This paper focused on urban change detection and growth pattern analysis for the period of 1978–2017 at Kolkata using remote sensing data and GIS. The supervised Maximum Likelihood Classification technique is used to classify the multi-temporal satellite data in five classes which are urban built-up, open land, vegetation, agricultural land and water body. Results revealed that urban built-up area has progressively increased by about 21.17% (239.097 km2) during study period due to the new construction of roads, flyovers, settlements, etc. Other geographical features such as open land, vegetation, agricultural land and water body have gradually declined. To assess the accuracy of classification, 88.27%, 92.42%, 91.62%, 90.18% and 89.34% overall accuracy and 0.851, 0.904, 0.893, 0.875 and 0.866 Kappa statistic have been achieved for the images of 1978, 1988, 2000, 2010 and 2017, respectively. The degree of magnitude of urban sprawl has measured using the Shannon entropy method which demonstrates that the overall entropy values are progressively increased throughout the entire region that means the urban built-up is gradually extended in different positions. Moreover, entropy outcomes revealed that urban development occurred more in the northern and southern regions as compared with the other regions. From this study, four urban growth patterns have been found which are low density continuous, continuous linear, noncontiguous linear, and leapfrog development. The important patterns are continuous linear and noncontiguous linear because most of the urban development happened along the sides of the major roads or highways. Future prediction has been obtained using CA–Markov chain model and estimates that the urban built-up may be increased by about 56.18% (509.82 km2) in the year of 2031.

中文翻译：

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1978-2017 年印度加尔各答的城市变化检测分析，使用多时相卫星数据

本文重点介绍了使用遥感数据和 GIS 对加尔各答 1978-2017 年期间的城市变化检测和增长模式分析。采用有监督的最大似然分类技术将多时相卫星数据分为城市建成区、开阔地、植被、农业用地和水体五类。结果显示，在研究期间，由于道路、立交桥、居民点等的新建，城市建成区面积逐步增加了约 21.17%（239.097 平方公里）。身体已经逐渐衰退。评估分类准确率，88.27%、92.42%、91.62%、90.18%和89.34%的总体准确率以及0.851、0.904、0.893、0.875和0。分别对 1978、1988、2000、2010 和 2017 年的图像进行了 866 个 Kappa 统计。使用香农熵方法测量城市蔓延的程度，表明整个区域的整体熵值逐渐增加，这意味着城市建成区在不同位置逐渐扩展。此外，熵结果显示，与其他地区相比，北部和南部地区的城市发展更多。从这项研究中，发现了四种城市增长模式，即低密度连续、连续线性、非连续线性和跨越式发展。重要的模式是连续线性和非连续线性，因为大多数城市发展发生在主要道路或高速公路的两侧。