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Dr. Amin Tayyebi
Monsanto Company, 800 North Lindbergh Blvd. St. Louis, MI 63167, USA

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0 Climate Change
0 Data Mining
0 Ecosystem Services
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Climate Change
Ecosystem Services
Big Data
Data Mining
Land-use and land-cover change
Spatial decision support system

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Journal article
Published: 03 July 2020 in Forest Policy and Economics
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The role of armed conflicts on land use/cover changes (LUCC), especially in Zagros forests of Iran, remains ambiguous after 30 years of the Iraq-Iran war. Our goal in this study was to assess LUCC in Sardasht related to the Iraq-Iran war in a 22 year period (1976–1998). LUCC of Sardasht city was evaluated using Landsat satellite image time series of MSS and TM data. We classified multi-temporal Landsat imagery using Random Forest classifier, then Land Change Modeler (LCM) was used to change detection and analysis. Change detection results showed that during 1976–1998, 5363.37 ha of forest areas were declined and converted to the croplands, rangelands and built-up areas. The highest decrease of forest areas was in periods of before (1976–1984) and after the war (1988–1993 and 1993–1998), 1331, 1734, and 2066 ha, respectively. While, during the war (1984–1988), only 54 ha decrease has taken place in forest lands of Sardasht. Also, increasing in other land uses during this period was significantly less than other periods. Calculation of annual rate of deforestation showed that the period of 1993–1998, has the highest rate of degradation in forest areas with a rate of −0.45%. While, during and before the war, it was −0.01% and − 0.20%, respectively. With the start of the war, residents of the region migrated to safe areas. The result of this migration was reducing forest conversion to other land uses. Trends in deforestation and forest degradation intensified after the end of the war. The causes of this destruction were destroying regulatory and control infrastructure on forests and natural resources in addition to the return of the inhabitants and an increase in demand for food and agricultural development. Moreover, after the war, the attention of the government was towards supplying the needs of human societies. Therefore, not enough attention was paid to monitoring and controlling over the degradation of natural resources. It is therefore necessary to reduce residents' dependence on natural resources through accurate and detailed planning and to increase their participation in forest conservation. In this regard, conservation programs should be continued strongly.

ACS Style

Hadi Beygi Heidarlou; Abbas Banj Shafiei; Mahdi Erfanian; Amin Tayyebi; Ahmad Alijanpour. Armed conflict and land-use changes: Insights from Iraq-Iran war in Zagros forests. Forest Policy and Economics 2020, 118, 102246 .

AMA Style

Hadi Beygi Heidarlou, Abbas Banj Shafiei, Mahdi Erfanian, Amin Tayyebi, Ahmad Alijanpour. Armed conflict and land-use changes: Insights from Iraq-Iran war in Zagros forests. Forest Policy and Economics. 2020; 118 ():102246.

Chicago/Turabian Style

Hadi Beygi Heidarlou; Abbas Banj Shafiei; Mahdi Erfanian; Amin Tayyebi; Ahmad Alijanpour. 2020. "Armed conflict and land-use changes: Insights from Iraq-Iran war in Zagros forests." Forest Policy and Economics 118, no. : 102246.

Original article
Published: 02 April 2020 in Journal of Sustainable Forestry
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Our ability to forecast future Land use/cover changes (LUCC) is extremely limited due to lack of understanding of how rapid and drastic changes like socio-economic shocks and disturbances (e.g., policy changes and economic crises) affect land use/cover. Energy policies changing in Iran have been implemented since 2010. In this study, we explored whether changes in energy policies affect the sustainability of forest cover and LUCC. Results showed that in the time periods of before and after implementation of the policies, 2,841 and 3,155 ha of forests converted to other land covers, respectively. It was also revealed that forest and rangelands degradation and their conversion to croplands and built-up areas have had the most contribution to increasing area of these land covers. Calculation annual rate of deforestation showed an increase in deforestation activities after the plan (−0.40% versus −0.53%). On the other hand, the population growth in the first period was 10,074 people, which was higher than the population increase in the second period (9,803 people). Therefore, it can be argued that the effect of the energy policies is likely to be greater than the increase in population and it appears to be able to cause a transition of land systems.

ACS Style

Hadi Beygi Heidarlou; Abbas Banj Shafiei; Mahdi Erfanian; Amin Tayyebi; Ahmad Alijanpour. Land Cover Changes in Northern Zagros Forests (Nw Iran) Before and During Implementation of Energy Policies. Journal of Sustainable Forestry 2020, 40, 234 -248.

AMA Style

Hadi Beygi Heidarlou, Abbas Banj Shafiei, Mahdi Erfanian, Amin Tayyebi, Ahmad Alijanpour. Land Cover Changes in Northern Zagros Forests (Nw Iran) Before and During Implementation of Energy Policies. Journal of Sustainable Forestry. 2020; 40 (3):234-248.

Chicago/Turabian Style

Hadi Beygi Heidarlou; Abbas Banj Shafiei; Mahdi Erfanian; Amin Tayyebi; Ahmad Alijanpour. 2020. "Land Cover Changes in Northern Zagros Forests (Nw Iran) Before and During Implementation of Energy Policies." Journal of Sustainable Forestry 40, no. 3: 234-248.

Journal article
Published: 30 October 2018 in Land Use Policy
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Zagros Forest provides various ecosystem services such as food, timber, water, carbon storage, air purification, wildlife habitat as well as social and cultural benefits for both humans and animals. Due to the economic expansion beginning in the early 1990s in Iran and its resulting desertification, Zagros has lost numerous forests over the last 30 years. To overcome this issue, Zagros Forest Preservation Plan (ZFPP) has been under implementation in Northwestern Iran since 2003 to reduce forest destruction and attract the people's participation. However, it faced shortcomings caused by a variety of factors including insufficient funds, incomplete preservation, and unsuitable organization during implementation. This research aims to study the effect of ZFPP on forest loss in Sardasht County as a representative of Iranian Northern Zagros Forests. A series of Landsat images were used to analyze the forest loss before ZFPP implementation (1993–2002), after 10 years of implementation (2002–2012), and finally after its revision (2012–2016). Land Change Modeler (LCM) was employed to detect land cover changes for land cover prediction in 2024. We used land cover maps between 2002 and 2012 for calibration. We then compared the predicted land cover map from LCM with actual land cover map in 2016 for validation. The results indicated that 3330, 4562, and 1234 ha of forestlands converted to agricultural lands, rangelands, and built-up areas during 1993–2002, 2002–2012, and 2012–2016, with annual deforestation rates of -0.40%, -0.52% and -0.36%, respectively. The highest deforestation rate was observed between 2002 and 2012 because of the destructive effects of population growth. Land cover prediction indicated that per capita forest area would continue to decline while the other land cover uses would continue to grow more severely around the existing agricultural lands and built-up areas in Sardasht until 2024.

ACS Style

Hadi Beygi Heidarlou; Abbas Banj Shafiei; Mahdi Erfanian; Amin Tayyebi; Ahmad Alijanpour. Effects of preservation policy on land use changes in Iranian Northern Zagros forests. Land Use Policy 2018, 81, 76 -90.

AMA Style

Hadi Beygi Heidarlou, Abbas Banj Shafiei, Mahdi Erfanian, Amin Tayyebi, Ahmad Alijanpour. Effects of preservation policy on land use changes in Iranian Northern Zagros forests. Land Use Policy. 2018; 81 ():76-90.

Chicago/Turabian Style

Hadi Beygi Heidarlou; Abbas Banj Shafiei; Mahdi Erfanian; Amin Tayyebi; Ahmad Alijanpour. 2018. "Effects of preservation policy on land use changes in Iranian Northern Zagros forests." Land Use Policy 81, no. : 76-90.

Journal article
Published: 01 July 2018 in Journal of Environmental Management
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Urbanization onto adjacent farmlands directly reduces the agricultural area available to meet the resource needs of a growing society. Soil conservation is a common objective in urban planning, but little focus has been placed on targeting soil value as a metric for conservation. This study assigns commodity and water storage values to the agricultural soils across all of the watersheds in Michigan's Lower Peninsula to evaluate how cities might respond to a soil conservation-based urbanization strategy. Land Transformation Model (LTM) simulations representing both traditional and soil conservation-based urbanization, are used to forecast urban area growth from 2010 to 2050 at five year intervals. The expansion of urban areas onto adjacent farmland is then evaluated to quantify the conservation effects of soil-based development. Results indicate that a soil-based protection strategy significantly conserves total farmland, especially more fertile soils within each soil type. In terms of revenue, ∼$88 million (in current dollars) would be conserved in 2050 using soil-based constraints, with the projected savings from 2011 to 2050 totaling more than $1.5 billion. Soil-based urbanization also increased urban density for each major metropolitan area. For example, there were 94,640 more acres directly adjacent to urban land by 2050 under traditional development compared to the soil-based urbanization strategy, indicating that urban sprawl was more tightly contained when including soil value as a metric to guide development. This study indicates that implementing a soil-based urbanization strategy would better satisfy future agricultural resource needs than traditional urban planning.

ACS Style

Samuel J. Smidt; Amin Tayyebi; Anthony D. Kendall; Bryan C. Pijanowski; David W. Hyndman. Agricultural implications of providing soil-based constraints on urban expansion: Land use forecasts to 2050. Journal of Environmental Management 2018, 217, 677 -689.

AMA Style

Samuel J. Smidt, Amin Tayyebi, Anthony D. Kendall, Bryan C. Pijanowski, David W. Hyndman. Agricultural implications of providing soil-based constraints on urban expansion: Land use forecasts to 2050. Journal of Environmental Management. 2018; 217 ():677-689.

Chicago/Turabian Style

Samuel J. Smidt; Amin Tayyebi; Anthony D. Kendall; Bryan C. Pijanowski; David W. Hyndman. 2018. "Agricultural implications of providing soil-based constraints on urban expansion: Land use forecasts to 2050." Journal of Environmental Management 217, no. : 677-689.

Research article
Published: 31 May 2018 in Land Degradation & Development
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In recent decades, extensive land transformations and environmental and climate change events such as floods and droughts, increasing heat waves, and forest fires have been observed in Iran. Monitoring and intensity analysis of the land cover dynamics and land degradation in Iran is lacking due to the lack of fine resolution land cover data before 2000. In this paper, we explore the type, extent, and intensity of land transformations and the intensity of transitions among land cover classes from 2000 to 2010 using GlobeLand30 land cover data. Our results indicate that approximately 35% of Iran changed during 2000‐2010, due mainly to the active gain of barren land. Furthermore, the increase in barren targeted grass and shrub. Barren expansion in Iran is alarming because most of the country is located in arid and semi‐arid regions. Iran has actively participated in desertification combat plans, and thus it is critical to explore extra intervals of land dynamics. This will help to evaluate the temporal rate of land degradation at multiple intervals and assess the effectiveness of desertification management strategies. Additionally, investigating the role of climate and human‐made interventions into the type and extent of land transformation is recommended.

ACS Style

Masoud Minaei; Hossein Shafizadeh-Moghadam; Amin Tayyebi. Spatiotemporal nexus between the pattern of land degradation and land cover dynamics in Iran. Land Degradation & Development 2018, 29, 2854 -2863.

AMA Style

Masoud Minaei, Hossein Shafizadeh-Moghadam, Amin Tayyebi. Spatiotemporal nexus between the pattern of land degradation and land cover dynamics in Iran. Land Degradation & Development. 2018; 29 (9):2854-2863.

Chicago/Turabian Style

Masoud Minaei; Hossein Shafizadeh-Moghadam; Amin Tayyebi. 2018. "Spatiotemporal nexus between the pattern of land degradation and land cover dynamics in Iran." Land Degradation & Development 29, no. 9: 2854-2863.

Articles
Published: 07 February 2018 in International Journal of Remote Sensing
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The main objective of this study is to examine how climate gradients (coastal to inland climate) and land-cover types affect land surface temperature (LST) diel variation. To achieve this, we applied LST harmonization model, which integrates LST at daytime and night-time using sine and cosine functions, to reconstruct a complete diel LST curve for census block groups (CBGs) with both highly vegetated and impervious land-cover types in 10 major cities of the Los Angeles region distributed throughout the coastal to inland climate gradient. We calculated diel LST metrics of minimum LST (LSTmin), maximum LST (LSTmax), diel LST range (DLSTR), and time of LSTmin and LSTmax for each CBG as well as LST differences between neighborhoods with extensive (>80%) impervious and vegetated surface. First, we examined how distance from coast explained the calculated LST products. Results showed that DLSTR (by factor of 2.50), LSTmax (by factor of 1.57), and LST differences between CBGs with extensive impervious and vegetated surfaces (by factor of 4) were higher for cities in inland compared to the coastal cities. Time of LSTmax shifted by 2.50 h from the coastal cities to the midland (regions located between coastal and inland areas) and then inland. Second, we examined how distance from coast and land-cover types explained estimated LST of CBGs at 14:00. Results showed that distance from coast and land-cover types together explained 81% of LST at 14:00. Percentage of vegetation was the most significant driver to explain LST. We concluded that using seamless LST data enables us to better evaluate temporally informative metrics of LST for use in human health, resource use, and natural resource management at regional scale.

ACS Style

Amin Tayyebi; G. Darrel Jenerette. Assessing diel urban climate dynamics using a land surface temperature harmonization model. International Journal of Remote Sensing 2018, 39, 3010 -3028.

AMA Style

Amin Tayyebi, G. Darrel Jenerette. Assessing diel urban climate dynamics using a land surface temperature harmonization model. International Journal of Remote Sensing. 2018; 39 (9):3010-3028.

Chicago/Turabian Style

Amin Tayyebi; G. Darrel Jenerette. 2018. "Assessing diel urban climate dynamics using a land surface temperature harmonization model." International Journal of Remote Sensing 39, no. 9: 3010-3028.

Journal article
Published: 01 February 2018 in Land Use Policy
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ACS Style

Amin Tayyebi; Hossein Shafizadeh-Moghadam; Amir H. Tayyebi. Analyzing long-term spatio-temporal patterns of land surface temperature in response to rapid urbanization in the mega-city of Tehran. Land Use Policy 2018, 71, 459 -469.

AMA Style

Amin Tayyebi, Hossein Shafizadeh-Moghadam, Amir H. Tayyebi. Analyzing long-term spatio-temporal patterns of land surface temperature in response to rapid urbanization in the mega-city of Tehran. Land Use Policy. 2018; 71 ():459-469.

Chicago/Turabian Style

Amin Tayyebi; Hossein Shafizadeh-Moghadam; Amir H. Tayyebi. 2018. "Analyzing long-term spatio-temporal patterns of land surface temperature in response to rapid urbanization in the mega-city of Tehran." Land Use Policy 71, no. : 459-469.

Journal article
Published: 01 September 2017 in Computers, Environment and Urban Systems
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ACS Style

Hossein Shafizadeh-Moghadam; Amin Tayyebi; Mohammad Ahmadlou; Mahmoud Reza Delavar; Mahdi Hasanlou. Integration of genetic algorithm and multiple kernel support vector regression for modeling urban growth. Computers, Environment and Urban Systems 2017, 65, 28 -40.

AMA Style

Hossein Shafizadeh-Moghadam, Amin Tayyebi, Mohammad Ahmadlou, Mahmoud Reza Delavar, Mahdi Hasanlou. Integration of genetic algorithm and multiple kernel support vector regression for modeling urban growth. Computers, Environment and Urban Systems. 2017; 65 ():28-40.

Chicago/Turabian Style

Hossein Shafizadeh-Moghadam; Amin Tayyebi; Mohammad Ahmadlou; Mahmoud Reza Delavar; Mahdi Hasanlou. 2017. "Integration of genetic algorithm and multiple kernel support vector regression for modeling urban growth." Computers, Environment and Urban Systems 65, no. : 28-40.

Journal article
Published: 01 July 2017 in Computers, Environment and Urban Systems
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ACS Style

Hossein Shafizadeh-Moghadam; Ali Asghari; Amin Tayyebi; Mohammad Taleai. Coupling machine learning, tree-based and statistical models with cellular automata to simulate urban growth. Computers, Environment and Urban Systems 2017, 64, 297 -308.

AMA Style

Hossein Shafizadeh-Moghadam, Ali Asghari, Amin Tayyebi, Mohammad Taleai. Coupling machine learning, tree-based and statistical models with cellular automata to simulate urban growth. Computers, Environment and Urban Systems. 2017; 64 ():297-308.

Chicago/Turabian Style

Hossein Shafizadeh-Moghadam; Ali Asghari; Amin Tayyebi; Mohammad Taleai. 2017. "Coupling machine learning, tree-based and statistical models with cellular automata to simulate urban growth." Computers, Environment and Urban Systems 64, no. : 297-308.

Data descriptor
Published: 05 May 2017 in Data
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Land cover data are often used to examine the impacts of landscape alterations on the environment from the local to global scale. Although various agencies produce land cover data at various spatial scales, data are still limited at the regional scale over extended timescales. This is a critical data gap since decision-makers often use future and long-term land cover maps to develop effective policies for sustainable environmental systems. As a result, land change science incorporates common data mining tools to create future land cover maps that extend over long timescales. This study applied one of the well-known land cover change models, called Land Transformation Model (LTM), to produce urbanization maps for the Lower Peninsula of Michigan in United States from 2010 to 2050 with five year intervals. Long-term urbanization data in the Lower Peninsula of Michigan can be used in various environmental studies such as assessing the impact of future urbanization on climate change, water quality, food security and biodiversity.

ACS Style

Amin Tayyebi; Samuel Smidt; Bryan C. Pijanowski. Long-Term Land Cover Data for the Lower Peninsula of Michigan, 2010–2050. Data 2017, 2, 16 .

AMA Style

Amin Tayyebi, Samuel Smidt, Bryan C. Pijanowski. Long-Term Land Cover Data for the Lower Peninsula of Michigan, 2010–2050. Data. 2017; 2 (2):16.

Chicago/Turabian Style

Amin Tayyebi; Samuel Smidt; Bryan C. Pijanowski. 2017. "Long-Term Land Cover Data for the Lower Peninsula of Michigan, 2010–2050." Data 2, no. 2: 16.

Journal article
Published: 30 March 2017 in GIScience & Remote Sensing
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ACS Style

Hossein Shafizadeh-Moghadam; Ali Asghari; Mohammad Taleai; Marco Helbich; Amin Tayyebi. Sensitivity analysis and accuracy assessment of the land transformation model using cellular automata. GIScience & Remote Sensing 2017, 54, 639 -656.

AMA Style

Hossein Shafizadeh-Moghadam, Ali Asghari, Mohammad Taleai, Marco Helbich, Amin Tayyebi. Sensitivity analysis and accuracy assessment of the land transformation model using cellular automata. GIScience & Remote Sensing. 2017; 54 (5):639-656.

Chicago/Turabian Style

Hossein Shafizadeh-Moghadam; Ali Asghari; Mohammad Taleai; Marco Helbich; Amin Tayyebi. 2017. "Sensitivity analysis and accuracy assessment of the land transformation model using cellular automata." GIScience & Remote Sensing 54, no. 5: 639-656.

Journal article
Published: 05 January 2017 in GIScience & Remote Sensing
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ACS Style

Hichem Omrani; Amin Tayyebi; Bryan Pijanowski. Integrating the multi-label land-use concept and cellular automata with the artificial neural network-based Land Transformation Model: an integrated ML-CA-LTM modeling framework. GIScience & Remote Sensing 2017, 54, 283 -304.

AMA Style

Hichem Omrani, Amin Tayyebi, Bryan Pijanowski. Integrating the multi-label land-use concept and cellular automata with the artificial neural network-based Land Transformation Model: an integrated ML-CA-LTM modeling framework. GIScience & Remote Sensing. 2017; 54 (3):283-304.

Chicago/Turabian Style

Hichem Omrani; Amin Tayyebi; Bryan Pijanowski. 2017. "Integrating the multi-label land-use concept and cellular automata with the artificial neural network-based Land Transformation Model: an integrated ML-CA-LTM modeling framework." GIScience & Remote Sensing 54, no. 3: 283-304.

Journal article
Published: 01 October 2016 in Environmental Modelling & Software
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ACS Style

Amin Tayyebi; Amir Hossein Tayyebi; Jamal Jokar Arsanjani; Hossein Shafizadeh Moghadam; Hichem Omrani. FSAUA: A framework for sensitivity analysis and uncertainty assessment in historical and forecasted land use maps. Environmental Modelling & Software 2016, 84, 70 -84.

AMA Style

Amin Tayyebi, Amir Hossein Tayyebi, Jamal Jokar Arsanjani, Hossein Shafizadeh Moghadam, Hichem Omrani. FSAUA: A framework for sensitivity analysis and uncertainty assessment in historical and forecasted land use maps. Environmental Modelling & Software. 2016; 84 ():70-84.

Chicago/Turabian Style

Amin Tayyebi; Amir Hossein Tayyebi; Jamal Jokar Arsanjani; Hossein Shafizadeh Moghadam; Hichem Omrani. 2016. "FSAUA: A framework for sensitivity analysis and uncertainty assessment in historical and forecasted land use maps." Environmental Modelling & Software 84, no. : 70-84.

Journal article
Published: 01 August 2016 in Ecological Modelling
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ACS Style

Amin Tayyebi; Jamal J. Arsanjani; Amir H. Tayyebi; Hichem Omrani; Hossein S. Moghadam. Group-based crop change planning: Application of SmartScape™ spatial decision support system for resolving conflicts. Ecological Modelling 2016, 333, 92 -100.

AMA Style

Amin Tayyebi, Jamal J. Arsanjani, Amir H. Tayyebi, Hichem Omrani, Hossein S. Moghadam. Group-based crop change planning: Application of SmartScape™ spatial decision support system for resolving conflicts. Ecological Modelling. 2016; 333 ():92-100.

Chicago/Turabian Style

Amin Tayyebi; Jamal J. Arsanjani; Amir H. Tayyebi; Hichem Omrani; Hossein S. Moghadam. 2016. "Group-based crop change planning: Application of SmartScape™ spatial decision support system for resolving conflicts." Ecological Modelling 333, no. : 92-100.

Journal article
Published: 01 July 2016 in Habitat International
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Global land cover maps are a vital source for mapping our globe into a set of thematic types. They have been extensively used as a basis layer for a large number of applications including ecosystem services, environmental planning, climate change, hydrological processes and policy making. While regional land cover maps for some areas such as Europe and North America has been greatly developed and very few temporal datasets exist, lack of such data for some regions specifically developing countries is evident. Although it seems global land cover maps such as MODIS could be a solution for mapping these regions, their coarse spatial resolution e.g., 500 m as well as their accuracy are very challenging. Recently, GlobeLand30 a global land cover with a relatively fine resolution at 30 m extracted from Landsat images has been released, which seems to be a potential dataset for mapping areas with limited land cover information such as developing countries. In this study, we look at GlobeLand30 of 2010 for Iran in order to find out the accuracy of this dataset as well as its implications. By having looked at 6 selected study sites around larger cities representing dissimilar eco-regions covering rural and urban areas, we conclude that the overall accuracy of GlobeLand30 with 77.9% was satisfactory for entire Iran. We also define six representative eco-regions dominated by diverse land type mixtures considering the administrative boundaries. The detailed implications of this dataset for developing different applications as well as informing regional policy makers are discussed.

ACS Style

Jamal Jokar Arsanjani; Amin Tayyebi; Eric Vaz. GlobeLand30 as an alternative fine-scale global land cover map: Challenges, possibilities, and implications for developing countries. Habitat International 2016, 55, 25 -31.

AMA Style

Jamal Jokar Arsanjani, Amin Tayyebi, Eric Vaz. GlobeLand30 as an alternative fine-scale global land cover map: Challenges, possibilities, and implications for developing countries. Habitat International. 2016; 55 ():25-31.

Chicago/Turabian Style

Jamal Jokar Arsanjani; Amin Tayyebi; Eric Vaz. 2016. "GlobeLand30 as an alternative fine-scale global land cover map: Challenges, possibilities, and implications for developing countries." Habitat International 55, no. : 25-31.

Journal article
Published: 07 June 2016 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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The importance of spatial accuracy of land use/cover change maps necessitates the use of high performance models. To reach this goal, calibrating machine learning (ML) approaches to model land use/cover conversions have received increasing interest among the scholars. This originates from the strength of these techniques as they powerfully account for the complex relationships underlying urban dynamics. Compared to other ML techniques, random forest has rarely been used for modeling urban growth. This paper, drawing on information from the multi-temporal Landsat satellite images of 1985, 2000 and 2015, calibrates a random forest regression (RFR) model to quantify the variable importance and simulation of urban change spatial patterns. The results and performance of RFR model were evaluated using two complementary tools, relative operating characteristics (ROC) and total operating characteristics (TOC), by overlaying the map of observed change and the modeled suitability map for land use change (error map). The suitability map produced by RFR model showed 82.48% area under curve for the ROC model which indicates a very good performance and highlights its appropriateness for simulating urban growth.

ACS Style

M. Ahmadlou; M. R. Delavar; H. Shafizadeh-Moghadam; A. Tayyebi. MODELING URBAN DYNAMICS USING RANDOM FOREST: IMPLEMENTING ROC AND TOC FOR MODEL EVALUATION. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2016, XLI-B2, 285 -290.

AMA Style

M. Ahmadlou, M. R. Delavar, H. Shafizadeh-Moghadam, A. Tayyebi. MODELING URBAN DYNAMICS USING RANDOM FOREST: IMPLEMENTING ROC AND TOC FOR MODEL EVALUATION. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2016; XLI-B2 ():285-290.

Chicago/Turabian Style

M. Ahmadlou; M. R. Delavar; H. Shafizadeh-Moghadam; A. Tayyebi. 2016. "MODELING URBAN DYNAMICS USING RANDOM FOREST: IMPLEMENTING ROC AND TOC FOR MODEL EVALUATION." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2, no. : 285-290.

Journal article
Published: 01 April 2016 in Science of The Total Environment
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Urbanization has increased heat in the urban environment, with many consequences for human health and well-being. Managing climate change in part through increasing vegetation is desired by many cities to mitigate current and future heat related issues. However, little information is available on what influences the current effectiveness and availability of vegetation for local cooling. In this study, we identified the variation in the interacting relationships among vegetation (normalized difference vegetation index), socioeconomic status (neighborhood income), elevation and land surface temperature (LST) to identify how vegetation based surface cooling services change throughout the pronounced coastal to desert climate gradient of the Los Angeles, CA metropolitan region, a megacity of > 18 million residents. A key challenge for understanding variation in vegetation as a climate change adaptation tool spanning neighborhood to megacity scales is developing new “big data” analytical tools. We used structural equation modeling (SEM) to quantify the interacting relationships among socio-economic status data obtained from government census data, elevation and new LST and vegetation data obtained from an airborne imaging campaign conducted in 2013 for the urban and suburban areas across a series of fifteen climate zones. Vegetation systematically increased in cooling effectiveness from 6.06 to 31.77 degrees with increasing distance from the coast. Vegetation and neighborhood income were positively correlated throughout all climate zones with a peak in the relationship occurring near 25 km from the coast. Because of the interaction between these two relationships, we also found that higher income neighborhoods were cooler and that this effect peaked at about 30 km from the coast. These results show the availability and effectiveness of vegetation on the local climate varies tremendously throughout the Los Angeles, CA metropolitan area. Further, using the more inland climate zones as future analogs for more coastal zones, suggests that in the warmer climate conditions projected for the region the effectiveness of vegetation for regional cooling may increase thus acting as a localized negative feedback mechanism.

ACS Style

Amin Tayyebi; G. Darrel Jenerette. Increases in the climate change adaption effectiveness and availability of vegetation across a coastal to desert climate gradient in metropolitan Los Angeles, CA, USA. Science of The Total Environment 2016, 548-549, 60 -71.

AMA Style

Amin Tayyebi, G. Darrel Jenerette. Increases in the climate change adaption effectiveness and availability of vegetation across a coastal to desert climate gradient in metropolitan Los Angeles, CA, USA. Science of The Total Environment. 2016; 548-549 ():60-71.

Chicago/Turabian Style

Amin Tayyebi; G. Darrel Jenerette. 2016. "Increases in the climate change adaption effectiveness and availability of vegetation across a coastal to desert climate gradient in metropolitan Los Angeles, CA, USA." Science of The Total Environment 548-549, no. : 60-71.

Articles
Published: 11 March 2016 in International Journal of Digital Earth
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Global land cover (LC) maps have been widely employed as the base layer for a number of applications including climate change, food security, water quality, biodiversity, change detection, and environmental planning. Due to the importance of LC, there is a pressing need to increase the temporal and spatial resolution of global LC maps. A recent advance in this direction has been the GlobeLand30 dataset derived from Landsat imagery, which has been developed by the National Geomatics Center of China (NGCC). Although overall accuracy is greater than 80%, the NGCC would like help in assessing the accuracy of the product in different regions of the world. To assist in this process, this study compares the GlobeLand30 product with existing public and online datasets, that is, CORINE, Urban Atlas (UA), OpenStreetMap, and ATKIS for Germany in order to assess overall and per class agreement. The results of the analysis reveal high agreement of up to 92% between these datasets and GlobeLand30 but that large disagreements for certain classes are evident, in particular wetlands. However, overall, GlobeLand30 is shown to be a useful product for characterizing LC in Germany, and paves the way for further regional and national validation efforts.

ACS Style

Jamal Jokar Arsanjani; Linda See; Amin Tayyebi. Assessing the suitability of GlobeLand30 for mapping land cover in Germany. International Journal of Digital Earth 2016, 9, 1 -19.

AMA Style

Jamal Jokar Arsanjani, Linda See, Amin Tayyebi. Assessing the suitability of GlobeLand30 for mapping land cover in Germany. International Journal of Digital Earth. 2016; 9 (9):1-19.

Chicago/Turabian Style

Jamal Jokar Arsanjani; Linda See; Amin Tayyebi. 2016. "Assessing the suitability of GlobeLand30 for mapping land cover in Germany." International Journal of Digital Earth 9, no. 9: 1-19.

Journal article
Published: 01 February 2016 in Land Use Policy
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Agricultural land use is increasingly changing due to different anthropogenic activities. A combination of economic, socio-political, and cultural factors exerts a direct impact on agricultural changes. This study aims to illustrate how stakeholders and policymakers can take advantage of a web-based spatial decision support system (SDSS), namely SmartScape™ to either test existing crop change policies or produce effective crop change decisions using tradeoff analysis. We addressed the consequences of two common crop change scenarios for Dane county in Wisconsin, United States, (a) replacing perennial energy crops with annual energy crops and (b) replacing annual energy crops with perennial energy crops. The results suggested that converting areas under grass and alfalfa production that were located on high quality soil and flat slope to corn promoted a net-income and availability of gross biofuel. Additionally, the model outcome proposed that converting areas under corn and soy production that were located on high slope to grass promoted net-energy, phosphorus loading, soil loss, soil carbon sequestration, nitrous oxide emission, grassland bird habitat, pollinator abundance, and biocontrol. Therefore, SmartScape™ can assist strategic crop change policy by comparing the tradeoff among ecosystem services to ensure that crop change policies have outcomes that are agreeable to a diversity of policymakers.

ACS Style

Amin Tayyebi; Amirhossein Tayyebi; Eric Vaz; Jamal Jokar Arsanjani; Marco Helbich. Analyzing crop change scenario with the SmartScape™ spatial decision support system. Land Use Policy 2016, 51, 41 -53.

AMA Style

Amin Tayyebi, Amirhossein Tayyebi, Eric Vaz, Jamal Jokar Arsanjani, Marco Helbich. Analyzing crop change scenario with the SmartScape™ spatial decision support system. Land Use Policy. 2016; 51 ():41-53.

Chicago/Turabian Style

Amin Tayyebi; Amirhossein Tayyebi; Eric Vaz; Jamal Jokar Arsanjani; Marco Helbich. 2016. "Analyzing crop change scenario with the SmartScape™ spatial decision support system." Land Use Policy 51, no. : 41-53.

Journal article
Published: 01 February 2016 in Computers and Electronics in Agriculture
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ACS Style

Amin Tayyebi; Timothy D. Meehan; Jeffrey Dischler; Gary Radloff; Michael Ferris; Claudio Gratton. SmartScape™: A web-based decision support system for assessing the tradeoffs among multiple ecosystem services under crop-change scenarios. Computers and Electronics in Agriculture 2016, 121, 108 -121.

AMA Style

Amin Tayyebi, Timothy D. Meehan, Jeffrey Dischler, Gary Radloff, Michael Ferris, Claudio Gratton. SmartScape™: A web-based decision support system for assessing the tradeoffs among multiple ecosystem services under crop-change scenarios. Computers and Electronics in Agriculture. 2016; 121 ():108-121.

Chicago/Turabian Style

Amin Tayyebi; Timothy D. Meehan; Jeffrey Dischler; Gary Radloff; Michael Ferris; Claudio Gratton. 2016. "SmartScape™: A web-based decision support system for assessing the tradeoffs among multiple ecosystem services under crop-change scenarios." Computers and Electronics in Agriculture 121, no. : 108-121.