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Radiometric calibration is a method that estimates the reflection of the target from the measured input radiation. The purpose of this study is to radiometrically calibrate three spectral bands of Sentinel-2A, including green, red and infrared. For this purpose, Landsat-8 OLI data are used. Because they have bands with the same wavelength range and they have the same structure. As a result, Landsat-8 OLI is appropriate for relative radiometric calibration.

The method used in this study is radiometric calibration uncorrected data from a sensor with corrected data from another sensor. Also, another aim of this study is a comparison between radiometric correction data and data that, in addition to radiometric correction, has been sharpened with panchromatic data. In this method, both of them have been used for radiometric calibration. Calibration coefficients have been obtained using the first-order polynomial equation.

This study showed that the corrected data has more valid answers than corrected and sharpened data. This method studied three land-cover types, including soil, water and vegetation, which it obtained the most accurate coefficients of calibration for soil class because R-square in all three bands was above 88%, and the root mean square error in all three bands was below 0.01. In the case of water and vegetation classes, only results of red and infrared bands were suitable.

For validating this method, the radiometric correction module of SNAP software was used. According to the results, the coefficient of radiometric calibration of the Landsat-8 sensor was very close to the coefficients obtained from the corrected data by SNAP.

This paper aims to give an oversight of what is being done by researchers in GIS and remote sensing (field) to explore minerals. The main objective of this review is to explore how GIS and remote sensing have been beneficial in identifying mineral deposits for easier and cost-effective mining.

The approach of this research used Web of Science to generate a database of published articles on the application of GIS and remote sensing techniques for mineral exploration. The literature was further digested, noting the main findings, adopted method, illustration and research scales.

When applied alone, each technique seems effective, but it is important to know that combining different methods is more effective in identifying ore deposits.

This paper also examined and provided possible solutions to both current and future perspective issues relating to the application of GIS and remote sensing to mineral exploration. The authors believe that the conclusions and recommendations drawn from case studies and literature review will be of great importance to geoscientists and policymakers.

Deepor Beel is one of the Ramsar Site and a wetland of great biodiversity, situated in the south-western part of Guwahati, Assam. With urban development at its forefront city of Guwahati, Deepor Beel is under constant threat. The study aims to calculate the lake water volume from the water surface area and the underwater terrain data using a triangulated irregular network (TIN) volume model.

The lake water surface boundaries for each year were combined with field-observed water level data to generate a description of the underwater terrain. Time series LANDSAT images of 2001, 2011 and 2019 were used to extract the modified normalized difference water index (MNDWI) in GIS domain.

The MNDWI was 0.462 in 2001 which reduced to 0.240 in 2019. This shows that the lake water storage capacity shrank in the last 2 decades. This leads to a major problem, i.e. the storage capacity of the lake has been declining gradually from 20.95 million m³ in 2001 to 16.73 million m³ in 2011 and further declined to 15.35 million m³ in 2019. The fast decline in lake water volume is a serious concern in the age of rapid urbanization of big cities like Guwahati.

None of the studies have been done previously to analyze the decline in the volume of Deepor Beel lake. Therefore, this study will provide useful insights in the water resource management and the conservation of Deepor Beel lake.

Conservation of green space is crucial to the sustainable urban development of China. Nanjing is a central city in the Yangtze River Delta cluster in eastern China. Owing to urbanization, the green spaces in this city have been affected significantly in terms of their scale and structure. Assessing such changes can provide a basis for environmental protection measures and sustainable development. Using Landsat remote-sensing image data from 1998 and 2007, we constructed a distribution map of the patches of green spaces in Nanjing, and analyzed and assessed the changes in scale and spatial layout of the green spaces using various landscape metrics including CA, PLAND, PD, MPS, LPI, NP, PD, TE, ED, MPI, and LSI. Coinciding with a sharp increase in urban population, the area of green spaces in Nanjing decreased by 27.06% between 1998 and 2007. The patches of green space increased by 39%, and the average area per patch decreased by about 47.52%. Green space patches were found to be unevenly distributed among the districts of Nanjing. In urban areas, significant numbers of such patches were found primarily in various types of parks, while in suburban areas, they were concentrated mainly in the hilly forestlands. Green spaces exhibited tendencies towards fragmentation, miniaturization, and discretization.

The purpose of this study is to analyze the horizontal expansion of Burayu Town between 1990 and 2020. The study typically acts as a baseline for integrated spatial planning in small- and medium-sized towns, which will help to plan sustainable utilization of land.

Landsat5-TM, Landsat7 ETM+, Landsat5 TM and Landsat8 OLI were used in the study, along with other auxiliary data. The LULC map classifications were generated using the Random Forest Package from the Comprehensive R Archive Network. Post-classification, spatial metrics, and per capita land consumption rate were used to understand the manner and rate of expansion of Burayu Town. Focus group discussions and key informant interviews were also used to validate land use classes through triangulation.

The study found that the built-up area was the most dynamic LULC category (85.1%) as it increased by over 4,000 ha between 1990 and 2020. Furthermore, population increase did not result in density increase as per capita land consumption increased from 0.024 to 0.040 during the same period.

As a result of financial limitations, there were no high-resolution satellite images available, making it challenging to pinpoint the truth as it is on the ground. Including senior citizens in the study region allowed this study to overcome these restrictions and detect every type of land use and cover.

Data on urban growth are useful for planning land uses, estimating growth rates and advising the government on how best to use land. This can be achieved by monitoring and reviewing development plans using satellite imaging data and GIS tools.

The use of Random Forest for image classification and the employment of local knowledge to validate the accuracy of land cover classification is a novel approach to properly customize remote sensing applications.

The purpose of this paper is to evaluate the potential impact of human-induced intervention on hydrological regimes of Gomti river, one of the important tributaries of the Ganga Alluvial Plain in India aiming at an overall assessment of the status quo.

The research methodology includes following four components: study of basin morphology, sub-surface geology and sediments profile of Gomti river; a comparison of LANDSAT satellite data of 1978 and IRS-1C/LISS-III satellite data of 2008 to study the changes occurring in the built-up area, forest and water bodies of the basin; study of flow patterns in different stretches of river Gomti from 1978 to 2012; and water quality assessment at different sites from origin of the river to its confluence in the Ganges.

The paper shows that over the years, the water source in the tributaries feeding the river Gomti has shrunk, reducing the flow in the river. A steady increase in developed land area due to rapid urban sprawl has occurred in recent decades, due to which forest cover and wetlands are decreasing, the river and floodplains are getting fragmented, the hydromorphology changed considerably and several tributaries are getting dried as a result of indiscriminate exploitation of groundwater. There is no flow in the initial 57 km stretch of the river with wide encroachment in active floodplains. Groundwater over-extraction to meet the demands of increasing population and intensive agriculture has led to reduction in base-flows and in some reaches even negative. Extensive land-use changes in the Gomti river basin (GRB) severely impact the river and floodplain connectivity, the impacts are already evident as several tributaries are getting dried during the non-monsoon months.

The information provided by the paper for GRB is significant for the understanding of the basin and to formulate integrated management and development plan of the basin. Significant changes have taken place in the GRB over the recent past and are still continuing. Because of the chosen river basin and the site-specific research approach, the research results may lack generalization. However, it provides a general framework of analysis which could be applied to other regions.

River channels with their floodplains and adjoining ecosystems have to be addressed as interconnected ecological entity in a holistic way. This requires comprehensive observations of the river systems and catchment characteristics using long-term data. The paper could be used as the starting point in the development of management and development strategies for the basin.

River and its floodplain offer multiple ecosystem services and deserve an integrated approach for their conservation and restoration. Conservation and protection of ecologically intact river-floodplain systems is extremely important and urgently needs integrated planning and management. This paper has adopted a integrated approach to study the integrity of river ecosystems and the potential pressures on them.

Over the past century, the rate of sea level rise (SLR) has increased more than twice the average historical rate and the US Environmental Protection Agency estimates that by 2100 the sea level will increase nearly two feet in many coastal areas. Property owners and municipalities typically respond to SLR by constructing seawalls and similar structures to protect shoreline property (a practice known as “armoring”). The degree to which SLR and armoring threaten key coastal habitats has not been well studied, however. This study, aims to develop an inundation model on behalf of Stratus Consulting to examine anticipated habitat changes in coastal Ocean County, New Jersey.

The model used a geographical information system to map predicted changes in coastal habitats under two alternative SLR scenarios and six different shoreline armoring scenarios. The paper then used information from local experts and the scientific literature to predict changes in the relative abundances of fish and bird species under the different scenarios.

Under all scenarios, the model predicted substantial declines in the areal extent of Spartina marshes and in the annual production of finfish and shrimp. Declines in these marsh‐dependent species would have significant impacts on commercial and recreational fisheries. The study also predicted substantial declines in bird species such as songbirds and dabbling ducks.

The results of the study can help local stakeholders and decision‐makers plan responses to SLR. Conventional armoring responses could result in substantial and irreversible losses of coastal habitats and the species dependent on these habitats.

The purpose of this study is to evaluate the potential of the DMC satellite data as suitable alternative to Landsat‐7 ETM+ satellite data sets in view of the aging conditions, the failure of the Scan Line Corrector (SLC) and resulting scan line anomaly within the Landsat‐7 ETM+ data sets.

The DMC and Landsat‐7 ETM+ satellite data were compared by obtaining quantitative parameters such as; spatial, geometric, spectral, radiometric properties from coincident date images of the two satellite sensors, while inter‐relationship between DMC and Landsat‐7 ETM+ satellite data were established by deriving sensor inter‐calibration from linear regression equation.

The result shows that the performances of UK‐DMC match well with Landsat‐7 ETM+ and the accuracy of the UK‐DMC with respect to spatial, geometric properties. The frequency of DN distribution in each waveband for the two sensors and a pair‐wise relationship between the DN of selected targets was established using linear regression equation with coefficient of determination (R²) values that range from 0.92 to 0.95. These are adequate for data integration of the UK‐DMC and Landsat‐7 ETM+ sensors, and indicate that UK‐DMC can be used as a replacement for Landsat‐7 ETM+ and can provide a suitable platform for multi‐temporal and multi‐sensor approach that is required for the study of environmental dynamics.

The challenge in this study is that information on DMC sensor calibration and radiometric parameters such as time‐dependent change in the data derived from pre‐flight measurements, in‐flight calibration and ground‐based calibration data were not available at the time of this study. Therefore, absolute radiometric correction of converting the digital number (DN) recorded by the sensor to spectral radiance detected by the sensor using sensor‐specific calibration parameters was not possible. The suitable alternative is to use spectrally invariant targets for relative radiometric correction of DN to DN pair wise pixel technique and selecting similar targets on the images.

This study shows that a suitable platform for multi‐temporal and multi‐sensor approach that is required for the study of environmental dynamics can be provided.

The issue of climate change was mentioned in this manuscript because satellite sensors that were used previously for climate change (multi‐disciplinary approach) does not have the temporal dynamics of daily coverage (temporal) and spatial resolution like the DMC satellites while there is usually a trade‐off between temporal and spatial resolution. The DMC satellites have got the exceptional capability of daily temporal and medium spatial resolution that can be suitable for monitoring climate change. That is why in this study investigation was carried out on the unique properties of the DMC satellites by making comparative assessments Landsat‐7 ETM+.

The originality/value of this paper lies on the fact that; for the first time the DMC satellite data are being compared with Landsat‐7 ETM+ because of similar characteristics in terms of wavebands (near infrared, red and green) and spatial resolution (Landsat‐7 ETM+: 30 m, DMC: 32 m).

This study aims to prove that land-use change plays a role in the occurrence of hydro-meteorological disasters in Central Java, especially in relation to its upstream and downstream.

The paper presents empirical findings from quantitative research using a spatial analysis and descriptive analysis.

The upstream and downstream area of Central Java is categorized as a rapid development area that results in changes in land use and land cover. The findings showed that there was an increasing number of hydrometeorological disasters such as floods and landslides as the impact of land-use change and rainfall conditions.

Analysis of the relationship between rainfall and disaster events with more technical and specific analysis could be done in the further research.

In this study, more analysis in the context of river basin systems including upstream and downstream in different periods to examine the linkage between them have been considered and incorporated.