Altimeter Data Research Articles

Methodology for classification of land use and vegetation cover using MODIS-EVI data

ABSTRACT This study aimed to verify the applicability of using MODIS-EVI sensor time series for land use and vegetation cover mapping in the Pampa biome, Rio Grande do Sul state, Brazil. The study period comprised the months from June 2013 to June 2014. The procedures included the use of MODIS Sensor images, altimetric data and nighttime images, associated with a hierarchical decision tree classifier, constructed using the C4.5 algorithm. The proposed approach stems from the consideration that the study area has varying characteristics and, therefore, should be treated simultaneously by different and intuitive classifiers, which justifies the choice of decision tree. To evaluate the results, reference data acquired from Landsat 8-OLI satellite images and IBGE data were used. The classification using the MODIS time series showed a global accuracy of 90.09% and Kappa index of 0.8885. When compared to the IBGE reference data, the Soybean class obtained a correlation coefficient of 0.94, the rice class obtained 0.97 and the silviculture class obtained the lowest value, 0.78. The highest spectral similarities were found in the vegetation cover classes, such as grassland, forest and silviculture. Therefore, with the use of multitemporal data from the MODIS sensor, combined with the use of altimetric data and nighttime images, it is possible to generate a land use and vegetation cover map for the Pampa biome with an acceptable accuracy, considering the MODIS sensor resolution limitations.

Оптимальное определение рельефа поверхности по совокупности фотометрических и альтиметрических данных

Оптимальное определение рельефа поверхности по совокупности фотометрических и альтиметрических данных

Ocean eddy detection in the Andaman Sea during April 2008

Eddies have an important role in momentum transport, water mass, heat, and marine biogeochemical cycles. So far the information regarding eddies in the Andaman Sea is still little known. By using National Centers for Environmental Prediction (NCEP) / National Center for Atmospheric Research (NCAR) wind data, Sea Surface Height (SSH), and geostrophic currents obtained from altimeter data, this paper aimed to detect eddies during April (intermonsoon). Eddies were formed by current turbulence, gradient pressure variations, and the influence of sea surface wind. Observations showed that the SSH variations was supported by the west wind from the Andaman Sea. Spatial SSH differences caused the dynamics of geostrophic currents and eddies. During April 2008, we found six eddies scattered around the Andaman Sea, where there were four eddies cyclones and two eddies anticyclones.

A Simplified Assimilation Scheme for a Coastal Wave Model Using Concepts of Particle Filter

In this work, observations of ocean wave height from satellite altimeters are assimilated into the coastal wave model simulating waves nearshore (SWAN) operating in the Indian coastal waters. The study has two distinctive features. The most important is the use of certain concepts of the modern particle filter technique, which does not represent the model probability density function (PDF) by a Gaussian. The other feature is the joint assimilation of data from three altimeters. The method starts by generating an initial ensemble by the bootstrap technique in which the significant wave height (SWH) field of a control run is perturbed by randomly adding bias to produce a member of the ensemble. At the first assimilation time, a weight-based resampling of the individual members, known as particles, is performed. Stronger particles are retained, while the weaker ones are discarded. In order to keep the ensemble size constant, the algorithm replicates a few strong members. After this resampling, a single model run is employed in the forecast step using a kind of averaging. At the next assimilation time, a synthetic ensemble is again formed by the same bootstrapping, and observations are assimilated. The forecast–assimilation cycle is repeated until the observations are exhausted. Assimilation experiments were conducted for 6 months from February through July in 2016. The power of the technique is evaluated by validating results with altimeter data as well as independent data sets from moored buoys. The results are found to be extremely encouraging for the use of this method in carrying out coastal wave forecasting.

Integrating Stereo Images and Laser Altimeter Data of the ZY3-02 Satellite for Improved Earth Topographic Modeling

The positioning accuracy is critical for satellite-based topographic modeling in cases of exterior orientation parameters with high uncertainty and scarce ground control data. The integration of multi-sensor data can help to ensure precision topographical modeling in such situations. Presently, research on the combined processing of optical camera images and laser altimeter data has focused on planetary observations, especially on the Moon and Mars. This study presents an endeavor to establish a combined adjustment model with one constraint in image space for integration of ZY3-02 stereo images and laser altimeter data for improved Earth topographic modeling. The geometric models for stereo images and laser altimeter data were built first, and then, the laser ranging information was introduced to construct a combined adjustment model on the basis of the block adjustment model. One constraint that minimized the back-projection discrepancies in image space was incorporated into the combined adjustment. Datasets in several areas were collected as experimental data for the validation work. Experimental results demonstrated that the inconsistencies between stereo images and laser altimeter data for the ZY3-02 satellite can be reduced, and the elevation accuracy of stereo images can be significantly improved after applying the proposed combined adjustment. Experiments further proved that the improved height accuracy is insensitive to the number and relative position of laser altimeter points (LAPs) in stereo images. Moreover, additional plane control points (PCPs) were incorporated to achieve better planimetric accuracy. Experimental results in the Dengfeng area showed that the adjustment results derived by using LAPs and additional four PCPs were only slightly lower than those for the block adjustment with four ground control points (GCPs). Generally, the proposed approach can effectively improve the quality of Earth topographic model.

Improving accuracy of altimeter-derived marine gravity anomalies in the East Vietnam Sea deep-basin and adjacent area

In recent years, the satellite altimeter technology allows enhancing the marine investigation in many areas. Up to now, many scientific studies have attempted to improve the accuracy and resolution of altimeter-derived gravity anomalies and have produced a gravity grid with interval of 1’×1’ for most oceans all over the world. However, these gravity anomalies are not very highly accurate and have a large difference compared to shipboard gravity anomalies, especially in the coastal and islands areas. The purpose of this article is to improve the accuracy of altimeter-derived marine gravity anomalies for geological structure research in the East Vietnam Sea deep-basin and adjacent areas. The least squares collocation method is used to correct the altimeter-derived marine gravity data based on the shipboard gravity data in order to improve the accuracy of marine gravity anomalies. In this article, the altimeter-derived marine gravity anomalies are taken from Sandwell, D. T., et al., (V24.1) and the shipboard gravity anomalies are from the survey projects between Vietnam, Russia and other countries. The mean-squared error when comparing both data is about 9,358 mGal. After correcting by collocation method, the error was reduced to 3,208 mGal (for the altimeter data coinciding with shipboard track). Also, in this article, the achieved results show the efficiency and actuality of the corrected-altimeter-derived marine gravity anomalies for more detailed researches of geological structures. Especially, it is more meaningful in the remote or sparsely surveyed regions.

Discrimination of different sea ice types from CryoSat-2 satellite data using an Object-based Random Forest (ORF)

Sea ice type is one of the most sensitive variables in Arctic sea ice monitoring, and it is important for the retrieval of ice thickness. In this study, we analyzed various waveform features that characterize the echo waveform shape and Sigma0 (i.e., backscatter coefficient) of CryoSat-2 synthetic aperture radar altimeter data over different sea ice types. Arctic and Antarctic Research Institute operational ice charts were input as reference. An object-based random forest (ORF) classification method is proposed with overall classification accuracy of 90.1%. Accuracy of 92.7% was achieved for first-year ice (FYI), which is the domain ice type in the Arctic. Accuracy of 76.7% was achieved at the border of FYI and multiyear ice (MYI), which is better than current state-of-the-art methods. Accuracy of 83.8% was achieved for MYI. Results showed the overall accuracy of the ORF method was increased by ∼8% in comparison with other methods, and the classification accuracy at the border of FYI and MYI was increased by ∼10.5%. Nevertheless, ORF classification performance might be influenced by the selected waveform features, snow loading, and the ability to distinguish sea ice from leads.

Satellite Altimetry Measurements of Sea Level in the Coastal Zone

Satellite radar altimetry provides a unique sea level data set that extends over more than 25 years back in time and that has an almost global coverage. However, when approaching the coasts, the extraction of correct sea level estimates is challenging due to corrupted waveforms and to errors in most of the corrections and in some auxiliary information used in the data processing. The development of methods dedicated to the improvement of altimeter data in the coastal zone dates back to the 1990s, but the major progress happened during the last decade thanks to progress in radar technology [e.g., synthetic aperture radar (SAR) mode and Ka-band frequency], improved waveform retracking algorithms, the availability of new/improved corrections (e.g., wet troposphere and tidal models) and processing workflows oriented to the coastal zone. Today, a set of techniques exists for the processing of coastal altimetry data, generally called “coastal altimetry.” They have been used to generate coastal altimetry products. Altimetry is now recognized as part of the integrated observing system devoted to coastal sea level monitoring. In this article, we review the recent technical advances in processing and the new technological capabilities of satellite radar altimetry in the coastal zone. We also illustrate the fast-growing use of coastal altimetry data sets in coastal sea level research and applications, as high-frequency (tides and storm surge) and long-term sea level change studies.

Temporal and Spatial Characteristics of Mesoscale Eddies in the Northern South China Sea: Statistics Analysis Based on Altimeter Data

Temporal and Spatial Characteristics of Mesoscale Eddies in the Northern South China Sea: Statistics Analysis Based on Altimeter Data

Remote Detection of Varying Water Storage in Relation to Surfacial Temperature of Aral Sea

Lake monitoring by remote sensing is of significant importance to understanding the lake and ambient ecological and environmental processes. In particular, whether lake water storage variation could predict lake surfacial temperature or vice versa has long fascinated the research community, in that it would greatly benefit the monitoring missions and scientific interpretation of the lake change processes. This study attempted to remotely detect the dynamics of the Aral Sea and pursue the relationships between varying lake water storage attributes and surface water temperature by using MODIS LST (Moderate-resolution Imaging Spectroradiometer Land Surface Temperature) 8-day composite products, satellite altimeter data, and actual meteorological measurements. Their associations with lake Surface Water Temperatures (SWT) were then analyzed. Results showed the lake water surface areas and elevations of the North Aral Sea tended to increasing trend from 2001 (2793.0 km2, 13.6 m) to 2015 (6997.8 km2, 15.9 m), while those of the South Aral Sea showed a decreasing trend during 2001 (20 434.6 km2, 3.9 m) and 2015 (3256.1 km2, 0.9 m). In addition, the annual daytime and nighttime lake SWT both decreased in the North Aral Sea, while only the daytime SWT in the South Aral Sea exhibited an increase, indicating a rising deviation of diurnal temperatures in the South Aral Sea during the past 15 yr. Moreover, a lower correlation was found between variations in the daytime SWT and storage capacity in the South Aral Sea (R2 = 0.33; P < 0.05), no fair correlations were tested between lake water storage and daytime SWT in the North Aral Sea nor between lake water storage and nighttime SWT in either part of the sea. These results implied that climate change, if any at least during the research period, has no significant effects on lake dynamics over the two sectors of the Aral Sea with anthropogenic disturbances. However, climate change and human activities may overlap to explain complex consequences in the lake storage variations. Our results may provide a reference for monitoring the spatiotemporal variations of lakes, increasing understanding of the lake water storage changes in relation to the lake SWT, which may benefit the ecological management of the Aral Sea region, in the effort to face the likely threats from climate change and human activities to the region.

Improving the geometry of Kaguya extended mission data through refined orbit determination using laser altimetry

The Japan Aerospace Exploration Agency’s (JAXA) Kaguya spacecraft carried a suite of instruments to map the Moon and its environment globally. During its extended mission, the average altitude was 50 km or lower, and Kaguya science products using these data hence have an increased spatial resolution. However, the geodetic position quality of these products is much worse than that of those acquired during the primary mission (at an altitude of 100 km) because of reduced radiometric tracking and frequent thrusting to maintain spacecraft attitude after the loss of momentum wheels. We have analyzed the Kaguya tracking data using gravity models based on the Gravity Recovery and Interior Laboratory (GRAIL) mission, and by making use of a new data type based on laser altimeter data collected by Kaguya: we adjust the spacecraft orbit such that the altimetry tracks fit a precise topographic basemap based on the Lunar Reconnaissance Orbiter’s (LRO) Lunar Orbiter Laser Altimeter (LOLA) data. This results in geodetically accurate orbits tied to the precise LOLA/LRO frame. Whereas previously archived orbits show errors at the level of several kilometers, the inclusion of altimetry greatly improves the orbit precision, to a level of several tens of meters. When altimetry data are not available, the combination of GRAIL gravity and radio tracking results in an orbit precision of around several hundreds of meters for the low-altitude phase of the extended mission. Our greatly improved orbits result in better geolocation of the Kaguya extended mission data set.

Quality assessment of a satellite altimetry data product DT18 in the Norwegian Sea: A comparison to tide gauge records and drifters data

• The altimetric product DT18 reproduces the sea level variability in the Norwegian Sea with an average error 3–4 cm. • Statistical tests conducted for the DT18 reveal some problems. • Errors of the DT18 have a shape of “diamonds” in the open sea. • Ageostrophic factors influence strongly the real current velocities in the Norwegian Sea. The objective of this paper is to assess the quality of the gridded altimetric sea level product DT18 as well as altimetry data from the Sea Level Climate Change Initiative in the Norwegian Sea. We compare the satellite altimetry data with two types of instrumental data. We use tide gauge records to assess the quality in the coastal zone and data from surface drifting buoys to assess the quality in the open ocean. Thus, we aim to complement previous studies by providing the objective assessment of the quality and performance of satellite altimetry in this important region. We demonstrate that the product DT18 reproduces the sea level variability in the coastal zone at an acceptable level (an average error is 3–4 cm), and it reproduces the structure of the time series quite well (almost with a 96% correlation). We found out that altimetry substantially smoothes the pattern of the sea level. This pattern is revealed in the coastal zone as well as in the open sea, where, in addition, it also manifests errors in a shape of “diamonds”, which can be due to data interpolation from satellite tracks. We detected the influence of ageostrophic factors on the current velocities using altimetry in the open sea, and this is also true for the coastal zone. Statistical tests also showed some discrepancies between altimetry data and field (buoys and drifters) data in the open sea. This is manifested in the statistical inequality of variances and in differences of empirical distribution functions. Summing up, we assert that some errors or discrepancies in altimetric data are still observed in high latitudes, both in the coastal zone and in the open part of the Norwegian Sea.

Iterative Pointing Angle Calibration Method for the Spaceborne Photon-Counting Laser Altimeter Based on Small-Range Terrain Matching

The satellite, Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) has been equipped with a new type of spaceborne laser altimeter, which has the benefits of having small footprints and a high repetition rate, and it can produce dense footprints on the ground. Focusing on the pointing angle calibration of this new spaceborne laser altimeter, this paper proposes a fast pointing angle calibration method using only a small range of terrain surveyed by airborne lidar. Based on the matching criterion of least elevation difference, an iterative pointing angle calibration method was proposed. In the experiment, the simulated photon-counting laser altimeter data and the Ice, Cloud and Land Elevation Satellite-2 data were used to verify the algorithm. The results show that when 1 km and 2.5 km lengths of track were used, the pointing angle error after calibration could be reduced to about 0.3 arc-seconds and less than 0.1 arc-seconds, respectively. Meanwhile, compared with the traditional pyramid search method, the proposed iterative pointing angle calibration method does not require well-designed parameters, which are important in the pyramid search method to balance calculation time and calibration result, and the iterative pointing angle calibration method could significantly reduce the calibration time to only about one-fifth of that of the pyramid search method.

ANALYSIS OF INFLUENCING FACTORS OF CURVE MATCHING BASED GEOMETRIC CALIBRATION FOR ZY3-02 ALTIMETER DATA

Abstract. High-precision on-orbit geometric calibration of spaceborne laser altimetry data is essential to its effective applications. Firstly, the existing calibration methods for laser altimeter data are analyzed. Then, a geometric calibration method based on curve matching is proposed. Compared to the existing methods, the proposed method does not rely on ground calibration field. Thus, it is efficiency in expense and time. Notably, three factors, i.e. matching method, initial control point selection and the step size of matching step, which significantly affect the results of calibration are analyzed respectively. The analysis was validated based on the original laser altimetry data obtained by ZY3-02 satellite. According to the results, the following conclusions can be drawn preliminarily: (1) Both the correlation coefficient maximum (COR) criterion and the mean square error minimum (MSD) criterion in the curve matching can be used to correct the systematic error in altimetry data. (2) The initial control points of the selected track should have a significant change trend and the slope within the laser footprints should be less than 15°. (3) Current experimental data show that the best step size for matching search is 10 m. The relevant conclusions can provide reference for the research of geometrical calibration and data processing of the same type of laser altimetry satellite.

Global Ocean Extreme Wave Heights from Spatial Ensemble Data

Abstract A novel approach to estimation of extreme value ocean significant wave height is investigated, in which data from adjacent regions are pooled to form a spatial ensemble. The equivalent duration of this ensemble region is the sum of the durations of the data pooled to form the ensemble. To create such a spatial ensemble, data from regions to be pooled must be independent and identically distributed. ERA-Interim reanalysis data are used to investigate the requirement of independent and identically distributed data on a global basis. As a result, typical spatial ensembles are defined for a number of regions of the world and the 100-yr return period significant wave height is calculated for these regions. It is shown that the method can result in a reduction in the confidence interval for such extreme value estimates of between 30% and 60%. The method is demonstrated both with ERA-Interim data and altimeter data.

DUACS DT2018: 25 years of reprocessed sea level altimetry products

Abstract. For more than 20 years, the multi-satellite Data Unification and Altimeter Combination System (DUACS) has been providing near-real-time (NRT) and delayed-time (DT) altimetry products. DUACS datasets range from along-track measurements to multi-mission sea level anomaly (SLA) and absolute dynamic topography (ADT) maps. The DUACS DT2018 ensemble of products is the most recent and major release. For this, 25 years of altimeter data have been reprocessed and are available through the Copernicus Marine Environment Monitoring Service (CMEMS) and the Copernicus Climate Change Service (C3S). Several changes were implemented in DT2018 processing in order to improve the product quality. New altimetry standards and geophysical corrections were used, data selection was refined and optimal interpolation (OI) parameters were reviewed for global and regional map generation. This paper describes the extensive assessment of DT2018 reprocessing. The error budget associated with DT2018 products at global and regional scales was defined and improvements on the previous version were quantified (DT2014; Pujol et al., 2016). DT2018 mesoscale errors were estimated using independent and in situ measurements. They have been reduced by nearly 3 % to 4 % for global and regional products compared to DT2014. This reduction is even greater in coastal areas (up to 10 %) where it is directly linked to the geophysical corrections applied to DT2018 processing. The conclusions are very similar concerning geostrophic currents, for which error was globally reduced by around 5 % and as much as 10 % in coastal areas.

Possible explosion crater origin of small lake basins with raised rims on Titan

The Cassini mission discovered lakes and seas comprising mostly methane in the polar regions of Titan. Lakes of liquid nitrogen may have existed during the epochs of Titan’s past in which methane was photochemically depleted, leaving a nearly pure molecular nitrogen atmosphere and, thus, far colder temperatures. The modern-day small lake basins with sharp edges have been suggested to originate from dissolution processes, due to their morphological similarity to terrestrial karstic lakes. Here we analyse the morphology of the small lake basins that feature raised rims to elucidate their origin, using delay-Doppler processed altimetric and bathymetric data acquired during the last close flyby of Titan by the Cassini spacecraft. We find that the morphology of the raised-rim basins is analogous to that of explosion craters from magma–water interaction on Earth and therefore propose that these basins are from near-surface vapour explosions, rather than karstic. We calculate that the phase transition of liquid nitrogen in the near subsurface during a warming event can generate explosions sufficient to form the basins. Hence, we suggest that raised-rim basins are evidence for one or more warming events terminating a nitrogen-dominated cold episode on Titan. Some lake basins in the polar regions of Titan may be craters from nitrogen vapour explosions due to past warming, according to analysis of their morphology in comparison to terrestrial explosion craters from magma–water interaction.

Long-term quality and stability assessment of CryoSat-2 Ocean Data

Since 8 April 2010 ESA’s Earth Explorer mission CryoSat-2 has been measuring marine and land ice thickness variations with a dedicated altimeter. With the effects of a fast-changing climate becoming apparent, it is increasingly important to understand exactly how Earth’s ice fields are responding and regulate climate and sea level. It is therefore of utmost importance that the quality of the CryoSat-2 altimeter data meets the highest accuracy and precision level, not only over the ice caps and sea-ice surface but over the oceans as well. The SIRAL altimeter of CryoSat-2 is capable of measuring high-resolution geophysical parameters from the open ocean to the coast. In this paper, we validate the CryoSat-2 geophysical ocean product, Baseline-B (GOP). The analyses focus on long-term monitoring, validation, and cross-calibration of these ocean altimeter data with all the concurrent altimeter data in the Radar Altimeter Database System RADS and with independent in-situ tide gauge measurements from the Permanent Service for Mean Sea Level PSMSL. The objective is to evaluate the stability of the CryoSat-2 measurement system and the identification and explanation of biases and bias drifts. A persistent monitoring of these biases in time is important to establish the data’s usefulness for investigation of long-term sea level and ice topography/volume changes. The results constitute the final status of the GOP baseline-B product for use as essential climate variables. GOP ocean data has a - 6.3 ± 0.2 cm range bias w.r.t. to all calibrated satellites in RADS and a drift of 0.14 mm yr −1 w.r.t. Jason-2. GOP data has significant wave height and sea state biases close to that of the Jasons’, and seems to be better handling the LRM-SAR transitions than the RADS CryoSat-2 product. GOP data w.r.t. PSMSL tide gauge data has an average correlation of R = 0.83, a mean st. dev. of σ = 6.30 cm, and a drift of 0.11 mm yr −1 , equivalent to 40 Gt yr −1 ice sheet mass loss. It is concluded that GOP CryoSat-2 performs better than RADS CryoSat-2, which seems to suffer from a 480-day platform temperature cycle. GOP is also on a par with the altimeter data from the Jason reference missions, and well suited for ocean and climate studies.

Design and regional assessment of an empirical tidal model based on FES2014 and coastal altimetry

The updated Empirical Ocean Tide model (EOT19p) currently available on limited regions is presented in this paper. Its implementation is focused on improving the accuracy of tidal estimation at the coast. EOT19p is derived using circa 27 years of coast-dedicated altimetric data and the FES2014 tide model, and it is based on a multi-mission, weighted least-squares approach. In this work the performance of EOT19p is assessed with respect to state-of-the-art tide models against in situ observations. The study is performed on two critical regions: the North Sea and the Malay Archipelago. Comparisons for eight major tidal constituents show that EOT19p improves coastal results with respect to its former version, EOT11a, of 35.39% in the North Sea and 20.07% in the Malay Archipelago, with large error reduction in the English Channel and the Irish Sea. The median absolute differences (MAD) against in situ data show that EOT19p is in line with the latest models, with lowest error occurring for single tidal constituents, such as M2 (with a MAD of 1.63 cm in the Malay Archipelago). Finally, the tidal height differences of three models (EOT19p, FES2014, and DTU16) compared with those obtained of their former versions (EOT11a, FES2012, and DTU10), show an increased agreement at coastal areas with the latest versions, and the regional average difference for M2 constituent drops from 3.75 cm to 0.70 cm in the North Sea, and from 3.02 to 1.44 cm in the Malay Archipelago.

Extraction of Revolving Channels of Drifters around Mesoscale Eddy Centers Based on Spatiotemporal Trajectory Clustering

The global oceanic transports of energy, plankton, and other tracers by mesoscale eddies can be estimated by combining satellite altimetry and in situ data. However, the revolving channels of particles entrained by mesoscale eddies, which could help explain the dynamic process of eddies entraining materials, are still unknown. In this study, satellite altimeter and drifter data from 1993 to 2016 are adopted, and the normalized trajectory clustering algorithm (N-TRACLUS) is proposed to extract the revolving channels of drifters. First, the trajectories of drifters are normalized and clustered by using the density-based spatial clustering of applications with noise (DBSCAN) algorithm. Next, the revolving channels of drifters around the eddy center are extracted. The ring or arc pattern in the middle of a normalized eddy appears when drifters are uninterruptedly entrained by eddies for more than 30 days. Moreover, the revolving channels of drifters in cyclonic eddies are relatively closer to the eddy center than those in anticyclonic eddies. These revolving channels suggest the principal mode of materials’ continuous motion processes that are inside eddies.