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68-482: The council monitors performance of city agencies and makes land use decisions, as well as, legislating on a variety of other issues. The city council also has sole responsibility for approving the city budget and each member is limited to three consecutive terms in office and can run again after a four-year respite. "Yerevan City Council elections are being conducted every five years with proportional lists of parties. The City Council has 65 members. The first person in

136-596: A neural network and the other used a simple weights-of-evidence model. A cellular land change model uses maps of suitability for various types of land use, and compares areas that are immediately adjacent to one another to project changes into the future. Variations in the scale of cells in a cellular model can have significant impacts on model outputs. Economic models are built on principles of supply and demand . They use mathematical parameters in order to predict what land types will be desired and which will be discarded. These are frequently built for urban areas, such as

204-399: A 2003 study of the highly dense Pearl River Delta in southern China . Agent-based models try to simulate the behavior of many individuals making independent choices, and then see how those choices affect the landscape as a whole. Agent-based modeling can be complex - for instance, a 2005 study combined an agent-based model with computer-based genetic programming to explore land change in

272-424: A better conceptual understanding of underlying constructs of the model and capture additional dimensions of land use. It is important to maintain the temporal and spatial continuity of data from airborne-based and survey-based observation through constellations of smaller satellite coverage, image processing algorithms, and other new data to link satellite-based land use information and land management information. It

340-712: A better understanding of feedback mechanisms across scales. As there is continuous reinvention of modeling environments, frameworks, and platforms, land change modeling can improve from better research infrastructure support. For example, model and software infrastructure development can help avoid duplication of initiatives by land change modeling community members, co-learn about land change modeling, and integrate models to evaluate impacts of land change. Better data infrastructure can provide more data resources to support compilation, curation, and comparison of heterogeneous data sources. Better community modeling and governance can advance decision-making and modeling capabilities within

408-529: A challenge that should be addressed as a modeling challenge. This is commonly caused by modelers use of information from after the first time period. This can cause a map to appear to have a level of accuracy that is much higher than a model’s actual predictive power. Additional improvements that have been discussed within the field include characterizing the difference between allocation errors and quantity errors, which can be done through three map comparisons, as well as including both observed and predicted change in

476-657: A commonly used method for pattern validation in which three maps, a reference map at time 1, a reference map at time 2, and a simulated map of time 2, are compared. This generates a cross-comparison of the three maps where the pixels are classified as one of these five categories: Because three map comparisons include both errors and correctly simulated pixels, it results in a visual expression of both allocation and quantity errors. Single-summary metrics are also used to evaluate LCMs. There are many single summary metrics that modelers have used to evaluate their models and are often utilized to compare models to each other. One such metric

544-454: A community with specific and achievable goals. Community modeling and governance would provide a step towards reaching community agreement on specific goals to move modeling and data capabilities forward. A number of modern challenges in land change modeling can potentially be addressed through contemporary advances in cyberinfrastructure such as crowd-source, “mining” for distributed data, and improving high-performance computing . Because it

612-519: A considerable portion old-growth forest deforestation is the result of small-scale migrant farming. As forest cover is removed, forest resources become exhausted and increasing populations lead to scarcity, which prompts people to move again to previously undisturbed forest, restarting the process of deforestation. There are several reasons behind this continued migration: poverty-driven lack of available farmland and high costs may lead to an increase in farming intensity on existing farmland. This leads to

680-478: A consistent, long-term record to quantify change variability over time. Through observing patterns in land cover changes, scientists can determine the consequences of these changes, predict the impact of future changes, and use this information to inform strategic land management . Modeling risk and vulnerability is also one of land change science's practical applications. Accurate predictions of how human activity will influence land cover change over time, as well as

748-429: A major impact on natural resources including water , soil , nutrients , plants and animals . Land use change is "the change from one land-use category to another". Land-use change, together with use of fossil fuels , are the major anthropogenic sources of carbon dioxide, a dominant greenhouse gas . Human activity is the most significant cause of land cover change, and humans are also directly impacted by

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816-494: A model’s performance to edit a “model’s output, data measurement, and the mapping and modeling of data” for future applications. The purpose for model evaluation is not to develop a singular metric or method to maximize a “correct” outcome, but to develop tools to evaluate and learn from model outputs to produce better models for their specific applications There are two types of validation in land change modeling: process validation and pattern validation. Process Validation compares

884-424: A more sustainable society and planet. Land change models are significant in their ability to help guide the land systems to positive societal and environmental outcomes at a time when attention to changes across land systems is increasing. A plethora of science and practitioner communities have been able to advance the amount and quality of data in land change modeling in the past few decades. That has influenced

952-471: A variety of human and environmental dynamics. Land change modeling has a variety of implementation opportunities in many science and practice disciplines, such as in decision-making, policy, and in real-world application in public and private domains. Land change modeling is a key component of land change science , which uses LCMs to assess long-term outcomes for land cover and climate. The science disciplines use LCMs to formalize and test land change theory, and

1020-403: A variety of outcomes in land change modeling. A notable property of all land change models is that they have some irreducible level of uncertainty in the model structure, parameter values, and/or input data. For instance, one uncertainty within land change models is a result from temporal non-stationarity that exists in land change processes, so the further into the future the model is applied,

1088-401: Is also important to have better information on land change actors and their beliefs, preferences, and behaviors to improve the predictive ability of models and evaluate the consequences of alternative policies. One important improvement for land change modeling can be made though better aligning model choices with model goals. It is important to choose the appropriate modeling approach based on

1156-422: Is an example of large-scale land use change. The deforestation of temperate regions since 1750 has had a major effect on land cover . The reshaping of landscapes to serve human needs, such as the deforestation for farmland , can have long-term effects on earth systems and exacerbate the causes of climate change. Although the burning of fossil fuels is the primary driver of present-day climate change, prior to

1224-644: Is important for modelers to find more data to better construct, calibrate, and validate structural models, the ability to analyze large amount of data on individual behaviors is helpful. For example, modelers can find point-of-sales data on individual purchases by consumers and internet activities that reveal social networks. However, some issues of privacy and propriety for crowdsourcing improvements have not yet been resolved. The land change modeling community can also benefit from Global Positioning System and Internet-enabled mobile device data distribution. Combining various structural-based data-collecting methods can improve

1292-494: Is important to integrate data across scales. A models design is based on the dominant processes and data from a specific scale of application and spatial extent. Cross-scale dynamics and feedbacks between temporal and spatial scales influences the patterns and processes of the model. Process like telecoupling , indirect land use change , and adaption to climate change at multiple scales requires better representation by cross-scale dynamics. Implementing these processes will require

1360-558: Is important to land use and land cover change for a variety of reasons. In particular, urbanization affects land change elsewhere through the shifting of urban-rural linkages, or the ecological footprint of the transfer of goods and services between urban and rural areas. Increases in urbanization lead to increases in consumption, which puts increased pressure on surrounding rural lands. The outward spread of urban areas can also take over adjacent land formerly used for crop cultivation. Urbanization additionally affects land cover through

1428-450: Is important to take into account, as it is constantly changing land cover and sometimes model uncertainty. To avoid model uncertainty and interpret model outputs more accurately, a model diagnosis is used to understand more about the connections between land change models and the actual land system of the spatial extent. The overall importance of model diagnosis with model uncertainty issues is its ability to assess how interacting processes and

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1496-411: Is needed to improve forecasting of future states that are non-stationary in processes, input variables, and boundary conditions. One can explicitly recognize stationarity assumptions and explore data for evidence in non-stationarity to better acknowledge and understand model uncertainty to improve uncertainty sources. Improvement in structural validation can help improve acknowledgement and understanding of

1564-445: Is one form of land-use regulation. For example, Portland, Oregon is required to have an urban growth boundary which contains at least 20,000 acres (81 km ) of vacant land. Additionally, Oregon restricts the development of farmland. The regulations are controversial, but an economic analysis concluded that farmland appreciated similarly to the other land. In colonial America, few regulations were originally put into place regarding

1632-416: Is surrounded with glassy walls at its top. The Yerevan History Museum is located in an attached building just to the west of the city hall. 40°10′29″N 44°30′15″E  /  40.17472°N 44.50417°E  / 40.17472; 44.50417 Land use Land use is an umbrella term to describe what happens on a parcel of land. It concerns the benefits derived from using the land, and also

1700-546: Is the Figure of Merit (FoM) which uses the hit, miss, and false alarm values generated from a three-map comparison to generate a percentage value that expresses the intersection between reference and simulated change. Single summary metrics can obfuscate important information, but the FoM can be useful especially when the hit, miss and false alarm values are reported as well. The separation of calibration from validation has been identified as

1768-476: Is useful to explore spatial land systems, uses, and covers. Land change modeling can account for complexity within dynamics of land use and land cover by linking with climatic, ecological, biogeochemical, biogeophysical and socioeconomic models. Additionally, LCMs are able to produce spatially explicit outcomes according to the type and complexity within the land system dynamics within the spatial extent. Many biophysical and socioeconomic variables influence and produce

1836-514: The Amazon and Central America . Moreover, the underlying drivers of economic development are often linked to global economic engagement, ranging from increased exports to a foreign debt . Broadly, urbanization is the increasing number of people who live in urban areas. Urbanization refers to both urban population growth and the physical growth of urban areas. According to the United Nations ,

1904-562: The Aral Sea is an example how local-scale land use and land change can have compounded impacts on regional climate systems, particularly when human activities heavily disrupt natural climatic cycles, how land change science can be used to map and study such changes. In 1960, the Aral Sea, located in Central Asia, was the world's fourth largest lake. However, a water diversion project, undertaken by

1972-496: The Industrial Revolution , deforestation and irrigation were the largest sources of human-driven greenhouse gas emissions . Even today, 35% of anthropogenic carbon dioxide contributions can be attributed to land use or land cover changes. Currently, almost 50% of Earth’s non-ice land surface has been transformed by human activities, with approximately 40% of that land used for agriculture , surpassing natural systems as

2040-599: The National Historic Preservation Act of 1966 (today embodied in 16 U.S.C. 461 et seq.) and the National Environmental Policy Act of 1969 (42 U.S.C. 4321 et seq.). Land change modeling Land change models (LCMs) describe, project, and explain changes in and the dynamics of land use and land-cover. LCMs are a means of understanding ways that humans change the Earth's surface in

2108-639: The Soviet Union to irrigate arid plains in what is now Kazakhstan , Uzbekistan , and Turkmenistan , resulted in the Aral Sea losing 85% of its land cover and 90% of its volume. The loss of the Aral Sea has had a significant effect on human-environment interactions in the region, including the decimation of the sea's fishing industry and the salinization of agricultural lands by the wind-spread of dried sea salt beds. Additionally, scientists have been able to use technology such as NASA 's Moderate Resolution Imaging Spectroradiometer (MODIS) to track changes to

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2176-533: The Yerevan Ararat Wine Factory . The construction of the building was completed in November 2004 during the period of Mayor Yervand Zakharyan , with a cost of AMD 3.1 billion. It was originally designed by architect Jim Torosyan . The construction was set at the beginning of the 1980s but stopped in 1991 due to financial difficulties. It remained unfinished until August 2003 when the construction process

2244-454: The Yucatan peninsula of Mexico. Many models do not limit themselves to one of the approaches above - they may combine several in order to develop a fully comprehensive and accurate model. Land change models are evaluated to appraise and quantify the performance of a model’s predictive power in terms of spatial allocation and quantity of change. Evaluating a model allows the modeler to evaluate

2312-519: The land management actions that humans carry out there. The following categories are used for land use: forest land , cropland ( agricultural land ), grassland , wetlands , settlements and other lands. The way humans use land, and how land use is changing, has many impacts on the environment . Effects of land use choices and changes by humans include for example urban sprawl , soil erosion , soil degradation , land degradation and desertification . Land use and land management practices have

2380-418: The urban heat island effect. Heat islands occur when, due to high concentrations of structures, such as buildings and roads, that absorb and re-emit solar radiation, and low concentrations of vegetative cover, urban areas experience higher temperatures than surrounding areas. The high temperatures associated with heat islands can compromise human health, particularly in low-income areas. The rapid decline of

2448-485: The Aral Sea and its surrounding climate over time. This use of modeling and satellite imagery to track human-caused land cover change is characteristic of the scope of land change science. Commonly, political jurisdictions will undertake land-use planning and regulate the use of land in an attempt to avoid land-use conflicts . Land use plans are implemented through land division and use ordinances and regulations, such as zoning regulations . The urban growth boundary

2516-499: The United States is 9.1 M km but the total used here refers only to the contiguous 48 states, without Alaska etc. Land use change is "the change from one land-use category to another". Land-use change, together with use of fossil fuels , are the major anthropogenic sources of carbon dioxide, a dominant greenhouse gas . Human activity is the most significant cause of land cover change, and humans are also directly impacted by

2584-466: The United States. Acreage statistics for each type of land use in the contiguous 48 states in 2017 were as follows: Special use areas in the table above include national parks (29 M acres) and state parks (15 M), wildlife areas (64.4 M), highways (21 M), railroads (3M), military bases (25 M), airports (3M) and a few others. Miscellaneous includes cemeteries, golf courses, marshes, deserts, and other areas of "low economic value". The total land area of

2652-434: The actions of private developers and individuals. Judicial decisions and enforcement of private land-use arrangements can reinforce public regulation, and achieve forms and levels of control that regulatory zoning cannot. There is growing concern that land use regulation is a direct cause of housing segregation in the United States today. Two major federal laws passed in the 1960s limit the use of land significantly. These are

2720-486: The analysis of land change models. Single summary metrics have been overly relied on in the past, and have varying levels of usefulness  when evaluating LCMs. Even the best single summary metrics often leave out important information, and reporting metrics like FoM along with the maps and values that are used to generate them can communicate necessary information that would otherwise be obfuscated. Scientists use LCMs to build and test theories in land change modeling for

2788-765: The availability of microdata and the diversity of people that see the findings and outcomes of land change modeling projects. For example, citizen-contributed data supported the implementation of Ushahidi in Haiti after the 2010 earthquake , helping at least 4,000 disaster events. Universities, non-profit agencies, and volunteers are needed to collect information on events like this to make positive outcomes and improvements in land change modeling and land change modeling applications. Tools such as mobile devices are available to make it easier for participants to participate in collecting micro-data on agents. Google Maps uses cloud-based mapping technologies with datasets that are co-produced by

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2856-477: The built environment. One improvement for land change modeling can be made through better data and integration with available data and models. Improved observational data can influence modeling quality. Finer spatial and temporal resolution data that can integrate with socioeconomic and biogeophysical data can help land change modeling couple the socioeconomic and biogeological modeling types. Land change modelers should value data at finer scales. Fine data can give

2924-557: The development of methods and technologies in model land change. The multitudes of land change models that have been developed are significant in their ability to address land system change and useful in various science and practitioner communities. For the science community, land change models are important in their ability to test theories and concepts of land change and its connections to human-environment relationships, as well as explore how these dynamics will change future land systems without real-world observation. Land change modeling

2992-709: The development of processors, data storage, network bandwidth, and coupling land change and environmental process models at high resolution. An additional way to improve land change modeling is through improvement of model evaluation approaches. Improvement in sensitivity analysis are needed to gain a better understand of the variation in model output in response to model elements like input data, model parameters, initial conditions, boundary conditions, and model structure. Improvement in pattern validation can help land change modelers make comparisons between model outputs parameterized for some historic case, like maps, and observations for that case. Improvement in uncertainty sources

3060-489: The dynamics of land use and land-cover. LCMs are a means of understanding ways that humans change the Earth's surface in the past, present, and future. Deforestation is the systematic and permanent conversion of previously forested land for other uses. It has historically been a primary facilitator of land use and land cover change. Forests are a vital part of the global ecosystem and are essential to carbon capture , ecological processes, and biodiversity . However, since

3128-568: The environmental consequences of these changes. Collective land use and land cover changes have fundamentally altered the functioning of key Earth systems . For instance, human changes to land use and land cover have a profound impact climate at a local and regional level, which in turn contributes to climate change . Land use by humans has a long history, first emerging more than 10,000 years ago. Human changes to land surfaces have been documented for centuries as having significant impacts on both earth systems and human well-being. Deforestation

3196-505: The environmental consequences of these changes. For example, deforestation (the systematic and permanent conversion of previously forested land for other uses) has historically been a primary facilitator of land use and land cover change. The study of land change relies on the synthesis of a wide range of data and a diverse range of data collection methods. These include land cover monitoring and assessments, modeling risk and vulnerability, and land change modeling . The IPCC defines

3264-496: The explore and experiment with different scenarios of land change modeling. The practical disciplines use LCMs to analyze current land change trends and explore future outcomes from policies or actions in order to set appropriate guidelines, limits and principles for policy and action. Research and practitioner communities may study land change to address topics related to land-climate interactions, water quantity and quality, food and fiber production, and urbanization, infrastructure, and

3332-416: The extent and timescale of changes, and how changes vary through time. To this end, scientists use a variety of tools, including satellite imagery and other sources of remotely sensed data (e.g., aircraft imagery), field observations, historical accounts, and reconstruction modeling. These tools, particularly satellite imagery, allow land change scientists to accurately monitor land-change rates and create

3400-461: The global urban population has increased rapidly since 1950, from 751 million to 4.2 billion in 2018, and current trends predict this number will continue to grow. Accompanying this population shift are significant changes in economic flow, culture and lifestyle, and spatial population distribution. Although urbanized areas cover just 3% of the Earth's surface, they nevertheless have a significant impact on land use and land cover change. Urbanization

3468-647: The impact that such changes have on the sustainability of ecological and human systems, can inform the creation of policy designed to address these changes. Studying risk and vulnerability entails the development of quantitative , qualitative , and geospatial models, methods, and support tools. The purpose of these tools is to communicate the vulnerability of both human communities and natural ecosystems to hazard events or long-term land change. Modeling risk and vulnerability requires analyses of community sensitivity to hazards, an understanding of geographic distributions of people and infrastructure, and accurate calculation of

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3536-423: The invention of agriculture, global forest cover has diminished by 35%. There is rarely one direct or underlying cause for deforestation. Rather, deforestation is the result of intertwining systemic forces working simultaneously or sequentially to change land cover. Deforestation occurs for many interconnected reasons. For instance, mass deforestation is often viewed as the product of industrial agriculture, yet

3604-579: The land as well as the land management actions (activities) carried out by humans to produce those products and benefits." As of the early 1990s, about 13% of the Earth was considered arable land, with 26% in pasture, 32% forests and woodland, and 1.5% urban areas. As of 2015, the total arable land is 10.7% of the land surface, with 1.3% being permanent cropland. For example, the US Department of Agriculture has identified six major types of land use in

3672-454: The landscape are represented, as well as the uncertainty within the landscape and its processes. A machine-learning approach uses land-cover data from the past to try to assess how land will change in the future, and works best with large datasets. There are multiple types of machine-learning and statistical models - a study in western Mexico from 2011 found that results from two outwardly similar models were considerably different, as one used

3740-682: The list of the party that has received more than 40% of seats, is considered elected mayor. If the parties fail to gather so many votes, the mayor will be elected by City Council." Next municipal elections are scheduled to be held in 2028. The seat of the Yerevan City Council is the Yerevan City Hall located on Argishti street at the Kentron district , facing the Square of Russia, the House of Moscow and

3808-405: The match between “the process in the model and the process operating in the real world”. Process validation is most commonly used in agent-based modeling whereby the modeler is using the behaviors and decisions to inform the process determining land change in the model. Pattern validation compares model outputs (ie. predicted change) and observed outputs (ie. reference change). Three map analyses are

3876-427: The more uncertain it is. Another uncertainty within land change models are data and parameter uncertainties within physical principles (i.e., surface typology), which leads to uncertainties in being able to understand and predict physical processes. Furthermore, land change model design are a product of both decision-making and physical processes. Human-induced impact on the socio-economic and ecological environment

3944-486: The overexploitation of farmland, and down the line results in desertification , another land cover change, which renders soil unusable and unprofitable, requiring farmers to seek out untouched and unpopulated old-growth forests. In addition to rural migration and subsistence farming, economic development can also play a substantial role in deforestation. For example, road and railway expansions designed to increase quality of life have resulted in significant deforestation in

4012-892: The past, present, and future. Land change models are valuable in development policy, helping guide more appropriate decisions for resource management and the natural environment at a variety of scales ranging from a small piece of land to the entire spatial extent. Moreover, developments within land-cover , environmental and socio-economic data (as well as within technological infrastructures) have increased opportunities for land change modeling to help support and influence decisions that affect human-environment systems , as national and international attention increasingly focuses on issues of global climate change and sustainability . Changes in land systems have consequences for climate and environmental change on every scale. Therefore, decisions and policies in relation to land systems are very important for reacting these changes and working towards

4080-555: The principal source of nitrogen emissions. Increasing land conversion by humans in future is not inevitable: In a discussion on response options to climate change mitigation and adaptation an IPCC special report stated that "a number of response options such as increased food productivity, dietary choices and food losses, and waste reduction, can reduce demand for land conversion, thereby potentially freeing land and creating opportunities for enhanced implementation of other response options". Land change science relies heavily on

4148-550: The probability of specific disturbances occurring. A key method for studying risk and vulnerability is land change modeling (LCM), which can be used to simulate changes and land use and land cover. LCMs can be used to predict how land use and land cover may change under alternate circumstances, which is useful for risk assessment, in that it allows for the prediction of potential impacts and can be used to inform policy decisions, albeit with some uncertainty. Land change models (LCMs) describe, project, and explain changes in and

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4216-471: The public and scientists. Examples in agriculture such as coffee farmers in Avaaj Otalo showed use of mobile phones for collecting information and as an interactive voice. Cyberinfrastructure developments may also increase the ability of land change modeling to meet computational demands of various modeling approaches given increasing data volumes and certain expected model interactions. For example, improving

4284-464: The scientific and application contexts of the specific study of interest. For example, when someone needs to design a model with policy and policy actors in mind, they may choose an agent-based model. Here, structural economic or agent-based approaches are useful, but specific patterns and trends in land change as with many ecological systems may not be as useful. When one needs to grasp the early stages of problem identification, and thus needs to understand

4352-430: The scientific patterns and trend of land change, machine learning and cellular approaches are useful. Land Change Modeling should also better integrate positive and normative approaches to explanation and prediction based on evidence-based accounts of land systems. It should also integrate optimization approaches to explore the outcomes that are the most beneficial and the processes that might produce those outcomes. It

4420-462: The synthesis of a wide range of data and a diverse range of data collection methods, some of which are detailed below. A primary function of land change science is to document and model long-term patterns of landscape change, which may result from both human activity and natural processes. In the course of monitoring and assessing land cover and land use changes, scientists look at several factors, including where land-cover and land-use are changing,

4488-437: The term land use as the "total of arrangements, activities and inputs applied to a parcel of land". The same report groups land use into the following categories: forest land , cropland ( agricultural land ), grassland , wetlands , settlements and other lands . Another definition is that of the United Nations ' Food and Agriculture Organization : "Land use concerns the products and/or benefits obtained from use of

4556-643: The usage of land. As society shifted from rural to urban, public land regulation became important, especially to city governments trying to control industry, commerce, and housing within their boundaries. The first zoning ordinance was passed in New York City in 1916, and, by the 1930s, most states had adopted zoning laws. In the 1970s, concerns about the environment and historic preservation led to further regulation. Today, federal, state, and local governments regulate growth and development through statutory law . The majority of controls on land, however, stem from

4624-501: Was continued and completed within 15 months. The city hall is a five-story building with a total area of 13,500 m. The main entrance is topped with the traditional Armenian symbol of endless circles representing the eternity and the ancient Armenian Kenats Tsar tree representing life. It has a 47-metre-high rectangular clock tower with the word "ԵՐԵՎԱՆ" ( YEREVAN ) carved in Armenian script , decorated with traditional ornaments. The tower

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