Land Suitability Assessment for Pulse (Green Gram) Production through Remote Sensing, GIS, and Multicriteria Analysis in the Coastal Region of Bangladesh

The agricultural potential of Bangladesh’s coastal region has been threatened by the impact of climate change. Pulse crops with high nutritional value and low production costs such as green gram constitute an important component of a healthy and accessible diet for the country. In order to optimize the production of this important staple, this research aims to promote climate-smart agriculture by optimizing the identification of the appropriate land. The objective of this research is to investigate, estimate, and identify the suitable land areas for green gram production based on the topography, climate, and soil characteristics in the coastal region of Bangladesh. The methodology of the study included a Geographic Information System (GIS) and the Multicriteria Decision-Making approach: the Analytical Hierarchy Process (AHP). Datasets were collected and prepared using Landsat 8 imagery, the Center for Hydrometeorology and Remote Sensing (CHRS) data portal and the Bangladesh Agricultural Research Council. All the datasets were processed into raster images and then reclassified into four classes: Highly Suitable (S1), Moderately Suitable (S2), Marginally Suitable (S3), and Not Suitable. Then, the AHP results were applied to produce a final green gram suitability map with four classes of suitability. The results of the study found that 12% of the coastal area (344,619.5 ha) is highly suitable for green gram production, while the majority of the land area (82.3% of the area) shows moderately suitable (S2) land. The sensitivity analysis results show that 3.3%, 63.4%, 28.0%, and 1.2% of the study area are S1, S2, S3, and NS, respectively. It is also found that the highly suitable land area belongs mostly to the southeastern part of the country. The result of this study can be utilized by policymakers to adopt a proper green gram production strategy, providing special agricultural incentive policies in the highly suitable area as a provision for the increased food production of the country.

Download Full-text

Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

Journal of Geographical Studies ◽

10.21523/gcj5.19030102 ◽

2020 ◽

Vol 3 (1) ◽

pp. 11-23 ◽

Cited By ~ 3

Author(s):

Abdulla Al Kafy ◽

Abdullah Al-Faisal ◽

Mohammad Mahmudul Hasan ◽

Md. Soumik Sikdar ◽

Mohammad Hasib Hasan Khan ◽

...

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Land Surface ◽

Agricultural Land ◽

Global Climate ◽

Urban Expansion ◽

Water Bodies ◽

Landsat 8 ◽

Lulc Changes ◽

The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

Download Full-text

Retrieving Total and Inorganic Suspended Sediments in Amazon Floodplain Lakes: A Multisensor Approach

Remote Sensing ◽

10.3390/rs11151744 ◽

2019 ◽

Vol 11 (15) ◽

pp. 1744 ◽

Cited By ~ 7

Author(s):

Daniel Maciel ◽

Evlyn Novo ◽

Lino Sander de Carvalho ◽

Cláudio Barbosa ◽

Rogério Flores Júnior ◽

...

Keyword(s):

Remote Sensing ◽

Atmospheric Correction ◽

Suspended Sediments ◽

Floodplain Lakes ◽

Empirical Modeling ◽

Landsat 8 ◽

Amazon Floodplain ◽

The Impact ◽

Sentinel 2

Remote sensing imagery are fundamental to increasing the knowledge about sediment dynamics in the middle-lower Amazon floodplains. Moreover, they can help to understand both how climate change and how land use and land cover changes impact the sediment exchange between the Amazon River and floodplain lakes in this important and complex ecosystem. This study investigates the suitability of Landsat-8 and Sentinel-2 spectral characteristics in retrieving total (TSS) and inorganic (TSI) suspended sediments on a set of Amazon floodplain lakes in the middle-lower Amazon basin using in situ Remote Sensing Reflectance (Rrs) measurements to simulate Landsat 8/OLI (Operational Land Imager) and Sentinel 2/MSI (Multispectral Instrument) bands and to calibrate/validate several TSS and TSI empirical algorithms. The calibration was based on the Monte Carlo Simulation carried out for the following datasets: (1) All-Dataset, consisting of all the data acquired during four field campaigns at five lakes spread over the lower Amazon floodplain (n = 94); (2) Campaign-Dataset including samples acquired in a specific hydrograph phase (season) in all lakes. As sample size varied from one season to the other, n varied from 18 to 31; (3) Lake-Dataset including samples acquired in all seasons at a given lake with n also varying from 17 to 67 for each lake. The calibrated models were, then, applied to OLI and MSI scenes acquired in August 2017. The performance of three atmospheric correction algorithms was also assessed for both OLI (6S, ACOLITE, and L8SR) and MSI (6S, ACOLITE, and Sen2Cor) images. The impact of glint correction on atmosphere-corrected image performance was assessed against in situ glint-corrected Rrs measurements. After glint correction, the L8SR and 6S atmospheric correction performed better with the OLI and MSI sensors, respectively (Mean Absolute Percentage Error (MAPE) = 16.68% and 14.38%) considering the entire set of bands. However, for a given single band, different methods have different performances. The validated TSI and TSS satellite estimates showed that both in situ TSI and TSS algorithms provided reliable estimates, having the best results for the green OLI band (561 nm) and MSI red-edge band (705 nm) (MAPE < 21%). Moreover, the findings indicate that the OLI and MSI models provided similar errors, which support the use of both sensors as a virtual constellation for the TSS and TSI estimate over an Amazon floodplain. These results demonstrate the applicability of the calibration/validation techniques developed for the empirical modeling of suspended sediments in lower Amazon floodplain lakes using medium-resolution sensors.

Download Full-text

Assessing the impact of arid area urbanization on flash floods using GIS, remote sensing, and HEC-HMS rainfall–runoff modeling

Hydrology Research ◽

10.2166/nh.2016.133 ◽

2016 ◽

Vol 47 (6) ◽

pp. 1142-1160 ◽

Cited By ~ 22

Author(s):

Mohamed El Alfy

Keyword(s):

Remote Sensing ◽

Hydrologic Modeling ◽

Integrated Approach ◽

Flash Floods ◽

Landsat 8 ◽

Arid Areas ◽

Rainfall Runoff ◽

Rapid Urbanization ◽

Runoff Modeling ◽

The Impact

This study uses an integrated approach, bringing together geographic information system (GIS), remote sensing, and rainfall–runoff modeling, to assess the urbanization impact on flash floods in arid areas. Runoff modeling was carried out as a function of the catchment characteristics and the maximum daily rainfall parameters. Land-use types were extracted from the supervised classification of SPOT-5 (2010) and Landsat-8 (2015) satellite images and were validated during field checks. Catchment morphometric characteristics were carried out using the correlated Topaz and Arc-Hydro tools. Maximum floods of the catchment were evaluated by coupling GIS and remote sensing with Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) hydrologic modeling. Peak discharges were estimated, and the abstraction losses were computed for different return periods. The model results were calibrated according to actual runoff event. The research shows that rapid urbanization adversely affects hydrological processes, since the sprawl on the alluvial channels is significant. This reduces infiltration into the underlying alluvium and increases runoff, leading to higher flood peaks and volumes even for short duration low intensity rainfall. To retain a considerable amount of water and sediments in these arid areas, construction of small dams at the fingertip channels at the outlet of the lower order sub-basins is recommended.

Download Full-text

Monitoring Sugarcane Growth Phases Based on Satellite Image Analysis (A Case Study in Indramayu and its Surrounding, West Java, Indonesia)

HAYATI Journal of Biosciences ◽

10.4308/hjb.26.3.117 ◽

2019 ◽

Vol 26 (3) ◽

pp. 117

Author(s):

Tri Muji Susantoro ◽

Ketut Wikantika ◽

Agung Budi Harto ◽

Deni Suwardi

Keyword(s):

Remote Sensing ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Satellite Image ◽

Landsat 8 ◽

Gas Field ◽

Research Results ◽

The Third ◽

Third Phase ◽

The Impact

This study is intended to examine the growing phases and the harvest of sugarcane crops. The growing phases is analyzed with remote sensing approaches. The remote sensing data employed is Landsat 8. The vegetation indices of Normalized Difference Vegetation Index (NDVI) and Enhanced Normalized Difference Vegetation Index (ENDVI) are employed to analyze the growing phases and the harvest of sugarcane crops. Field survey was conducted in March and August 2017. The research results shows that March is the peak of the third phase (Stem elonging phase or grand growth phase), the period from May to July is the fourth phase (maturing or ripening phase), and the period from August to October is the peak of harvest. In January, the sugarcane crops begin to grow and some sugarcane crops enter the third phase again. The research results also found the sugarcane plants that do not grow well near the oil and gas field. This condition is estimated due as the impact of hydrocarbon microseepage. The benefit of this research is to identify the sugarcane growth cycle and harvest. Having knowing this, it will be easier to plan the seed development and crops transport.

Download Full-text

Monitoring of specially protected natural territories of forest-steppe landscapes of the Stavropol upland by means of remote sensing data

Proceedings of the International conference “InterCarto/InterGIS” ◽

10.35595/2414-9179-2021-1-27-364-376 ◽

2021 ◽

Vol 27 (1) ◽

pp. 364-376

Author(s):

Tigran Shahbazyan

Keyword(s):

Remote Sensing ◽

Satellite Imagery ◽

Satellite Images ◽

Remote Sensing Data ◽

Anthropogenic Factors ◽

Forest Steppe ◽

Landsat 8 ◽

Sensing Data ◽

Ndvi Index ◽

The Impact

The article considers the methodology of monitoring specially protected natural areas using remote sensing data. The research materials are satellite images of the Landsat 5 and Landsat 8 satellites, obtained from the resource of the US Geological Survey. The key areas of the study were 3 specially protected areas located within the boundaries of the forest-steppe landscapes of the Stavropol upland, the reserves «Alexandrovskiy», «Russkiy Les», «Strizhament». The space survey materials were selected for the period 1991–2020, and the data from the summer seasons were used. The NDVI index is chosen as the method of processing the spectral channels of satellite imagery. To integrate long-term satellite imagery into a single raster image, the method of variance of the variation series for the NDVI index was used. The article describes an algorithm for processing satellite images, which allows us to identify the features of the dynamics of the vegetation state of the studied territory for the period 1991–2020. The bitmap image constructed by means of the variance of the NDVI index was classified by the quantile method, to translate numerical values into classes with qualitative characteristics. There were 4 classes of the territory according to the degree of dynamism of the vegetation state: “stable”, “slightly variable”, “moderately variable”, “highly variable”. The paper highlights the factors of landscape transformation, including natural and anthropogenic ones. In the course of the study, the determining influence of anthropogenic factors of transformation was noted. The greatest impact is on the reserve «Alexandrovskiy», the least on the reserve «Russkiy Les», in the reserve «Strizhament» the impact is expressed locally. The paper identifies the leading anthropogenic factors of vegetation transformation, based on their influence on vegetation.

Download Full-text

Sediment predictions in Wadi Al-Naft using soil water assessment tool

MATEC Web of Conferences ◽

10.1051/matecconf/201816203008 ◽

2018 ◽

Vol 162 ◽

pp. 03008 ◽

Cited By ~ 2

Author(s):

Imzahim Abdulkareem Alwan ◽

Ibtisam Karim ◽

Mahmood Mohamed

Keyword(s):

Soil Water ◽

Assessment Tool ◽

Agricultural Research ◽

Satellite Image ◽

Water Model ◽

Landsat 8 ◽

North East ◽

The Impact ◽

Soil Water Assessment Tool ◽

Water Assessment

Sediment production is the amount of sediment in the unit area that is transported through the basin by water transfer over a specified period of time. The main aim of present study is to predict sediment yield of Wadi, Al-Naft watershed with 8820 Km2area, that is located in the North-East of Diyala Governorate in Iraq, using Soil-Water Assessment Tool, (SWAT) and to predict the impact of land management and the input data including the land use, soil type, and soil texture maps which are obtained from Landsat-8 satellite image. Digital Elevation Model,(DEM) with resolution (14 14) meter is used to delineate the watershed with the aid of model. Three Land-sat images were used to cover the study area which were mosaic processed and the study area masked- up from the mosaic, image. The area of study has been registries by Arc-GIS 10.2 and digitized the soil hydrologic group through assistant of Soil Plant Assistant Water Model, (SPAW) which was progressed by USDA, Agricultural, Research Service, using the data of soil textural and organic matter from Food and Agriculture Organization (FAO), the available water content, saturated hydraulic conductivity, and bulk density. The results of average, sediment depth and the maximum upland sediment for simulation period (2010-2020) were predicted to be (1.7 mm), and (12.57 Mg/ha), respectively.

Download Full-text

Observations and Recommendations for the Calibration of Landsat 8 OLI and Sentinel 2 MSI for Improved Data Interoperability

Remote Sensing ◽

10.3390/rs10091340 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1340 ◽

Cited By ~ 24

Author(s):

Dennis Helder ◽

Brian Markham ◽

Ron Morfitt ◽

Jim Storey ◽

Julia Barsi ◽

...

Keyword(s):

Remote Sensing ◽

Sensor Calibration ◽

Landsat 8 ◽

Data Sets ◽

Optical Remote Sensing ◽

Data Interoperability ◽

Satellite Systems ◽

Combining Data ◽

The Impact ◽

Sentinel 2

Combining data from multiple sensors into a single seamless time series, also known as data interoperability, has the potential for unlocking new understanding of how the Earth functions as a system. However, our ability to produce these advanced data sets is hampered by the differences in design and function of the various optical remote-sensing satellite systems. A key factor is the impact that calibration of these instruments has on data interoperability. To address this issue, a workshop with a panel of experts was convened in conjunction with the Pecora 20 conference to focus on data interoperability between Landsat and the Sentinel 2 sensors. Four major areas of recommendation were the outcome of the workshop. The first was to improve communications between satellite agencies and the remote-sensing community. The second was to adopt a collections-based approach to processing the data. As expected, a third recommendation was to improve calibration methodologies in several specific areas. Lastly, and the most ambitious of the four, was to develop a comprehensive process for validating surface reflectance products produced from the data sets. Collectively, these recommendations have significant potential for improving satellite sensor calibration in a focused manner that can directly catalyze efforts to develop data that are closer to being seamlessly interoperable.

Download Full-text

Monitoring and analysis of the expansion of the Ajmr Port, Davao City, Philippines using multi-source remote sensing data

PeerJ ◽

10.7717/peerj.7512 ◽

2019 ◽

Vol 7 ◽

pp. e7512 ◽

Cited By ~ 1

Author(s):

Humei Li ◽

Mingquan Wu ◽

Dinghui Tian ◽

Lianxi Wu ◽

Zheng Niu

Keyword(s):

Remote Sensing ◽

Land Use ◽

Good Condition ◽

Coastal Region ◽

Remote Sensing Data ◽

Vegetation Coverage ◽

Port Area ◽

The Impact ◽

Port Construction ◽

Port Expansion

Ports have been built or expanded in a number of countries to cater to increasing maritime trade in the 21st century. Port expansion is associated with economic and environmental impacts on the local and regional scales, and these impacts can be studied using remote sensing. The present study presents new results from multi-source remote sensing monitoring of the Ajmr Port expansion. An analysis of land use and vegetation coverage at the port is used to monitor the impact of port construction on the local ecology, while changes in roads, buildings, and lights are used to monitor the economic impact. The results show that: (1) After nine years of expansion, the port area has gradually expanded from the central to the southern coastal area, with an increase of 21.68 hectares during the expansion period. After the expansion, the area of builidings and construction in the study area increased significantly, while the area of water and green areas decreased significantly, indicating that the port construction changed the land use structure of the area. (2) From the perspective of vegetation coverage, the vegetation coverage within 5 km from the port is in good condition. After 9 years, the vegetation coverage in the region between 0.6 and 1 increased from 43.71% to 44.25%, reflecting the higher overall greening level in the region. (3) By analyzing the increase in roads and buildings, it can be seen that the port’s comprehensive transportation capacity has improved, the population of the region has increased significantly. As the scale of construction has been continuously expanded , the prosperity as increased. (4) By analyzing the changes in the light index, the light data from the northeast to the southwest in the region is very obvious, and it is clearly located along the coast, indicating that the economic development of the coastal zone is faster than other regions, and the coastal region has promoted the development of the inland region.

Download Full-text

Role of a Mine in Changing Its Surroundings—Land Use and Land Cover and Impact on the Natural Environment in Barapukuria, Bangladesh

Sustainability ◽

10.3390/su132413602 ◽

2021 ◽

Vol 13 (24) ◽

pp. 13602

Author(s):

Hossain Mohammad Arifeen ◽

Md. Shahariar Chowdhury ◽

Haoran Zhang ◽

Tanita Suepa ◽

Nowshad Amin ◽

...

Keyword(s):

Remote Sensing ◽

Land Use ◽

Information System ◽

Land Cover ◽

Geographical Information System ◽

Agricultural Land ◽

Research Work ◽

Geographical Information ◽

Landsat 8 ◽

The Impact

Land use and land cover (LULC) change is considered among the most discussed issues associated with development nowadays. It is necessary to provide factual and up-to-date information to policymakers to fulfil the increasing population’s food, work, and habitation needs while ensuring environmental sustainability. Geographical Information System (GIS) and Remote sensing can perform such work adequately. This study aims to assess land use and land cover changes concerning the Barapukuria coal mine and its adjacent areas in Bangladesh by applying remote sensing and GIS (geographical information system) techniques. This research work used time-series satellite images from the Landsat 7 ETM+ satellite between 1999 and 2009 and the Landsat 8 OLI/TIRS satellite for 2019. Supervised classification maximum likelihood classifier matrix was implemented using ERDAS Imagine 2018. The images were categorised into four definite classes: settlement, agricultural land, forest land, and waterbody. Analytical results clearly indicated that settlements and agricultural land had increasing and decreasing trends over the past 20 years, respectively. Settlements increased from 22% to 34% between 1999 and 2019. However, agricultural land reduced from 69% to 59% in the same period. Settlements grew by more than 50% during this period. The research had an overall accuracy of 70%, while the kappa coefficient was more than 0.60. There were land subsidence issues because of mining activities, leading to 1.003 km2 area being depressed and 1500 houses cracked. This research depicts the present LULC scenario and the impact of the coalfield area. It is expected to reduce the burden on policymakers to prepare a proper and effective mines development policy in Bangladesh and meet sustainable development goal (SDG) 15 (Life on land).

Download Full-text

Simulating the Impact of Urban Surface Evapotranspiration on the Urban Heat Island Effect Using the Modified RS-PM Model: A Case Study of Xuzhou, China

Remote Sensing ◽

10.3390/rs12030578 ◽

2020 ◽

Vol 12 (3) ◽

pp. 578

Author(s):

Yuchen Wang ◽

Yu Zhang ◽

Nan Ding ◽

Kai Qin ◽

Xiaoyan Yang

Keyword(s):

Remote Sensing ◽

Urban Heat Island ◽

Land Surface ◽

Estimation Method ◽

Bare Soil ◽

Urban Surface ◽

Landsat 8 ◽

Heat Island ◽

Urban Heat ◽

The Impact

As an important energy absorption process in the Earth’s surface energy balance, evapotranspiration (ET) from vegetation and bare soil plays an important role in regulating the environmental temperatures. However, little research has been done to explore the cooling effect of ET on the urban heat island (UHI) due to the lack of appropriate remote-sensing-based estimation models for complex urban surface. Here, we apply the modified remote sensing Penman–Monteith (RS-PM) model (also known as the urban RS-PM model), which has provided a new regional ET estimation method with the better accuracy for the urban complex underlying surface. Focusing on the city of Xuzhou in China, ET and land surface temperature (LST) were inversed by using 10 Landsat 8 images during 2014–2018. The impact of ET on LST was then analyzed and quantified through statistical and spatial analyses. The results indicate that: (1) The alleviating effect of ET on the UHI was stronger during the warmest months of the year (May–October) but not during the colder months (November–March); (2) ET had the most significant alleviating effect on the UHI effect in those regions with the highest ET intensities; and (3) in regions with high ET intensities and their surrounding areas (within a radius of 150 m), variation in ET was a key factor for UHI regulation; a 10 W·m−2 increase in ET equated to 0.56 K decrease in LST. These findings provide a new perspective for the improvement of urban thermal comfort, which can be applied to urban management, planning, and natural design.

Download Full-text