Journal articles: 'RemoteSensing'

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Srivastava, Hari Shanker, and Santvana Nigam. "https://www.cloudpublications.org/journals/index.php/RemoteSensing/article/view/508." International Journal of Advanced Remote Sensing and GIS 9, no. 1 (September 29, 2020): 3384–404. http://dx.doi.org/10.23953/cloud.ijarsg.480.

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David Mayunga, Selassie. "Monitoring of Land Use/Cover Change Using Remote Sensing and GIS techniques: A case study of Loliondo Game Controlled Area, Tanzania." Trends Journal of Sciences Research 3, no. 1 (July 26, 2018): 36–50. http://dx.doi.org/10.31586/remotesensing.0301.04.

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Takahashi, Masayuki, Motoaki Kishino, and Joji Ishizaka. "Organization for Monitoring of Marine Organisms by Remotesensing and its International Collaboration." Oceanography in Japan 4, no. 4 (1995): 355–60. http://dx.doi.org/10.5928/kaiyou.4.355.

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MILOVANOVIĆ, Milan. "APPLICATION OF REMOTESENSING FOR WILDFIRES BURN SEVERITY DETECTION - CASESTUDY OF TARA MOUNTAIN." PROCEEDINGS International Scientific Symposium NEW TRENDS IN GEOGRAPHY October 3-4, 2019 Ohrid 2019 (2019): 157–64. http://dx.doi.org/10.37658/procgeo19157m.

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Asadi, SS, B. V. T. Vasantha Rao, M. V. Raju, and M. Anand Sagar. "Identification of Ambient Air Pollution Prevention Zones Using Remotesensing and GIS:A Model Study." Current World Environment 6, no. 2 (December 25, 2006): 207–15. http://dx.doi.org/10.12944/cwe.6.2.02.

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Lange, M. A., N. Blindow, B. Breuer, K. Grosfeld, T. Kleiner, C. O. Mohrholz, M. Nicolaus, C. Oelke, H. Sandhäger, and M. Thoma. "Numerical model studies of Antarctic ice-sheet–ice-shelf–ocean systems and ice caps." Annals of Glaciology 41 (2005): 111–20. http://dx.doi.org/10.3189/172756405781813186.

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AbstractThe cryosphere is an essential component of the global climate system, equally affecting climate processes significantly and being subject, and particularly sensitive, to changes in climate conditions. Numerical models are an important tool for assessing climate-change impacts on the Antarctic ice–sheet–ice–shelf–ocean system. They not only complement field and satellite remotesensing investigations but are often the only feasible alternative for addressing some of the important parameters and processes. Over the last few years, our group has made significant progress in developing and applying innovative numerical methods. In this paper, we provide a brief overview of some of the methods employed and the major results obtained for a number of case studies in the Atlantic sector of Antarctica.

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ZHAO Xiao, 赵晓, 侯晴宇 HOU Qingyu, 梁冰冰 LIANG Bingbing, and 张伟 ZHANG Wei. "A method for cloud detection in high-resolution remotesensing image based on multi-attribute fusion." Optical Technique 40, no. 2 (2014): 145–50. http://dx.doi.org/10.3788/gxjs20144002.0145.

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P. Madesh, P. Madesh, and N. Ravikumar N. Ravikumar. "Water Resource Management through Remotesensing and GIS in a Watershed of Gundlupet Taluk, Chamarajanagar District, Karnatak, India." Indian Journal of Applied Research 2, no. 1 (October 1, 2011): 50–52. http://dx.doi.org/10.15373/2249555x/oct2012/16.

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Raj, Nithu, and B. Gurugnanam. "STUDIES ON COASTAL GEOMORPHOLOGICAL LANDFORMS IN THE SOUTHEASTCOAST OF THIRUVALLUR COASTAL STRETCH, USING REMOTESENSING AND GIS TECHNIQUES." International Journal of Advanced Research 5, no. 3 (March 31, 2017): 1859–66. http://dx.doi.org/10.21474/ijar01/3702.

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Xie, Xiuchuan, Tao Yang, DongDong Li, Zhi Li, and Yanning Zhang. "Hierarchical Clustering-Aligning Framework Based Fast Large-Scale 3D Reconstruction Using Aerial Imagery." Remote Sensing 11, no. 3 (February 5, 2019): 315. http://dx.doi.org/10.3390/rs11030315.

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With extensive applications of Unmanned Aircraft Vehicle (UAV) in the field of remotesensing, 3D reconstruction using aerial images has been a vibrant area of research. However,fast large-scale 3D reconstruction is a challenging task. For aerial image datasets, large scale meansthat the number and resolution of images are enormous, which brings significant computationalcost to the 3D reconstruction, especially in the process of Structure from Motion (SfM). In thispaper, for fast large-scale SfM, we propose a clustering-aligning framework that hierarchicallymerges partial structures to reconstruct the full scene. Through image clustering, an overlappingrelationship between image subsets is established. With the overlapping relationship, we proposea similarity transformation estimation method based on joint camera poses of common images.Finally, we introduce the closed-loop constraint and propose a similarity transformation-based hybridoptimization method to make the merged complete scene seamless. The advantage of the proposedmethod is a significant efficiency improvement without a marginal loss in accuracy. Experimentalresults on the Qinling dataset captured over Qinling mountain covering 57 square kilometersdemonstrate the efficiency and robustness of the proposed method.

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Babu, P. Mynar, G. Jai Sankar, V. Sreenivasulu, and Dr K. Harikrishna. "Hydrochemical Analysis and Evaluation of Groundwater Quality in Part of Krishna District, Andhra Pradesh – Using Remotesensing and GIS Techniques." International Journal of Engineering Research 3, no. 8 (August 1, 2014): 476–81. http://dx.doi.org/10.17950/ijer/v3s8/801.

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Mohammedshum, A. A., M. A. Gebresilassie, C. M. Rulinda, G. H. Kahsay, and M. S. Tesfay. "Application of Geographic Information System and Remotesensing in effective solid waste disposal sites selection in Wukro town, Tigray, Ethiopia." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-2 (November 11, 2014): 115–19. http://dx.doi.org/10.5194/isprsarchives-xl-2-115-2014.

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Identifying solid waste disposal sites and appropriately managing them is a challenging task to many developing countries. This is a critical problem too in Ethiopia in general and in Wukro town in particular. The existing site for Wukro town is not sufficient in its capacity and it is damaging the environment due to its location, and the type of waste dumped, while the surrounding area is being irrigated. Due to the swift expansion and urbanization developments in Wukro town, it badly needs to develop controlled solid waste dumping site to prevent several contamination problems. This study was conducted first, to assess the existing waste management strategies in Wukro town; and second, to find out the potential waste disposal sites for the town, using GIS and Remote Sensing techniques. The study exploited the Multi-Criteria Evaluation (MCE) methods to combine necessary factors considered for dumping site selection. The selected method also uses various geographical data including remote sensing data, with GIS spatial analysis tools. Accordingly, site suitability maps for each of the factors were developed in a GIS environment. Results indicate that 12 dumping sites were appropriate and they were further ranked against their suitability in terms of wind direction, proximity to settlement area and distance from the center of the town. Finally, two sites are the best suitable for dumping site. This study indicated that the application of Geographic Information System and Remote Sensing techniques are efficient and low cost tools to study and select appropriate dumping site so as to facilitate decision making processes.

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Li, Zhu, Guo, and Chen. "A Graph Regularized Multilinear Mixing Model for Nonlinear Hyperspectral Unmixing." Remote Sensing 11, no. 19 (September 20, 2019): 2188. http://dx.doi.org/10.3390/rs11192188.

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Spectral unmixing of hyperspectral images is an important issue in the fields of remotesensing. Jointly exploring the spectral and spatial information embedded in the data is helpful toenhance the consistency between mixing/unmixing models and real scenarios. This paper proposesa graph regularized nonlinear unmixing method based on the recent multilinear mixing model(MLM). The MLM takes account of all orders of interactions between endmembers, and indicates thepixel-wise nonlinearity with a single probability parameter. By incorporating the Laplacian graphregularizers, the proposed method exploits the underlying manifold structure of the pixels’ spectra,in order to augment the estimations of both abundances and nonlinear probability parameters.Besides the spectrum-based regularizations, the sparsity of abundances is also incorporated for theproposed model. The resulting optimization problem is addressed by using the alternating directionmethod of multipliers (ADMM), yielding the so-called graph regularized MLM (G-MLM) algorithm.To implement the proposed method on large hypersepectral images in real world, we proposeto utilize a superpixel construction approach before unmixing, and then apply G-MLM on eachsuperpixel. The proposed methods achieve superior unmixing performances to state-of-the-artstrategies in terms of both abundances and probability parameters, on both synthetic and real datasets.

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García-Fernández, Marta, Enoc Sanz-Ablanedo, and José Ramón Rodríguez-Pérez. "High-Resolution Drone-Acquired RGB Imagery to Estimate Spatial Grape Quality Variability." Agronomy 11, no. 4 (March 30, 2021): 655. http://dx.doi.org/10.3390/agronomy11040655.

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Remotesensing techniques can help reduce time and resources spent collecting samples of crops and analyzing quality variables. The main objective of this work was to demonstrate that it is possible to obtain information on the distribution of must quality variables from conventional photographs. Georeferenced berry samples were collected and analyzed in the laboratory, and RGB images were taken using a low-cost drone from which an orthoimage was made. Transformation equations were calculated to obtain absolute reflectances for the different bands and to calculate 10 vegetation indices plus two new proposed indices. Correlations for the 12 indices with values for 15 must quality variables were calculated in terms of Pearson’s correlation coefficients. Significant correlations were obtained for 100-berries weight (0.77), malic acid (−0.67), alpha amino nitrogen (−0.59), phenolic maturation index (0.69), and the total polyphenol index (0.62), with 100-berries weight and the total polyphenol index obtaining the best results in the proposed RGB-based vegetation index 2 and RGB-based vegetation index 3. Our findings indicate that must variables important for the production of quality wines can be related to the RGB bands in conventional digital images, potentially improving and aiding management and increasing productivity.

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Conesa, Conejero, Vera, Ramírez-Cuesta, and Ruiz-Sánchez. "Terrestrial and Remote Indexes to Assess Moderate Deficit Irrigation in Early-Maturing Nectarine Trees." Agronomy 9, no. 10 (October 11, 2019): 630. http://dx.doi.org/10.3390/agronomy9100630.

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Monitoring plant water status is relevant for the sustainable management ofirrigation under water deficit conditions. Two treatments were applied to an early-maturingnectarine orchard: control (well irrigated) and precise deficit irrigation (PDI, based on soilwater content thresholds). Moderate water deficits generated by PDI were assessed bycomparing terrestrial: stem water potential (Ψstem) and gas exchange parameters, with remote:canopy temperature, normalized difference vegetation (NDVI), and soil adjusted vegetationindex (SAVI), plant water status indicators. The Ψstem was the only indicator that showedsignificant differences between treatments. NDVI and SAVI at the postharvest period wereappropriate indexes for estimating winter pruning, although they did not serve well as plantstress indicator. Vapor pressure deficit along with Ψstem values were able to predict remotesensing data. Ψstem and canopy to air temperature difference values registered the highestsignal intensity and NDVI the highest sensitivity for detecting water deficit situations. Theresults suggest that care should be taken when using instantaneous remote indicators toevaluate moderate water deficits in deciduous fruit trees; more severe/longer water stressconditions are probably needed. The proposed PDI strategy promoted water saving whilemaintaining yield, and could be considered a promising tool for semi-arid agrosystems.

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Kääb, Andreas, Frank Paul, Max Maisch, Martin Hoelzle, and Wilfried Haeberli. "The new remote-sensing-derived Swiss glacier inventory: II. First results." Annals of Glaciology 34 (2002): 362–66. http://dx.doi.org/10.3189/172756402781817473.

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AbstractComplete Swiss glacier inventories are available for 1850 (reconstructed) and 1973 (from aerial photography). Connected to the Global Land Ice Measurements from Space project, a new Swiss glacier inventory for approximately the year 2000 (SGI 2000) is compiled mainly based on satellite imagery. The developed and applied remotesensing and geographical information system (GIS) methods are described in part I of the contribution. In part II, the inventory design, first-result analyses and comparisons with former glacial conditions are presented. As basic entries SGI 2000 contains the individual glacier identification, planimetric glacier boundaries as derived from image analysis, digitized central flowlines and polygonal glacier basin maps. All other parameters are automatically deduced from the above entries and a digital elevation model within a GIS. Here, we analyze a set of small Bernese and Valais glaciers of area <10 km2. These glaciers lost about 21% of area from 1973 to 1998, in addition to about 80% during 1850–1973, both with respect to the 1973 area. In order to track the latest trend in more detail, anintermediate glacier condition has been compiled from satellite imagery of 1985. This analysis gave an increasing speed of area loss (19%) for 1985–98.

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Freile, Juan, Alejandro Solano-Ugalde, Dusan Brinkhuizen, Paul Greenfield, Mitch Lysinger, Jonas Nilsson, Lelis Navarrete, and Robert Ridgely. "FOURTH REPORT OF THE COMMITTEE FOR ECUADORIAN RECORDS IN ORNITHOLOGY (CERO) AND A REVISION OF UNDOCUMENTED AND ERRONEOUS RECORDS IN LITERATURE." Revista Ecuatoriana de Ornitología, no. 5 (January 1, 2020): 52–79. http://dx.doi.org/10.18272/reo.vi5.1277.

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We present new distributional records of birds in Ecuador submitted to the Committee for Ecuadorian Records in Ornithology (CERO) from September 2015 through July 2017. This report includes four species new to Ecuador (Plegadis ridgwayi, Cathartes burrovianus, Malacoptila mystacalis, Vireo gilvus), two species new to Galapagos (Calidris pugnax, Larosterna inca), five species with first documented country records (Fregata minor, Syrigma sibilatrix, Calidris pugnax, Larus belcheri, Sternula antillarum), remarkable range extensions for eight species (Anas bahamensis, Fregata sp., Jabiru mycteria, Phimosus infuscatus, Caracara cheriway, Larus dominicanus, Chloroceryle aenea, Sturnella militaris), new records of eight rare species (Anhima cornuta, Mustelirallus albicollis, Larus argentatus, Larosterna inca, Myrmoborus lugubris, Machetornis rixosa, Progne elegans, Conirostrum bicolor) and new records of Nothoprocta curvirostris and Tyrannus tyrannus. We present the first Ecuadorian records of three subspecies (Tolmomyias sulphurescens insignis, Myiarchus swainsoni phaenotus, Oxyura jamaicensis andina, although the taxonomic validity of the latter is debated). Further we discuss the subspecific identity of Petrochelidon pyrrhonota in Ecuador. Finally, we invalidate previous records of 43 species for mainland Ecuador and 6 species for Galapagos, as published in different sources, and reject a remotesensing record of Cypseloides niger. CERO revises and updates the country bird list, which currently stands at 1690 species (1632 confirmed and documented; 58 undocumented).

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Ben-Ahmed, Olfa, Thierry Urruty, Noel Richard, and Christine Fernandez-Maloigne. "Toward Content-Based Hyperspectral Remote Sensing Image Retrieval (CB-HRSIR): A Preliminary Study Based on Spectral Sensitivity Functions." Remote Sensing 11, no. 5 (March 12, 2019): 600. http://dx.doi.org/10.3390/rs11050600.

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With the emergence of huge volumes of high-resolution Hyperspectral Images (HSI)produced by different types of imaging sensors, analyzing and retrieving these images requireeffective image description and quantification techniques. Compared to remote sensing RGB images,HSI data contain hundreds of spectral bands (varying from the visible to the infrared ranges) allowingprofile materials and organisms that only hyperspectral sensors can provide. In this article, we studythe importance of spectral sensitivity functions in constructing discriminative representation ofhyperspectral images. The main goal of such representation is to improve image content recognitionby focusing the processing on only the most relevant spectral channels. The underlying hypothesisis that for a given category, the content of each image is better extracted through a specific set ofspectral sensitivity functions. Those spectral sensitivity functions are evaluated in a Content-BasedImage Retrieval (CBIR) framework. In this work, we propose a new HSI dataset for the remotesensing community, specifically designed for Hyperspectral remote sensing retrieval and classification.Exhaustive experiments have been conducted on this dataset and on a literature dataset. Obtainedretrieval results prove that the physical measurements and optical properties of the scene containedin the HSI contribute in an accurate image content description than the information provided by theRGB image presentation.

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Abuzar, Muhammad Khubaib, Muhammad Shafiq, Syed Amer Mahmood, Muhammad Irfan, Tayyaba Khalil, Nusaiba Khubaib, Amna Hamid, and Sobia Shaista. "Drought Risk Assessment in the Khushab Region of Pakistan Using Satellite Remote Sensing and Geospatial Methods." International Journal of Economic and Environmental Geology 10, no. 1 (May 24, 2019): 48–56. http://dx.doi.org/10.46660/ijeeg.vol10.iss1.2019.217.

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Drought is a harmful and slow natural phenomenon that has significant effects on the economy, social life,agriculture and environment of the country. Due to its slow process it is difficult to study this phenomenon. RemoteSensing and GIS tools play a key role in studying different hazards like droughts. The main objective of the study wasto investigate drought risk by using GIS and Remote Sensing techniques in district Khushab, Pakistan. Landsat ETMimages for the year 2003, 2009 and 2015 were utilized for spatial and temporal analysis of agricultural andmeteorological drought. Normalized difference vegetation index (NDVI) Standardized Precipitation Index (SPI) andrainfall anomaly indices were calculated to identify the drought prone areas in the study area. To monitormeteorological drought SPI values were used and NDVI was calculated for agricultural drought. These indices wereintegrated to compute the spatial and temporal drought maps. Three zones; no drought, slight drought and moderatedrought were identified. Final drought map shows that 30.21% of the area faces moderate drought, 28.36% faces slightdrought while nearly 41.3% faces no drought situation. Drought prevalence and severity is present more in the southernpart of Khushab district than the northern part. Most of the northern part is not under any type of drought. Thus, anoverall outcome of this study shows that risk areas can be assessed appropriately by integration of various data sourcesand thereby management plans can be prepared to deal with the hazard.

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Abuzar, Muhammad Khubaib, Muhammad Shafiq, Syed Amer Mahmood, Muhammad Irfan, Tayyaba Khalil, Nusaiba Khubaib, Amna Hamid, and Sobia Shaista. "Drought Risk Assessment in the Khushab Region of Pakistan Using Satellite Remote Sensing and Geospatial Methods." International Journal of Economic and Environmental Geology 10, no. 1 (May 24, 2019): 48–56. http://dx.doi.org/10.46660/ojs.v10i1.217.

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Drought is a harmful and slow natural phenomenon that has significant effects on the economy, social life,agriculture and environment of the country. Due to its slow process it is difficult to study this phenomenon. RemoteSensing and GIS tools play a key role in studying different hazards like droughts. The main objective of the study wasto investigate drought risk by using GIS and Remote Sensing techniques in district Khushab, Pakistan. Landsat ETMimages for the year 2003, 2009 and 2015 were utilized for spatial and temporal analysis of agricultural andmeteorological drought. Normalized difference vegetation index (NDVI) Standardized Precipitation Index (SPI) andrainfall anomaly indices were calculated to identify the drought prone areas in the study area. To monitormeteorological drought SPI values were used and NDVI was calculated for agricultural drought. These indices wereintegrated to compute the spatial and temporal drought maps. Three zones; no drought, slight drought and moderatedrought were identified. Final drought map shows that 30.21% of the area faces moderate drought, 28.36% faces slightdrought while nearly 41.3% faces no drought situation. Drought prevalence and severity is present more in the southernpart of Khushab district than the northern part. Most of the northern part is not under any type of drought. Thus, anoverall outcome of this study shows that risk areas can be assessed appropriately by integration of various data sourcesand thereby management plans can be prepared to deal with the hazard.

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Gultepe, I., T. Kuhn, M. Pavolonis, C. Calvert, J. Gurka, A. J. Heymsfield, P. S. K. Liu, et al. "Ice Fog in Arctic During FRAM–Ice Fog Project: Aviation and Nowcasting Applications." Bulletin of the American Meteorological Society 95, no. 2 (February 1, 2014): 211–26. http://dx.doi.org/10.1175/bams-d-11-00071.1.

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Ice fog and frost occur commonly (at least 26% of the time) in the northern latitudes and Arctic regions during winter at temperatures usually less than about –15°C. Ice fog is strongly related to frost formation—a major aviation hazard in the northern latitudes. In fact, it may be considered a more dangerous event than snow because of the stronger aircraft surface adhesion compared to snow particles. In the winter of 2010/11, the Fog Remote Sensing and Modeling–Ice Fog (FRAM-IF) project was organized near Yellowknife International Airport, Northwest Territories, Canada, with the main goals of advancing understanding of ice fog microphysical and visibility characteristics, and improving its prediction using forecast models and remotesensing retrievals. Approximately 40 different sensors were used to measure visibility, precipitation, ice particle spectra, vertical thermodynamic profiles, and ceiling height. Fog coverage and visibility parameters were estimated using both Geostationary Operational Environmental Satellites (GOES) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. During this project, the inversion layer usually was below a height of 1.5 km. High humidity typically was close to the ground, frequently producing ice fog, frost, and light snow precipitation. At low temperatures, snow crystals can be swept away by a very low wind speed (∼1 m s−1). Ice fog during the project was not predicted by any forecast model. These preliminary results in the northern latitudes suggest that ice fog and frost studies, over the Arctic regions, can help us to better understand ice microphysical processes such as ice nucleation, visibility, and parameterizations of ice fog.

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Normandin, Cassandra, Philippe Paillou, Sylvia Lopez, Eugene Marais, and Klaus Scipal. "Monitoring the Dynamics of Ephemeral Rivers from Space: An Example of the Kuiseb River in Namibia." Water 14, no. 19 (October 6, 2022): 3142. http://dx.doi.org/10.3390/w14193142.

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Ephemeral rivers are characterized by brief episodic flood events, which recharge subterraean alluvial aquifers that sustain humans, riparian vegetation, and wildlife in the hyper-arid Namib Desert. Yet we only have a poor understanding of the dynamics and feedback mechanisms in these hydrological systems as arid and semi-arid zones are typically poorly equipped with reliable in situ monitoring stations to provide necessary information. The main objective of our study is to show the potential of satellite data to monitor the dynamics of ephemeral rivers, such as the Kuiseb located in Namibia, since remotesensing offers the advantage of adapted spatial and temporal resolutions. For this study, multi-spectral imagery (Sentinel-2), Synthetic Aperture Radar (SAR, Sentinel-1), and SAR interferometry (Sentinel-1) data were used to produce Normalized Difference Vegetation Index (NDVI) maps, backscattering maps (as σ0), and interferograms, respectively. These parameters provide information on the hydrologic and vegetation dynamics of the river. Strong variations in NDVI, σ0, and interferograms are observed during March–April 2017 and June–July 2018 in a tributary of the Kuiseb in the central Namib Desert. In those years, rain events caused the reactivation of the tributary. However, during a major flood in 2021, when no rain occured, no variations in NDVI were detected in this tributary, unlike the σ0 and interferogram anomalies after the flood. Thus, these variations cannot be explained by rains, which were non-existent during this period, but seem to be linked to the dynamics of the aquifer of the Kuiseb River, wherein floods recharge the alluvial aquifers and the rising water table levels produce a signal that is measurable by satellite radar sensors. All these results present a preliminary work that might be used by water resource managers to automate the processing and methods used to create an ephemeral river monitoring tool.

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Birajdar, F., G. Venkataraman, I. Bahuguna, and H. Samant. "A Revised Glacier Inventory of Bhaga Basin Himachal Pradesh, India : Current Status and Recent Glacier Variations." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-8 (November 27, 2014): 37–43. http://dx.doi.org/10.5194/isprsannals-ii-8-37-2014.

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Himalayan glaciers show large uncertainty regarding their present and future state due to their sensitive reaction towards change in climatic condition. Himalayan glaciers are unique as they are located in tropical, high altitude regions, predominantly valley type and many are covered with debris. The great northern plains of India sustain on the perennial melt of glaciers meeting the water requirements of agriculture, industries, domestic sector even in the months of summer when large tracts of the country go dry. Therefore, it is important to monitor and assess the state of snow and glaciers and to know the sustainability of glaciers in view of changing global scenarios of climate and water security of the nation. Any information pertaining to Himalayan glaciers is normally difficult to be obtained by conventional means due to its harsh weather and rugged terrains. Due to the ecological diversity and geographical vividness, major part of the Indian Himalaya is largely un-investigated. Considering the fact that Himalayan glaciers are situated in a harsh environment, conventional techniques of their study is challenging and difficult both in terms of logistics and finances whereas the satellite remote sensing offers a potential mode for monitoring glaciers in long term. In order to gain an updated overview of the present state of the glacier cover and its changes since the previous inventories, an attempt has been made to generate a new remotesensing- derived glacier inventory on 1:50,000 scale for Bhaga basin (N32°28'19.7'' - N33°0'9.9'' ; E76°56'16.3'' - E77°25'23.7'' ) Western Himalaya covering an area of 1695.63 km2. having 231 glaciers and occupying glacierized area of 385.17 ±3.71 km2. ranging from 0.03 km2. to 29.28 km2. Glacier inventory has been carried out using high resolution IRS P6 LISS III data of 2011, ASTER DEM and other ancillary data. Specific measurements of mapped glacier features are the inputs for generating the glacier inventory data sheet with 37 parameters as per the UNESCO/TTS format, 11 additional parameters associated with the de-glaciated valley as per the suggestions of Space Application Center Ahmadabad and 9 newly introduced parameters of present study. The data sheet provides glacier wise details for each glacier on the significant glacier parameters like morphology, dimensions, orientation, elevation, etc. for both the active glacier component as well as the associated de-glaciated valley features. Assessment of recent variation in the glacierized area between 2001 and 2011. Results indicate that 231 glaciers covering an area of 391.56 ±3.76 km2. in 2001 has been reduced to 385.17 ±3.71 km2. in 2011; a loss of 1.63 ±1.0% in glacierized area within a period of 10 years. The present paper brings out the methodology adopted and salient results of the glacier inventory carried out which will help to enrich the existing database required for water resources assessment of the country and also meet the requirements of various researches working on climate change related studies.

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Ge, Yufeng, J. Alex Thomasson, Ruixiu Sui, and James Wooten. "Regression-kriging for characterizing soils with remotesensing data." Frontiers of Earth Science, June 21, 2011. http://dx.doi.org/10.1007/s11707-011-0174-1.

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Jiang, Xin, Alan D. Ziegler, Shijing Liang, Dashan Wang, and Zhenzhong Zeng. "Forest Restoration Potential in China: Implications for Carbon Capture." Journal of Remote Sensing 2022 (January 2022). http://dx.doi.org/10.34133/remotesensing.0006.

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Reforestation is an eco-friendly strategy for countering rising carbon dioxide concentrations in the atmosphere and the negative effects of forest loss and degradation. China, with one of the world’s most considerable afforestation rates, has increased its forest cover from 16.6% 20 years ago to 23.0% by 2020. However, the maximum potential forest coverage achieved via tree planting and restoration is uncertain. To map potential tree coverage across China, we developed a random forest regression model relating environmental factors and appropriate forest types. We estimate 67.2 million hectares of land currently available for tree restoration after excluding existing forested areas, urban areas, and agriculture land covers/uses, which is 50% higher than the current understanding. Converting these lands to the forest would generate 3.99 gigatons of new above- and belowground carbon stocks, representing an important contribution to achieving carbon neutrality. This potential is spatially imbalanced, with the largest restorable carbon potential being located in the southwest (29.5%), followed by the northeast (17.2%) and northwest (16.8%). Our study highlights the need to align tree restoration areas with the uneven distribution of carbon sequestration potential. In addition to being a biological mitigation strategy to partially offset carbon dioxide emissions from fossil fuel burning, reforestation should provide other environmental services such as the restoration of degraded soils, conservation of biological diversity, revitalization of hydrological integrity, localized cooling, and improvement in air quality. Because of the collective benefits of forest restoration, we encourage that such activities be ecosystem focused as opposed to solely focusing on tree planting.

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Liu, Xiaoqiang, Qin Ma, Xiaoyong Wu, Tianyu Hu, Guanhua Dai, Jin Wu, Shengli Tao, et al. "Nonscalability of Fractal Dimension to Quantify Canopy Structural Complexity from Individual Trees to Forest Stands." Journal of Remote Sensing 2022 (January 2022). http://dx.doi.org/10.34133/remotesensing.0001.

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Canopy structural complexity is a critical emergent forest attribute, and light detection and ranging (lidar)-based fractal dimension has been recognized as its powerful measure at the individual tree level. However, the current lidar-based estimation method is highly sensitive to data characteristics, and its scalability from individual trees to forest stands remains unclear. This study proposed an improved method to estimate fractal dimension from lidar data by considering Shannon entropy, and evaluated its scalability from individual trees to forest stands through mathematical derivations. Moreover, a total of 280 forest stand scenes simulated from the terrestrial lidar data of 115 trees spanning large variability in canopy structural complexity were used to evaluate the robustness of the proposed method and the scalability of fractal dimension. The results show that the proposed method can significantly improve the robustness of lidar-derived fractal dimensions. Both mathematical derivations and experimental analyses demonstrate that the fractal dimension of a forest stand is equal to that of the tree with the largest fractal dimension in it, manifesting its nonscalability from individual trees to forest stands. The nonscalability of fractal dimension reveals its limited capability in canopy structural complexity quantification and indicates that the power-law scaling theory of a forest stand underlying fractal geometry is determined by its dominant tree instead of the entire community. Nevertheless, we believe that fractal dimension is still a useful indicator of canopy structural complexity at the individual tree level and might be used along with other stand-level indexes to reflect the “tree-to-stand” correlation of canopy structural complexity.

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Li, Ming, Jingzhi Li, Yuting Liu, and Fan Liu. "Detail Injection-Based Convolutional Auto-Encoder for Pansharpening." Journal of Remote Sensing 2022 (January 2022). http://dx.doi.org/10.34133/remotesensing.0004.

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The purpose of pansharpening is to generate high-resolution multispectral (MS) images using both low-resolution MS images and high-resolution panchromatic images. Traditional remote sensing image fusion algorithms can be simplified to a unified detail injection (Di) context that treats the injected MS details as panchromatic-detail and integration with injection gain. The injected details are developed from traditional fusion strategies with clear physical interpretation and facilitate fast convergence of deep learning models for high-quality image fusion. The excellent ability of convolutional autoencoder (CAE) networks to retain image information enables its application to remote sensing image fusion. In this paper, a fusion method Di-based CAE (DiCAE) based on Di and CAE is proposed. DiCAE method is based on Di as the theoretical foundation and CAE network as the core of the algorithm. In addition, our method is evaluated through experiments on different satellite datasets, and the fusion results obtained by DiCAE have better objective evaluation metrics and better visual results compared to other state-of-the-art methods.

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Qi, Jianbo, Jingyi Jiang, Kun Zhou, Donghui Xie, and Huaguo Huang. "Fast and Accurate Simulation of Canopy Reflectance under Wavelength-Dependent Optical Properties Using a Semi-Empirical 3D Radiative Transfer Model." Journal of Remote Sensing, December 28, 2022. http://dx.doi.org/10.34133/remotesensing.0017.

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Chang, Zhongbing, Lei Fan, Jean-Pierre Wigneron, Ying-Ping Wang, Philippe Ciais, Jérôme Chave, Rasmus Fensholt, et al. "Estimating aboveground carbon dynamic of China using optical and microwave remote sensing datasets from 2013 to 2019." Journal of Remote Sensing, January 5, 2023. http://dx.doi.org/10.34133/remotesensing.0005.

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Jin, Suming, Jon Dewitz, Patrick Danielson, Brian Granneman, Catherine Costello, Kelcy Smith, and Zhe Zhu. "National Land Cover Database 2019: A new strategy for creating clean leaf-on and leaf-off Landsat composite images." Journal of Remote Sensing, January 11, 2023. http://dx.doi.org/10.34133/remotesensing.0022.

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Morales, Carmen, Alfonso Sanchez-Paus Díaz, Daniel Dionisio, Laura Guarnieri, Giulio Marchi, Danae Maniatis, and Danilo Mollicone. "Earth Map: A Novel Tool for Fast Performance of Advanced Land Monitoring and Climate Assessment." Journal of Remote Sensing 3 (January 2023). http://dx.doi.org/10.34133/remotesensing.0003.

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Earth Map ( https://earthmap.org/ ) is an innovative and free application developed by the Food and Agriculture Organization of the United Nations that was designed in the framework of the Food and Agriculture Organization of the United Nations–Google partnership and facilitates the visualization, processing, and analysis of land and climate data. Earth Map makes petabytes of multitemporal, multiscale, multiparametric, and quasi-real-time satellite imagery and geospatial datasets available to any user thanks to the power of Google Earth Engine ( https://earthengine.google.com/ ) and a point-and-click graphical user interface. These are further complemented with more planetary-scale analytical capabilities so that global and local changes and trends on Earth’s surface can be easily detected, quantified, and visualized. It does not require users to master coding techniques, thereby avoiding bottlenecks in terms of technical capacities of nonexpert users. It ultimately paves the way for countries, research institutes, farmers, and members of the general public to access critical knowledge to develop science-based policy interventions, leverage investments, and sustain livelihoods. We provide a full overview of Earth Map’s software architecture, design, features, and datasets. To illustrate the possible applications of the tool, different examples are presented including a few case studies that show how quick historical analysis of environmental and climate parameters can be performed and research questions answered. The examples demonstrate that Earth Map is a comprehensive and user-friendly tool for land monitoring and climate assessment and that it has the potential to be used to assess land use, land use change, climate change impacts, and natural disasters.

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Liu, Quanyong, Jiangtao Peng, Genwei Zhang, Weiwei Sun, and Qian Du. "Deep Contrastive Learning Network for Small-Sample Hyperspectral Image Classification." Journal of Remote Sensing, January 19, 2023. http://dx.doi.org/10.34133/remotesensing.0025.

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"The design of environmental geographic information systems." Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences 324, no. 1579 (March 31, 1988): 373–80. http://dx.doi.org/10.1098/rsta.1988.0026.

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The development of geographic information systems (gis) is recognized as a prerequisite for the effective exploitation of remotely sensed data. Current commercial systems represent a solution with a strong bias from either the mapping or the remotesensing market. They thus lack full cross discipline functionality and a model-oriented approach. This paper examines some of the key issues in truly integrated gis design. The five data types of image, object (vector), terrain, tabular and knowledge are identified along with the operations required with them within a gis. The term ‘geoschema’ is introduced (analogous to schema within a database) to describe the organization of the geographical datasets. Three-dimensional data handling, the necessity of qualifying data and the user interface are given particular attention. An efficient method of implementing an integrated spatial index into the data sets is described. 1

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Li, Sheng, Zhenyu Xing, and du ke. "Evaluation of a Gaussian dispersiontransformation technique for tomographicmapping of concentration field of atmosphericchemicals using multi-path optical remotesensing." Applied Optics, May 2, 2022. http://dx.doi.org/10.1364/ao.453052.

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"Recent ionospheric observations relating to solar-wind-magnetosphere coupling." Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences 328, no. 1598 (June 14, 1989): 93–105. http://dx.doi.org/10.1098/rsta.1989.0026.

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Simultaneous observations in the high-latitude ionosphere and in the near-Earth interplanetary medium have revealed the control exerted by the interplanetary magnetic field and the solar wind flow on field-perpendicular convection of plasma in both the ionosphere and the magnetosphere. Previous studies, using statistical surveys of data from both low-altitude polar-orbiting satellites and ground-based radars and magnetometers, have established that magnetic reconnection at the dayside magnetopause is the dominant driving mechanism for convection. More recently, ground-based data and global auroral images of higher temporal resolution have been obtained and used to study the response of the ionospheric flows to changes in the interplanetary medium. These observations show that ionospheric convection responds rapidly (within a few minutes) to both increases and decreases in the reconnection rate over a range of spatial scales, as well as revealing transient enhancements which are also thought to be related to magnetopause phenomena. Such results emphasize the potential of ground-based radars and other remotesensing instruments for studies of the Earth’s interaction with the interplanetary medium.

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Journal articles on the topic 'RemoteSensing'

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