A Multi-Temporal Landsat Data Analysis for Land-use/Land-cover Change in Haridwar Region using Remote Sensing Techniques

Kumar, Saurabh; Shwetank,; Jain, Kamal

doi:10.1016/j.procs.2020.04.127

Cited by 30 publications

(12 citation statements)

References 13 publications

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“…Remote sensing has provided a strong foundation for retrieving heat maps and determining the earth's surface radiative energy using large-scale and well-timed automated sensing of energy from the electromagnetic spectrum [26]. These images also have a wide diversity of applications in global research on urban land use analysis [27]. Using the images with appropriate resolutions, it is now possible to retrieve UHIs at different continental and regional scales, produce quantitative data on heterogeneous land surface characteristics, and better understand the relationship between temperature and urban and non-urban environments [28].…”

Section: Spatial Modelingmentioning

confidence: 99%

Climate Change Risk of Urban Growth and Land Use/Land Cover Conversion: An In-Depth Review of the Recent Research in Iran

et al. 2021

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This research is the first literature review of the past three decades' studies on the effects of urban developent and land use/land cover (LULC) change on Iran's climate change. For this purpose, 67 articles were found, evaluated, and classified according to the spatial and temporal scale, case study, period, data type, climatic factor, methodology, and meteorological data. Moreover, the reviewed literature methodologies were classified according to the purpose, method, and data source. According to the spatial-scale results, national- and city-level studies had the lowest and highest numbers, respectively. Tehran was the most case studies because Tehran is Iran’s capital and the largest metropolitan city. In terms of the temporal scale, studies predicting future changes (urban development and climate change) included 5% of the total literature. Satellite images were the most applied data in the reviewed literature (58%). Overall, 79% of the studies used temperature-related factors to explain the climatic impacts of urban growth and LULC conversion. Spatial modeling with 52% publications was the most used method, while numerical modeling with 12% studies was the least used method. This review showed broad study gaps in applying numerical models, neighborhood scales, urban micro-scale parameters, and long-term projections forecasts due to rapid urban development in Iran compared to the rest of the world. Therefore, our synthesis will assist researchers in facilitating better design for future studies in Iran and similar countries.

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Section: Spatial Modelingmentioning

confidence: 99%

Climate Change Risk of Urban Growth and Land Use/Land Cover Conversion: An In-Depth Review of the Recent Research in Iran

et al. 2021

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“…Cambios en la cobertura del suelo de 2000 a 2018 en el PNCM. En relación a la agricultura se observaron aumentos de 9.76 % (2000-2010), 9.65 % (2010-2018) y 20.36 % (2000-2018); valores similares a los consignados por Kumar et al (2020) en un análisis de cambio de cobertura en los márgenes del río Ganges en el distrito de Haridwar, India, para los años 1996, 2003, 2010 y 2017 en donde la agricultura tuvo un incremento de 17.32 %; pero inferior al obtenido por Martin et al…”

Section: Detección De Cambio De Uso Del Suelounclassified

Análisis multitemporal del uso del suelo y vegetación en el Parque Nacional Cumbres de Monterrey

Sandoval-García

Jiménez-Pérez

Yamallel

et al. 2021

RMCF

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El Parque Nacional Cumbres de Monterrey se caracteriza por su accidentada orografía que determina la distribución de una gran diversidad de ecosistemas, los cuales generan bienes y servicios ambientales como la captura de carbono y el abasto de agua para el Área Metropolitana de Monterrey; sin embargo, está sujeto a una fuerte presión por el avance progresivo de asentamientos humanos, el cambio de uso del suelo con fines agropecuarios e incendios forestales. El objetivo de la presente investigación fue determinar la dinámica de cambio del uso del suelo y de la vegetación, mediante el análisis multitemporal con imágenes satelitales de alta resolución. Los resultados indican que los ecosistemas están experimentando cambios constantes debido a factores tanto naturales como antropogénicos; por una parte, los bosques de pino, encino-pino y encino registran una tasa anual de cambio de 0.406, 0.272 y 0.245, respectivamente que equivalen a una recuperación de cobertura forestal de 3 590.50 ha. En tanto que, ecosistemas como el pastizal, matorral desértico rosetófilo y matorral desértico micrófilo presentan una tasa anual de cambio de -0.954, -0.735 y -0.562 que representan una pérdida de cobertura de 1 919.97 ha. Esta dinámica de uso del suelo pone en riesgo la integridad, capacidad de resiliencia y la multifuncionalidad de los bienes y servicios que proporciona Parque Nacional Cumbres de Monterrey al Área Metropolitana de Monterrey.

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“…However, with the rapid development of advanced technologies and the completion of ground survey data, the application of RS Big Data in long-term forest management has become an inevitable trend. Especially, the technologies of RS innovation have presented their particular abilities to solve innumerable earth resource problems (Kumar and Jain 2020). Meanwhile, nowadays we have entered the RS big data era, attracting more and more attention from government programmes, commercial applications to an academic realm (Liu et al 2018).…”

Section: Introductionmentioning

confidence: 99%

A decision support system for Taiwan’s forest resource management using Remote Sensing Big Data

Wang

Lin

Chu

et al. 2021

Enterprise Information Systems

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This study aims to incorporate the application of RS technology with management strategies and proposes the Remote Sensing Knowledge-Based Decision Support System (RS-KBDSS) framework. It is not only focusing on considering RS technology for discussing the accuracy of estimation but also conducting strategic thinking that is needed for keeping the inventory and monitoring task running by obtaining knowledge and decision support. This study offers more flexible and accurate estimation models for different resolution images and different kinds of models. The results obtained by the study is satisfied with the practical application.

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A Multi-Temporal Landsat Data Analysis for Land-use/Land-cover Change in Haridwar Region using Remote Sensing Techniques

Cited by 30 publications

References 13 publications

Climate Change Risk of Urban Growth and Land Use/Land Cover Conversion: An In-Depth Review of the Recent Research in Iran

Climate Change Risk of Urban Growth and Land Use/Land Cover Conversion: An In-Depth Review of the Recent Research in Iran

Análisis multitemporal del uso del suelo y vegetación en el Parque Nacional Cumbres de Monterrey

A decision support system for Taiwan’s forest resource management using Remote Sensing Big Data

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