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Mr. Md Moniruzzaman
Senior Research Fellow, ASICT Division, Bangladesh Agricultural Research Institute, Gazipur 1701, Bangladesh

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Research Keywords & Expertise

0 GIS
0 Remote Sensing
0 Drought Analysis
0 vegetation dynamics
0 UAV remote sensing

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GIS
vegetation dynamics
Remote Sensing

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Short Biography

I am M.Tech. graduate in Remote Sensing & GIS and having 5 years of professional experience of remote sensing and GIS applications in the field of agriculture, climate change, earth observation, environment, stormwater modelling, urban planning and development. Motivated to pursue higher studies and committed to bring changes for society with knowledge and expertise.

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Journal article
Published: 22 July 2021 in Atmosphere
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This research assessed the changes in spatial patterns and the seasonal trends in temperature, precipitation, and relative humidity over 36 years (1979–2014) using Climate Forecast System Reanalysis (CFSR) datasets. The evaluation of climate deviations was the prime objective of this research. The augmented Dickey–Fuller Test (ADF) was used to scrutinize whether the data was either stationary or non-stationary. The results of the ADF test showed that all the datasets were found to be stationary at lag order 3. To observe undulations in the time series data, trend analyses were done using Sen’s slope (SS), Mann–Kendall (MK), and Cox and Stuart (CS) tests. For all the statistical analyses, we considered the 5% significance level (α = 0.05) and p< 0.05 to be statistically significant. We observed significant (p< 0.05) trends in spring (MAM) and autumn (SON) for minimum temperature (Tmin) in Punjab. We also noted a significant (p< 0.05) trend in precipitation during autumn (SON). Annually, all the variables showed a non-significant (p > 0.05) trend for Punjab, Pakistan, during the period 1979–2014. Climate variability, such as a decrease in precipitation, higher temperature, and relative humidity fluctuations, were the reasons for the imbalance in the sustainability of Punjab, Pakistan.

ACS Style

Alishbah Syed; Xingpeng Liu; Moniruzzaman; Iman Rousta; Warda Syed; Jiquan Zhang; Haraldur Olafsson. Assessment of Climate Variability among Seasonal Trends Using In Situ Measurements: A Case Study of Punjab, Pakistan. Atmosphere 2021, 12, 939 .

AMA Style

Alishbah Syed, Xingpeng Liu, Moniruzzaman, Iman Rousta, Warda Syed, Jiquan Zhang, Haraldur Olafsson. Assessment of Climate Variability among Seasonal Trends Using In Situ Measurements: A Case Study of Punjab, Pakistan. Atmosphere. 2021; 12 (8):939.

Chicago/Turabian Style

Alishbah Syed; Xingpeng Liu; Moniruzzaman; Iman Rousta; Warda Syed; Jiquan Zhang; Haraldur Olafsson. 2021. "Assessment of Climate Variability among Seasonal Trends Using In Situ Measurements: A Case Study of Punjab, Pakistan." Atmosphere 12, no. 8: 939.

Original article
Published: 09 June 2021 in Earth Systems and Environment
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Bangladesh is an agriculture-dependent country and very often this sector struggles a lot due to various natural hazards including drought and flood. Almost every year in kharif crop season, Bangladesh undergoes through drought which causes a lot of yield loss. So, this has become important to identify the drought-prone areas to reduce the risk of crops yield loss and for policymaking to suggest alternative drought-tolerant crops. The agricultural drought is related to soil properties because of having spatially dynamic in nature. In the present study, agricultural drought has been assessed comprising meteorological drought of kharif season and water holding capacity (WHC) in Geographic Information System (GIS) platform, as GIS is a widely used as a powerful tool to manage and model the spatial data. The metrological drought map has prepared by rainfall data with the calculation of Standardized Precipitation Index (SPI) using GIS and WHC of soil map has converted from soil texture map. Finally, the agricultural drought map has been derived by overlying metrological drought map and WHC of soil map. The study has found that the north-west and south-west region along with Barisal division of Bangladesh are more prone to agricultural drought area than the other parts. Some districts of the middle part of the country (Dhaka, Manikganj and Faridpur: 492 km2) also suffered in extreme agricultural drought during kharif season.

ACS Style

Abdullah Aziz; A. B. M. Zahid Hossain; Moniruzzaman; Rokib Ahmed; Taslima Zahan; Saiful Azim; Abdul Qayum; Abdulllah Al Mamun; Abdul Kader; Niaz Md. Farhat Rahman. Mapping of Agricultural Drought in Bangladesh using Geographic Information System (GIS). Earth Systems and Environment 2021, 1 -11.

AMA Style

Abdullah Aziz, A. B. M. Zahid Hossain, Moniruzzaman, Rokib Ahmed, Taslima Zahan, Saiful Azim, Abdul Qayum, Abdulllah Al Mamun, Abdul Kader, Niaz Md. Farhat Rahman. Mapping of Agricultural Drought in Bangladesh using Geographic Information System (GIS). Earth Systems and Environment. 2021; ():1-11.

Chicago/Turabian Style

Abdullah Aziz; A. B. M. Zahid Hossain; Moniruzzaman; Rokib Ahmed; Taslima Zahan; Saiful Azim; Abdul Qayum; Abdulllah Al Mamun; Abdul Kader; Niaz Md. Farhat Rahman. 2021. "Mapping of Agricultural Drought in Bangladesh using Geographic Information System (GIS)." Earth Systems and Environment , no. : 1-11.

Journal article
Published: 29 December 2020 in Remote Sensing
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Rapid urban growth processes give rise to impervious surfaces and are regarded as the primary cause of urban flooding or waterlogging in urban areas. The high rate of urbanization has caused waterlogging and urban flooding in many parts of Dhaka city. Therefore, the study is undertaken to quantify the changes in land use/land cover (LULC) and urban runoff extent based on the Natural Resources Conservation Service (NRCS) Curve Number (CN) during 1978–2018. The five-decadal LULC has been analyzed using three-generation Landsat time-series data considering six different classes, namely agriculture, built-up, wetland, open land, green spaces, and water bodies for the years 1978, 1988, 1998, 2007, and 2018. Significant changes in LULC for the study area from 1978–2018 are observed as 13.1%, 4.8%, and 7.8% reduction in agricultural land, green spaces, and water bodies, respectively, and a 22.1% increase in the built-up area is estimated. Within Dhaka city, 14.6%, 16.0%, and 12.3% reduction in agricultural land, green spaces, and water bodies, respectively, and a radical increase of 41.9% in built-up area are reckoned. The decadal runoff assessment has been carried out using the NRCS-CN method, considering an extreme rainfall event of 341 mm/day (13 September 2004). The catchment area under very high runoff category is observed as 159.5 km2 (1978) and 318.3 km2 (2018), whereas, for Dhaka city, the setting is dynamic as the area under the very high runoff category has increased from 74.24 km2 (24.44%) to 174.23 km2 (57.36%) in years 1978 and 2018, respectively, and, mostly, the very high runoff potential areas correspond to the dense built-up surfaces.

ACS Style

Moniruzzaman; Praveen Thakur; Pramod Kumar; Ashraful Alam; Vaibhav Garg; Iman Rousta; Haraldur Olafsson. Decadal Urban Land Use/Land Cover Changes and Its Impact on Surface Runoff Potential for the Dhaka City and Surroundings Using Remote Sensing. Remote Sensing 2020, 13, 83 .

AMA Style

Moniruzzaman, Praveen Thakur, Pramod Kumar, Ashraful Alam, Vaibhav Garg, Iman Rousta, Haraldur Olafsson. Decadal Urban Land Use/Land Cover Changes and Its Impact on Surface Runoff Potential for the Dhaka City and Surroundings Using Remote Sensing. Remote Sensing. 2020; 13 (1):83.

Chicago/Turabian Style

Moniruzzaman; Praveen Thakur; Pramod Kumar; Ashraful Alam; Vaibhav Garg; Iman Rousta; Haraldur Olafsson. 2020. "Decadal Urban Land Use/Land Cover Changes and Its Impact on Surface Runoff Potential for the Dhaka City and Surroundings Using Remote Sensing." Remote Sensing 13, no. 1: 83.

Preprint
Published: 15 December 2020
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The spatiotemporal variability of vegetation in the Middle East was investigated for the period 2001–2019 using the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day/500 m composites of the Normalized Difference Vegetation Index (NDVI; MOD13A1). The results reveal a strong increase in the NDVI coverage in the Middle East during the study period (R = 0.75, p-value = 0.05). In Egypt, the annual coverage exhibits the strongest positive trend (R = 0.99, p-value = 0.05). In Turkey, both the vegetation coverage and density increased from 2001 to 2019, which can be attributed to the construction of some of the biggest dams in the Middle East, such as the Atatürk and Ilisu dams. Significant increases in the annual coverage and maximum and average NDVI in Saudi Arabia are due to farming in the northern part of the country for which groundwater and desalinated seawater are used. The results of this study suggest that the main factors affecting the vegetation coverage in the Middle East are governmental policies. These policies can have a positive effect on the vegetation coverage in some countries such as Egypt, Saudi Arabia, Qatar, Kuwait, Iran, and Turkey.

ACS Style

Iman Rousta; Haraldur Olafsson; Hao Zhang; Moniruzzaman; Jaromir Krzyszczak; Piotr Baranowski. Anthropogenic Factors Affecting the Vegetation Dynamics in the Arid Middle East. 2020, 1 .

AMA Style

Iman Rousta, Haraldur Olafsson, Hao Zhang, Moniruzzaman, Jaromir Krzyszczak, Piotr Baranowski. Anthropogenic Factors Affecting the Vegetation Dynamics in the Arid Middle East. . 2020; ():1.

Chicago/Turabian Style

Iman Rousta; Haraldur Olafsson; Hao Zhang; Moniruzzaman; Jaromir Krzyszczak; Piotr Baranowski. 2020. "Anthropogenic Factors Affecting the Vegetation Dynamics in the Arid Middle East." , no. : 1.

Research article
Published: 12 November 2020 in SN Applied Sciences
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Satellite-retrieved aerosol optical depth essentially provides an economical option for regular monitoring of particulate matter (PM) concentration; however, the constrains and challenges come in terms of estimation accuracy. In the present study, we estimated PM2.5 and PM10 (PM of aerodynamic diameter lesser than 2.5, 10 µm, respectively) for 11 sites in Bangladesh using different methods. Univariate model showed destitute performance (R2 < 0.1), whereas integrating MODIS-AOD with surface meteorology, multivariate models enhanced accuracy (R2 > 0.6); meanwhile, radial kernel-based ‘eps’-type support vector regression model outperformed rest (R2 > 0.8). Furthermore, we investigated variations in ground concentration of PM2.5, PM10 during 2013–2018 and found annual mean concentration of 76.34 ± 34.12 µg m−3 and 136.25 ± 68.94 µg m−3, respectively. Predominant anthropogenic contribution to elevated pollution is well remarked by PM2.5/PM10 ratio, highest during January (0.65 ± 0.06) and lowest during July (0.48 ± 0.11). Grievous pollution found in Narayanganj (PM2.5: 100.35 ± 56.76 µg m−3, PM10: 200.25 ± 91.79 µg m−3) and slightest in Sylhet (PM2.5: 56.13 ± 26.99 µg m−3, PM10: 103.94 ± 49.37 µg m−3). Intra-annual pattern asserts winter as sternly befouled and least pollution during monsoon, which may indicate significant influence of meteorology on PM pollution. We found that PM divulged negative correlation with air temperature (PM2.5: −0.78, PM10: −0.73), relative humidity (PM2.5: −0.66, PM10: −0.73) and rainfall (PM2.5: −0.59, PM10: −0.61). This study showed outrageous situation of PM pollution in urban areas in Bangladesh and proposed modest pathway for regular monitoring of PM that will help to combat pollution.

ACS Style

Amitesh Gupta; Moniruzzaman; Avinash Hande; Iman Rousta; Haraldur Olafsson; Karno Kumar Mondal. Estimation of particulate matter (PM2.5, PM10) concentration and its variation over urban sites in Bangladesh. SN Applied Sciences 2020, 2, 1 -15.

AMA Style

Amitesh Gupta, Moniruzzaman, Avinash Hande, Iman Rousta, Haraldur Olafsson, Karno Kumar Mondal. Estimation of particulate matter (PM2.5, PM10) concentration and its variation over urban sites in Bangladesh. SN Applied Sciences. 2020; 2 (12):1-15.

Chicago/Turabian Style

Amitesh Gupta; Moniruzzaman; Avinash Hande; Iman Rousta; Haraldur Olafsson; Karno Kumar Mondal. 2020. "Estimation of particulate matter (PM2.5, PM10) concentration and its variation over urban sites in Bangladesh." SN Applied Sciences 2, no. 12: 1-15.

Journal article
Published: 29 July 2020 in Remote Sensing
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Drought has severe impacts on human society and ecosystems. In this study, we used data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) sensors to examine the drought effects on vegetation in Afghanistan from 2001 to 2018. The MODIS data included the 16-day 250-m composites of the Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI) with Land Surface Temperature (LST) images with 1 km resolution. The TRMM data were monthly rainfalls with 0.1-degree resolution. The relationship between drought and index-defined vegetation variation was examined by using time series, regression analysis, and anomaly calculation. The results showed that the vegetation coverage for the whole country, reaching the lowest levels of 6.2% and 5.5% were observed in drought years 2001 and 2008, respectively. However, there is a huge inter-regional variation in vegetation coverage in the study period with a significant rising trend in Helmand Watershed with R = 0.66 (p value = 0.05). Based on VCI for the same two years (2001 and 2008), 84% and 72% of the country were subject to drought conditions, respectively. Coherently, TRMM data confirm that 2001 and 2008 were the least rainfall years of 108 and 251 mm, respectively. On the other hand, years 2009 and 2010 were registered with the largest vegetation coverage of 16.3% mainly due to lower annual LST than average LST of 14 degrees and partially due to their slightly higher annual rainfalls of 378 and 425 mm, respectively, than the historical average of 327 mm. Based on the derived VCI, 28% and 21% of the study area experienced drought conditions in 2009 and 2010, respectively. It is also found that correlations are relatively high between NDVI and VCI (r = 0.77, p = 0.0002), but slightly lower between NDVI and precipitation (r = 0.51, p = 0.03). In addition, LST played a key role in influencing the value of NDVI. However, both LST and precipitation must be considered together in order to properly capture the correlation between drought and NDVI.

ACS Style

Iman Rousta; Haraldur Olafsson; Moniruzzaman; Hao Zhang; Yuei-An Liou; Terence Mushore; Amitesh Gupta. Impacts of Drought on Vegetation Assessed by Vegetation Indices and Meteorological Factors in Afghanistan. Remote Sensing 2020, 12, 2433 .

AMA Style

Iman Rousta, Haraldur Olafsson, Moniruzzaman, Hao Zhang, Yuei-An Liou, Terence Mushore, Amitesh Gupta. Impacts of Drought on Vegetation Assessed by Vegetation Indices and Meteorological Factors in Afghanistan. Remote Sensing. 2020; 12 (15):2433.

Chicago/Turabian Style

Iman Rousta; Haraldur Olafsson; Moniruzzaman; Hao Zhang; Yuei-An Liou; Terence Mushore; Amitesh Gupta. 2020. "Impacts of Drought on Vegetation Assessed by Vegetation Indices and Meteorological Factors in Afghanistan." Remote Sensing 12, no. 15: 2433.

Original article
Published: 27 March 2020 in Modeling Earth Systems and Environment
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The study investigates the relationship between drought and vegetation variations in three main basins of western and southwestern of Iran, using the comprehensive approach of time-series analysis, Standardized Precipitation Index (SPI), and anomaly calculation. A total of 30 ground stations’ daily meteorological data and the MODIS 16-day composite NDVI products (2000–2017) were used in this case. The results showed that in the Great Karoun River (GKRW) and Karkheh River (KRW) sub-regions, the NDVI decreased slightly over the study period. Simultaneously, in the West Marginal (WMW) sub-region the NDVI slightly increased somewhat. Overall, the NDVI in the whole study area presented an insignificant decrease. Also the results found that there is a significant relationship (p < 0.02) between the NDVI (0.3–0.7) with spring drought and between NDVI (0.2–0.3) with fall drought (p < 0.01). There is a marginally significant relationship (R = 0.43, p = 0.07) between NDVI (0.3–0.4) with fall drought and a relatively high, but insignificant relationship between NDVI (0.7–0.8) with spring drought (R = 0.41, p = 0.09). Low temperature can play an important role in determining the relationship between SPI and NDVI, which evidenced that it can trade-off the effect of a very wet year. As well as a year with very wet condition can affect the NDVI of the coming years. Since summer is hot season in the study area and most of the vegetation consists of shrubs and grasslands, of which the NDVI ranges between 0.2 and 0.4, the vegetation cover can be significantly affected by a wet summer with abundant precipitation.

ACS Style

Iman Rousta; Haraldur Olafsson; Moniruzzaman; Jonas Ardö; Hao Zhang; Terence Darlington Mushore; Shifa Shahin; Saiful Azim. The 2000–2017 drought risk assessment of the western and southwestern basins in Iran. Modeling Earth Systems and Environment 2020, 6, 1201 -1221.

AMA Style

Iman Rousta, Haraldur Olafsson, Moniruzzaman, Jonas Ardö, Hao Zhang, Terence Darlington Mushore, Shifa Shahin, Saiful Azim. The 2000–2017 drought risk assessment of the western and southwestern basins in Iran. Modeling Earth Systems and Environment. 2020; 6 (2):1201-1221.

Chicago/Turabian Style

Iman Rousta; Haraldur Olafsson; Moniruzzaman; Jonas Ardö; Hao Zhang; Terence Darlington Mushore; Shifa Shahin; Saiful Azim. 2020. "The 2000–2017 drought risk assessment of the western and southwestern basins in Iran." Modeling Earth Systems and Environment 6, no. 2: 1201-1221.

Journal article
Published: 11 February 2019
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ACS Style

Ali-Akbar Sabziparvar; Seyed Hossein Mir Mousavi; Mostafa Karampour; Mehdi Doostkamian; Esmaeil Haghighi; Iman Rousta; Haraldur Olafsson; Omar Sarif; R.D. Gupta; Moniruzzaman; Khairul Hasan; Ali GhasemiBaghtash. Harmonic Analysis of the Spatiotemporal Pattern of Thunderstorms in Iran (1961–2010). 2019, 2019, 1 -14.

AMA Style

Ali-Akbar Sabziparvar, Seyed Hossein Mir Mousavi, Mostafa Karampour, Mehdi Doostkamian, Esmaeil Haghighi, Iman Rousta, Haraldur Olafsson, Omar Sarif, R.D. Gupta, Moniruzzaman, Khairul Hasan, Ali GhasemiBaghtash. Harmonic Analysis of the Spatiotemporal Pattern of Thunderstorms in Iran (1961–2010). . 2019; 2019 (34):1-14.

Chicago/Turabian Style

Ali-Akbar Sabziparvar; Seyed Hossein Mir Mousavi; Mostafa Karampour; Mehdi Doostkamian; Esmaeil Haghighi; Iman Rousta; Haraldur Olafsson; Omar Sarif; R.D. Gupta; Moniruzzaman; Khairul Hasan; Ali GhasemiBaghtash. 2019. "Harmonic Analysis of the Spatiotemporal Pattern of Thunderstorms in Iran (1961–2010)." 2019, no. 34: 1-14.

Research article
Published: 11 February 2019 in Advances in Meteorology
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The current study aimed at investigating cycles and the spatial autocorrelation pattern of anomalies of thunderstorms in Iran during different periods from 1961 to 2010. In this analysis, 50-year periods (1961–2010) of thunderstorm codes have been collected from 283 synoptic stations of Meteorological Organization of Iran. The study period has been divided into five different decades (1961–1970, 1971–1980, 1981–1990, 1991–2000, and 2001–2010). Spectral analysis and Moran’s I were used to analyze cycles and the spatial autocorrelation pattern, respectively. Furthermore, in order to conduct the calculations, programming facilities of MATLAB have been explored. Finally, Surfer and GIS were employed to come up with the graphical depiction of the maps. The results showed that the maximum of positive anomalies mainly occurred in the northwestern and western parts of Iran due to their special topography, during all the five studied periods. On the other hand, the minimum of negative anomalies took place in central regions of the country because of lack of appropriate conditions (e.g., enough humidity). Moran’s I spatial analysis further confirmed these findings as Moran’s I depicts the positive and negative spatial autocorrelation patterns in line with negative and positive anomalies, respectively. However, in recent decades, this pattern has experienced a declining trend, especially in southern areas of Iran. The results of harmonic analysis indicated that mainly short-term and midterm cycles dominated Iran’s thunderstorms.

ACS Style

Ali Akbar Sabziparvar; Seyed Hossein Mir Mousavi; Mostafa Karampour; Mehdi Doostkamian; Esmaeil Haghighi; Iman Rousta; Haraldur Olafsson; Omar Sarif; Rajan Dev Gupta; Moniruzzaman; Khairul Hasan; Ali Ghasemi. Harmonic Analysis of the Spatiotemporal Pattern of Thunderstorms in Iran (1961–2010). Advances in Meteorology 2019, 2019, 1 -14.

AMA Style

Ali Akbar Sabziparvar, Seyed Hossein Mir Mousavi, Mostafa Karampour, Mehdi Doostkamian, Esmaeil Haghighi, Iman Rousta, Haraldur Olafsson, Omar Sarif, Rajan Dev Gupta, Moniruzzaman, Khairul Hasan, Ali Ghasemi. Harmonic Analysis of the Spatiotemporal Pattern of Thunderstorms in Iran (1961–2010). Advances in Meteorology. 2019; 2019 ():1-14.

Chicago/Turabian Style

Ali Akbar Sabziparvar; Seyed Hossein Mir Mousavi; Mostafa Karampour; Mehdi Doostkamian; Esmaeil Haghighi; Iman Rousta; Haraldur Olafsson; Omar Sarif; Rajan Dev Gupta; Moniruzzaman; Khairul Hasan; Ali Ghasemi. 2019. "Harmonic Analysis of the Spatiotemporal Pattern of Thunderstorms in Iran (1961–2010)." Advances in Meteorology 2019, no. : 1-14.

Journal article
Published: 19 November 2018 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Urbanization has given a massive pace in Land Use Land Cover (LULC) changes in rapidly growing cities like Khulna, i.e. the third largest city of Bangladesh. Such impacting changes have taken place in over-decadal scale. It is important because detailed analysis with regularly monitoring will be fruitful to drag the attention of decision maker and urban planner for sustainable development and to overcome the problem of urban sprawl. In this present study, changes in LULC as an impact of urbanization, have been investigated for years 1997, 2002, 2007, 2012 and 2017; using three generation of Landsat data in geographic information system (GIS) domain which has the height competence in recent time. Initially, LULC have categorised into Built-up, Vegetation, Vacant Land, and Waterbody with the help of supervised classification technique. Field work had been carried out for acquiring training dataset and validation. The accuracy has been achieved more than 85% for the changes assessed. Analysis has an outlet with increase in built-up area by 27.92% in year 1997 to 2017 and continued respectively in each successive interval of half a decade at the given years. On the other side waterbody and vacant land decreased correspondingly. Bound to mention, instead to having largest temporal durability, the moderate spatial resolution of Landsat data has a limitation for such urban studies. These changes are responsible by both of natural or anthropogenic factors. Such study will provide a better way out of optimization of land-use to prepare detail area plan (DAP) of Khulna City Corporation (KCC) and Khulna development authority (KDA).

ACS Style

M. Moniruzzam; A. Roy; C. M. Bhatt; A. Gupta; N. T. T. An; M. R. Hassan. IMPACT ANALYSIS OF URBANIZATION ON LAND USE LAND COVER CHANGE FOR KHULNA CITY, BANGLADESH USING TEMPORAL LANDSAT IMAGERY. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2018, XLII-5, 757 -760.

AMA Style

M. Moniruzzam, A. Roy, C. M. Bhatt, A. Gupta, N. T. T. An, M. R. Hassan. IMPACT ANALYSIS OF URBANIZATION ON LAND USE LAND COVER CHANGE FOR KHULNA CITY, BANGLADESH USING TEMPORAL LANDSAT IMAGERY. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2018; XLII-5 ():757-760.

Chicago/Turabian Style

M. Moniruzzam; A. Roy; C. M. Bhatt; A. Gupta; N. T. T. An; M. R. Hassan. 2018. "IMPACT ANALYSIS OF URBANIZATION ON LAND USE LAND COVER CHANGE FOR KHULNA CITY, BANGLADESH USING TEMPORAL LANDSAT IMAGERY." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5, no. : 757-760.