Journal articles on the topic 'Landsat satellites Remote sensing'
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1
Lodwick, G. D., and S. H. Paine. "SATELLITE REMOTE SENSING IN SURVEYING PRESENT OPPORTUNITIES, FUTURE POSSIBILITIES." Canadian Surveyor 40, no. 3 (September 1986): 315–26. http://dx.doi.org/10.1139/tcs-1986-0025.
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Of all the areas of the earth sciences affected by satellite remote sensing, the surveying profession has been one of the last to take advantage of its unique features. This is due in part to: resolution limitations of Landsat 1, 2 and 3, difficulties in registration and positioning of the imagery, technical constraints in handling vast quantities of digital data, and the excellent methods currently available for the production of cartographic products. Nevertheless, satellite remote sensing has now emerged as a complementary procedure to many existing techniques utilized in surveying and mapping. Already, Landsat is being used for topographic mapping, hydrographic surveying and resource mapping purposes. However, with the improved resolution of Landsat 4, the potential of stereoscopic coverage with the SPOT satellites and present developments in computer processing and data manipulation, satellite remote sensing in the next decade will emerge as an indispensable tool for mapping and cartography.
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Arifjanov, Aybek, Shamshodbek Akmalov, Shakhzod Shodiev, and Abdukarim Haitov. "Discussion of different Remote sensing satellite possibilities for scientifical Earth observations." E3S Web of Conferences 264 (2021): 04007. http://dx.doi.org/10.1051/e3sconf/202126404007.
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More than 1,000 satellites are launched into space, and they differ in their functions, rotation orbits, resolution, and other properties. Scientists divide the satellites into low-resolution, medium-resolution, high-resolution, and very high-resolution satellites by their properties. Now, the biggest challenge facing scientists is to use some of these different resolution images in their field. To get the expected result, it is very important to analyze the image that needs an which gives more accurate results. Therefore, the main attention of this article is aimed to find the answer to these problems. In this article 3 satellite images which have different resolution are analyzed. The possibility of middle-resolution images of MODIS, high-resolution images of Landsat, and very high-resolution images of WorldView-2 (WV-2) satellites using GIS are analyzed. A research area was the Syrdarya region, and downloaded different images of satellites of this area and compared with using e Cognition. According to the results, a more accurate satellite image for irrigation sets information is WorldView-2 images. In comparison analysis, it shows more accurate properties than other satellite images. As irrigation sets are small objects for the analysis, very high spatial resolution satellite images are important. Water discharge and surface change happen very fast; thus, it requires daily monitoring of the condition. And in this case, the temporal resolution of the MODIS and Landsat is 16 day, and it is a too long period.
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Ezzell, Carol. "Landsat remote sensing project short of funds for satellites." Nature 325, no. 6101 (January 1987): 187. http://dx.doi.org/10.1038/325187a0.
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Bedell, Richard. "Remote Sensing in Mineral Exploration." SEG Discovery, no. 58 (July 1, 2004): 1–14. http://dx.doi.org/10.5382/segnews.2004-58.fea.
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ABSTRACT The proliferation of remote sensing platforms has resulted in unprecedented opportunities for ore deposit vectoring. Importantly, remote sensing technology is now beyond the vague identifıcation of alteration, and can accurately map specifıc minerals and directly contribute to the understanding of ore systems. Remote sensing is making discoveries of new alteration zones within classic and previously well mapped ore systems, as well as outlining their geometry and mineralogy. Confıning this review to the geologically important reflected-light remote sensing systems, there are four main categories of sensors readily available to economic geologists, including the following: (1) submeter resolution panchromatic satellites that offer little spectral information but provide base maps; (2) multispectral Landsat satellites that can map iron and clay alteration; (3) the new ASTER satellite that can map important alteration groups and some specifıc minerals; and (4) hyperspectral airborne scanners that can provide maps of specifıc mineral species important to detailed alteration mapping. At the core of comprehending this plethora of technology is the difference between spectral and spatial resolution. This review will provide an understanding of the more fundamental aspects of remote sensing systems that will help fıeld geologists to interact better with and leverage this rapidly evolving technology.
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Mycke-Dominko, Małgorzata. "The Remote Sensing Method of Forest Fire Danger Rating Categorization." Miscellanea Geographica 11, no. 1 (December 1, 2004): 359–62. http://dx.doi.org/10.2478/mgrsd-2004-0038.
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Abstract The article presents the use of satellite images in the determination of forest fire danger rating categories. The assessment was carried out based on images from the LANDSAT TM, IKONOS and NOAA satellites, with the finding that the LANDSAT TM images are the most useful. A new solution proposed is to make forest fire danger rating categories refer to forest ranger sub-districts, what gives the forest service greater control over forest fire prevention activities. Forest fire danger assessment was done taking into account remote sensing indices such as the NDVI, TNDVI, and IHT, as well by the analysis of the spatial distribution and the number of fires in the previous six years. In accordance with the Polish State Forest Classification System, three classes were specified: 1 – high fire danger, 2 – moderate fire danger, 3 – low fire danger.
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Orlov, P. Yu, M. A. Boyarchuk, I. G. Zhurkin, and V. V. Nekrasov. "Development of geo-information technique and experimental studies on cross-calibration of Kanopus-V spacecraft series’ RSE sensors." Geodesy and Cartography 966, no. 12 (January 20, 2021): 31–42. http://dx.doi.org/10.22389/0016-7126-2020-966-12-31-42.
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Cross-calibration of the Earth’s remote sensing payload is an addition to the traditionally used flight calibration. It consists of homogeneous terrain regions` image acquiring with a calibrated and reference apparatus and comparing the measured values of the spectral radiance. When selecting references for cross-calibration, the main requirements are the proximity of the spatial resolution and spectral channels of the satellite payload, as well as the observation conditions. Remote sensing spacecrafts Sentinel-2A / 2B and Landsat 8 were selected asreferences. An algorithm was developed to search for intersections of Earth remote sensing satellites ground tracks, which enables finding the parts of the Earth’s surface observed from satellites involved in calibration at a time difference not exceeding 30 minutes. Prediction of satellite paths is carried out using the analytical propagation model SGP4, and two-line element sets of orbital parameters (TLE) taken from open sources. Using the obtained intersection points of propagated ground tracks, the Kanopus-V grouping survey was planned and the corresponding materials by foreign systems were obtained. Basing on them, spectral radiance values obtained by calibrating satellites were compared showing the result of less than 10 % discrepancy.
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Laidler, Gita J., and Paul Treitz. "Biophysical remote sensing of arctic environments." Progress in Physical Geography: Earth and Environment 27, no. 1 (March 2003): 44–68. http://dx.doi.org/10.1191/0309133303pp358ra.
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Various remote sensing studies have been conducted to investigate methods and applications of vegetation mapping and analysis in arctic environments. The general purpose of these studies is to extract information on the spatial and temporal distribution of vegetation as required for tundra ecosystem and climate change studies. Because of the recent emphasis on understanding natural systems at large spatial scales, there has been an increasing interest in deriving biophysical variables from satellite data. Satellite remote sensing offers potential for extrapolating, or ‘scaling up’ biophysical measures derived from local sites, to landscape and even regional scales. The most common investigations include mapping spatial vegetation patterns or assessing biophysical tundra characteristics, using medium resolution satellite data. For instance, Landsat TM data have been shown to be useful for broad vegetation mapping and analysis, but not accurately representative of smaller vegetation communities or local spatial variation. It is anticipated, that high spatial resolution remote sensing data, now available from commercial remote sensing satellites, will provide the necessary sampling scale to link field data to remotely sensed reflectance data. As a result, it is expected that these data will improve the representation of biophysical variables over sparsely vegetated regions of the Arctic.
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Silva, Isadora Taborda, Jéssica Rabito Chaves, Helen Rezende Figueiredo, Bruno Silva Ferreira, César Claudio Cáceres Encina, Dhonatan Diego Pessi, Normandes Matos Silva, Eliane Guaraldo, and Antonio Conceição Paranhos Filho. "Identification of Continental Wetlands Using Different Orbital Remote Sensors." Terr Plural 15 (2021): 1–25. http://dx.doi.org/10.5212/terraplural.v.15.2115518.001.
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This paper evaluates the potential of false-color composite images, from 3 different remote sensing satellites, for the identification of continental wetlands. Landsat 8, Sentinel-2 and CBERS-4 scenes from three different Ramsar sites (i.e., sites designated to be of international importance) two sites located within the Mato-Grossense Pantanal and one within the Sul-mato-grossense were used for analyses. For each site, images from both the dry and rainy seasons were analyzed using Near-Infrared (NIR), Shortwave Infrared (SWIR), and visible (VIS) bands. The results show that false-color composite images from both the Landsat 8 and the Sentinel-2 satellites, with both SWIR 2-NIR-BLUE and NIR-SWIR-RED spectral band combinations, allow the identification of wetlands.
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Rodrigues, Jose Carlos Verle, Michael H. Cosh, E. Raymond Hunt, Gilberto J. de Moraes, Geovanny Barroso, William A. White, and Ronald Ochoa. "Tracking Red Palm Mite Damage in the Western Hemisphere Invasion with Landsat Remote Sensing Data." Insects 11, no. 9 (September 11, 2020): 627. http://dx.doi.org/10.3390/insects11090627.
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Red palm mites (Raoiella indica Hirst, Acari: Tenuipalpidae) were first observed in the western hemisphere on the islands and countries surrounding the Caribbean Sea, infesting the coconut palm (Cocos nucifera L.). Detection of invasive pests usually relies upon changes in vegetation properties as result of the pest activity. These changes may be visible in time series of satellite data records, such as Landsat satellites, which have been available with a 16-day repeat cycle at a spatial resolution of 30 m since 1982. Typical red palm mite infestations result in the yellowing of the lower leaves of the palm crown; remote sensing model simulations have indicated that this feature may be better detected using the green normalized difference vegetation index (GNDVI). Using the Google Earth Engine programming environment, a time series of Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus and Landsat 8 Operational Land Imager data was generated for plantations in northern and northeast Brazil, El Salvador, and Trinidad-Tobago. Considering the available studied plantations, there were little or no differences of GNDVI before and after the dates when red palm mites were first revealed at each location. A discussion of possible alternative approaches are discussed related to the limitations of the current satellite platforms.
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Fichtelmann, B., E. Borg, and E. Schwarz. "The Influence of the Time Equation on Remote Sensing Data Interpretation." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 28, 2015): 195–201. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-195-2015.
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The interpretation of optical Earth observation data (remote sensing data from satellites) requires knowledge of the exact geographic position of each pixel as well as the exact local acquisition time. But these parameters are not available in each case. If a satellite has a sun-synchronous orbit, equator crossing time (ECT) can be used to determine the local crossing time (LCT) and its corresponding solar zenith distance. Relation between local equator crossing time (LECT) and LCT is given by orbit geometry. The calculation is based on ECT of satellite. The method of actual ECT determination for different satellites on basis of the two-line-elements (TLE), available for their full lifetime period and with help of orbit prediction package is well known. For land surface temperature (LST) studies mean solar conditions are commonly used in the relation between ECT given in Coordinated Universal Time (UTC) and LECT given in hours, thus neglecting the difference between mean and real Sun time (MST, RST). Its difference is described by the equation of time (ET). Of particular importance is the variation of LECT during the year within about ±15 minutes. This is in each case the variation of LECT of a satellite, including satellites with stable orbit as LANDSAT (L8 around 10:05 a.m.) or ENVISAT (around 10:00 a.m.). In case of NOAA satellites the variation of LECT is overlaid by a long-term orbital drift. Ignatov et al. (2004) developed a method to describe the drift-based variation of LECT that can be viewed as a formal mathematical approximation of a periodic function with one or two Fourier terms. But, nevertheless, ET is not included in actual studies of LST. Our paper aims to demonstrate the possible influence of equation of time on simple examples of data interpretation, e.g. NDVI.
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Ballesteros, Rocío, Miguel Moreno, Fellype Barroso, Laura González-Gómez, and José Ortega. "Assessment of Maize Growth and Development with High- and Medium-Resolution Remote Sensing Products." Agronomy 11, no. 5 (May 10, 2021): 940. http://dx.doi.org/10.3390/agronomy11050940.
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The availability of a great amount of remote sensing data for precision agriculture purposes has set the question of which resolution and indices, derived from satellites or unmanned aerial vehicles (UAVs), offer the most accurate results to characterize vegetation. This study focused on assessing, comparing, and discussing the performances and limitations of satellite and UAV-based imagery in terms of canopy development, i.e., the leaf area index (LAI), and yield, i.e., the dry aboveground biomass (DAGB), for maize. Three commercial maize fields were studied over four seasons to obtain the LAI and DAGB. The normalized difference vegetation index (NDVI) and visible atmospherically resistant index (VARI) from satellite platforms (Landsat 5TM, 7 ETM+, 8OLI, and Sentinel 2A MSI) and the VARI and green canopy cover (GCC) from UAV imagery were compared. The remote sensing predictors in addition to the growing degree days (GDD) were assessed to estimate the LAI and DAGB using multilinear regression models (MRMs). For LAI estimation, better adjustments were obtained when predictors from the UAV platform were considered. The DAGB estimation revealed similar adjustments for both platforms, although the Landsat imagery offered slightly better adjustments. The results obtained in this study demonstrate the advantage of remote sensing platforms as a useful tool to estimate essential agronomic features.
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Fernández-Pacheco, V. M., C. A. López-Sánchez, E. Álvarez-Álvarez, M. J. Suárez López, L. García-Expósito, E. Antuña Yudego, and J. L. Carús-Candás. "Estimation of PM10 Distribution using Landsat5 and Landsat8 Remote Sensing." Proceedings 2, no. 23 (October 31, 2018): 1430. http://dx.doi.org/10.3390/proceedings2231430.
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Air pollution is one of the major environmental problems, especially in industrial and highly populated areas. Remote sensing image is a rich source of information with many uses. This paper is focused on estimation of air pollutants using Landsat-5 TM and Landsat-8 OLI satellite images. Particulate Matter with particle size less than 10 microns (PM10) is estimated for the study area of Principado de Asturias (Spain). When a satellite records the radiance of the surface received at sensor, does not represent the true radiance of the surface. A noise caused by Aerosol and Particulate Matters attenuate that radiance. In many applications of remote sensing, that noise called path radiance is removed during pre-processing. Instead, path radiance was used to estimate the PM10 concentration in the air. A relationship between the path radiance and PM10 measurements from ground stations has been established using Random Forest (RF) algorithm and a PM10 map was generated for the study area. The results show that PM10 estimation through satellite image is an efficient technique and it is suitable for local and regional studies.
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Calderón-Chaparro, Rafael Andrés, and German Vargas-Cuervo. "Determination of Hydrothermal Prospects in Paipa Geothermal Region (Boyacá, Colombia) Using Remote Sensing and Field Data." Earth Sciences Research Journal 23, no. 4 (October 1, 2019): 265–82. http://dx.doi.org/10.15446/esrj.v23n4.77810.
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Geothermal resources (e.g. hot springs) are found with the help of field techniques, such as geological, geochemistry and geophysical. These techniques in some occasions are difficult to apply because of the limit access to the research area, rising operational costs and constrained spatially the exploration areas. The thermal infrared (TIR) remote sensing is an important tool for the exploration of geothermal resources, due to the low cost and high efficiency in the study of large geographic areas. The aim of this study is to use thermal imagery of satellite remote sensing and combined with geological-geophysical data, for spatial determination of exploratory prospects of hot springs in the geothermal region of Paipa, Boyacá. The images used in this study are from satellites Landsat-7 ETM+, Landsat-8 OLI/TIRS, MODIS, ALOS-PALSAR and Pléiades. Also, field data is used, such as soil temperature, surface temperature, air temperature, relative humidity, atmospheric pressure and thermal imagery of surface geothermal manifestations. The Landsat thermal bands were radiometrically calibrated, then atmospherically and surface emissivity corrected, applying single channel and split window algorithms, for Landsat-7 ETM+ and Landsat-8 TIRS, respectively. The field data helped to correct the thermal bands. And the soil temperature data are used to create a subsurface temperature map at 1-meter depth. Once primary and secondary data is had, in a geographic information system (GIS) is implemented an unweighted spatial model, which use four input indicators (satellite temperature index, soil temperature index, structural lineaments index and iso-resistivity index) to determine the areas with higher probability to find geothermal fluids. Six prospects are highlighted for hydrothermal fluid extraction, in which two of them are already known. Results allow to concluded that thermal remote sensing are useful to map geothermal anomalies in the Paipa region, and by using these anomalies plus geological-geophysical information is possible to determine exact exploration areas.
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Zhao, Qiang, Le Yu, Zhenrong Du, Dailiang Peng, Pengyu Hao, Yongguang Zhang, and Peng Gong. "An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends." Remote Sensing 14, no. 8 (April 13, 2022): 1863. http://dx.doi.org/10.3390/rs14081863.
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As satellite observation technology develops and the number of Earth observation (EO) satellites increases, satellite observations have become essential to developments in the understanding of the Earth and its environment. However, the current impacts to the remote sensing community of different EO satellite data and possible future trends of EO satellite data applications have not been systematically examined. In this paper, we review the impacts of and future trends in the use of EO satellite data based on an analysis of data from 15 EO satellites whose data are widely used. Articles that reference EO satellite missions included in the Web of Science core collection for 2020 were analyzed using scientometric analysis and meta-analysis. We found the following: (1) the number of publications and citations referencing EO satellites is increasing exponentially; however, the number of articles referencing AVHRR, SPOT, and TerraSAR is tending to decrease; (2) papers related to EO satellites are concentrated in a small number of journals: 43.79% of the articles that were reviewed were published in only 13 journals; and (3) remote sensing impact factor (RSIF), a new impact index, was constructed to measure the impacts of EO satellites and to predict future trends in applications of their data. Landsat, Sentinel, MODIS, Gaofen, and WorldView were found to be the most significant current EO satellite missions and MODIS data to have the widest range of applications. Over the next five years (2021–2025), it is expected that Sentinel will become the satellite mission with the greatest influence.
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Williams, Richard S. "Satellite Remote Sensing of Vatnajökull, Iceland." Annals of Glaciology 9 (1987): 127–35. http://dx.doi.org/10.3189/s0260305500000501.
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Iceland’s largest ice cap, Vatnajökull, has been the test site for a series of airborne and satellite remote-sensing studies since 1966. Various types of image data acquired by the Landsat Multispectral Scanner (MSS) and the Seasat Synthetic Aperture Radar (SAR) are assessed for their value to glaciological studies of Vatnajökull. A low Sun angle winter 1973 MSS band 7 Landsat image of Vatnajökull provides information about the distribution and size of subglacial volcanic calderas, cauldron subsidence caused by subglacial geothermal and (or) intrusive volcanic activity, and delineation of the probable position of surface ice divides. Two types of multi-spectral digital enhancements were applied to a late summer 1973 MSS image of Vatnajökull. The first type was used to prepare a planimetric base map showing the location of the principal surface features and an inventory of 38 named outlet glaciers, one internal ice cap (Öraefajökull), and two detached glaciers which comprise this complex ice cap, and to measure its area (8300 km2). The second type provides information about the position of the snow line at the approximate end of the 1973 melt season, the areas encompassed by the ice fades of the ablation area and the slush zone and wet-snow facies/percolation facies of the accumulation area. More information about the surface morphology of Vatnajökull was available from the Sow Sun angle winter and the digitally enhanced summer Landsat image of the ice cap than from the Seasat SAR image.
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Williams, Richard S. "Satellite Remote Sensing of Vatnajökull, Iceland." Annals of Glaciology 9 (1987): 127–35. http://dx.doi.org/10.1017/s0260305500000501.
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Iceland’s largest ice cap, Vatnajökull, has been the test site for a series of airborne and satellite remote-sensing studies since 1966. Various types of image data acquired by the Landsat Multispectral Scanner (MSS) and the Seasat Synthetic Aperture Radar (SAR) are assessed for their value to glaciological studies of Vatnajökull. A low Sun angle winter 1973 MSS band 7 Landsat image of Vatnajökull provides information about the distribution and size of subglacial volcanic calderas, cauldron subsidence caused by subglacial geothermal and (or) intrusive volcanic activity, and delineation of the probable position of surface ice divides. Two types of multi-spectral digital enhancements were applied to a late summer 1973 MSS image of Vatnajökull. The first type was used to prepare a planimetric base map showing the location of the principal surface features and an inventory of 38 named outlet glaciers, one internal ice cap (Öraefajökull), and two detached glaciers which comprise this complex ice cap, and to measure its area (8300 km2). The second type provides information about the position of the snow line at the approximate end of the 1973 melt season, the areas encompassed by the ice fades of the ablation area and the slush zone and wet-snow facies/percolation facies of the accumulation area. More information about the surface morphology of Vatnajökull was available from the Sow Sun angle winter and the digitally enhanced summer Landsat image of the ice cap than from the Seasat SAR image.
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Kibirige, Daniel, and Endre Dobos. "Estimation of surface soil moisture by integrating environmental data and remote-sensing satellites." Multidiszciplináris tudományok 11, no. 1 (2021): 22–37. http://dx.doi.org/10.35925/j.multi.2021.1.3.
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Soil moisture (SM) or soil water content is a critical variable in the climate system and a key parameter in earth surface processes. This study aimed to assess citizen observatory (CO) data's suitability to develop a method to estimate surface SM distribution using Sentinel-1B and Landsat 8 data; acquired between January 2019 and June 2019. Three approaches were developed and compared using multiple linear regression (MLR), regression-kriging (RK) and cokriging (CK). MLR provided more realistic spatial patterns over the landscape, even in a data-poor environment. RK was found to be a potential tool to refine the results, while CO was found to be less effective. The obtained results showed that CO data harmonised with Sentinel-1B SAR, Landsat 8, and terrain data could estimate and map soil moisture content.
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Lou, Hezhen, Yujia Zhang, Shengtian Yang, Xuelei Wang, Zihao Pan, and Ya Luo. "A New Method for Long-Term River Discharge Estimation of Small- and Medium-Scale Rivers by Using Multisource Remote Sensing and RSHS: Application and Validation." Remote Sensing 14, no. 8 (April 8, 2022): 1798. http://dx.doi.org/10.3390/rs14081798.
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River discharge is an important hydrological parameter of river water resources. Especially in small- and medium-scale rivers, data deficiency is the biggest problem for studies of river discharge. In recent years, remote sensing has become a rapid and convenient method to estimate river discharge. However, remote sensing images still have some difficulty generating continuous long-term river discharge. To address this problem, we developed a new method coupling the remote sensing hydrology station method (RSHS) with statistical regression downscaling, using data from optical satellites (Landsat-8, Sentinel-2), radar satellites (Sentinel-1), and un-manned aerial vehicles (UAVs). We applied this method to monitor monthly river discharge for small- and medium-scale rivers from 2016 to 2020 on Yunnan-Guizhou Plateau and evaluated the accuracy of the results. The results show that (1) by applying the newly constructed method, the water body continuity index obtained by Landsat-8 increased by 7% and the average river length percentage in the channel reached 90.7%, a 40% increase; (2) there were only 10 river flow data points, on average, in the 5-year period obtained before this method was applied; after this method was applied, more than 50 river flow data points could be obtained, on average, extending the quantity of data fivefold; in addition, improper extreme values could also be avoided; (3) with better continuity of water body distribution, the images provided steadier river widths. The relative error of daily flow estimation from Landsat-8 images was reduced by 60% and the mean percentage error was reduced by one-fourth. The relative error of the multisource remote sensing composited flow was reduced by 37% with a reduction in the mean percentage error of over a half; (4) in addition, we found that when the threshold difference between water bodies and land in remote sensing images is more than 0.2, the impact of water body recognition error on flow accuracy can be ignored. This method helps to overcome the absence of remote sensing methods for the long-term estimation of flow series in small- and medium-scale rivers, improves the accuracy of remote sensing methods for calculating flow, and provides ideas for regional water resource management and utilization.
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Stupin, Vladimir P. "POSSIBILITIES OF THE SAGA GIS IN THE STUDY AND MAPPING OF THE DEBRIS FLOW HAZARD OF THE BAIKAL MOUNTAIN COUNTRY." Interexpo GEO-Siberia 1 (May 21, 2021): 184–93. http://dx.doi.org/10.33764/2618-981x-2021-1-184-193.
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The possibilities and limitations of SAGA GIS for processing DEM and remote sensing materials of free access in the interests of specialized mapping of debris flow hazard in the Baikal region are considered. The results of processing the SRTM and ASTER GRID DEMS, as well as the spectrosonal images obtained from the Landsat-8 and Sentinel-2 satellites in the SAGA environment are compared. The most effective tools of GIS-analysis of territories from the point of view of the potential hazard assessment of debris flows based on remote sensing data are determined.
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Kalashnikov, Kirill, and Ekaterina Kulik. "THE USE OF ARCHIVAL LAND SURVEY DATA AT STUDY THE STATUS OF AGRICULTURAL LAND ACCORDING TO REMOTE SENSING." Interexpo GEO-Siberia 4, no. 2 (2019): 221–28. http://dx.doi.org/10.33764/2618-981x-2019-4-2-221-228.
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The state data funds have a huge database of various land management information on the entire territory of the Russian Federation. This database requires constant updating and is now significantly outdated. In most regions, not inventory of agricultural land, there are no actual data about their qualitative, quantitative condition is not carried out soil, and geobotanical surveys, are not updated thematic maps of the status and use of lands. The article shows the possibility of joint application of the results of soil, geobotanical surveys and planning and cartographic materials with archival data of Landsat satellites. The features of identifying the processes of overgrowth of agricultural land according to the sensor Landsat Thematic Mapper are analyzed. The technology of accounting for the vegetation period in the recognition of agricultural land on satellite images is demonstrated.
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Song, Wanjuan, Tian Zhao, Xihan Mu, Bo Zhong, Jing Zhao, Guangjian Yan, Li Wang, and Zheng Niu. "Using a Vegetation Index-Based Mixture Model to Estimate Fractional Vegetation Cover Products by Jointly Using Multiple Satellite Data: Method and Feasibility Analysis." Forests 13, no. 5 (April 29, 2022): 691. http://dx.doi.org/10.3390/f13050691.
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Remote sensing fractional vegetation cover (FVC) requires both finer-resolution and high-frequency in climate and ecosystem research. The increasing availability of finer-resolution (≤ 30 m) remote sensing data makes this possible. However, data from different satellites have large differences in spatial resolution, spectral response function, and so on, making joint use difficult. Herein, we showed that the vegetation index (VI)-based mixture model with the appropriate VI values of pure vegetation (Vv) and bare soil (Vs) from the MODIS BRDF product via the multi-angle VI method (MultiVI) was feasible to estimate FVC with multiple satellite data. Analyses of the spatial resolution and spectral response function differences for MODIS and other satellites including Landsat 8, Chinese GF 1, and ZY 3 predicted that (1) the effect of Vv and Vs downscaling on FVC estimation uncertainty varied from satellite to satellite due to the positioning differences, and (2) after spectral normalization, the uncertainty (RMSDs) for FVC estimation decreased by ~2.6% compared with the results without spectral normalization. FVC estimation across multiple satellite data will help to improve the spatiotemporal resolution of FVC products, which is an important development for numerous biophysical applications. Herein, we proved that the VI-based mixture model with Vv and Vs from MultiVI is a strong candidate.
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Fryskowska, A., M. Wojtkowska, P. Delis, and A. Grochala. "SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 647–52. http://dx.doi.org/10.5194/isprs-archives-xli-b7-647-2016.
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The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands). Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5‐0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of Landsat 8 with data from the new high resolution panchromatic EROS B satellite are analyzed. The range of panchromatic band for EROS B is 0.4‐0.9 μm and spatial resolution is 0.7 m. Research relied on improving the spatial resolution of natural color band combinations (bands: 4,3,2) and of desired false color band composition of Landsat 8 satellite imagery. For this purpose, six algorithms have been tested: Brovey’s, Mulitplicative, PCA, IHS, Ehler's, HPF. On the basis of the visual assessment, it was concluded that the best results of multispectral and panchromatic image integration, regardless land cover, are obtained for the multiplicative method. These conclusions were confirmed by statistical analysis using correlation coefficient, ERGAS and R-RMSE indicators.
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Fryskowska, A., M. Wojtkowska, P. Delis, and A. Grochala. "SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 647–52. http://dx.doi.org/10.5194/isprsarchives-xli-b7-647-2016.
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The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands). Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5‐0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of Landsat 8 with data from the new high resolution panchromatic EROS B satellite are analyzed. The range of panchromatic band for EROS B is 0.4‐0.9 μm and spatial resolution is 0.7 m. Research relied on improving the spatial resolution of natural color band combinations (bands: 4,3,2) and of desired false color band composition of Landsat 8 satellite imagery. For this purpose, six algorithms have been tested: Brovey’s, Mulitplicative, PCA, IHS, Ehler's, HPF. On the basis of the visual assessment, it was concluded that the best results of multispectral and panchromatic image integration, regardless land cover, are obtained for the multiplicative method. These conclusions were confirmed by statistical analysis using correlation coefficient, ERGAS and R-RMSE indicators.
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Sliusar, N. N., A. P. Belousova, G. M. Batrakova, R. D. Garifzyanov, M. Huber-Humer, and M. Ritzkowski. "Assessment of the State of the Territories of Closed Waste Disposal Facilities by Vegetation Indices." Ecology and Industry of Russia 25, no. 9 (September 8, 2021): 30–37. http://dx.doi.org/10.18412/1816-0395-2021-9-30-37.
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The possibilities of using remote sensing of the Earth data to assess the formation of phytocenoses at reclaimed dumps and landfills are presented. The objects of study are landfills and dumps in the Perm Territory, which differed from each other in the types and timing of reclamation work. The state of the vegetation cover on the reclaimed and self-overgrowing objects was compared with the reference plots with naturally formed herbage of zonal meadow vegetation. The process of reclamation of the territory of closed landfills was assessed by the presence and homogeneity of the vegetation layer and by the values of the vegetation index NDVI. To identify the dynamics of changes in the vegetation cover, we used multi-temporal satellite images from the open resources of Google Earth and images in the visible and infrared ranges of the Landsat-5/TM and Landsat-8/OLI satellites. It is shown that the data of remote sensing of the Earth, in particular the analysis of vegetation indices, can be used to assess the dynamics of overgrowing of territories of reclaimed waste disposal facilities, as well as an additional and cost-effective method for monitoring the restoration of previously disturbed territories.
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Li, Teng, Bozhong Zhu, Fei Cao, Hao Sun, Xianqiang He, Mingliang Liu, Fang Gong, and Yan Bai. "Monitoring Changes in the Transparency of the Largest Reservoir in Eastern China in the Past Decade, 2013–2020." Remote Sensing 13, no. 13 (June 30, 2021): 2570. http://dx.doi.org/10.3390/rs13132570.
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Based on characteristics analysis about remote sensing reflectance, the Secchi Disk Depth (SDD) in the Qiandao Lake was predicted from the Landsat8/OLI data, and its changing rates on a pixel-by-pixel scale were obtained from satellite remote sensing for the first time. Using 114 matchups data pairs during 2013–2019, the SDD satellite algorithms suitable for the Qiandao Lake were obtained through both the linear regression and machine learning (Support Vector Machine) methods, with remote sensing reflectance (Rrs) at different OLI bands and the ratio of Rrs (Band3) to Rrs (Band2) as model input parameters. Compared with field observations, the mean absolute relative difference and root mean squared error of satellite-derived SDD were within 20% and 1.3 m, respectively. Satellite-derived results revealed that SDD in the Qiandao Lake was high in boreal spring and winter, and reached the lowest in boreal summer, with the annual mean value of about 5 m. Spatially, high SDD was mainly concentrated in the southeast lake area (up to 13 m) close to the dam. The edge and runoff area of the lake were less transparent, with an SDD of less than 4 m. In the past decade (2013–2020), 5.32% of Qiandao Lake witnessed significant (p < 0.05) transparency change: 4.42% raised with a rate of about 0.11 m/year and 0.9% varied with a rate of about −0.09 m/year. Besides, the findings presented here suggested that heavy rainfall would have a continuous impact on the Qiandao Lake SDD. Our research could promote the applications of land observation satellites (such as the Landsat series) in water environment monitoring in inland reservoirs.
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Silva, E. A., M. M. Pedrosa, S. C. Azevedo, G. P. Cardim, and F. P. S. Carvalho. "ASSESSMENT OF SURFACE WATER AT THE SOBRADINHO RESERVOIR UNDER THE EFFECTS OF DROUGHT USING MULTI-TEMPORAL LANDSAT IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 387–92. http://dx.doi.org/10.5194/isprs-archives-xli-b8-387-2016.
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The matrix of energy generation in Brazil is predominantly hydroelectric power. Consequently, the reservoirs need constant monitoring due to the large volume of artificially dammed water. Images from remote sensing can provide reliable information concerning water bodies. In this paper, we use remote sensing imagery to monitor the Sobradinho dam in three different epochs. The objective was to verify quantitatively the area of the dam’s surface reduced due to the drought of 2015, which was considered the worst in history. The approach used water surface area estimations from bands of Landsat5 and Landsat8 satellites which highlight water bodies better from other features present on surface of the Earth. Through the techniques of growth region and normalized difference water index (NDWI), we determined the surface area of the reservoir in 2011 and calculated the decrease caused by the drought. By analyzing the numbers provided by the results it is possible to estimate how the Sobradinho reservoir has been affected by the drastic drought. The results show that the Landsat images enable the monitoring of large reservoirs. Bearing in mind that monitoring is a primary and indispensable tool, not only for technical study, but also for economic and environmental research, it can help establish planning projects and water administration strategies for future decisions about the hydrical resource priority.
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Silva, E. A., M. M. Pedrosa, S. C. Azevedo, G. P. Cardim, and F. P. S. Carvalho. "ASSESSMENT OF SURFACE WATER AT THE SOBRADINHO RESERVOIR UNDER THE EFFECTS OF DROUGHT USING MULTI-TEMPORAL LANDSAT IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 387–92. http://dx.doi.org/10.5194/isprsarchives-xli-b8-387-2016.
Full textAbstract:
The matrix of energy generation in Brazil is predominantly hydroelectric power. Consequently, the reservoirs need constant monitoring due to the large volume of artificially dammed water. Images from remote sensing can provide reliable information concerning water bodies. In this paper, we use remote sensing imagery to monitor the Sobradinho dam in three different epochs. The objective was to verify quantitatively the area of the dam’s surface reduced due to the drought of 2015, which was considered the worst in history. The approach used water surface area estimations from bands of Landsat5 and Landsat8 satellites which highlight water bodies better from other features present on surface of the Earth. Through the techniques of growth region and normalized difference water index (NDWI), we determined the surface area of the reservoir in 2011 and calculated the decrease caused by the drought. By analyzing the numbers provided by the results it is possible to estimate how the Sobradinho reservoir has been affected by the drastic drought. The results show that the Landsat images enable the monitoring of large reservoirs. Bearing in mind that monitoring is a primary and indispensable tool, not only for technical study, but also for economic and environmental research, it can help establish planning projects and water administration strategies for future decisions about the hydrical resource priority.
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Kayastha, Priya, Andrew R. Dzialowski, Scott H. Stoodley, Kevin L. Wagner, and Abubakarr S. Mansaray. "Effect of Time Window on Satellite and Ground-Based Data for Estimating Chlorophyll-a in Reservoirs." Remote Sensing 14, no. 4 (February 11, 2022): 846. http://dx.doi.org/10.3390/rs14040846.
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Algal blooms in freshwater ecosystems can negatively impact aquatic and human health. Satellite remote sensing of chlorophyll a (Chl-a) is often used to help determine the severity of algal blooms. However, satellite revisit flyover schedules may not match the erratic nature of algal blooms. Studies have paired satellite and ground-based data that were not collected on the same day, assuming Chl-a concentrations did not change significantly by the flyover date. We determined the effects of an increasing time window between satellite overpass dates and field-based collection of Chl-a on algorithms for Landsat 5, Landsat 8, and Sentinel-2, using 14 years (2006–2020) of Chl-a data from 10 Oklahoma reservoirs. Multiple regression models were built, and selected statistics were used to rank the time windows. The Sentinel-2 results showed strong relationships between Chl-a and satellite data collected up to a ±5-day window. The strength of these relationships decreased beyond a ±3-day time window for Landsat 8 and a ±1-day time window for Landsat 5. Our results suggest that the time window between field sampling and satellite overpass can impact the use of satellite data for Chl-a monitoring in reservoirs. Furthermore, longer time windows can be used with higher resolution (spatial, spectral) satellites.
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Бочаров, Александр Вячеславович, Олег Алексеевич Тихомиров, and Павел Николаевич Кравченко. "EVALUATION OF CHANGE IN THE AREA OF THE KRASNOGORSK SAND QUARRY ACCORDING TO THE DATA OF SENSORS OF SATELLITES OF THE LANDSAT SERIES IN 1988-2021." Вестник Тверского государственного университета. Серия: География и геоэкология, no. 1(37) (March 25, 2022): 32–37. http://dx.doi.org/10.26456/2226-7719-2022-1-32-37.
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Цель исследования - оценить динамику изменения площади водной поверхности песчаного карьера с 1988 по 2021 гг. Исследование проведено на основании данных дистанционного зондирования Земли. Для оценки трансформации природно-антропогенных комплексов использованы данные полученные сенсорами спутников серии Landsat. The purpose of the study is to assess the dynamics of changes in the water surface area of a sand pit from 1988 to 2021. The study was carried out on the basis of Earth remote sensing data. To assess the transformation of natural-anthropogenic complexes, the data obtained by the sensors of the Landsat series satellites were used.
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Bonansea, Matias, Claudia Rodriguez, and Lucio Pinotti. "Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir." Hydrology Research 49, no. 5 (December 18, 2017): 1608–17. http://dx.doi.org/10.2166/nh.2017.116.
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Abstract Landsat satellites, 5 and 7, have significant potential for estimating several water quality parameters, but to our knowledge, there are few investigations which integrate these earlier sensors with the newest and improved mission of Landsat 8 satellite. Thus, the comparability of water quality assessing across different Landsat sensors needs to be evaluated. The main objective of this study was to assess the feasibility of integrating Landsat sensors to estimate chlorophyll-a concentration (Chl-a) in Río Tercero reservoir (Argentina). A general model to retrieve Chl-a was developed (R2 = 0.88). Using observed versus predicted Chl-a values the model was validated (R2 = 0.89) and applied to Landsat imagery obtaining spatial representations of Chl-a in the reservoir. Results showed that Landsat 8 can be combined with Landsat 5 and 7 to construct an empirical model to estimate water quality characteristics, such as Chl-a in a reservoir. As the number of available and upcoming sensors with open access will increase with time, we expect that this trend will certainly further promote remote sensing applications and serve as a valuable basis for a wide range of water quality assessments.
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Czapski, Paweł, Mariusz Kacprzak, Jan Kotlarz, Karol Mrowiec, Katarzyna Kubiak, and Miłosz Tkaczyk. "Preliminary analysis of the forest health state based on multispectral images acquired by Unmanned Aerial Vehicle." Folia Forestalia Polonica 57, no. 3 (September 1, 2015): 138–44. http://dx.doi.org/10.1515/ffp-2015-0014.
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Abstract The main purpose of this publication is to present the current progress of the work associated with the use of a lightweight unmanned platforms for various environmental studies. Current development in information technology, electronics and sensors miniaturisation allows mounting multispectral cameras and scanners on unmanned aerial vehicle (UAV) that could only be used on board aircraft and satellites. Remote Sensing Division in the Institute of Aviation carries out innovative researches using multisensory platform and lightweight unmanned vehicle to evaluate the health state of forests in Wielkopolska province. In this paper, applicability of multispectral images analysis acquired several times during the growing season from low altitude (up to 800m) is presented. We present remote sensing indicators computed by our software and common methods for assessing state of trees health. The correctness of applied methods is verified using analysis of satellite scenes acquired by Landsat 8 OLI instrument (Operational Land Imager).
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Stupin, Vladimir P., and Irina A. Karpova. "GIS ANALYSIS OF DEM IN THE INTERESTS OF SPECIALIZED MAPPING OF MINING TERRAIN." Interexpo GEO-Siberia 1 (May 21, 2021): 194–203. http://dx.doi.org/10.33764/2618-981x-2021-1-194-203.
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Using the example of the Korshunovsky GOK quarry, the possibilities of processing publicly available SRTM C-SIR and ASTER GDEM DEM data and remote sensing materials obtained from LANDSAT and SENTINEL satellites in the SAGA GIS for specialized mapping of mountainous terrain are considered. The results of constructing derived geomorphometric maps based on DEM are presented. Restrictions on the use of the materials under consideration are justified.
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Yeprintsev, S. A., ,. S. A. Kurolap, O. V. Klepikov, and ,. S. V. Shekoyan. "ASSESSMENT OF THE ANTHROPOGENIC LOAD OF URBANIZED AREAS BASED ON EARTH REMOTE SENSING DATA." ECOLOGY ECONOMY INFORMATICS. GEOINFORMATION TECHNOLOGIES AND SPACE MONITORING 2, no. 6 (2021): 53–58. http://dx.doi.org/10.23885/2500-123x-2021-2-6-53-58.
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The high anthropogenic load characteristic of urban settlements entails the need for constant monitoring of factors that can potentially have a negative impact on the quality of the environment and the health of the population. Ground-based research methods used for spatial zoning of urbanized territories according to the level of anthropogenic load entail significant time costs, which, despite the high accuracy, significantly reduces their effectiveness. Remote sensing technologies have become a good alternative to ground-based methods. To assess the anthropogenic load of the cities of Central Russia (Voronezh, Lipetsk, Belgorod), an archive of multi-channel satellite images obtained from Landsat-7 and Landsat-8 satellites has been created. The satellite images are grouped into three periods (2001, 2016 and 2020). The processing of satellite images of the studied cities of Central Russia, as well as suburban areas, was carried out in the Scanex Image Processor software package. Spatial assessment of the ratio of the areas of anthropogenic-altered territories and the natural framework was made by determining the value of NDVI within cities and suburban ten-kilometer zones. For the analysis of satellite images of the above-mentioned time periods, equal areas of territories were allocated, where the NDVI indicators of the studied urbanized territories of the cities of Voronezh, Lipetsk, Belgorod, as well as suburban tenkilometer zones with subsequent spatial geoinformation zoning of territories according to this indicator were calculated. The obtained results made it possible to study a number of environmental quality parameters (the level of anthropogenic load, the natural framework of the territory, hydrological objects), as well as their dynamics over a twenty-year period.
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Zhang, Li Juan, Xing Ping Wen, Jun Wang, and Yang Zhou. "Research on the Relationship of Surface Temperature and Urban Heat Island Using the Thermal Infrared Remote Sensing Image." Advanced Materials Research 889-890 (February 2014): 1634–37. http://dx.doi.org/10.4028/www.scientific.net/amr.889-890.1634.
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The temperature of the earth's land surface plays a very import ant role in the land-air interactions. It is critical parameters in the research of global change. Therefore, the use of satellite remote sensing data for surface temperature retrieval has become an important task of the study. Regional surface temperature is an important parameter of thermal energy distribution in the region, to obtain which is the most convenient and effective method. Thermal infrared remote sensing is an important area, and from thermal infrared remote sensing image information extracting temperature is a prerequisite for applying thermal infrared remote sensing technology .Based on remote sensing image data reading, radiometric calibration, regional cropping pretreatment; Then Landsat band 6 inversion of surface brightness temperature, It introduces the effect of the urban heat island using Landsat remote sensing ,having obtained the changes of spatial distribution of surface temperature, and prospects for future development in this field.
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Serhii, A. Shevchuk, Viktor I. Vyshnevskyi, and P. Bilous Olena. "The Use of Remote Sensing Data for Investigation of Environmental Consequences of Russia-Ukraine War." Journal of Landscape Ecology 15, no. 3 (December 1, 2022): 36–53. http://dx.doi.org/10.2478/jlecol-2022-0017.
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Abstract The usage of remote sensing data for tracking or monitoring war conflicts is a reality nowadays. The Russian invasion in Ukraine seriously impacted on the environment of the attacked country in all areas: air, soil, water, flora and fauna. The war has created a massive increase in air pollution in some regions of Ukraine, and might have effect in neighbouring countries. The Russian attack has caused many fires at places such as oil depots, industrial complexes, equipment and ammunition stockpiles, the forests, and residential areas. In addition to this, many bridges, hydraulic and other structures located over and near the water bodies were destroyed. These events were analysed in this paper by using publicly available remote sensing data: NOAA-2, Suomi NPP, Aqua and Terra satellites, Sentinel and Landsat satellites, as well as from other sources open to public. We assume that the use of remote sensing data is an excellent tool to monitor effects of military conflicts on environment. The conducted research with proposed method can serve as a good scientific practice that should be implemented for monitoring of the harm to nature caused by wars.
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Van Niekerk, Elna, and Luke Sandham. "Visual interpretation of ASTER satellite data, Part 1: Geologic mapping in the Cradle of Humankind World Heritage Site." Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie 26, no. 3 (September 21, 2007): 177–95. http://dx.doi.org/10.4102/satnt.v26i3.132.
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Since the first earth observing satellite was launched in 1972, remote sensing has become a powerful tool in the arsenal of geoscientists. This satellite became known as Landsat 1 and carried the Multispectral Scanner (MSS) delivering imagery at a spatial resolution of 80, and spectral resolution from blue to near infrared. Ongoing satellite and sensor development to the end of the century produced the Landsat Thematic Mapper (TM) with improved spatial and spectral resolution, as well as the SPOT series of satellites delivering the highest spatial but limited spectral resolution. These developments culminated in the SPOT 4 (1998) and Landsat Enhanced Thematic Mapper (1999) sensors. While Landsat ETM in particular provided much improved spatial and spectral resolutions, on the basis of which a large amount of geoscientific remote sensing was conducted world wide, the data did not provide adequate spectral and spatial sensitivity to be optimally effective for geological mapping at the local scale. On 18 December 1999 the Terra platform was launched, carrying five remote sensing instruments, including ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer). ASTER consists of three separate instrument subsystems, each operating in a different spectral region, and using separate optical systems. These are the Visible and Very Near Infrared (VNIR) subsystem with a 15m-spatial resolution, the Short Wave Infrared (SWIR) subsystem with a 30m-spatial resolution and the Thermal Infrared (TIR) subsystem with a 90m-spatial resolution. ASTER effectively offers an improvement on Landsat MSS, Landsat TM, Landsat ETM+ and SPOT spectral and spatial resolutions. Given the paucity of published research on geological remote sensing at the local scale in South Africa, and particularly on the use of ASTER for geological mapping in South Africa, it is imperative that the value of ASTER be investigated. This article reports on the improved detail and scale achieved in the mapping of litho-stratigraphy, geological structures and mining-related features by the visual interpretation of processed ASTER images. ASTER imagery obtained from the EOS website was subjected to a range of image enhancement and analysis techniques including colour composites, band ratios, normalised difference indices, regression and decorrelation, in order to obtain optimal visual interpretability. Eight images thus obtained could be used for visual analysis, and it became evident that litho-stratigraphy, faults, fracture zones and elements of the regional seam system, as well as remnants of mining activities, were readily identifiable. Some of these were in accordance with the most recent and accurate geological map of the area, but many of them had apparently not been mapped. These features were annotated and were verified by field checks. In all cases the accuracy of detection and location from satellite imagery was confirmed on the ground. The improved detail and accuracy obtained by visual interpretation of processed ASTER satellite data for mapping a section of the Cradle of Humankind World Heritage Site demonstrated the potential value of this data for a variety of other geoscience applications. It appears that the improved accuracy can be ascribed jointly to the higher spatial and spectral resolution provided by ASTER data.
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Aulicino, Giuseppe, and Peter Wadhams. "Editorial for the Special Issue “Remote Sensing of the Polar Oceans”." Remote Sensing 14, no. 24 (December 7, 2022): 6195. http://dx.doi.org/10.3390/rs14246195.
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This Special Issue gathers papers reporting research on various aspects of the use of satellites for monitoring polar oceans. It includes contributions presenting improvements in the retrieval of sea ice concentration, extent and area, and concerning error information; the interannual and decadal variability of sea surface temperature and sea ice concentration in the Barents Sea; validation and comparison of Arctic salinity products; melt pond retrieval applying a Linear Polar algorithm to Landsat data; the characterization of surface layer freshening from sea surface salinity and coloured detrital matter in the Kara and Laptev Seas; multi-sensor estimations of chlorophyll-a concentrations in the Western Antarctic Peninsula; and enhanced techniques for detection and monitoring of glacier dynamics and iceberg paths.
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Amos, E. M., D. Blakeway, and C. D. Warren. "Remote Sensing Techniques in Civil Engineering Surveys." Geological Society, London, Engineering Geology Special Publications 2, no. 1 (1986): 119–24. http://dx.doi.org/10.1144/gsl.1986.002.01.26.
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AbstractThis paper outlines selected remote sensing techniques and their application to civil engineering surveys.In BS 5930, emphasis has been placed on the interpretation of black and white aerial photography to provide information. However, other techniques such as true colour and false colour infrared photography, thermal infrared, radar and landsat satellite imagery may be useful in appropriate applications.
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Pflug, B., M. Main-Knorn, A. Makarau, and R. Richter. "Validation of aerosol estimation in atmospheric correction algorithm ATCOR." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 677–83. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-677-2015.
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Atmospheric correction of satellite images is necessary for many applications of remote sensing, i.e. computation of vegetation indices and biomass estimation. The first step in atmospheric correction is estimation of the actual aerosol properties. Due to the spatial and temporal variability of aerosol amount and type, this step becomes crucial for an accurate correction of satellite data. Consequently, the validation of aerosol estimation contributes to the validation of atmospheric correction algorithms. In this study we present the validation of aerosol estimation using own sun photometer measurements in Central Europe and measurements of AERONET-stations at different locations in the world. Our ground-based sun photometer measurements of vertical column aerosoloptical thickness (AOT) spectra are performed synchronously to overpasses of the satellites RapidEye, Landsat 5, Landsat 7 and Landsat 8. Selected AERONET data are collocated to Landsat 8 overflights. The validation of the aerosol retrieval is conducted by a direct comparison of ground-measured AOT with satellite derived AOT using the ATCOR tool for the selected satellite images. The mean uncertainty found in our experiments is ΔAOT550nm ≈ 0.03±0.02 for cloudless conditions with cloud+haze fraction below 1%. This AOT uncertainty approximately corresponds to an uncertainty in surface albedo of Δρ ≈ 0.003. Inclusion of cloudy and hazy satellite images into the analysis results in mean ΔAOT550nm ≈ 0.04±0.03 for both RapidEye and Landsat imagery. About ⅓ of samples perform with the AOT uncertainty better than 0.02 and about ⅔ perform with AOT uncertainty better than 0.05.
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Thorning, L., and T. Tukiainen. "Landsat image database for Greenland." Rapport Grønlands Geologiske Undersøgelse 165 (January 1, 1995): 76–78. http://dx.doi.org/10.34194/rapggu.v165.8283.
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As a consequence of the GIRS project (Geological Information from Remote Sensing; Tukiainen & Thorning, this report) a database of Landsa1 images for Greenland suited for geological interpretation has been established at the Geological Survey of Greenland (GGU) with the help of funds from the Mineral Resources Administration for Greenland. This note briefly introduces the new GGU facility. This database has been established in order to make satellite images more readily available for all potential users of Landsat data in Greenland at standard conditions and price.
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Xie, Ming Xiao, Yin Cai, and Meng Guo Li. "Analysis of the Coral Reef Evolution Based on Satellite Remote Sensing Images." Applied Mechanics and Materials 333-335 (July 2013): 1719–23. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.1719.
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Based on analysis of the ETM+ and TM remote sensing images of LandSAT satellites, the stability and evolution characteristics of the nearshore coral reefs at Changjiang, China was investigated. The results showed that the maximum distance from the outside edge of the coral reefs to the shoreline is 1.1km, and the corresponding minimum distance is 200m. From 1973 to 2013, the locations of coral reef chain are relatively stable with maximum variation 50m. Generally, the natural tidal currents and waves can not destroy the coral reefs, and the human activities do not change the biological environment of the coastal area. Therefore, the Changjiang coral reefs could keep stable in the long term.
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Pour, A. B., M. Hashim, and J. K. Hong. "APPLICATION OF MULTISPECTRAL SATELLITE DATA FOR GEOLOGICAL MAPPING IN ANTARCTIC ENVIRONMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W1 (September 29, 2016): 77–81. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w1-77-2016.
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Remote sensing imagery is capable to provide a solution to overcome the difficulties associated with geological field mapping in the Antarctic. Advanced optical and radar satellite imagery is the most applicable tool for mapping and identification of inaccessible regions in Antarctic. Consequently, an improved scientific research using remote sensing technology would be essential to provide new and more complete lithological and structural data to fill the numerous knowledge gaps on Antarctica’s geology. In this investigation, Oscar coast area in Graham Land, Antarctic Peninsula (AP) was selected to conduct a remote sensing study using Landsat-7 Thematic Mapper (TM), Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Contrast-enhanced Red-Green-Blue (RGB) composites, band ratios and Relative Band Depth (RBD) image processing techniques were applied to Landsat-8 and ASTER dataset for establishing the spectral separation of the main lithologic groups exposed in the study area. The outcomes of this investigation demonstrated the applications of SWIR and TIR bands of the multispectral remote sensing datasets to identify lithological units and producing geological maps with suitable accuracy of ice-free rock regions in the Antarctic Peninsula. The results could be extended to map coverage of non-investigated regions further east and validated previously inferred geological observations concerning other rocks and mineral deposits throughout the Antarctica.
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Pham, Thao Thi Phuong, Duan Dinh Ho, and To Van Dang. "EXTRACTING THE WATERLINE FROM LANDSAT IMAGES." Science and Technology Development Journal 12, no. 12 (June 28, 2009): 52–58. http://dx.doi.org/10.32508/stdj.v12i12.2319.
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Remote sensing technology nowadays is one of the most useful tools for scientific research in general and for oceanography in particular. From satellite images, the useful information such as waterline images can be extracte for a large region simultaneously. After tidal adjustments, the waterlines can be used as the observed shorelines which are important inputs for estimating shoreline changes by either using the integration of remote sensing and GIS or using numerical models. Based on the spectral bands of various Landsat images, the paper presents the methods to detect the waterlines in Phan Thiet region in the 40 years period using the images of 1973, 1976, 1990, and 2002 respectively. The extracted results relatively agree with the information of waterline from the images.
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Beiranvand Pour, A., M. Hashim, and M. Pournamdari. "CHROMITITE PROSPECTING USING LANDSAT TM AND ASTER REMOTE SENSING DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-2/W2 (October 19, 2015): 99–103. http://dx.doi.org/10.5194/isprsannals-ii-2-w2-99-2015.
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Studying the ophiolite complexes using multispectral remote sensing satellite data are interesting because of high diversity of minerals and the source of podiform chromitites. This research developed an approach to discriminate lithological units and detecting host rock of chromitite bodies within ophiolitic complexes using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat Thematic Mapper (TM) satellite data. Three main ophiolite complexes located in south of Iran have been selected for the study. Spectral transform techniques, including minimum noise fraction (MNF) and specialized band ratio were employed to detect different rock units and the identification of high-potential areas of chromite ore deposits within ophiolitic complexes. A specialized band ratio (4/1, 4/5, 4/7) of ASTER, MNF components and Spectral Angle Mapper (SAM) on ASTER and Landsat TM data were used to distinguish ophiolitic rock units. Results show that the specialized band ratio was able to identify different rock units and serpentinized dunite as host rock of chromitites within ophiolitic complexes, appropriately. MNF components of ASTER and Landsat TM data were suitable to distinguish ophiolitic rock complexes at a regional scale. The integration of SAM and Feature Level Fusion (FLF) used in this investigation discriminated the ophiolitic rock units and prepared detailed geological map for the study area. Accordingly, high potential areas (serpentinite dunite) were identified in the study area for chromite exploration targets.The approach used in this research offers the image processing techniques as a robust, reliable, fast and cost-effective method for detecting serpentinized dunite as host rock of chromitite bodies within vast ophiolite complexes using ASTER and Landsat TM satellite data.
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Khanh Ni, Tran Ngoc, Hoang Cong Tin, Vo Trong Thach, Cédric Jamet, and Izuru Saizen. "Mapping Submerged Aquatic Vegetation along the Central Vietnamese Coast Using Multi-Source Remote Sensing." ISPRS International Journal of Geo-Information 9, no. 6 (June 16, 2020): 395. http://dx.doi.org/10.3390/ijgi9060395.
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Submerged aquatic vegetation (SAV) in the Khanh Hoa (Vietnam) coastal area plays an important role in coastal communities and the marine ecosystem. However, SAV distribution varies widely, in terms of depth and substrate types, making it difficult to monitor using in-situ measurement. Remote sensing can help address this issue. High spatial resolution satellites, with more bands and higher radiometric sensitivity, have been launched recently, including the Vietnamese Natural Resources, Environment, and Disaster Monitoring Satellite (VNREDSat-1) (V1) sensor from Vietnam, launched in 2013. The objective of the study described here was to establish SAV distribution maps for South-Central Vietnam, particularly in the Khanh Hoa coastal area, using Sentinel-2 (S2), Landsat-8, and V1 imagery, and then to assess any changes to SAV over the last ten years, using selected historical data. The satellite top-of-atmosphere signals were initially converted to radiance, and then corrected for atmospheric effects. This treated signal was then used to classify Khanh Hoa coastal water substrates, and these classifications were evaluated using 101 in-situ measurements, collected in 2017 and 2018. The results showed that the three satellites could provide high accuracy, with Kappa coefficients above 0.84, with V1 achieving over 0.87. Our results showed that, from 2008 to 2018, SAV acreage in Khanh Hoa was reduced by 74.2%, while gains in new areas compensated for less than half of these losses. This is the first study to show the potential for using V1 and S2 data to assess the distribution status of SAV in Vietnam, and its outcomes will contribute to the conservation of SAV beds, and to the sustainable exploitation of aquatic resources in the Khanh Hoa coastal area.
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Parente, Leandro, Evandro Taquary, Ana Silva, Carlos Souza, and Laerte Ferreira. "Next Generation Mapping: Combining Deep Learning, Cloud Computing, and Big Remote Sensing Data." Remote Sensing 11, no. 23 (December 3, 2019): 2881. http://dx.doi.org/10.3390/rs11232881.
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The rapid growth of satellites orbiting the planet is generating massive amounts of data for Earth science applications. Concurrently, state-of-the-art deep-learning-based algorithms and cloud computing infrastructure have become available with a great potential to revolutionize the image processing of satellite remote sensing. Within this context, this study evaluated, based on thousands of PlanetScope images obtained over a 12-month period, the performance of three machine learning approaches (random forest, long short-term memory-LSTM, and U-Net). We applied these approaches to mapped pasturelands in a Central Brazil region. The deep learning algorithms were implemented using TensorFlow, while the random forest utilized the Google Earth Engine platform. The accuracy assessment presented F1 scores for U-Net, LSTM, and random forest of, respectively, 96.94%, 98.83%, and 95.53% in the validation data, and 94.06%, 87.97%, and 82.57% in the test data, indicating a better classification efficiency using the deep learning approaches. Although the use of deep learning algorithms depends on a high investment in calibration samples and the generalization of these methods requires further investigations, our results suggest that the neural network architectures developed in this study can be used to map large geographic regions that consider a wide variety of satellite data (e.g., PlanetScope, Sentinel-2, Landsat-8).
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Çolak, E., and A. F. Sunar. "REMOTE SENSING & GIS INTEGRATION FOR MONITORING THE AREAS AFFECTED BY FOREST FIRES: A CASE STUDY IN IZMIR, TURKEY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W4 (March 6, 2018): 165–70. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w4-165-2018.
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<p><strong>Abstract.</strong> A forest fire is stated as an ecological disaster whether it is man-made or caused naturally. İzmir is one of the regions where forest fires are most intensified in Turkey. The study area located at Aegean region of Turkey suffered two forest fires in 2017; Menderes and Bayındır areas. This study presents the integration of remote sensing (Sentinel 2 and Landsat 8 satellite images) and GIS data to map and evaluate the forest burned areas due to both forest fires. For this purpose, different indexes such as Burn Area Index (BAI), Mid Infrared Burn Index (MIRBI), Normalized Burn Ratio (NBR) and Normalized Burn Ratio Thermal (NBRT) Burn Index are applied besides different classification algorithms. The results showed that different vegetation types/zones are being affected. Sentinel 2 and Landsat 8 data are integrated to the GIS established with fieldwork data to analyse and also validate the results. Digital Elevation Model (DEM) data produced from ASTER satellite is also overlaid to the outcomes to emphasize the destructed forest areas. The efficiency of using two different satellites are outlined by comparing the accuracy of forest fire maps produced.</p>
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Aliev, Ruslan, and Aleksey Medvedkov. "Analysis of the climatogenic dynamics of the Batagay thermodenudation “crater” using remote sensing data." InterCarto. InterGIS 26, no. 2 (2020): 366–75. http://dx.doi.org/10.35595/2414-9179-2020-2-26-366-375.
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The article discusses the contribution of the climatogenic factor to the development of the Batagai thermo-denudation “crater” — the largest object in the world of thermo-denudation origin. The Batagai “crater” is the result of accelerated activation of exodynamic processes in the continuous permafrost zone of the Yansky Plateau (Northern Yakutia), located in the coldest region of Russia. According to satellite imagery from Landsat series satellites (Landsat-7 and Ladsat-8) for the period from 1999 to 2017. The rate of its growth was established taking into account the exposure factor for certain time intervals. Based on the selected satellite images, they were visually decrypted to highlight the “crater” edge, with reference to each year for the entire 18-year period. The results obtained were compared with climatic indicators for the corresponding time intervals. From climate data, those were analyzed that had positive dynamics and favored the development of thermo-denudation processes. So, for the Batagai “crater” area over the past 50 years, there has been a stable tendency towards an increase in temperature values (average summer by 1,6°C and average annual by 2,2°C) and the amount of precipitation (an increase in the annual amount of 25 mm due to summer autumn period). Over the past two decades, a certain correlation has been revealed between the growth rate of the Batagai “crater” and the dynamics of the main climatic indicators. During the analyzed period, it was established that the northwestern side of the “crater” is distinguished by the highest rate of degradation. Given the statistically revealed relationship, as well as the high ice content of the rocks (40–60 %) and their special sand vein structure, this allows us to consider the Batagai “crater” — a vivid indicator of climate warming.
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Tukiainen, T., and L. Thorning. "Use of SPOT and Landsat TM satellite data in geological reconnaissance." Rapport Grønlands Geologiske Undersøgelse 165 (January 1, 1995): 73–75. http://dx.doi.org/10.34194/rapggu.v165.8282.
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As a part of the SUPRASYD project in southern Greenland (Garde & Schonwandt. this report) a pilot project was initiated in order to assess the use of satellite based remote sensing in mineral resource reconnaissance work (the GIRS project: Geological lnformation from Remote Sensing). The objectives were to evaluate the usefulness of modem satellite data imagery during the various stages of a GGU field programme. A detailed account of the project is given in Tukiainen et al. (1993), this note briefly summarises some of the main results.
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Garrido-Rubio, Jesús, Alfonso Calera Belmonte, Lorena Fraile Enguita, Irene Arellano Alcázar, Mario Belmonte Mancebo, Isidro Campos Rodríguez, and Raquel Bravo Rubio. "Remote sensing-based soil water balance for irrigation water accounting at the Spanish Iberian Peninsula." Proceedings of the International Association of Hydrological Sciences 380 (December 18, 2018): 29–35. http://dx.doi.org/10.5194/piahs-380-29-2018.
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Abstract. Temporal series maps of irrigated areas, and the corresponding irrigation water requirements based on remote sensing, is a recognized tool contributing to water governance at different scales, from water user associations to whole river basin districts. These thematic cartographies offer a first estimation of the crop irrigation requirements, and a biophysical based approach of the temporal and spatial distribution of the crop water use in the cultivated areas. This work describes the operational application of these methodologies, providing valuable information for water governance and management purposes. The basic products obtained in the whole Spanish part of the Iberian Peninsula during the period 2014–2017 were: (i) annual maps of irrigated crops based on time series of multispectral satellite imagery; and (ii) the direct remote sensing-based water accounting, by quantifying agricultural water flows (e.g. rainfall, irrigation, evapotranspiration, drainage and recharge), through a remote sensing-based soil water balance. Hence this paper provides a remote sensing based water accounting approach, which relies on dense time series of multispectral imagery acquired by the multisensor constellation arranged by Landsat 8 and Sentinel-2 satellites, jointly with meteorological data and agronomic knowledge. Then, based on these purpose and approach, annual and monthly maps of net irrigation water requirements have been elaborated at the most practical spatial and temporal scales for water governance purposes over big areas such river basin districts. This work summarizes the methodologies used and discuss the technical and non-technical feasibility of the proposed approach.