Organized by: Beijing Normal University, National Natural Science Foundation of China Hosted by: Institute of Resources Science, Beijing Normal UniversityKey Laboratory of Environmental Change and Natural Disaster, Mi...Organized by: Beijing Normal University, National Natural Science Foundation of China Hosted by: Institute of Resources Science, Beijing Normal UniversityKey Laboratory of Environmental Change and Natural Disaster, Ministry of Education of ChinaTopics:1) Detecting and monitoring LUCC2) Temporal-spatial characteristics in LUCC3) Driving model for LUCC4) Forecasting and modeling LUCC 5) Phenological and biochemical response on LUCC6) Regional LUCC and microclimate 7) LUCC in the context of global change8) Impact of global change on the sustainable land-use modelingAbstract submission: The official language of this conference is English. We invite papers written in English and an abstract of less than one page of standard A4 size to the Conference Secretariat by Apr 15, 2001. Registration Fee: 280 US$ (300 US$ after July 15, 2001)Add:No. 19, Xinjiekouwai Street, 100875, Institute of Resources Science, Beijing Normal University, Beijing, ChinaTel:86-10-62207656 or 62209024 Fax:010-62208178http:// 202.112.93.50/LUCCD2001/index.htmlE-mail: Pwang@bnu.edu.cn Cyh@bnu.edu.展开更多
In this research,the integration of remotely sensed data and Cellular Automata-Markov model(CA-Markov)have been used to analyze the dynamics of land use change and its prediction for the next year.Training phase for t...In this research,the integration of remotely sensed data and Cellular Automata-Markov model(CA-Markov)have been used to analyze the dynamics of land use change and its prediction for the next year.Training phase for the CA-Markov model has been created based on the input pair of land use,which is the result of land use mapping using Maximum Likelihood(ML)algorithm.Three-map comparison has been used to evaluate process accuracy assessment of the training phase for the CA-Markov model.Furthermore,the simulation phase for the CAMarkov model can be used to predict land use map for the next year.The analyze of the dynamics of land use change and its prediction during the period 1990 to 2050 can be obtained that the land serves as a water absorbent surfaces such as primary forest,secondary forest and the mixed garden area continued to decline.Meanwhile,on build land area that can lead to reduced surface water absorbing tends to increase from year to year.The results of this research can be used as input for the next research,which aims to determine the impact of land use changes in hydrological conditions against flooding in the research area.展开更多
Background:Land use change plays a vital role in global carbon dynamics.Understanding land use change impact on soil carbon stock is crucial for implementing land use management to increase carbon stock and reducing c...Background:Land use change plays a vital role in global carbon dynamics.Understanding land use change impact on soil carbon stock is crucial for implementing land use management to increase carbon stock and reducing carbon emission.Therefore,the objective of our study was to determine land use change and to assess its effect on soil carbon stock in semi-arid part of Rajasthan,India.Landsat temporal satellite data of Pushkar valley region of Rajasthan acquired on 1993,2003,and 2014 were analyzed to assess land use change.Internal trading of land use was depicted throughmatrices.Soil organic carbon(SOC)stock was calculated for soil to a depth of 30 cm in each land use type in 2014 using field data collection.The SOC stock for previous years was estimated using stock change factor.The effect of land use change on SOC stock was determined by calculating change in SOC stock(t/ha)by deducting the base-year SOC stock from the final year stock of a particular land use conversion.Results:The total area under agricultural lands was increased by 32.14%while that under forest was decreased by 23.14%during the time period of 1993–2014.Overall land use change shows that in both the periods(1993–2003 and 2003–2014),7%of forest area was converted to agricultural land and about 15%changes occurred among agricultural land.In 1993–2003,changes among agricultural land led to maximum loss of soil carbon,i.e.,4.88 Mt C and during 2003–2014,conversion of forest to agricultural land led to loss in 3.16 Mt C.Conclusion:There was a continuous decrease in forest area and increase in cultivated area in each time period.Land use change led to alteration in carbon equity in soil due to change or loss in vegetation.Overall,we can conclude that the internal trading of land use area during the 10-year period(1993–2003)led to net loss of SOC stock by 8.29 Mt C.Similarly,land use change during 11-year period(2003–2014)caused net loss of SOC by 2.76 Mt C.Efforts should be made to implement proper land use management practices to enhance the SOC content.展开更多
文摘Organized by: Beijing Normal University, National Natural Science Foundation of China Hosted by: Institute of Resources Science, Beijing Normal UniversityKey Laboratory of Environmental Change and Natural Disaster, Ministry of Education of ChinaTopics:1) Detecting and monitoring LUCC2) Temporal-spatial characteristics in LUCC3) Driving model for LUCC4) Forecasting and modeling LUCC 5) Phenological and biochemical response on LUCC6) Regional LUCC and microclimate 7) LUCC in the context of global change8) Impact of global change on the sustainable land-use modelingAbstract submission: The official language of this conference is English. We invite papers written in English and an abstract of less than one page of standard A4 size to the Conference Secretariat by Apr 15, 2001. Registration Fee: 280 US$ (300 US$ after July 15, 2001)Add:No. 19, Xinjiekouwai Street, 100875, Institute of Resources Science, Beijing Normal University, Beijing, ChinaTel:86-10-62207656 or 62209024 Fax:010-62208178http:// 202.112.93.50/LUCCD2001/index.htmlE-mail: Pwang@bnu.edu.cn Cyh@bnu.edu.
文摘In this research,the integration of remotely sensed data and Cellular Automata-Markov model(CA-Markov)have been used to analyze the dynamics of land use change and its prediction for the next year.Training phase for the CA-Markov model has been created based on the input pair of land use,which is the result of land use mapping using Maximum Likelihood(ML)algorithm.Three-map comparison has been used to evaluate process accuracy assessment of the training phase for the CA-Markov model.Furthermore,the simulation phase for the CAMarkov model can be used to predict land use map for the next year.The analyze of the dynamics of land use change and its prediction during the period 1990 to 2050 can be obtained that the land serves as a water absorbent surfaces such as primary forest,secondary forest and the mixed garden area continued to decline.Meanwhile,on build land area that can lead to reduced surface water absorbing tends to increase from year to year.The results of this research can be used as input for the next research,which aims to determine the impact of land use changes in hydrological conditions against flooding in the research area.
文摘Background:Land use change plays a vital role in global carbon dynamics.Understanding land use change impact on soil carbon stock is crucial for implementing land use management to increase carbon stock and reducing carbon emission.Therefore,the objective of our study was to determine land use change and to assess its effect on soil carbon stock in semi-arid part of Rajasthan,India.Landsat temporal satellite data of Pushkar valley region of Rajasthan acquired on 1993,2003,and 2014 were analyzed to assess land use change.Internal trading of land use was depicted throughmatrices.Soil organic carbon(SOC)stock was calculated for soil to a depth of 30 cm in each land use type in 2014 using field data collection.The SOC stock for previous years was estimated using stock change factor.The effect of land use change on SOC stock was determined by calculating change in SOC stock(t/ha)by deducting the base-year SOC stock from the final year stock of a particular land use conversion.Results:The total area under agricultural lands was increased by 32.14%while that under forest was decreased by 23.14%during the time period of 1993–2014.Overall land use change shows that in both the periods(1993–2003 and 2003–2014),7%of forest area was converted to agricultural land and about 15%changes occurred among agricultural land.In 1993–2003,changes among agricultural land led to maximum loss of soil carbon,i.e.,4.88 Mt C and during 2003–2014,conversion of forest to agricultural land led to loss in 3.16 Mt C.Conclusion:There was a continuous decrease in forest area and increase in cultivated area in each time period.Land use change led to alteration in carbon equity in soil due to change or loss in vegetation.Overall,we can conclude that the internal trading of land use area during the 10-year period(1993–2003)led to net loss of SOC stock by 8.29 Mt C.Similarly,land use change during 11-year period(2003–2014)caused net loss of SOC by 2.76 Mt C.Efforts should be made to implement proper land use management practices to enhance the SOC content.