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Artigos de revistas sobre o tema "Sub-Meter resolution imagery"

Autor: Grafiati

Publicado: 31 de agosto de 2024

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1

Almeida, Luís, Rafael Almar, Erwin Bergsma, et al. "Deriving High Spatial-Resolution Coastal Topography From Sub-meter Satellite Stereo Imagery." Remote Sensing 11, no. 5 (2019): 590. http://dx.doi.org/10.3390/rs11050590.

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High spatial resolution coastal Digital Elevation Models (DEMs) are crucial to assess coastal vulnerability and hazards such as beach erosion, sedimentation, or inundation due to storm surges and sea level rise. This paper explores the possibility to use high spatial-resolution Pleiades (pixel size = 0.7 m) stereoscopic satellite imagery to retrieve a DEM on sandy coastline. A 40-km coastal stretch in the Southwest of France was selected as a pilot-site to compare topographic measurements obtained from Pleiades satellite imagery, Real Time Kinematic GPS (RTK-GPS) and airborne Light Detection a

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Tian, J., X. Zhuo, X. Yuan, C. Henry, P. d’Angelo, and T. Krauss. "APPLICATION ORIENTED QUALITY EVALUATION OF GAOFEN-7 OPTICAL STEREO SATELLITE IMAGERY." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2022 (May 17, 2022): 145–52. http://dx.doi.org/10.5194/isprs-annals-v-1-2022-145-2022.

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Abstract. GaoFen-7 (GF-7) satellite mission is further expanding the very high resolution 3D mapping application. Carrying the first civilian Chinese sub-meter resolution stereo satellite sensors, GF-7 satellite was launched on November 7, 2019. With 0.65 meter resolution on backward view and 0.8 meter resolution forward view, GF-7 has been designed to meet the demand of natural resource monitoring, land surveying, and other mapping applications in China. The use of GF-7 for 3D city reconstruction is unfortunately restricted by the fixed large stereo view angle of forward and backward cameras

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Manos, Elias, Chandi Witharana, Mahendra Rajitha Udawalpola, Amit Hasan, and Anna K. Liljedahl. "Convolutional Neural Networks for Automated Built Infrastructure Detection in the Arctic Using Sub-Meter Spatial Resolution Satellite Imagery." Remote Sensing 14, no. 11 (2022): 2719. http://dx.doi.org/10.3390/rs14112719.

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Rapid global warming is catalyzing widespread permafrost degradation in the Arctic, leading to destructive land-surface subsidence that destabilizes and deforms the ground. Consequently, human-built infrastructure constructed upon permafrost is currently at major risk of structural failure. Risk assessment frameworks that attempt to study this issue assume that precise information on the location and extent of infrastructure is known. However, complete, high-quality, uniform geospatial datasets of built infrastructure that are readily available for such scientific studies are lacking. While im

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Xu, Huiyao, Jia Song, and Yunqiang Zhu. "Evaluation and Comparison of Semantic Segmentation Networks for Rice Identification Based on Sentinel-2 Imagery." Remote Sensing 15, no. 6 (2023): 1499. http://dx.doi.org/10.3390/rs15061499.

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Efficient and accurate rice identification based on high spatial and temporal resolution remote sensing imagery is essential for achieving precision agriculture and ensuring food security. Semantic segmentation networks in deep learning are an effective solution for crop identification, and they are mainly based on two architectures: the commonly used convolutional neural network (CNN) architecture and the novel Vision Transformer architecture. Research on crop identification from remote sensing imagery using Vision Transformer has only emerged in recent times, mostly in sub-meter resolution o

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Yalcin, I., S. Kocaman, S. Saunier, and C. Albinet. "RADIOMETRIC QUALITY ASSESSMENT FOR MAXAR HD IMAGERY." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 29, 2021): 797–804. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-797-2021.

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Abstract. The requirement for very high-resolution satellite imagery by different applications has been increasing continuously. Several commercial and government-supported missions provide sub-meter spatial resolutions from optical sensors aboard Earth Observation (EO) satellites. The MAXAR satellite constellation acquires images with up to 30 cm Ground Sampling Distances (GSDs); and the High-Definition (HD) image production technology developed by MAXAR doubles the resolution by using artificial intelligence methods. Although the spatial resolution is one of the most important image quality

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Farella, E. M., F. Remondino, C. Cahalane, et al. "GEOMETRIC PROCESSING OF VERY HIGH-RESOLUTION SATELLITE IMAGERY: QUALITY ASSESSMENT FOR 3D MAPPING NEEDS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W3-2023 (October 19, 2023): 47–54. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-47-2023.

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Abstract. In recent decades, the geospatial domain has benefitted from technological advances in sensors, methodologies, and processing tools to expand capabilities in mapping applications. Airborne techniques (LiDAR and aerial photogrammetry) generally provide most of the data used for this purpose. However, despite the relevant accuracy of these technologies and the high spatial resolution of airborne data, updates are not sufficiently regular due to significant flight costs and logistics. New possibilities to fill this information gap have emerged with the advent of Very High Resolution (VH

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Udawalpola, M., A. Hasan, A. K. Liljedahl, A. Soliman, and C. Witharana. "OPERATIONAL-SCALE GEOAI FOR PAN-ARCTIC PERMAFROST FEATURE DETECTION FROM HIGH-RESOLUTION SATELLITE IMAGERY." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-M-3-2021 (August 10, 2021): 175–80. http://dx.doi.org/10.5194/isprs-archives-xliv-m-3-2021-175-2021.

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Abstract. Regional extent and spatiotemporal dynamics of Arctic permafrost disturbances remain poorly quantified. High spatial resolution commercial satellite imagery enables transformational opportunities to observe, map, and document the micro-topographic transitions occurring in Arctic polygonal tundra at multiple spatial and temporal frequencies. The entire Arctic has been imaged at 0.5 m or finer resolution by commercial satellite sensors. The imagery is still largely underutilized, and value-added Arctic science products are rare. Knowledge discovery through artificial intelligence (AI),

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Höschle, Caroline, Hannah C. Cubaynes, Penny J. Clarke, Grant Humphries, and Alex Borowicz. "The Potential of Satellite Imagery for Surveying Whales." Sensors 21, no. 3 (2021): 963. http://dx.doi.org/10.3390/s21030963.

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The emergence of very high-resolution (VHR) satellite imagery (less than 1 m spatial resolution) is creating new opportunities within the fields of ecology and conservation biology. The advancement of sub-meter resolution imagery has provided greater confidence in the detection and identification of features on the ground, broadening the realm of possible research questions. To date, VHR imagery studies have largely focused on terrestrial environments; however, there has been incremental progress in the last two decades for using this technology to detect cetaceans. With advances in computatio

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Wohlfeil, J., H. Hirschmüller, B. Piltz, A. Börner, and M. Suppa. "FULLY AUTOMATED GENERATION OF ACCURATE DIGITAL SURFACE MODELS WITH SUB-METER RESOLUTION FROM SATELLITE IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B3 (July 23, 2012): 75–80. http://dx.doi.org/10.5194/isprsarchives-xxxix-b3-75-2012.

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Belart, Joaquín M. C., Etienne Berthier, Eyjólfur Magnússon, et al. "Winter mass balance of Drangajökull ice cap (NW Iceland) derived from satellite sub-meter stereo images." Cryosphere 11, no. 3 (2017): 1501–17. http://dx.doi.org/10.5194/tc-11-1501-2017.

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Abstract. Sub-meter resolution, stereoscopic satellite images allow for the generation of accurate and high-resolution digital elevation models (DEMs) over glaciers and ice caps. Here, repeated stereo images of Drangajökull ice cap (NW Iceland) from Pléiades and WorldView2 (WV2) are combined with in situ estimates of snow density and densification of firn and fresh snow to provide the first estimates of the glacier-wide geodetic winter mass balance obtained from satellite imagery. Statistics in snow- and ice-free areas reveal similar vertical relative accuracy (< 0.5 m) with and without gro

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Gong, K., and D. Fritsch. "A DETAILED STUDY ABOUT DIGITAL SURFACE MODEL GENERATION USING HIGH RESOLUTION SATELLITE STEREO IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 1, 2016): 69–76. http://dx.doi.org/10.5194/isprsannals-iii-1-69-2016.

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Photogrammetry is currently in a process of renaissance, caused by the development of dense stereo matching algorithms to provide very dense Digital Surface Models (DSMs). Moreover, satellite sensors have improved to provide sub-meter or even better Ground Sampling Distances (GSD) in recent years. Therefore, the generation of DSM from spaceborne stereo imagery becomes a vivid research area. This paper presents a comprehensive study about the DSM generation of high resolution satellite data and proposes several methods to implement the approach. The bias-compensated Rational Polynomial Coeffici

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Gong, K., and D. Fritsch. "A DETAILED STUDY ABOUT DIGITAL SURFACE MODEL GENERATION USING HIGH RESOLUTION SATELLITE STEREO IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 1, 2016): 69–76. http://dx.doi.org/10.5194/isprs-annals-iii-1-69-2016.

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Photogrammetry is currently in a process of renaissance, caused by the development of dense stereo matching algorithms to provide very dense Digital Surface Models (DSMs). Moreover, satellite sensors have improved to provide sub-meter or even better Ground Sampling Distances (GSD) in recent years. Therefore, the generation of DSM from spaceborne stereo imagery becomes a vivid research area. This paper presents a comprehensive study about the DSM generation of high resolution satellite data and proposes several methods to implement the approach. The bias-compensated Rational Polynomial Coeffici

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13

Martinuzzi, Sebastián, Olga M. Ramos-González, Tischa A. Muñoz-Erickson, Dexter H. Locke, Ariel E. Lugo, and Volker C. Radeloff. "Vegetation cover in relation to socioeconomic factors in a tropical city assessed from sub-meter resolution imagery." Ecological Applications 28, no. 3 (2018): 681–93. http://dx.doi.org/10.1002/eap.1673.

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Soroush, Mehrnoush, Alireza Mehrtash, Emad Khazraee, and Jason A. Ur. "Deep Learning in Archaeological Remote Sensing: Automated Qanat Detection in the Kurdistan Region of Iraq." Remote Sensing 12, no. 3 (2020): 500. http://dx.doi.org/10.3390/rs12030500.

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In this paper, we report the results of our work on automated detection of qanat shafts on the Cold War-era CORONA Satellite Imagery. The increasing quantity of air and space-borne imagery available to archaeologists and the advances in computational science have created an emerging interest in automated archaeological detection. Traditional pattern recognition methods proved to have limited applicability for archaeological prospection, for a variety of reasons, including a high rate of false positives. Since 2012, however, a breakthrough has been made in the field of image recognition through

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Li, S., and H. Tang. "BUILDING DAMAGE EXTRACTION TRIGGERED BY EARTHQUAKE USING THE UAV IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 929–36. http://dx.doi.org/10.5194/isprs-archives-xlii-3-929-2018.

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When extracting building damage information, we can only determine whether the building is collapsed using the post-earthquake satellite images. Even the satellite images have the sub-meter resolution, the identification of slightly damaged buildings is still a challenge. As the complementary data to satellite images, the UAV images have unique advantages, such as stronger flexibility and higher resolution. In this paper, according to the spectral feature of UAV images and the morphological feature of the reconstructed point clouds, the building damage was classified into four levels: basicall

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d'Angelo, P., G. Kuschk, and P. Reinartz. "Evaluation of Skybox Video and Still Image products." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1 (November 7, 2014): 95–99. http://dx.doi.org/10.5194/isprsarchives-xl-1-95-2014.

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The SkySat-1 satellite lauched by Skybox Imaging on November 21 in 2013 opens a new chapter in civilian earth observation as it is the first civilian satellite to image a target in high definition panchromatic video for up to 90 seconds. The small satellite with a mass of 100 kg carries a telescope with 3 frame sensors. Two products are available: Panchromatic video with a resolution of around 1 meter and a frame size of 2560 &times; 1080 pixels at 30 frames per second. Additionally, the satellite can collect still imagery with a swath of 8 km in the panchromatic band, and multispectral im

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Tang, Hongzhao, Junfeng Xie, Xinming Tang, Wei Chen, and Qi Li. "On-Orbit Radiometric Performance of GF-7 Satellite Multispectral Imagery." Remote Sensing 14, no. 4 (2022): 886. http://dx.doi.org/10.3390/rs14040886.

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China’s first civilian, sub-meter, high-resolution stereo mapping satellite, GF-7, launched on 3 November 2019. Radiometric characterization of GF-7 multispectral imagery has been performed in this study. A relative radiometric accuracy evaluation of the GF-7 multispectral imagery was performed using several large uniform scenes, and the results showed that the accuracy is better than 2%. The absolute radiometric evaluation of the GF-7 satellite sensor was conducted at the Baotou and Dunhuang calibration sites, using the reflectance-based vicarious approach. The synchronous measurements of sur

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Boldt, M., A. Thiele, K. Schulz, and S. Hinz. "SAR Image Segmentation Using Morphological Attribute Profiles." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3 (August 11, 2014): 39–44. http://dx.doi.org/10.5194/isprsarchives-xl-3-39-2014.

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In the last years, the spatial resolution of remote sensing sensors and imagery has continuously improved. Focusing on spaceborne Synthetic Aperture Radar (SAR) sensors, the satellites of the current generation (TerraSAR-X, COSMO-SykMed) are able to acquire images with sub-meter resolution. Indeed, high resolution imagery is visually much better interpretable, but most of the established pixel-based analysis methods have become more or less impracticable since, in high resolution images, self-sufficient objects (vehicle, building) are represented by a large number of pixels. Methods dealing wi

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Zhang, Weixing, Chandi Witharana, Anna Liljedahl, and Mikhail Kanevskiy. "Deep Convolutional Neural Networks for Automated Characterization of Arctic Ice-Wedge Polygons in Very High Spatial Resolution Aerial Imagery." Remote Sensing 10, no. 9 (2018): 1487. http://dx.doi.org/10.3390/rs10091487.

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The microtopography associated with ice-wedge polygons governs many aspects of Arctic ecosystem, permafrost, and hydrologic dynamics from local to regional scales owing to the linkages between microtopography and the flow and storage of water, vegetation succession, and permafrost dynamics. Wide-spread ice-wedge degradation is transforming low-centered polygons into high-centered polygons at an alarming rate. Accurate data on spatial distribution of ice-wedge polygons at a pan-Arctic scale are not yet available, despite the availability of sub-meter-scale remote sensing imagery. This is becaus

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Hasan, A., M. R. Udawalpola, C. Witharana, and A. K. Liljedahl. "COUNTING ICE-WEDGE POLYGONS FROM SPACE: USE OF COMMERCIAL SATELLITE IMAGERY TO MONITOR CHANGING ARCTIC POLYGONAL TUNDRA." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-M-3-2021 (August 10, 2021): 67–72. http://dx.doi.org/10.5194/isprs-archives-xliv-m-3-2021-67-2021.

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Abstract. The microtopography associated with ice wedge polygons (IWPs) governs the Arctic ecosystem from local to regional scales due to the impacts on the flow and storage of water and therefore, vegetation and carbon. Increasing subsurface temperatures in Arctic permafrost landscapes cause differential ground settlements followed by a series of adverse microtopographic transitions at sub decadal scale. The entire Arctic has been imaged at 0.5 m or finer resolution by commercial satellite sensors. Dramatic microtopographic transformation of low-centered into high-centered IWPs can be identif

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Manos, Elias, Chandi Witharana, Amal S. Perera, and Anna K. Liljedahl. "A multi-objective comparison of CNN architectures in Arctic human-built infrastructure mapping from sub-meter resolution satellite imagery." International Journal of Remote Sensing 44, no. 24 (2023): 7670–705. http://dx.doi.org/10.1080/01431161.2023.2287563.

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Duchesne, Rocio R., Mark J. Chopping, and Ken D. Tape. "Capability of the CANAPI algorithm to derive shrub structural parameters from satellite imagery in the Alaskan Arctic." Polar Record 52, no. 2 (2015): 124–33. http://dx.doi.org/10.1017/s0032247415000509.

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ABSTRACTThe observed greening of Arctic vegetation and the expansion of shrubs in the last few decades probably have profound implications for the tundra ecosystem, including feedbacks to climate. Uncertainty surrounding this vegetation shift and its implications calls for monitoring of vegetation structural parameters, such as fractional cover of shrubs. In this study, CANAPI, a semi-automated image interpretation algorithm that identifies and traces crowns by locating its crescent-shaped sunlit portion, was evaluated for its ability to derive structural data for tall (> 0.5 m) shrubs in t

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Witharana, Chandi, Mahendra R. Udawalpola, Anna K. Liljedahl, et al. "Automated Detection of Retrogressive Thaw Slumps in the High Arctic Using High-Resolution Satellite Imagery." Remote Sensing 14, no. 17 (2022): 4132. http://dx.doi.org/10.3390/rs14174132.

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Retrogressive thaw slumps (RTS) are considered one of the most dynamic permafrost disturbance features in the Arctic. Sub-meter resolution multispectral imagery acquired by very high spatial resolution (VHSR) commercial satellite sensors offer unique capacities in capturing the morphological dynamics of RTSs. The central goal of this study is to develop a deep learning convolutional neural net (CNN) model (a UNet-based workflow) to automatically detect and characterize RTSs from VHSR imagery. We aimed to understand: (1) the optimal combination of input image tile size (array size) and the CNN

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McCarty, J. L., C. S. R. Neigh, M. L. Carroll, and M. R. Wooten. "Extracting smallholder cropped area in Tigray, Ethiopia with wall-to-wall sub-meter WorldView and moderate resolution Landsat 8 imagery." Remote Sensing of Environment 202 (December 2017): 142–51. http://dx.doi.org/10.1016/j.rse.2017.06.040.

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Cruz, C., A. C. Blanco, J. Babaan, J. A. Cruz, R. R. Sta. Ana, and E. Paringit. "LINEAR SPECTRAL UNMIXING OF SENTINEL-3 IMAGERY FOR URBAN LAND COVER - LAND SURFACE TEMPERATURE (LST) ANALYSIS: A CASE STUDY OF METRO MANILA, PHILIPPINES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W19 (December 23, 2019): 141–48. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w19-141-2019.

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Abstract. The advancement of remote sensing technologies is a huge advantage in various environmental applications including the monitoring of the rapid development in an urban area. This study aims to estimate the composition of the different classes (vegetation, impervious surfaces, soil) in Metro Manila, Philippines using a 300-meter spatial resolution Sentinel-3 Ocean and Land Colour Instrument image. The relationship between these land cover fractions with the spatial distribution of land surface temperature at this scale is evaluated. Sentinel-3 image has a higher spectral resolution (i.

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Su, S., L. Fanara, X. Zhang, K. Gwinner, E. Hauber, and J. Oberst. "DETECTING THE SOURCES OF ICE BLOCK FALLS AT THE MARTIAN NORTH POLAR SCARPS BY ANALYSIS OF MULTI-TEMPORAL HIRISE IMAGERY." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 29, 2021): 673–78. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-673-2021.

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Abstract. We have developed a method for automatically detecting the sources of ice block falls at the Martian north polar scarps. Multitemporal red-filter High Resolution Imaging Science Experiment (HiRISE) images were processed by using the open source NASA Ames Stereo Pipeline in combination with the USGS Integrated Software for Imagers and Spectrometers to produce 0.25 m resolution images as well as a 1 m resolution DTM. The multi-temporal HiRISE images were firstly ortho-rectified by the DTM, and then co-registered by using the Enhanced Correlation Coefficient Maximization (ECC) algorithm

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Issa, S. M., B. S. Dahy, and N. Saleous. "ACCURATE MAPPING OF DATE PALMS AT DIFFERENT AGE-STAGES FOR THE PURPOSE OF ESTIMATING THEIR BIOMASS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2020 (August 3, 2020): 461–67. http://dx.doi.org/10.5194/isprs-annals-v-3-2020-461-2020.

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Abstract. The main objective of the current study was to produce an accurate map of date palm (DP) plantations in the Emirate of Abu Dhabi in United Arab Emirates (UAE) using moderate resolution Landsat-8 (OLI) imagery. The second objective was to be able to create a more detailed map depicting three different categories of date palms at three different age stages: young, medium, and mature. This was achieved using a hierarchical integrated approach: first, Landsat-8 OLI imagery were used to map mature date palms in the study area; second, an object oriented classification (OOC) approach was a

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Naughton, Joseph, and Walter McDonald. "Evaluating the Variability of Urban Land Surface Temperatures Using Drone Observations." Remote Sensing 11, no. 14 (2019): 1722. http://dx.doi.org/10.3390/rs11141722.

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Urbanization and climate change are driving increases in urban land surface temperatures that pose a threat to human and environmental health. To address this challenge, we must be able to observe land surface temperatures within spatially complex urban environments. However, many existing remote sensing studies are based upon satellite or aerial imagery that capture temperature at coarse resolutions that fail to capture the spatial complexities of urban land surfaces that can change at a sub-meter resolution. This study seeks to fill this gap by evaluating the spatial variability of land surf

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Ganeva, Dessislava, Eugenia Roumenina, Petar Dimitrov, et al. "Preharvest Durum Wheat Yield, Protein Content, and Protein Yield Estimation Using Unmanned Aerial Vehicle Imagery and Pléiades Satellite Data in Field Breeding Experiments." Remote Sensing 16, no. 3 (2024): 559. http://dx.doi.org/10.3390/rs16030559.

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Unmanned aerial vehicles (UAVs) are extensively used to gather remote sensing data, offering high image resolution and swift data acquisition despite being labor-intensive. In contrast, satellite-based remote sensing, providing sub-meter spatial resolution and frequent revisit times, could serve as an alternative data source for phenotyping. In this study, we separately evaluated pan-sharpened Pléiades satellite imagery (50 cm) and UAV imagery (2.5 cm) to phenotype durum wheat in small-plot (12 m × 1.10 m) breeding trials. The Gaussian process regression (GPR) algorithm, which provides predict

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Kaiser, Soraya, Guido Grosse, Julia Boike, and Moritz Langer. "Monitoring the Transformation of Arctic Landscapes: Automated Shoreline Change Detection of Lakes Using Very High Resolution Imagery." Remote Sensing 13, no. 14 (2021): 2802. http://dx.doi.org/10.3390/rs13142802.

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Water bodies are a highly abundant feature of Arctic permafrost ecosystems and strongly influence their hydrology, ecology and biogeochemical cycling. While very high resolution satellite images enable detailed mapping of these water bodies, the increasing availability and abundance of this imagery calls for fast, reliable and automatized monitoring. This technical work presents a largely automated and scalable workflow that removes image noise, detects water bodies, removes potential misclassifications from infrastructural features, derives lake shoreline geometries and retrieves their moveme

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Xia, T., W. P. Kustas, M. C. Anderson, et al. "Mapping evapotranspiration with high resolution aircraft imagery over vineyards using one and two source modeling schemes." Hydrology and Earth System Sciences Discussions 12, no. 11 (2015): 11905–57. http://dx.doi.org/10.5194/hessd-12-11905-2015.

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Abstract. Thermal and multispectral remote sensing data from low-altitude aircraft can provide high spatial resolution necessary for sub-field (≤ 10 m) and plant canopy (≤ 1m) scale evapotranspiration (ET) monitoring. In this study, high resolution aircraft sub-meter scale thermal infrared and multispectral shortwave data are used to map ET over vineyards in central California with the Two Source Energy Balance (TSEB) model and with a simple model called DATTUTDUT (Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature) which uses contextual information within the image to

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Kaiser, Soraya, Julia Boike, Guido Grosse, and Moritz Langer. "The Potential of UAV Imagery for the Detection of Rapid Permafrost Degradation: Assessing the Impacts on Critical Arctic Infrastructure." Remote Sensing 14, no. 23 (2022): 6107. http://dx.doi.org/10.3390/rs14236107.

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Ground subsidence and erosion processes caused by permafrost thaw pose a high risk to infrastructure in the Arctic. Climate warming is increasingly accelerating the thawing of permafrost, emphasizing the need for thorough monitoring to detect damages and hazards at an early stage. The use of unoccupied aerial vehicles (UAVs) allows a fast and uncomplicated analysis of sub-meter changes across larger areas compared to manual surveys in the field. In our study, we investigated the potential of photogrammetry products derived from imagery acquired with off-the-shelf UAVs in order to provide a low

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Wang, Zifeng, Junguo Liu, Jinbao Li, and David Zhang. "Multi-Spectral Water Index (MuWI): A Native 10-m Multi-Spectral Water Index for Accurate Water Mapping on Sentinel-2." Remote Sensing 10, no. 10 (2018): 1643. http://dx.doi.org/10.3390/rs10101643.

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Accurate water mapping depends largely on the water index. However, most previously widely-adopted water index methods are developed from 30-m resolution Landsat imagery, with low-albedo commission error (e.g., shadow misclassified as water) and threshold instability being identified as the primary issues. Besides, since the shortwave-infrared (SWIR) spectral band (band 11) on Sentinel-2 is 20 m spatial resolution, current SWIR-included water index methods usually produce water maps at 20 m resolution instead of the highest 10 m resolution of Sentinel-2 bands, which limits the ability of Senti

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Xia, Ting, William P. Kustas, Martha C. Anderson, et al. "Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes." Hydrology and Earth System Sciences 20, no. 4 (2016): 1523–45. http://dx.doi.org/10.5194/hess-20-1523-2016.

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Abstract. Thermal and multispectral remote sensing data from low-altitude aircraft can provide high spatial resolution necessary for sub-field (≤ 10 m) and plant canopy (≤ 1 m) scale evapotranspiration (ET) monitoring. In this study, high-resolution (sub-meter-scale) thermal infrared and multispectral shortwave data from aircraft are used to map ET over vineyards in central California with the two-source energy balance (TSEB) model and with a simple model having operational immediate capabilities called DATTUTDUT (Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature). Th

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Ku, Mengjun, Hao Jiang, Kai Jia, et al. "Cropland Inundation Mapping in Rugged Terrain Using Sentinel-1 and Google Earth Imagery: A Case Study of 2022 Flood Event in Fujian Provinces." Agronomy 14, no. 1 (2024): 138. http://dx.doi.org/10.3390/agronomy14010138.

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South China is dominated by mountainous agriculture and croplands that are at risk of flood disasters, posing a great threat to food security. Synthetic aperture radar (SAR) has the advantage of being all-weather, with the ability to penetrate clouds and monitor cropland inundation information. However, SAR data may be interfered with by noise, i.e., radar shadows and permanent water bodies. Existing cropland data derived from open-access landcover data are not accurate enough to mask out these noises mainly due to insufficient spatial resolution. This study proposed a method that extracted cr

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Qing, Yuanyuan, Jiang Zhu, Hongchuan Feng, Weixian Liu, and Bihan Wen. "Two-Way Generation of High-Resolution EO and SAR Images via Dual Distortion-Adaptive GANs." Remote Sensing 15, no. 7 (2023): 1878. http://dx.doi.org/10.3390/rs15071878.

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Synthetic aperture radar (SAR) provides an all-weather and all-time imaging platform, which is more reliable than electro-optical (EO) remote sensing imagery under extreme weather/lighting conditions. While many large-scale EO-based remote sensing datasets have been released for computer vision tasks, there are few publicly available SAR image datasets due to the high costs associated with acquisition and labeling. Recent works have applied deep learning methods for image translation between SAR and EO. However, the effectiveness of those techniques on high-resolution images has been hindered

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Lewis, Sarah A., Peter R. Robichaud, Andrew T. Hudak, Eva K. Strand, Jan U. H. Eitel, and Robert E. Brown. "Evaluating the Persistence of Post-Wildfire Ash: A Multi-Platform Spatiotemporal Analysis." Fire 4, no. 4 (2021): 68. http://dx.doi.org/10.3390/fire4040068.

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As wildland fires amplify in size in many regions in the western USA, land and water managers are increasingly concerned about the deleterious effects on drinking water supplies. Consequences of severe wildfires include disturbed soils and areas of thick ash cover, which raises the concern of the risk of water contamination via ash. The persistence of ash cover and depth were monitored for up to 90 days post-fire at nearly 100 plots distributed between two wildfires in Idaho and Washington, USA. Our goal was to determine the most ‘cost’ effective, operational method of mapping post-wildfire as

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Shahtakhtinskiy, Aydin, Shuhab D. Khan, and Sara S. Rojas. "Quantifying the Impact of Hurricane Harvey on Beach−Dune Systems of the Central Texas Coast and Monitoring Their Changes Using UAV Photogrammetry." Remote Sensing 15, no. 24 (2023): 5779. http://dx.doi.org/10.3390/rs15245779.

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Historically, the Texas Gulf Coast has been affected by many tropical storms and hurricanes. The most recent severe impact was caused by Hurricane Harvey, which made landfall in August 2017 on the central Texas coast. We evaluated the impact of Hurricane Harvey on the barrier islands of the central Texas coast, including San Jose Island, Mustang Island, and North Padre Island. We used public data sets, including 1 m resolution bare-earth digital elevation models (DEMs), derived from airborne lidar acquisitions before (2016) and after (2018) Hurricane Harvey, and sub-meter scale aerial imagery

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Palaseanu-Lovejoy, Monica, Marina Bisson, Claudia Spinetti, Maria Fabrizia Buongiorno, Oleg Alexandrov, and Thomas Cecere. "High-Resolution and Accurate Topography Reconstruction of Mount Etna from Pleiades Satellite Data." Remote Sensing 11, no. 24 (2019): 2983. http://dx.doi.org/10.3390/rs11242983.

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The areas characterized by dynamic and rapid morphological changes need accurate topography information with frequent updates, especially if these are populated and involve infrastructures. This is particularly true in active volcanic areas such as Mount (Mt.) Etna, located in the northeastern portion of Sicily, Italy. The Mt. Etna volcano is periodically characterized by explosive and effusive eruptions and represents a potential hazard for several thousands of local people and hundreds of tourists present on the volcano itself. In this work, a high-resolution, high vertical accuracy digital

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Zhu, Xiaoyong, Xinming Tang, Guo Zhang, Bin Liu, and Wenmin Hu. "Accuracy Comparison and Assessment of DSM Derived from GFDM Satellite and GF-7 Satellite Imagery." Remote Sensing 13, no. 23 (2021): 4791. http://dx.doi.org/10.3390/rs13234791.

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Digital Surface Model (DSM) derived from high resolution satellite imagery is important for various applications. GFDM is China’s first civil optical remote sensing satellite with multiple agile imaging modes and sub-meter resolution. Its panchromatic resolution is 0.5 m and 1.68 m for multi-spectral images. Compared with the onboard stereo viewing instruments (0.8 m for forward image, 0.65 m for back image, and 2.6 m for back multi-spectrum images) of GF-7, a mapping satellite of China in the same period, their accuracy is very similar. However, the accuracy of GFDM DSM has not yet been verif

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Zhang, Chunmei, Chunmei Wang, Yongqing Long, et al. "Comparative Analysis of Gully Morphology Extraction Suitability Using Unmanned Aerial Vehicle and Google Earth Imagery." Remote Sensing 15, no. 17 (2023): 4302. http://dx.doi.org/10.3390/rs15174302.

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Gully erosion is considered to be a highly destructive form of soil erosion, often leading to the occurrence of natural calamities like landslides and mudslides. Remote sensing images have been extensively utilized in gully erosion research, and the suitability of extracting gully morphology parameters in various topographic regions needs to be clarified. Based on field measurements, this paper focuses on two widely used high-resolution remote sensing images: Unmanned Aerial Vehicle (UAV) and Google Earth (GE) imagery. It systematically examines the accuracy of gully morphological characterist

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Bhuiyan, Md Abul Ehsan, Chandi Witharana, and Anna K. Liljedahl. "Use of Very High Spatial Resolution Commercial Satellite Imagery and Deep Learning to Automatically Map Ice-Wedge Polygons across Tundra Vegetation Types." Journal of Imaging 6, no. 12 (2020): 137. http://dx.doi.org/10.3390/jimaging6120137.

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We developed a high-throughput mapping workflow, which centers on deep learning (DL) convolutional neural network (CNN) algorithms on high-performance distributed computing resources, to automatically characterize ice-wedge polygons (IWPs) from sub-meter resolution commercial satellite imagery. We applied a region-based CNN object instance segmentation algorithm, namely the Mask R-CNN, to automatically detect and classify IWPs in North Slope of Alaska. The central goal of our study was to systematically expound the DLCNN model interoperability across varying tundra types (sedge, tussock sedge,

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Berthier, E., C. Vincent, E. Magnússon, et al. "Glacier topography and elevation changes from Pléiades very high resolution stereo images." Cryosphere Discussions 8, no. 5 (2014): 4849–83. http://dx.doi.org/10.5194/tcd-8-4849-2014.

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Abstract. In response to climate change, most glaciers are losing mass and hence contribute to sea-level rise. Repeated and accurate mapping of their surface topography is required to estimate their mass balance and to extrapolate/calibrate sparse field glaciological measurements. In this study we evaluate the potential of Pléiades sub-meter stereo imagery to derive digital elevation models (DEMs) of glaciers and their elevation changes. Our five validation sites are located in Iceland, the European Alps, the Central Andes, Nepal and Antarctica. For all sites, nearly simultaneous field measure

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Shean, David E., Ian R. Joughin, Pierre Dutrieux, Benjamin E. Smith, and Etienne Berthier. "Ice shelf basal melt rates from a high-resolution digital elevation model (DEM) record for Pine Island Glacier, Antarctica." Cryosphere 13, no. 10 (2019): 2633–56. http://dx.doi.org/10.5194/tc-13-2633-2019.

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Abstract. Ocean-induced basal melting is responsible for much of the Amundsen Sea Embayment ice loss in recent decades, but the total magnitude and spatiotemporal evolution of this melt is poorly constrained. To address this problem, we generated a record of high-resolution digital elevation models (DEMs) for Pine Island Glacier (PIG) using commercial sub-meter satellite stereo imagery and integrated additional 2002–2015 DEM and altimetry data. We implemented a Lagrangian elevation change (Dh∕Dt) framework to estimate ice shelf basal melt rates at 32–256 m resolution. We describe this methodol

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Ardelean, Florina, Alexandru Onaca, Marinela-Adriana Chețan, et al. "Assessment of Spatio-Temporal Landscape Changes from VHR Images in Three Different Permafrost Areas in the Western Russian Arctic." Remote Sensing 12, no. 23 (2020): 3999. http://dx.doi.org/10.3390/rs12233999.

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Our study highlights the usefulness of very high resolution (VHR) images to detect various types of disturbances over permafrost areas using three example regions in different permafrost zones. The study focuses on detecting subtle changes in land cover classes, thermokarst water bodies, river dynamics, retrogressive thaw slumps (RTS) and infrastructure in the Yamal Peninsula, Urengoy and Pechora regions. Very high-resolution optical imagery (sub-meter) derived from WorldView, QuickBird and GeoEye in conjunction with declassified Corona images were involved in the analyses. The comparison of v

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Zhu, Xiaoxiao, Zhikun Ren, Sheng Nie, et al. "DEM Generation from GF-7 Satellite Stereo Imagery Assisted by Space-Borne LiDAR and Its Application to Active Tectonics." Remote Sensing 15, no. 6 (2023): 1480. http://dx.doi.org/10.3390/rs15061480.

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China’s first optical stereo mapping satellite with a sub-meter resolution, GaoFen-7 (GF-7), launched in November 2019, shows significant potential for providing high-resolution topographic and geomorphic data for quantitative research on active tectonics. However, no studies have evaluated the capability of the GF-7-generated digital elevation model (DEM) for quantitatively studying active tectonics. This study aimed to validate the accuracy of the DEMs extracted from GF-7 stereo imagery, with or without ground control points (GCPs), and evaluated the potential of applying GF-7 DEMs to active

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Novo-Fernández, Alís, Carlos A. López-Sánchez, Asunción Cámara-Obregón, Marcos Barrio-Anta, and Iyán Teijido-Murias. "Estimating Forest Variables for Major Commercial Timber Plantations in Northern Spain Using Sentinel-2 and Ancillary Data." Forests 15, no. 1 (2024): 99. http://dx.doi.org/10.3390/f15010099.

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In this study, we used Spanish National Forest Inventory (SNFI) data, Sentinel-2 imagery and ancillary data to develop models that estimate forest variables for major commercial timber plantations in northern Spain. We carried out the analysis in two stages. In the first stage, we considered plots with and without sub-meter geolocation, three pre-processing levels for the Sentinel-2 images and two machine learning algorithms. In most cases, geometrically, radiometrically, atmospherically and topographically (L2A-ATC) corrected images and the random forest algorithm provided the best results, w

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Harvey, Mark C., Danielle K. Hare, Alex Hackman, et al. "Evaluation of Stream and Wetland Restoration Using UAS-Based Thermal Infrared Mapping." Water 11, no. 8 (2019): 1568. http://dx.doi.org/10.3390/w11081568.

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Large-scale wetland restoration often focuses on repairing the hydrologic connections degraded by anthropogenic modifications. Of these hydrologic connections, groundwater discharge is an important target, as these surface water ecosystem control points are important for thermal stability, among other ecosystem services. However, evaluating the effectiveness of the restoration activities on establishing groundwater discharge connection is often difficult over large areas and inaccessible terrain. Unoccupied aircraft systems (UAS) are now routinely used for collecting aerial imagery and creatin

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Yuan, Jiayu, Zhiwei Wu, Shun Li, Ping Kang, and Shihao Zhu. "Multi-Feature-Based Identification of Subtropical Evergreen Tree Species Using Gaofen-2 Imagery and Algorithm Comparison." Forests 14, no. 2 (2023): 292. http://dx.doi.org/10.3390/f14020292.

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The species and distribution of trees in a forest are critical to the understanding of forest ecosystem processes and the development of forest management strategies. Subtropical forest landscapes feature a complex canopy structure and high stand density. Studies on the effects of classification algorithms on the remote sensing-based identification of tree species are few. GF-2 is the first satellite in China with sub-meter accuracy which has the high resolution and short replay cycle. Here, we considered three representative tree types (Masson pine, Chinese fir, and broadleaved evergreen tree

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Dimyati, Akhmad E. Firlli, Lili Somantri, and Nanin Trianawati Sugito. "Klasifikasi Berbasis Objek Citra Satelit Sentinel 2 untuk Pemetaan Perubahan Lahan di Kecamatan Parongpong Kabupaten Bandung Barat." Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian 19, no. 1 (2022): 24–28. http://dx.doi.org/10.15294/jg.v19i1.33958.

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Kecamatan Parongpong merupakan kawasan pinggiran kota dimana wilayah ini menjadi salah satu wilayah favorit dalam pemilihan wilayah pemukiman, di sisi lain wilayah ini masih di dominasi oleh lahan pertanian. Pentingnya monitoring dalam Perubahan lahan di suatu wilayah terutama wilayah pinggiran kota adalah sangat penting. Penggunaan data citra satelit resolusi menengah akan menjadi pilihan yang baik karena aksesnya yang mudah dan ketersediaan data gratis. Sentinel-2 adalah salah satu Citra satelit resolusi menengah yang dapat diakses gratis dimana memiliki resolusi spasial 10 meter dalam salur

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