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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).

Satellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of satellite data with a relatively low spatial resolution has not yet made it possible to determine the satellite indices free of disturbing landscape elements such as mountains, forests and lakes.

In this context, the Normalized Difference Vegetation Index (NDVI) was used based on both Moderate Resolution Imaging Spectroradiometer (MODIS) (250 × 250 m) and high-resolution Landsat 5/8 (30 × 30 m) images to investigate the effect of a higher spatial resolution of satellite-based weather index contracts for hedging winter wheat yields. For three farms in north-east Germany, insurance contracts both at field and farm level were designed.

The results indicate that with an increasing spatial resolution of satellite data, the basis risk of satellite-based weather index insurance contracts can be reduced. However, the results also show that the design of NDVI-based insurance contracts at farm level also reduces the basis risk compared to field level. The study shows that higher-resolution satellite data are advantageous, whereas satellite indices at field level do not reduce the basis risk.

To the best of the author’s knowledge, the effect of increasing spatial resolution of satellite images for satellite-based weather index insurance is investigated for the first time at the field level compared to the farm level.

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.

The selection of wavelength region and number of bands is a research problem for remote sensing experts for utilization of data provided by the sensor system. The present study proposes to make an evaluation for optimum band selection and classification accuracy.

The entropy, brightness value overlap index (BVOI), optimum index factor (OIF) and spectral separability analysis, i.e. Euclidean distance (ED), divergence, transformed divergence (TD) and Jefferies‐Matusita (JM) distance and accuracy of MLC classification were carried out. For the present study Terra ASTER, Landsat ETM⁺ and IRS 1D LISS III dataset has been used. The first three methods were for the spectral evaluation of the three satellite data used and for determination of information content, variance and spectral overlap among the classes present in the natural and man‐made landscape. The fourth method is for selection of spectral band combinations with highest separability of classes using divergence matrices. These band combinations are selected for the classification and subsequent accuracy assessment.

The OIF values are clearly indicating that the performance of ASTER data is the best, having the lowest correlation between the bands; hence the separability of the feature is also highest, while LISS III have shown high correlation between the bands, with the poor separability of the features. Landsat ETM⁺ data are in between these two sensors, better than LISS III but poorer than ASTER. The BVOI outputs of the three datasets of man‐made landscape show that band 3 of ASTER has the least overlap of the classes, followed by band 4 of ETM⁺. Very high overlap of the classes has been found in LISS III data. It has been found from spectral separability analysis of all the three datasets for the man‐made landscape that ASTER data with band combination of spectral bands 123468 contains the highest value of all the measures of spectral separability, i.e. ED (291.72), divergence (2,133.37), TD (2,000.00) and JM distance (1,414.10).

It can be inferred from the present study that spectral resolution plays a very important role in discrimination of vegetation features. ASTER data which are with the highest number of the bands amongst the satellite data used had shown highest classification accuracy, while LISS III data with lowest number of bands had shown lowest accuracy, and Landsat ETM⁺ stood in between the two sensors.

It is important to evaluate the sensor systems and their spectral regions for discrimination of vegetation features. The number of bands present in a particular sensor and the spectral regions used in it are some of the crucial factors which decide the usefulness of the data for different applications, including vegetation‐related studies. The selection of spectral wavelength region, i.e. spectral bands and the sensor system, presents the research problem for remote sensing experts to suggest the best spectral regions and satellite sensor for the discrimination of the vegetation features in different landscapes, namely man‐made and natural.

In the present study all the three datasets are extensively examined and tested for their vegetation discrimination capabilities using well‐established methodologies. All the parameters applied on the datasets revealed that spectral resolution definitely plays a role in the performance of the data as far as discrimination of features is concerned both in natural and man‐made landscape with desirable accuracy.

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.

This paper aims to develope an integrated image processing method to investigate the spatiotemporal dynamics of Phragmites invasion in the Detroit River International Wildlife Refuge on the basis of publically available sources.

This new approach integrates the standard time-series analysis of Landsat images with USDA National Agriculture Imagery Program (NAIP) imagery and USGS Digital Orthophoto Quarter Quads (DOQQ) datasets, which are either classified or manually interpreted with the aid of ground control points. Three different types of spatiotemporal dimensions are designed to test this integrated time-series image analysis method: the selected sites and selected time-points with high spatial resolution and sufficient validation data points, the intermediate time-series with continued yearly images and periodical validation data, and the long time-series with periodical images without enough validation data. The support vector machine (SVM) method was used to classify the Landast TM sequence images to detect the Phragmites invasion.

The habitat map produced by NAIP images and field collection data shows that the total Phragmites area of DRIWR in 2010 is 4221.87 acres without treatment areas and similar with the removed non-vegetation method. It is confirmed that the pre-classification method can obtain more accurate results.

The test results show that the Landsat-5 data can be used for long-term environmental management and monitoring of Phragmites invasion and can achieve rehabilitation of invasion areas.

Urban growth has increasingly drawn much attention of erudite scholars due to its central role in achieving a sustainable urbanization. Despite this awareness, studies on urban growth have continued to dwell on the traditional method of presenting geographical Information, which has proved to be slow and inadequate. The purpose of this paper is to adopt a Geographical Information System (GIS) in assessing the spatial pattern and the physical planning problems associated with the expansion of Ore township between 1964 and 2002. Moreover, the study tends to serve as baseline study for subsequent studies on medium‐sized and nodal towns.

The study utilized data from secondary sources such as Landsat‐TM, February, 1986, Landsat ETM+, December, 2002; Topographical map of Ore 1964 and population census data of Ore 1991. The study employed ILWIS Academic 3.2 GISsoftware to process the imageries. Coordinates extracted from the topographical map in UTM were used to georeference the enhanced and filtered images upon which supervised classification was performed, followed by error matrix operation and ground truthing to ensure high level accuracy. This results in six domains, namely, built‐up, forest reserve, farmland, secondary forest roads and water bodies, which were analyzed on temporal basis. Predictive model was used.

The study found that Ore township occupied an area of 1.2 km² in 1964, expanded to 11.3 km² in 1986 and 13.2 km² in 2002 respectively. The prediction showed a possible expansion of 55.33 km² by 2027. The results further revealed physical planning problems generated by these expansions – housing, inadequate waste disposal system, encroachment into agricultural lands, inadequate health facilities and poor drainage system. From field survey, 62 percent of 125 residential housing units sampled disposed refuse themselves, while 20 percent have no organized refuse collection and 18 percent dispose through other means. This suggests the vulnerability of inhabitants to health risks and environment problems.

Urban growth data are useful in evaluating environmental impacts, delineating growth boundaries, developing land use zoning plans and estimating the expansion rate of a town to advise the government towards proper planning and distribution of utilities. These can be achieved through the adoption of GIS approaches to information gathering and analysis for regular monitoring and evaluation of development plans. Although it is capital intensive, it is worthwhile.

The use of GIS and remotely‐sensed data integrated with population census data and topographical map data has demonstrated the capability inherent in the new tools, GIS and remote sensing, to generate to some extent base line data for the town planners, in order to proactively channel the urban development in an appropriate direction, particularly the medium‐sized and nodal towns that are somewhat neglected.

This study aims to determine shoreline change statistics and net erosion and accretion, along the Kuakata Coast, a magnificent sea beach on Bangladesh’s southernmost point.

The research follows a three stages way to achieve the target. First, this study has used the geographic information system (GIS) and remote sensing (RS) to detect the temporal observation of shoreline change from the year 1991 to 2021 through satellite data. Then, the digital shoreline analysis system (DSAS) has also been explored. What is more, a prediction has been done for 2041 on shoreline shifting scenario. The shoreline displacement measurement was primarily separated into three analytical zones. Several statistical parameters, including Net Shoreline Movement (NSM), Shoreline Change Envelope (SCE), End Point Rate (EPR) and Linear Regression Rate (LRR) were calculated in the DSAS to quantify the rates of coastline movement with regard to erosion and deposition.

EPR and LRR techniques revealed that the coastline is undergoing a shift of landward (erosion) by a median rate of 3.15 m/yr and 3.17 m/yr, respectively, from 1991 to 2021, 2.85 km² of land was lost. Naval and climatic influences are the key reasons for this variation. This study identifies the locations of a significantly eroded zone in Kuakata from 1991 to 2021. It highlights the places that require special consideration while creating a zoning plan or other structural design.

This research demonstrates the spatio-temporal pattern of the shoreline location of the Kuakata beach, which would be advantageous for the region’s shore management and planning due to the impacts on the fishing industry, recreation and resource extraction. Moreover, the present research will be supportive of shoreline vulnerability. Hence, this study will suggest to the local coastal managers and decision-makers for particularizing the coastal management plans in Kuakata coast zone.

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 paper is to analyze the characteristics of spatio-temporal dynamics and the evolution of land use change is essential for understanding and assessing the status and transition of ecosystems. Such analysis, when applied to Horqin sandy land, can also provide basic information for appropriate decision-making.

By integrating long time series Landsat imageries and geographic information system (GIS) technology, this paper explored the spatio-temporal dynamics and evolution-induced land use change of the largest sandy land in China from 1983 to 2016. Accurate and consistent land use information and land use change information was first extracted by using the maximum likelihood classifier and the post-classification change detection method, respectively. The spatio-temporal dynamics and evolution were then analyzed using three kinds of index models: the dynamic degree model to analyze the change of regional land resources, the dynamic change transfer matrix and flow direction rate to analyze the change direction, and the barycenter transfer model to analyze the spatial pattern of land use change.

The results indicated that land use in Horqin sandy land during the study period changed dramatically. Vegetation and sandy land showed fluctuating changes, cropland and construction land steadily increased, water body decreased continuously, and the spatial distribution patterns of land use were generally unbalanced. Vegetation, sandy land and cropland were transferred frequently. The amount of vegetation loss was the largest. Water body loss was 473.6 km², which accounted for 41.7 per cent of the total water body. The loss amount of construction land was only 1.0 km². Considerable differences were noted in the rate of gravity center migration among the land use types in different periods, and the overall rate of construction land migration was the smallest. Moreover, the gravity center migration rates of the water body and sandy land were relatively high and were related to the fragile ecological environment of Horqin sandy land.

The results not only confirmed the applicability and effectiveness of the combined method of remote sensing and GIS technology but also revealed notable spatio-temporal dynamics and evolution-induced land use change throughout the different time periods (1983-1990, 1990-2000, 2000-2010, 2010-2014, 2014-2016 and 1983-2016).