion lies in Africa and South America, with current cultivated land accounting for approximately 20% of the net potential arable land in the world, negative effect from climate change may decline the potential. In summary, climate change is likely to alter the global distribution of potential arable land and further influence agricultural related socio-economic aspects by the end of this century.","abstract_html":"This thesis uses several global databases, including soil properties, slope, temperature and precipitation to simulate agricultural land suitability under both current and projected climate from thirteen general circulation models (GCMs) and two emission scenarios, A1B & B1, which represent relatively high and low emission, respectively. Two ensemble methods, Simple Average Method (SAM) and Root Mean Square Error Ensemble Method (RMSEMM), are employed to assemble the regional climate change which attempts to abate the uncertainty involved in global GCM projections. Fuzzy logic, which handles land classification in an approximate yet efficient way, is adopted to estimate the land suitability through empirically determined membership functions of soil properties, slope, air temperature and Humidity Index, and fuzzy rules chosen through a learning process based on remote sensed crop land products. Land suitability under five scenarios, which are the baseline scenario with the present climate and four climate change projections, A1B-SAM, A1B-RMSEMM, B1-SAM, and B1-RMSEMM, is assessed for both global and seven important agricultural regions in the world. The change patterns of climatic factors and land suitability are explored and analyzed. It is found that countries at the high latitudes of north hemisphere are more likely to benefit from climate change, while countries at mid- and low latitudes may suffer different levels of loss of potential arable land. Expansions of the gross potential arable land are likely to occur in regions at the north high latitudes, like Russia, North China and U.S., while shrinking can be expected in South America, Africa, India and Europe. Although the greatest potential for agricultural expansion lies in Africa and South America, with current cultivated land accounting for approximately 20% of the net potential arable land in the world, negative effect from climate change may decline the potential. In summary, climate change is likely to alter the global distribution of potential arable land and further influence agricultural related socio-economic aspects by the end of this century.","abstract_has_math":false,"creators":["Zhang, Xiao"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Cai, Ximing"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-08-20T17:55:40Z","date_published":"2010-08-20T17:55:40Z","updated_at":"2026-07-22T22:25:09Z","subjects":["Agricultural land availability","Climate change","Global"],"languages":["en"],"rights":["Copyright 2010 Xiao Zhang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/16712","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Cai, Ximing"]},{"key":"dc:creator","label":"Author","values":["Zhang, Xiao"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2010-08-20T17:55:40Z","2010-08"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Agricultural land availability","Climate change","Global"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2010 Xiao Zhang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/16712"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis uses several global databases, including soil properties, slope, temperature and precipitation to simulate agricultural land suitability under both current and projected climate from thirteen general circulation models (GCMs) and two emission scenarios, A1B & B1, which represent relatively high and low emission, respectively. Two ensemble methods, Simple Average Method (SAM) and Root Mean Square Error Ensemble Method (RMSEMM), are employed to assemble the regional climate change which attempts to abate the uncertainty involved in global GCM projections. Fuzzy logic, which handles land classification in an approximate yet efficient way, is adopted to estimate the land suitability through empirically determined membership functions of soil properties, slope, air temperature and Humidity Index, and fuzzy rules chosen through a learning process based on remote sensed crop land products. Land suitability under five scenarios, which are the baseline scenario with the present climate and four climate change projections, A1B-SAM, A1B-RMSEMM, B1-SAM, and B1-RMSEMM, is assessed for both global and seven important agricultural regions in the world. The change patterns of climatic factors and land suitability are explored and analyzed. It is found that countries at the high latitudes of north hemisphere are more likely to benefit from climate change, while countries at mid- and low latitudes may suffer different levels of loss of potential arable land. Expansions of the gross potential arable land are likely to occur in regions at the north high latitudes, like Russia, North China and U.S., while shrinking can be expected in South America, Africa, India and Europe. Although the greatest potential for agricultural expansion lies in Africa and South America, with current cultivated land accounting for approximately 20% of the net potential arable land in the world, negative effect from climate change may decline the potential. In summary, climate change is likely to alter the global distribution of potential arable land and further influence agricultural related socio-economic aspects by the end of this century.","Item withdrawn by Alexis Thompson (athmpsn1@illinois.edu) on 2010-07-15T14:05:09Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Thesis.doc: 5914624 bytes, checksum: 8b910b3bc57f4eae000dc1a653c92212 (MD5) Zhang_Xiao.pdf: 2599506 bytes, checksum: 81fd135c342b83310284844cd7b041a3 (MD5)","Made available in DSpace on 2010-08-20T17:55:40Z (GMT). No. of bitstreams: 4 Zhang_Xiao.pdf: 2599506 bytes, checksum: 81fd135c342b83310284844cd7b041a3 (MD5) Thesis.doc: 5914624 bytes, checksum: 8b910b3bc57f4eae000dc1a653c92212 (MD5) 1_Zhang_Xiao.pdf: 2601390 bytes, checksum: 9d4472302184ac87d709a21134772b54 (MD5) license.txt: 4060 bytes, checksum: 78abe4a89bdef04a50619743dd5ee262 (MD5)"]},{"key":"dc:title","label":"Title","values":["Impacts of climate change on global agricultural land availability"]}]}],"canonical_facts":{"dc:contributor":["Cai, Ximing"],"dc:creator":["Zhang, Xiao"],"dc:date":["2010-08-20T17:55:40Z","2010-08"],"dc:description":["This thesis uses several global databases, including soil properties, slope, temperature and precipitation to simulate agricultural land suitability under both current and projected climate from thirteen general circulation models (GCMs) and two emission scenarios, A1B & B1, which represent relatively high and low emission, respectively. Two ensemble methods, Simple Average Method (SAM) and Root Mean Square Error Ensemble Method (RMSEMM), are employed to assemble the regional climate change which attempts to abate the uncertainty involved in global GCM projections. Fuzzy logic, which handles land classification in an approximate yet efficient way, is adopted to estimate the land suitability through empirically determined membership functions of soil properties, slope, air temperature and Humidity Index, and fuzzy rules chosen through a learning process based on remote sensed crop land products. Land suitability under five scenarios, which are the baseline scenario with the present climate and four climate change projections, A1B-SAM, A1B-RMSEMM, B1-SAM, and B1-RMSEMM, is assessed for both global and seven important agricultural regions in the world. The change patterns of climatic factors and land suitability are explored and analyzed. It is found that countries at the high latitudes of north hemisphere are more likely to benefit from climate change, while countries at mid- and low latitudes may suffer different levels of loss of potential arable land. Expansions of the gross potential arable land are likely to occur in regions at the north high latitudes, like Russia, North China and U.S., while shrinking can be expected in South America, Africa, India and Europe. Although the greatest potential for agricultural expansion lies in Africa and South America, with current cultivated land accounting for approximately 20% of the net potential arable land in the world, negative effect from climate change may decline the potential. In summary, climate change is likely to alter the global distribution of potential arable land and further influence agricultural related socio-economic aspects by the end of this century.","Item withdrawn by Alexis Thompson (athmpsn1@illinois.edu) on 2010-07-15T14:05:09Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Thesis.doc: 5914624 bytes, checksum: 8b910b3bc57f4eae000dc1a653c92212 (MD5) Zhang_Xiao.pdf: 2599506 bytes, checksum: 81fd135c342b83310284844cd7b041a3 (MD5)","Made available in DSpace on 2010-08-20T17:55:40Z (GMT). No. of bitstreams: 4 Zhang_Xiao.pdf: 2599506 bytes, checksum: 81fd135c342b83310284844cd7b041a3 (MD5) Thesis.doc: 5914624 bytes, checksum: 8b910b3bc57f4eae000dc1a653c92212 (MD5) 1_Zhang_Xiao.pdf: 2601390 bytes, checksum: 9d4472302184ac87d709a21134772b54 (MD5) license.txt: 4060 bytes, checksum: 78abe4a89bdef04a50619743dd5ee262 (MD5)"],"dc:identifier":["http://hdl.handle.net/2142/16712"],"dc:language":["en"],"dc:rights":["Copyright 2010 Xiao Zhang"],"dc:subject":["Agricultural land availability","Climate change","Global"],"dc:title":["Impacts of climate change on global agricultural land availability"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:09Z"}