Oceanographic Field Estimates from Remote Sensing and Glider Fleets

2012 ◽  
Vol 29 (11) ◽  
pp. 1657-1662 ◽  
Author(s):  
A. Alvarez ◽  
B. Mourre
Keyword(s):  
Remote Sensing ◽  
Thermal Field ◽  
Coastal Region ◽  
Remote Sensing Data ◽  
Optimal Interpolation ◽  
Thermocline Depth ◽  
Temperature Profiles ◽  
Merging Techniques ◽  
Field Estimate ◽  
Better Than

Abstract This work investigates the merging of temperature observations from a glider fleet and remote sensing, based on a field experiment conducted in an extended coastal region offshore La Spezia, Italy, in August 2010. Functional optimal interpolation and spline formalisms are used to integrate temperature profiles from a fleet of three gliders with remotely sensed sea surface temperature into a volumetric thermal field estimate. Independent measurements from a towed ScanFish vehicle are used for validation. Results indicate that the optimal interpolation approach performs better than the spline model at and above the thermocline depth as long as anisotropic covariances computed from the remote sensing data are used. Below the thermocline, the two merging techniques give similar performance.

Cuckoo Search Based Decision Fusion Techniques for Natural Terrain Understanding

2014 ◽  
Vol 5 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Arpita Sharma ◽  
Samiksha Goel
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Cuckoo Search ◽  
Decision Fusion ◽  
Majority Voting ◽  
Natural Terrain ◽  
Terrain Features ◽  
Level Fusion ◽  
Better Than

This paper proposes two novel nature inspired decision level fusion techniques, Cuckoo Search Decision Fusion (CSDF) and Improved Cuckoo Search Decision Fusion (ICSDF) for enhanced and refined extraction of terrain features from remote sensing data. The developed techniques derive their basis from a recently introduced bio-inspired meta-heuristic Cuckoo Search and modify it suitably to be used as a fusion technique. The algorithms are validated on remote sensing satellite images acquired by multispectral sensors namely LISS3 Sensor image of Alwar region in Rajasthan, India and LANDSAT Sensor image of Delhi region, India. Overall accuracies obtained are substantially better than those of the four individual terrain classifiers used for fusion. Results are also compared with majority voting and average weighing policy fusion strategies. A notable achievement of the proposed fusion techniques is that the two difficult to identify terrains namely barren and urban are identified with similar high accuracies as other well identified land cover types, which was not possible by single analyzers.

Study of Ancient Land Boundaries at Tauric Chersonesos Using Satellite Images

2019 ◽  
Vol 25 (1) ◽  
pp. 44-58 ◽  
Author(s):  
Edgar A. Terekhin ◽  
Tatiana N. Smekalova
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Satellite Images ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Field Surveys ◽  
The 1960S ◽  
Better Than ◽  
Made In

Abstract The near chora (agricultural land) of Tauric Chersonesos was investigated using multiyear remote sensing data and field surveys. The boundaries of the land plots were studied with GIS (Geographic Information Systems) technology and an analysis of satellite images. Reliable reconstruction of the borders has been done for 231 plots (from a total of about 380), which is approximately 53% of the Chersonesean chora. During the last 50 years, most of the ancient land plots have been destroyed by modern buildings, roads, or forests. However, in the 1960s, a significant part of the chora was still preserved. Changes in preservation with time were studied with the aid of satellite images that were made in 1966 and 2015. During that period, it was found that the number of plots with almost-complete preservation decreased from 47 to 0. Those land plots whose preservation was better than 50% dropped from 104 to 4. A temporal map shows this decline in preservation. It was found that the areas of land plots could be determined accurately with satellite images; compared to field surveys, this accuracy was about 99%.

Research of Improved Minnaert Topographic Correction Model and Application

2014 ◽  
Vol 543-547 ◽  
pp. 2780-2783
Author(s):  
Yan Zhen Wu ◽  
Zuo Cheng Wang ◽  
Fu Pin Yang ◽  
Xiao Bo Luo
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Remote Sensing Images ◽  
Topographic Correction ◽  
Correction Model ◽  
Model Based ◽  
Effective Factor ◽  
Quantitative Remote Sensing ◽  
Scs Model ◽  
Better Than

The topographic correction of remote sensing images is an important factor to improve the precision of quantitative remote sensing data processing. In the existing topographic correction models,the Minnaert model is the only model based on the assumption of non-Lambertian.the Minnaert coefficient K is an effective factor for the correction results. To improve the correction accuracy,we correct the image in accordance with the slope grading idea to select different areas from the image, then use different k values in different slope regions.In this paper, the topography correction is efficiently corrected by SCS model, Minnaert model and improved Minnaert model, based on HJCCD image and the corresponding DEM in Heihe . The results showed that the improved Minnaert model can eliminate the effect of topography better than other methods and can be widely used.

A Method of Using WRF-Simulated Surface Temperature to Estimate Daily Evapotranspiration

2020 ◽  
Vol 59 (5) ◽  
pp. 901-914 ◽  
Author(s):  
Dakang Wang ◽  
Yan Liu ◽  
Tao Yu ◽  
Yin Zhang ◽  
Qixin Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Continuous Time ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Temperature Data ◽  
Model Data ◽  
Simulated Surface ◽  
Surface Temperature Data ◽  
Better Than

AbstractSurface temperature is one of the key parameters for estimating regional evapotranspiration (ET) based on the Surface Energy Balance System (SEBS) model using remote sensing data. However, continuous daily remote sensing surface temperature data are often not available due to the weather and environmental conditions. This paper proposed a scheme to obtain reliable ET that estimating ET using WRF-simulated surface skin temperature (TSK) and then modifying the deviation using the normalized difference vegetation index (NDVI). This study aims to explore whether the model data can be a viable option when the continuous-time-series remote sensing surface temperature is missing for estimating ET. Comparison results show that the correlation between WRF TSK and the measured temperature of the 2-cm soil (Ts) is better than MODIS land surface temperature (LST) in the study area, while the correlation between MODIS LST and the measured surface radiation temperature (IRT) is better than WRF TSK. The MODIS LST is significantly higher than Ts, and the WRF TSK is closer to Ts than MODIS LST. However, the ET calculated using WRF TSK was not good, exhibiting relatively high ET in the whole area and a poor correlation with the measurements, whereby R2, RMSE, and the percent bias (PBIAS) were equal to 0.1256, 5.2783 mm, and −202.17%, respectively. According to the principle of land surface process simulation in WRF, this paper proposes using NDVI to modify ET calculated using TSK. The comparison between the modified ET and the measurements exhibited a relatively good correlation, with R2 = 0.7532, RMSE = 1.0993 mm, and PBIAS = −17.9%. Therefore, the model surface temperature data can be used to estimate continuous-time-series regional ET when NDVI is used to modify the deviation, which indicates the surface temperature data simulated by the WRF Model can become the optional data for estimating ET and compensate for the shortcoming of poor time continuity of remote sensing data, further expanding the application prospects of meteorological model data in the remote sensing field.

scholarly journals Upper tropospheric CH<sub>4</sub> and N<sub>2</sub>O retrievals from MetOp/IASI within the project MUSICA

2017 ◽  
Author(s):  
Omaira E. García ◽  
Eliezer Sepúlveda ◽  
Matthias Schneider ◽  
Andreas Wiegele ◽  
Christian Borger ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Mixing Ratios ◽  
Remote Sensor ◽  
Individual Observation ◽  
Atmospheric Sounding ◽  
Different Seasons ◽  
Ch4 And N2o ◽  
The Individual ◽  
Better Than

Abstract. This paper presents upper tropospheric methane (CH4) and nitrous oxide (N2O) concentrations retrieved from thermal infrared spectra as observed by the remote sensor IASI (Infrared Atmospheric Sounding Interferometer) on-board the EUMETSAT/MetOp meteorological satellites. The CH4 and N2O mixing ratios are retrieved as side products of the MetOp/IASI retrieval developed for the European Research Council project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). The MUSICA/IASI CH4 and N2O retrieval strategy is described in detail as well as their characterisation in terms of the vertical resolution and expected errors. Theoretically, we document that MUSICA/IASI products can capture the upper tropospheric CH4 and N2O variability (at ≈ 300–350 hPa) with a precision better than 2 %. We compare the remote sensing data to coincident high precision aircraft vertical profiles taken within the HIAPER Pole-to-Pole Observations (HIPPO) project and empirically estimate a precision of 2.1 % (38.2 ppbv) for each individual IASI CH4 observation. The precision is improved to 1.7 % (32.1 ppbv) for IASI data that have been averaged within 2° × 2° boxes. For N2O the empirically estimated precision is 2.7 % (8.7 ppbv) for each individual observation and 2.1 % (6.9 ppbv) for the 2° × 2° averages. The empirical study works with data from the missions HIPPO1 and HIPPO5, which cover latitudes between 67º S and 80º N during typical winter and summer conditions in both hemispheres, thus being reasonably representative for global observation during different seasons. In addition, we present a product that combines the CH4 and N2O retrieval estimates. The combination is made a-posteriori and we theoretically and empirically show that the combined product has a much better precision than the individual CH4 and N2O products. For the combined product the theoretical precision is 0.8 % and the comparison with HIPPO data gives an empirical precision estimate of 1.5 % (26.3 ppbv) when considering all individual IASI observations and of 1.2 % (21.8 ppbv) for the 2° ×2° averages. In the case that the horizontal, vertical and temporal variation of N2O can be robustly modeled, we can easily reconstruct CH4 from the combined product and generate high quality IASI CH4 data.

scholarly journals ESTABLISHING THE SCHEME OF THE FAULTS IN SOUTH CENTRAL COASTAL REGION ON THE BASIS OF INTERPRETING THE GEOLOGICAL-GEOPHYSICAL DATA

2018 ◽  
Vol 17 (4) ◽  
pp. 393-405
Author(s):  
Bui Nhi Thanh ◽  
Duong Quoc Hung ◽  
Nguyen Van Luong ◽  
Nguyen Van Diep ◽  
Mai Duc Dong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Seismic Data ◽  
Tectonic Evolution ◽  
Coastal Region ◽  
Remote Sensing Data ◽  
Geological Hazards ◽  
Sensing Data ◽  
South Central ◽  
Shallow Seismic

The scheme of the faults in South Central coastal region was established on the basis of interpreting the high resolution shallow seismic data and the deep-seismic data, in combination with the previous studies on geodynamics, tectonic evolution, geological hazards of the South Central coastal region. The fault systems were formed based on updated geophysical, geomorphological, tectonophysic and remote sensing data, including 19 faults in 3 directions: Sub-longitudinal (8 faults), NE-SW (7 faults) and NW-SE (4 faults).

scholarly journals Monitoring and analysis of the expansion of the Ajmr Port, Davao City, Philippines using multi-source remote sensing data

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7512 ◽  
Author(s):  
Humei Li ◽  
Mingquan Wu ◽  
Dinghui Tian ◽  
Lianxi Wu ◽  
Zheng Niu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Good Condition ◽  
Coastal Region ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Port Area ◽  
The Impact ◽  
Port Construction ◽  
Port Expansion

Ports have been built or expanded in a number of countries to cater to increasing maritime trade in the 21st century. Port expansion is associated with economic and environmental impacts on the local and regional scales, and these impacts can be studied using remote sensing. The present study presents new results from multi-source remote sensing monitoring of the Ajmr Port expansion. An analysis of land use and vegetation coverage at the port is used to monitor the impact of port construction on the local ecology, while changes in roads, buildings, and lights are used to monitor the economic impact. The results show that: (1) After nine years of expansion, the port area has gradually expanded from the central to the southern coastal area, with an increase of 21.68 hectares during the expansion period. After the expansion, the area of builidings and construction in the study area increased significantly, while the area of water and green areas decreased significantly, indicating that the port construction changed the land use structure of the area. (2) From the perspective of vegetation coverage, the vegetation coverage within 5 km from the port is in good condition. After 9 years, the vegetation coverage in the region between 0.6 and 1 increased from 43.71% to 44.25%, reflecting the higher overall greening level in the region. (3) By analyzing the increase in roads and buildings, it can be seen that the port’s comprehensive transportation capacity has improved, the population of the region has increased significantly. As the scale of construction has been continuously expanded , the prosperity as increased. (4) By analyzing the changes in the light index, the light data from the northeast to the southwest in the region is very obvious, and it is clearly located along the coast, indicating that the economic development of the coastal zone is faster than other regions, and the coastal region has promoted the development of the inland region.

scholarly journals Thermal Stability Optimization of the Luojia 1-01 Nighttime Light Remote-Sensing Camera’s Principal Distance

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 990 ◽  
Author(s):  
Kun Zhang ◽  
Xing Zhong ◽  
Guo Zhang ◽  
Deren Li ◽  
Zhiqiang Su ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mathematical Model ◽  
Thermal Stability ◽  
Optical System ◽  
Remote Sensing Data ◽  
Geometric Accuracy ◽  
Sensing Data ◽  
Nighttime Light ◽  
Application Requirements ◽  
Better Than

The instability of the principal distance of the nighttime light remote-sensing camera of the Luojia 1-01 satellite directly affects the geometric accuracy of images, consequently affecting the results of analysis of nighttime light remote-sensing data. Based on the theory of optical passive athermal design, a mathematical model of optical-passive athermal design for principal distance stabilization is established. Positive and negative lenses of different materials and the mechanical structures of different materials are matched to optimize the optical system. According to the index requirements of the Luojia 1-01 camera, an image-telecentric optical system was designed under the guidance of the established mathematical model. In the temperature range of −20 °C to +60 °C, the principal distance of the system changes from −0.01 μm to +0.28 μm. After on-orbit testing, the geometric accuracy of the designed nighttime light remote-sensing camera is better than 0.20 pixels and less than index requirement of 0.3 pixels, which indicating that the principal distance maintains good stability on-orbit and meets the application requirements of nighttime light remote sensing.

scholarly journals Evaluation of the smoke-injection height from wild-land fires using remote-sensing data

2012 ◽  
Vol 12 (4) ◽  
pp. 1995-2006 ◽  
Author(s):  
M. Sofiev ◽  
T. Ermakova ◽  
R. Vankevich
Keyword(s):  
Remote Sensing ◽  
Convective Available Potential Energy ◽  
Remote Sensing Data ◽  
New Method ◽  
Plume Rise ◽  
Physical Processes ◽  
Plume Height ◽  
Fire Plumes ◽  
Semi Empirical ◽  
Better Than

Abstract. A new methodology for the estimation of smoke-injection height from wild-land fires is proposed and evaluated. It is demonstrated that the approaches developed for estimating the plume rise from stacks, such as the formulas of G. Briggs, can be formally written in terms characterising the wild-land fires: fire energy, size and temperature. However, these semi-empirical methods still perform quite poorly because the physical processes controlling the uplift of the wildfire plumes differ from those controlling the plume rise from stacks. The proposed new methodology considers wildfire plumes in a way similar to Convective Available Potential Energy (CAPE) computations. The new formulations are applied to a dataset collected within the MISR Plume Height Project for about 2000 fire plumes in North America and Siberia. The estimates of the new method are compared with remote-sensing observations of the plume top by the MISR instrument, with two versions of the Briggs' plume-rise formulas, with the 1-D plume-rise model BUOYANT, and with the prescribed plume-top position (the approach widely used in dispersion modelling). The new method has performed significantly better than all these approaches. For two-thirds of the cases, its predictions deviated from the MISR observations by less than 500 m, which is the uncertainty of the observations themselves. It is shown that the fraction of "good" predictions is much higher (>80%) for the plumes reaching the free troposphere.

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