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  1. AU="Maithani, Sandeep"
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  1. Article ; Online: Trend Analysis of Nitrogen dioxide (NO2) in Northern Part of India During Paddy Residue Burning Using a Contextual Approach

    Maithani, Sandeep / Sharma, Surendra Kumar

    J Indian Soc Remote Sens. 2023 Jan., v. 51, no. 1 p.61-73

    2023  

    Abstract: Mann–Kendall (MK) test is a non-parametric technique widely used for trend analysis in time series datasets. However, the datasets tend to be noisy which increases data variance and often results in false rejection of null hypothesis. The present study ... ...

    Abstract Mann–Kendall (MK) test is a non-parametric technique widely used for trend analysis in time series datasets. However, the datasets tend to be noisy which increases data variance and often results in false rejection of null hypothesis. The present study investigates use of spatial autocorrelation (i.e., contextual information) to address influence of noise in the MK test. By incorporating spatial autocorrelation, the false trend can be identified, while at the same time spatial autocorrelation provides support for strengthening the results. The contextual MK test (CMK) was used for analysing NO₂ trend in the Northern Indian states of Punjab, Haryana, Delhi, Uttar Pradesh, Madhya Pradesh, and Rajasthan during paddy stubble burning, using TROPOspheric Monitoring Instrument total vertical column density data. The serial correlation in the datasets was removed using pre-whitening before running the CMK and conventional MK test. In year 2021, MK test identified 12.9% of the grid cells with monotonous increasing trend of NO₂, which increased to 14.1% when CMK test was used. Similarly, cells with monotonous increasing NO₂ trend in year 2020, were 8.7% and 9.5% using MK and CMK tests respectively. Thus, CMK test was able to identify more cells having a monotonous increasing trend of NO₂ compared to the MK test, while at the same time the spurious trend could also be efficiently handled. Subsequently, using CMK test state-wise analysis of NO₂ trend was also carried out.
    Keywords autocorrelation ; data collection ; nitrogen dioxide ; paddies ; stubble ; time series analysis ; troposphere ; variance ; India
    Language English
    Dates of publication 2023-01
    Size p. 61-73.
    Publishing place Springer India
    Document type Article ; Online
    ZDB-ID 2439566-3
    ISSN 0974-3006 ; 0255-660X
    ISSN (online) 0974-3006
    ISSN 0255-660X
    DOI 10.1007/s12524-022-01623-7
    Database NAL-Catalogue (AGRICOLA)

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  2. Article: Calibration of a Multi-criteria Evaluation Based Cellular Automata Model for Indian Cities Having Varied Growth Patterns

    Maithani, Sandeep

    Journal of the Indian Society of Remote Sensing. 2018 Feb., v. 46, no. 2

    2018  

    Abstract: The study aims to investigate the efficiency of Cellular Automata (CA) based models for simulation of urban growth in two Indian cities (Dehradun and Saharanpur) having different growth patterns. The transition rules in the CA model were defined using ... ...

    Abstract The study aims to investigate the efficiency of Cellular Automata (CA) based models for simulation of urban growth in two Indian cities (Dehradun and Saharanpur) having different growth patterns. The transition rules in the CA model were defined using Multi-Criteria Evaluation technique. The model was calibrated by varying two parameters namely the neighbourhood (type and size) and model iterations. The model results were assessed using two measures, i.e., percent correct match and Moran’s Index. It was found that for Dehradun, which had a dispersed growth pattern, Von Neumann neighbourhood of small size produced the highest accuracy, in terms of pattern and location of simulated urban growth. For Saharanpur, which had a compact growth pattern, large neighbourhoods, produced the most optimum results, irrespective of the type of neighbourhood. For both study areas, large number of model iterations failed to increase the accuracy of urban growth assessment.
    Keywords cities ; models ; remote sensing ; urbanization
    Language English
    Dates of publication 2018-02
    Size p. 199-210.
    Publishing place Springer India
    Document type Article
    ZDB-ID 2439566-3
    ISSN 0974-3006 ; 0255-660X
    ISSN (online) 0974-3006
    ISSN 0255-660X
    DOI 10.1007/s12524-017-0681-y
    Database NAL-Catalogue (AGRICOLA)

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  3. Article: A Deep Neural Network-Based Approach for Studying the Relationship Between Land Surface Temperature and Surface Air Temperature

    Bhandari, Ravi / Maithani, Sandeep / Karnatak, Harish

    Journal of the Indian Society of Remote Sensing. 2022 Mar., v. 50, no. 3

    2022  

    Abstract: Air temperature is one of the most important parameters for assessing and monitoring the changing weather and climate patterns. Measurement of air temperature is done from a limited number of automatic weather stations distributed in certain parts of the ...

    Abstract Air temperature is one of the most important parameters for assessing and monitoring the changing weather and climate patterns. Measurement of air temperature is done from a limited number of automatic weather stations distributed in certain parts of the country, with a lot of discontinuities in space and time because of various operational constraints. Contrary to it, satellites provide seamless observations of Land Surface Temperature in space and time globally, only obscured by the cloud cover. Though Land Surface Temperature and Air Temperature have different physical interpretations, nevertheless some previous studies have shown some correlation between them, which varies according to elevation, land cover type, time of observation (day or night). Hence, land surface temperature can be one of the means to derive air temperature in the regions where the availability of automatic weather stations is limited. The present study attempts to develop a deep neural network-based model to estimate air temperature from land surface temperature based on elevation and land cover. The model results were evaluated by comparing them with ground observations using statistical indices viz., Nash and Sutcliffe’s coefficient of efficiency, Legates and McCabe coefficient of efficiency, Coefficient of determination, and Index of agreement. The values obtained for these indices are 0.74, 0.85, 0.85, and 0.97 respectively, which reflect the predictive capability of the model.
    Keywords air temperature ; climate ; cloud cover ; land cover ; models ; space and time ; surface temperature
    Language English
    Dates of publication 2022-03
    Size p. 563-568.
    Publishing place Springer India
    Document type Article
    ZDB-ID 2439566-3
    ISSN 0974-3006 ; 0255-660X
    ISSN (online) 0974-3006
    ISSN 0255-660X
    DOI 10.1007/s12524-021-01483-7
    Database NAL-Catalogue (AGRICOLA)

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  4. Article: Exploring the Relationship Between Spatio-temporal Land Cover Dynamics and Surface Temperature Over Dehradun Urban Agglomeration, India

    Nautiyal, Garima / Maithani, Sandeep / Sharma, Archana

    Journal of the Indian Society of Remote Sensing. 2021 June, v. 49, no. 6

    2021  

    Abstract: In present study, using artificial neural network (ANN), the land cover maps for three years (i.e. 2000, 2010 and 2019) were derived from Landsat optical data and the decadal spatio-temporal land cover dynamics was analysed. The classes delineated were ... ...

    Abstract In present study, using artificial neural network (ANN), the land cover maps for three years (i.e. 2000, 2010 and 2019) were derived from Landsat optical data and the decadal spatio-temporal land cover dynamics was analysed. The classes delineated were built-up (urban and suburban), cultivated, vegetation, bare soil and river courses. Subsequently, the land cover change patterns were correlated with the LST values, which were retrieved from Landsat thermal data using mono-widow algorithm. The spatio-temporal clustering of high and low LST values (i.e. LST hot and cold spots) over different land covers, with special emphasis on built-up areas, was carried out. The variation in human thermal comfort levels during the period 2000–2019 was also investigated using thermal field variance index. The domain of the present study was Dehradun urban agglomeration.
    Keywords Landsat ; algorithms ; cold ; humans ; land cover ; neural networks ; rivers ; soil ; surface temperature ; variance ; vegetation ; India
    Language English
    Dates of publication 2021-06
    Size p. 1307-1318.
    Publishing place Springer India
    Document type Article
    ZDB-ID 2439566-3
    ISSN 0974-3006 ; 0255-660X
    ISSN (online) 0974-3006
    ISSN 0255-660X
    DOI 10.1007/s12524-021-01323-8
    Database NAL-Catalogue (AGRICOLA)

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  5. Article: Hyperspectral and multispectral data fusion using fast discrete curvelet transform for urban surface material characterization

    Malleswara Rao, Jillela / Siddiqui, Asfa / Maithani, Sandeep / Kumar, Pramod

    Geocarto international. 2022 June 22, v. 37, no. 7

    2022  

    Abstract: The objective of the present study is to analyze the quality of hyperspectral data fusion using low spatial hyperspectral (LSH) Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) 8 m data and high spatial multispectral (HSM) ... ...

    Abstract The objective of the present study is to analyze the quality of hyperspectral data fusion using low spatial hyperspectral (LSH) Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) 8 m data and high spatial multispectral (HSM) WorldView-3 image at 1.24 m remote sensing images with spectral unmixing technique. The resultant HSH data shows new prospects for urban surface material characterization with spectrally distinct classes. The spatial resolution of LSH is enhanced by injecting the high-frequency details from the corresponding HSM bands in fast discrete curvelet transform domain. The image fusion-based products’ quality has been analyzed by endmembers extraction and fractional maps generated using Piecewise Convex Multiple-Model Endmember Detection (PCOMMEND) method. Experimental results showed that the fusion has improved the spatial as well as spectral separability to extract the endmembers, particularly for the urban surface materials like the combination of water and asphalt, and bare soil and roof tiles.
    Keywords bitumen ; data quality ; extracts ; image analysis ; objectives ; product quality ; remote sensing ; soil ; spatial data ; surfaces ; tiles
    Language English
    Dates of publication 2022-0622
    Size p. 2018-2030.
    Publishing place Taylor & Francis
    Document type Article
    ISSN 1752-0762
    DOI 10.1080/10106049.2020.1818855
    Database NAL-Catalogue (AGRICOLA)

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  6. Article: Investigating the Effect of Lockdown During COVID-19 on Land Surface Temperature: Study of Dehradun City, India

    Maithani, Sandeep / Nautiyal, Garima / Sharma, Archana

    Journal of the Indian Society of Remote Sensing. 2020 Sept., v. 48, no. 9

    2020  

    Abstract: Urban environment imposes challenges due to its dynamics and thermodynamic characteristics of the built environment. The present study aims to study the effect of lockdown during COVID-19 on the spatio-temporal land surface temperature (LST) patterns in ... ...

    Abstract Urban environment imposes challenges due to its dynamics and thermodynamic characteristics of the built environment. The present study aims to study the effect of lockdown during COVID-19 on the spatio-temporal land surface temperature (LST) patterns in Dehradun city. The TIRS sensor data of 14 April 2020 (post-lockdown), 28 April 2019, 25 April 2018 and 08 May 2017 were downloaded, and LST was retrieved using radiative transfer equation. The wardwise change in LST, urban hot spots and thermal comfort was studied as a function of built-up density. It was observed that there was an overall decrease in LST values in Dehradun city in post-COVID lockdown period. Wards with high built-up density had minimum decrease in LST; on the contrary, wards with large proportion of open spaces and having low, medium built-up density had the maximum decrease in LST. Hot spot analysis was carried out using Getis Ord GI* statistic, and the level of thermal comfort was found using the urban thermal field variance index. It was observed that there was an increase in number of hot spots accompanied by a decrease in thermal comfort level post-lockdown. The methodology proposed in the present study can be applied to other Indian cities which exhibit similar growth patterns and will provide a tool for rational decision making.
    Keywords COVID-19 infection ; equations ; radiative transfer ; surface temperature ; thermodynamics ; urban areas ; variance ; India
    Language English
    Dates of publication 2020-09
    Size p. 1297-1311.
    Publishing place Springer India
    Document type Article
    Note NAL-AP-2-clean
    ZDB-ID 2439566-3
    ISSN 0974-3006 ; 0255-660X
    ISSN (online) 0974-3006
    ISSN 0255-660X
    DOI 10.1007/s12524-020-01157-w
    Database NAL-Catalogue (AGRICOLA)

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  7. Article: Spatio-Temporal Variations in Night Lights, Economy and Night Light Emissions in States of India

    Rehman, Sami / Honap, Vaishnavi / Siddiqui, Asfa / Maske, Ambadas / Maithani, Sandeep

    Journal of the Indian Society of Remote Sensing. 2021 Dec., v. 49, no. 12

    2021  

    Abstract: Increased urbanisation in developing countries has resulted in significant urban growth of towns and cities. The lights observed from the sky at night can be used as a proxy to monitor the process of the country’s urban growth, development, and economy. ... ...

    Abstract Increased urbanisation in developing countries has resulted in significant urban growth of towns and cities. The lights observed from the sky at night can be used as a proxy to monitor the process of the country’s urban growth, development, and economy. The present study conducted an analysis using remote sensing data, i.e. (VIIRS DNB satellite datasets) for estimating changes in gross state domestic product (GSDP), bright illuminating areas and associated light pollution from regions of India for the year 2012–13 and 2018–19. Amongst states, the most populous state of India, Uttar Pradesh shows the highest contribution (11.96%) in 2018–19 for total sum of stable lights (SOL) for the nation. The highest annual mean SOL percentage increase (2012–13 to 2018–19) in night lights was witnessed in the state of Bihar (~ 220%). A strong correlation is observed between log SOL and log GSDP for both the time periods viz. 2012–13 (R² = 0.88) and 2018–19 (R² = 0.82). Statistics revealed that there was a growth of 31.16% in bright lit areas from 2012–13 to 2018–19. 1.27% average increase in light pollution was observed from 2012–13 to 2018–19 in India.
    Keywords data collection ; pollution ; satellites ; statistics ; urbanization ; India
    Language English
    Dates of publication 2021-12
    Size p. 2933-2943.
    Publishing place Springer India
    Document type Article
    ZDB-ID 2439566-3
    ISSN 0974-3006 ; 0255-660X
    ISSN (online) 0974-3006
    ISSN 0255-660X
    DOI 10.1007/s12524-021-01427-1
    Database NAL-Catalogue (AGRICOLA)

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  8. Article: Investigating the Effect of Lockdown During COVID-19 on Land Surface Temperature: Study of Dehradun City, India

    Maithani, Sandeep / Nautiyal, Garima / Sharma, Archana

    J. Ind. Soc. Remote Sens.

    Abstract: Urban environment imposes challenges due to its dynamics and thermodynamic characteristics of the built environment. The present study aims to study the effect of lockdown during COVID-19 on the spatio-temporal land surface temperature (LST) patterns in ... ...

    Abstract Urban environment imposes challenges due to its dynamics and thermodynamic characteristics of the built environment. The present study aims to study the effect of lockdown during COVID-19 on the spatio-temporal land surface temperature (LST) patterns in Dehradun city. The TIRS sensor data of 14 April 2020 (post-lockdown), 28 April 2019, 25 April 2018 and 08 May 2017 were downloaded, and LST was retrieved using radiative transfer equation. The wardwise change in LST, urban hot spots and thermal comfort was studied as a function of built-up density. It was observed that there was an overall decrease in LST values in Dehradun city in post-COVID lockdown period. Wards with high built-up density had minimum decrease in LST; on the contrary, wards with large proportion of open spaces and having low, medium built-up density had the maximum decrease in LST. Hot spot analysis was carried out using Getis Ord GI* statistic, and the level of thermal comfort was found using the urban thermal field variance index. It was observed that there was an increase in number of hot spots accompanied by a decrease in thermal comfort level post-lockdown. The methodology proposed in the present study can be applied to other Indian cities which exhibit similar growth patterns and will provide a tool for rational decision making.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #746932
    Database COVID19

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  9. Article ; Online: Investigating the Effect of Lockdown During COVID-19 on Land Surface Temperature

    Maithani, Sandeep / Nautiyal, Garima / Sharma, Archana

    Journal of the Indian Society of Remote Sensing

    Study of Dehradun City, India

    2020  Volume 48, Issue 9, Page(s) 1297–1311

    Keywords Earth and Planetary Sciences (miscellaneous) ; Geography, Planning and Development ; covid19
    Language English
    Publisher Springer Science and Business Media LLC
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2439566-3
    ISSN 0974-3006 ; 0255-660X
    ISSN (online) 0974-3006
    ISSN 0255-660X
    DOI 10.1007/s12524-020-01157-w
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article: Urban growth dynamics of an Indian metropolitan using CA Markov and Logistic Regression

    Siddiqui, Asfa / Siddiqui, Almas / Maithani, Sandeep / Jha, A.K / Kumar, Pramod / Srivastav, S.K

    National Authority for Remote Sensing and Space Sciences The Egyptian Journal of Remote Sensing and Space Sciences (Online). 2018 Dec., v. 21, no. 3

    2018  

    Abstract: The inescapable phenomenon of growth due to urbanization is witnessed by urban centres. The rate of growth of an urban area can be attributed to a number of factors that play a pivotal role in depicting the land use dynamics. The need to identify, ... ...

    Abstract The inescapable phenomenon of growth due to urbanization is witnessed by urban centres. The rate of growth of an urban area can be attributed to a number of factors that play a pivotal role in depicting the land use dynamics. The need to identify, quantify and analyse the drivers of growth is essential to understand the phenomenon of urban growth in a fast growing agglomeration like Lucknow, capital of the most populous state, Uttar Pradesh in India. In this study the urban growth within the planning area was analysed for the year 1993, 2003 and 2013 using certain bio-physical and proximity factors affecting the growth pattern of the city. Factors maps were generated for the various years and the growth was predicted for the year 2023 using integrated Logistic Regression based CA-Markov analysis embedded in the LULC Dynamics Modelling Platform v1.0 developed under the ISRO Geosphere Biosphere Programme at IIRS, ISRO, Dehradun. The predictions show that the city is expected to grow manifolds to 441.2 sq. km in 2023 from mere 53.6 sq. km in 1993. Results show that the model was successful in depicting the infill growth but could not completely predict the expansion phenomenon. The results indicate that integration of remote sensing, GIS and growth models provide important information related to the process of urban expansion useful for planners preparing vision documents for cities.
    Keywords biosphere ; cities ; dynamic models ; geographic information systems ; growth models ; land use ; planning ; prediction ; regression analysis ; remote sensing ; urban areas ; urbanization ; India
    Language English
    Dates of publication 2018-12
    Size p. 229-236.
    Publishing place Elsevier B.V.
    Document type Article
    ISSN 1110-9823
    DOI 10.1016/j.ejrs.2017.11.006
    Database NAL-Catalogue (AGRICOLA)

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