Spatiotemporal urbanization processes in the megacity of Mumbai, India: A Markov chains-cellular automata urban growth model
TL;DR: In this paper, an integrated Markov Chains-Cellular Automata (MC-CA) urban growth model was implemented to predict the city's expansion for the years 2020-2030.
About: This article is published in Applied Geography.The article was published on 2013-06-01. It has received 308 citations till now. The article focuses on the topics: Urban density & Urban climate.
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10 Nov 2007
TL;DR: In this paper, the authors discuss the relationship between the environment and the environment, and propose a framework to improve the quality of the air quality of air quality in the environment of the environment.
Abstract: 《美国地理学家联合会会刊》代表着美国地理学的最高水平，其载文及其变化从一个侧面反映出美国地理学的发展历程。通过对其学术论文进行统计分析，考察美国地理学的总体地位和不同领域相对地位的变化，梳理美国地理学百年发展脉络，得出以下结论：20世纪以来美国地理学经历了战前初步发展、战后快速发展和20世纪80年代以来的持续发展三大阶段，美国地理学的第二个春天正在到来；逐步形成了环境科学，研究方法、模式和地理信息科学，自然与社会，人口、地方、区域，综合地理五大领域框架；长期关注与人类发展密切相关的问题，人文地理学始终占据主导地位；非常注重实践，强调理论来源于实践、应用于实践；研究领域相对稳定，但不同方向的相对地位却此消彼长。依据载文数量的相对比例，可以概括出美国地理学发展脉络：自然(1911-1915)→经济(1916-1920)→自然(1921-1925)→地图学(1926-1930)→地方(1931-1935)→自然(1936-1940)→地理教育(1941-1945)→生态环境(1946-1950)→地方(1951-1955)→经济(1956-1975)→自然(1977-1990)→经济(1990-2005)。上述研究领域、方向及其变化，也基本上代表了世界地理学的整体发展规律。
318 citations
TL;DR: A new dataset is presented, consisting of 21,030 polygons from across the country that were manually classified as “built-up” or “not built-up,” which is used for supervised image classification and detection of urban areas in India and has potential use in GEE for temporal large-scale analysis of the urbanization process.
Abstract: Urbanization often occurs in an unplanned and uneven manner, resulting in profound changes in patterns of land cover and land use. Understanding these changes is fundamental for devising environmentally responsible approaches to economic development in the rapidly urbanizing countries of the emerging world. One indicator of urbanization is built-up land cover that can be detected and quantified at scale using satellite imagery and cloud-based computational platforms. This process requires reliable and comprehensive ground-truth data for supervised classification and for validation of classification products. We present a new dataset for India, consisting of 21,030 polygons from across the country that were manually classified as “built-up” or “not built-up,” which we use for supervised image classification and detection of urban areas. As a large and geographically diverse country that has been undergoing an urban transition, India represents an ideal context to develop and test approaches for the detection of features related to urbanization. We perform the analysis in Google Earth Engine (GEE) using three types of classifiers, based on imagery from Landsat 7 and Landsat 8 as inputs. The methodology produces high-quality maps of built-up areas across space and time. Although the dataset can facilitate supervised image classification in any platform, we highlight its potential use in GEE for temporal large-scale analysis of the urbanization process. Our methodology can easily be applied to other countries and regions.
164 citations
Cites background from "Spatiotemporal urbanization process..."
...The urbanization of India is also reflected in the rapid expansion of built-up areas [22,50,51] and low-density sprawl [48], together with a decline of other types of land cover, including open land, agriculture land, and bodies of water [52–54]....
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TL;DR: In this article, cellular automata (CA)-Markov and geospatial techniques were utilized to assess and project urban growth and land cover changes in Nizwa city, Al Dakhliyah governorate, Oman.
163 citations
TL;DR: The past and present land-use/land-cover (LULC) changes and urban expansion pattern for the cities of the Kathmandu valley and their surroundings using Landsat satellite images from 1988 to 2016 is explored.
Abstract: This study explored the past and present land-use/land-cover (LULC) changes and urban expansion pattern for the cities of the Kathmandu valley and their surroundings using Landsat satellite images from 1988 to 2016. For a better analysis, LULC change information was grouped into seven time-periods (1988–1992, 1992–1996, 1996–2000, 2000–2004, 2004–2008, 2008–2013, and 2013–2016). The classification was conducted using the support vector machines (SVM) technique. A hybrid simulation model that combined the Markov-Chain and Cellular Automata (MC-CA) was used to predict the future urban sprawl existing by 2024 and 2032. Research analysis explored the significant expansion in urban cover which was manifested at the cost of cultivated land. The urban area totaled 40.53 km2 in 1988, which increased to 144.35 km2 in 2016 with an average annual growth rate of 9.15%, an overall increase of 346.85%. Cultivated land was the most affected land-use from this expansion. A total of 91% to 98% of the expanded urban area was sourced from cultivated land alone. Future urban sprawl is likely to continue, which will be outweighed by the loss of cultivated land as in the previous decades. The urban area will be expanded to 200 km2 and 238 km2 and cultivated land will decline to 587 km2 and 555 km2 by 2024 and 2032. Currently, urban expansion is occurring towards the west and south directions; however, future urban growth is expected to rise in the southern and eastern part of the study area, dismantling the equilibrium of environmental and anthropogenic avenues. Since the study area is a cultural landscape and UNESCO heritage site, balance must be found not only in developing a city, but also in preserving the natural environment and maintaining cultural artifacts.
148 citations
Cites background from "Spatiotemporal urbanization process..."
...Estimating urban growth, analyzing spatiotemporal pattern, and assessing the characteristics and consequences of urbanization have been more possible due to the utilization of urban growth models [17,28]....
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...Over time, land-use change maps provide essential information for land-use planning [17,18] that can help to understand the drivers and dynamics of land-cover transformation and predict the future economic and environmental influences [3]....
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TL;DR: In this paper, the authors analyzed the spatial evolution of a once polynuclei urban area to a mega-region in a 35-year time frame using multi-temporal and multi-source satellite data.
142 citations
References
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TL;DR: A general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies is presented and tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interob server agreement are developed as generalized kappa-type statistics.
Abstract: This paper presents a general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies. The procedure essentially involves the construction of functions of the observed proportions which are directed at the extent to which the observers agree among themselves and the construction of test statistics for hypotheses involving these functions. Tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interobserver agreement are developed as generalized kappa-type statistics. These procedures are illustrated with a clinical diagnosis example from the epidemiological literature.
64,109 citations
Additional excerpts
...The kappa index of 83% shows an “almost perfect” agreement (Landis & Koch, 1977, p. 165) and confirms the accuracy of the model....
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Book•
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01 Aug 1996
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Abstract: A fuzzy set is a class of objects with a continuum of grades of membership. Such a set is characterized by a membership (characteristic) function which assigns to each object a grade of membership ranging between zero and one. The notions of inclusion, union, intersection, complement, relation, convexity, etc., are extended to such sets, and various properties of these notions in the context of fuzzy sets are established. In particular, a separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
52,705 citations
TL;DR: The Analytic Hierarchy Process (AHP) as discussed by the authors is a multicriteria decision-making approach in which factors are arranged in a hierarchic structure, and the principles and philosophy of the theory are summarized giving general background information of the type of measurement utilized, its properties and applications.
7,202 citations
TL;DR: The analytic hierarchy process (AHP) includes both the rating and comparison methods and requires developing a reliable hierarchic structure or feedback network that includes criteria of various types of influence, stakeholders, and decision alternatives to determine the best choice.
Abstract: People make three general types of judgments to express importance, preference, or likelihood and use them to choose the best among alternatives in the presence of environmental, social, political, and other influences. They base these judgments on knowledge in memory or from analyzing benefits, costs, and risks. From past knowledge, we sometimes can develop standards of excellence and poorness and use them to rate the alternatives one at a time. This is useful in such repetitive situations as student admissions and salary raises that must conform with established norms. Without norms one compares alternatives instead of rating them. Comparisons must fall in an admissible range of consistency. The analytic hierarchy process (AHP) includes both the rating and comparison methods. Rationality requires developing a reliable hierarchic structure or feedback network that includes criteria of various types of influence, stakeholders, and decision alternatives to determine the best choice.
3,831 citations
"Spatiotemporal urbanization process..." refers background or methods in this paper
...Guan et al. (2011) also linked the MCeCA model to the analytical hierarchy process (AHP; Saaty, 1990), which allows weighting of land use transition potential on the basis of a set of potential maps (e.g., magnitude of slope), and incorporates growth constraints....
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...(2011) also linked the MCeCA model to the analytical hierarchy process (AHP; Saaty, 1990), which allows weighting of land use transition potential on the basis of a set of potential maps (e....
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Book•
01 Jan 1983
TL;DR: This book provides an introduction to statistical methods for analysing data in the form of spatial point distributions, described in intuitive terms and illustrated by many applications to real data drawn from the biological and biomedical sciences.
Abstract: A spatial point pattern is a set of data consisting of a map of points These points might represent, for example, cases of a disease in a human or animal population, or trees in a forest, or cells in a microscopic tissue section This book provides an introduction to statistical methods for analysing data in the form of spatial point distributions Theoretical results are described in intuitive terms and statistical methods are illustrated by many applications to real data drawn from the biological and biomedical sciences
2,911 citations