scholarly journals LAI, FAPAR and FCOVER ground-truth map creation from FASat-C satellite imagery and in-situ measurements in Chimbarongo, Chile, for satellite products validation

2016 ◽  
pp. 51 ◽  
Author(s):  
C. Latorre-Sánchez ◽  
F. Camacho ◽  
C. Mattar ◽  
A. Santamaría-Artigas ◽  
N. Leiva-Büchi ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Field Data ◽  
Ground Truth ◽  
Landsat 8 ◽  
Data Sampling ◽  
Least Squares Regression ◽  
Ground Field ◽  
Global Land

<p align="justify">In remote sensing, validation exercises are essential to ensure the quality of the products originated from satellite Earth observations. To assess the measurement uncertainty derived from satellite products, several ground field data from different ecosystems must be available for use. In the same order of importance, it is necessary to define data sampling and up-scaling methodologies to allow a suitable comparison between the ground data and the pixel size of the product. This paper shows the applied methodology used in the FP7 ImagineS project (Implementing Multi-scale Agricultural Indicators Exploiting Sentinels) to validate 10-days global LAI, FAPAR and vegetation cover products at 1km spatial resolution using in-situ data. These global products are derived from PROBA-V observations in the Copernicus Global Land Service. In particular, this case study shows the results of the field-campaign carried out in January of 2015 in the agricultural area of Chimbarongo, Chile. The methodology to scale the ground data and to create ground-based maps using FASat-C Chilean satellite imagery with a 5,8 m spatial resolution using multivariate least squares regression is shown. Finally, the same methodology was used with a 30 m spatial resolution Landsat-8 image to analyze the effect of the field-data input on the ground-truth maps used to validate the results. Our results show the reliability on the presented methodology and the consistency of the method with regard to the input data. Better results and lower RMSE errors were obtained using FASat-C data. The comparison with satellite products at 1 km shows a good agreement with Copernicus Global Land products derived from PROBA-V observations, and systematic negative bias for the MODIS products.</p>

scholarly journals Urban thermal micro-mapping using satellite imagery and ground-truth measurements: Kyiv city area case study

2019 ◽  
pp. 40-48
Author(s):  
Iryna Piestova ◽  
Mykola Lubskyi ◽  
Mykhailo Svideniuk ◽  
Stanislav Golubov ◽  
Oleksandr Laptiev
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Thermal Conditions ◽  
Ground Truth ◽  
Bare Soil ◽  
Landsat 8 ◽  
Thermal Anomalies ◽  
City Area ◽  
Thermal Emissivity ◽  
Sentinel 2A

The aim of this research is to enhance approaches existing for the assessment of cities thermal conditions under climate change impact by using multispectral satellite data for Kyiv city area. This paper describes the method and results of the Earth’s surface temperature (LST) and thermal emissivity calculation. Particularly, the thermal distribution was estimated based on spectral densities according to Planck’s law for “grey bodies” by using the Landsat-8 TIRS and Sentinel-2 MSI satellite imagery. Furthermore, the result was calibrated by ground data collected during the ground-truth measurements of the typical city surfaces temperature and thermal emissivity. The spatial resolution of the LST images obtained was enhanced by using the approach of subpixel processing, that is the pairs of invariant images shifted with subpixel accuracy. As a result, such an approach allowed to enhance the spatial resolution of the image up 46%, which is much higher than the potential performance of the thermal imaging sensors existing. The interrelation between the Earth’s surface type and the temperature was revealed by the results of the Sentinel-2A MSI image of 21 August 2017 supervised classification. Thus, the image was divided into the six major classes of the urban environment: building’s rooftops, roads surface, bare soil, grass, wood, and water. As a result, surfaces with vegetation much more cool next to artificial ones. The time-series analysis of 18 thermal images (Landsat TM and Landsat-8 TIRS) of Kyiv for the period from 6 Jun 1985 till 1 June 2018 was done for spatiotemporal changes investigation. Therefore, the sites of the LST thermal anomalies caused by landscape changes were developed. Among them are the sites of increased LST where thw “Olimpiyskiy” national sport center and adjacent parking was built and the site of decreased LST where the tram depot was liquidated and the territory was flooded.

scholarly journals Closing the gap between Earth-based and interplanetary mission observations: Vesta seen by VLT/SPHERE

2019 ◽  
Vol 623 ◽  
pp. A6 ◽  
Author(s):  
R. JL. Fétick ◽  
L. Jorda ◽  
P. Vernazza ◽  
M. Marsset ◽  
A. Drouard ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Spatial Resolution ◽  
Ground Truth ◽  
Space Mission ◽  
Contour Extraction ◽  
Dawn Mission ◽  
The North ◽  
Adaptive Optics Imaging ◽  
Interplanetary Missions

Context. Over the past decades, several interplanetary missions have studied small bodies in situ, leading to major advances in our understanding of their geological and geophysical properties. These missions, however, have had a limited number of targets. Among them, the NASA Dawn mission has characterised in detail the topography and albedo variegation across the surface of asteroid (4) Vesta down to a spatial resolution of ~20 m pixel−1 scale. Aims. Here our aim was to determine how much topographic and albedo information can be retrieved from the ground with VLT/SPHERE in the case of Vesta, having a former space mission (Dawn) providing us with the ground truth that can be used as a benchmark. Methods. We observed Vesta with VLT/SPHERE/ZIMPOL as part of our ESO large programme (ID 199.C-0074) at six different epochs, and deconvolved the collected images with a parametric point spread function (PSF). We then compared our images with synthetic views of Vesta generated from the 3D shape model of the Dawn mission, on which we projected Vesta’s albedo information. Results. We show that the deconvolution of the VLT/SPHERE images with a parametric PSF allows the retrieval of the main topographic and albedo features present across the surface of Vesta down to a spatial resolution of ~20–30 km. Contour extraction shows an accuracy of ~1 pixel (3.6 mas). The present study provides the very first quantitative estimate of the accuracy of ground-based adaptive-optics imaging observations of asteroid surfaces. Conclusions. In the case of Vesta, the upcoming generation of 30–40 m telescopes (ELT, TMT, GMT) should in principle be able to resolve all of the main features present across its surface, including the troughs and the north–south crater dichotomy, provided that they operate at the diffraction limit.

scholarly journals Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery

2020 ◽  
Vol 12 (23) ◽  
pp. 3958
Author(s):  
Parwati Sofan ◽  
David Bruce ◽  
Eriita Jones ◽  
M. Rokhis Khomarudin ◽  
Orbita Roswintiarti
Keyword(s):  
Spatial Resolution ◽  
Fire Detection ◽  
Ground Truth ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Ground Truth Data ◽  
Spectral Instrument ◽  
Tropical Peatland ◽  
Tropical Environments ◽  
Sentinel 2

This study establishes a new technique for peatland fire detection in tropical environments using Landsat-8 and Sentinel-2. The Tropical Peatland Combustion Algorithm (ToPeCAl) without longwave thermal infrared (TIR) (henceforth known as ToPeCAl-2) was tested on Landsat-8 Operational Land Imager (OLI) data and then applied to Sentinel-2 Multi Spectral Instrument (MSI) data. The research is aimed at establishing peatland fire information at higher spatial resolution and more frequent observation than from Landsat-8 data over Indonesia’s peatlands. ToPeCAl-2 applied to Sentinel-2 was assessed by comparing fires detected from the original ToPeCAl applied to Landsat-8 OLI/Thermal Infrared Sensor (TIRS) verified through comparison with ground truth data. An adjustment of ToPeCAl-2 was applied to minimise false positive errors by implementing pre-process masking for water and permanent bright objects and filtering ToPeCAl-2’s resultant detected fires by implementing contextual testing and cloud masking. Both ToPeCAl-2 with contextual test and ToPeCAl with cloud mask applied to Sentinel-2 provided high detection of unambiguous fire pixels (>95%) at 20 m spatial resolution. Smouldering pixels were less likely to be detected by ToPeCAl-2. The detected smouldering pixels from ToPeCAl-2 applied to Sentinel-2 with contextual testing and with cloud masking were only 35% and 56% correct, respectively; this needs further investigation and validation. These results demonstrate that even in the absence of TIR data, an adjusted ToPeCAl algorithm (ToPeCAl-2) can be applied to detect peatland fires at 20 m resolution with high accuracy especially for flaming. Overall, the implementation of ToPeCAl applied to cost-free and available Landsat-8 and Sentinel-2 data enables regular peatland fire monitoring in tropical environments at higher spatial resolution than other satellite-derived fire products.

scholarly journals Monitoring of Surface Temperature on Parco delle Biancane (Italian Geothermal Area) Using Optical Satellite Data, UAV and Field Campaigns

2020 ◽  
Vol 12 (12) ◽  
pp. 2018
Author(s):  
Malvina Silvestri ◽  
Enrica Marotta ◽  
Maria Fabrizia Buongiorno ◽  
Gala Avvisati ◽  
Pasquale Belviso ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Spatial Resolution ◽  
Satellite Data ◽  
Field Measurements ◽  
Geothermal Field ◽  
Landsat 8 ◽  
Ground Field ◽  
Thermal Images ◽  
Field Campaigns ◽  
Temperature Maps

The purpose of this study is to analyze the surface temperature and the distribution of thermal signatures on Tuscany’s geothermal districts using data obtained through three separate surveys via satellite and an unmanned aerial vehicle (UAV). The analysis considers the highest available spatial resolution ranging from hundreds of meters per pixel of the satellite thermal images and the tenths/hundreds of centimeters per pixel of the thermal images acquired by the UAV. The surface temperature maps obtained by satellite data acquired at suitable spatial resolution and the thermal measurements obtained by the thermal camera installed on the UAV were orthorectified and geocoded. This allowed, for example, following the evolution of thermal anomalies, which may represent a modification of the current state of the geothermal field and a possible hazard for both the population and industrial assets. Here, we show the results obtained in three field campaigns during which the simultaneous acquisition of Landsat 8 satellite and UAV (FlyBit octocopter, IDS, Rome, Italy) thermal data were analyzed. By removing the atmosphere contribution from Landsat 8 data, we have produced three surface temperature maps that are compared with the ground field measurements and the surface temperature maps elaborated by FLIR VUE PRO-R on the UAV.

scholarly journals Very Hot Plasmas in the Solar System

1980 ◽  
Vol 5 ◽  
pp. 351-359 ◽  
Author(s):  
W. I. Axford
Keyword(s):  
Solar Wind ◽  
Solar System ◽  
Spatial Resolution ◽  
Ground Truth ◽  
Astrophysical Plasmas ◽  
The Earth ◽  
Emission And Absorption Spectra ◽  
New Ideas ◽  
The Universe

In contrast to most astrophysical situations where information about hot plasmas can be obtained only from emission and absorption spectra, often without spatial resolution, plasmas in the solar system in many cases provide us with the opportunity to make direct, in situ measurements. Such plasmas, notably the solar wind and the plasmas contained in the magnetosphere of the earth, Jupiter, and other planets, must be heated by processes which are in many cases similar to those occurring in astrophysical plasmas and their behaviour should also be to some extent similar. It is therefore interesting and instructive to be able to compare our observations and understanding of these accessible solar system plasmas with those found elsewhere in the universe which are not so easy to observe in detail. This might provide us with some new ideas and perspectives on the nature and behaviour of hot plasmas in general and also an opportunity to test some of our ideas against “ground truth”.

scholarly journals Selection of informative features to highlight areas of waste disposal on high spatial resolution satellite imagery

2019 ◽  
pp. 29-44
Author(s):  
A. B. Murynin ◽  
A. A. Richter ◽  
M. A. Shakhramanyan
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Waste Disposal ◽  
High Spatial Resolution ◽  
Ground Truth ◽  
Space Images ◽  
Radar Images ◽  
High Resolution Images ◽  
Interpretive Signs ◽  
Selection Of

The paper deals with the problem of integrated interpretation of waste disposal facilities according to satellite imagery and ground truth monitoring, features of space images of landfills from various points of view: texture analysis, statistical properties, fractal analysis, color features, and the possibility of using machine learning methods. The main visual interpretive signs of landfills on optical and radar images of high spatial resolution are given. The fractal dimension of landfills was calculated for high resolution images using two models.

scholarly journals SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8

2016 ◽  
Vol XLI-B7 ◽  
pp. 647-652
Author(s):  
A. Fryskowska ◽  
M. Wojtkowska ◽  
P. Delis ◽  
A. Grochala
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Thermal Infrared ◽  
Visual Assessment ◽  
Landsat 8 ◽  
Image Integration ◽  
Panchromatic Image ◽  
False Color ◽  
New Sensors ◽  
Band Combinations

The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands). Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5&dash;0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of Landsat 8 with data from the new high resolution panchromatic EROS B satellite are analyzed. The range of panchromatic band for EROS B is 0.4&dash;0.9 μm and spatial resolution is 0.7 m. Research relied on improving the spatial resolution of natural color band combinations (bands: 4,3,2) and of desired false color band composition of Landsat 8 satellite imagery. For this purpose, six algorithms have been tested: Brovey’s, Mulitplicative, PCA, IHS, Ehler's, HPF. On the basis of the visual assessment, it was concluded that the best results of multispectral and panchromatic image integration, regardless land cover, are obtained for the multiplicative method. These conclusions were confirmed by statistical analysis using correlation coefficient, ERGAS and R-RMSE indicators.

scholarly journals Pattern of Turbidity Change in the Middle Reaches of the Yarlung Zangbo River, Southern Tibetan Plateau, from 2007 to 2017

2021 ◽  
Vol 13 (2) ◽  
pp. 182
Author(s):  
Ming Shen ◽  
Siyuan Wang ◽  
Yingkui Li ◽  
Maofeng Tang ◽  
Yuanxu Ma
Keyword(s):  
Tibetan Plateau ◽  
Satellite Imagery ◽  
Large Scale ◽  
Environmental Changes ◽  
Landsat 8 ◽  
The Tibetan Plateau ◽  
Important Indicator ◽  
Yarlung Zangbo River ◽  
Southern Tibetan Plateau

Turbidity is an important indicator of riverine conditions, especially in a fragile environment such as the Tibetan Plateau. Remote sensing, with the advantages of large-scale observations, has been widely applied to monitor turbidity change in lakes and rivers; however, few studies have focused on turbidity change of rivers on the Tibetan Plateau. We investigated the pattern of turbidity change in the middle reaches of the Yarlung Zangbo River, southern Tibetan Plateau, based on multispectral satellite imagery and in situ measurements. We developed empirical models from in situ measured water leaving reflectance and turbidity, and applied the best performed s-curve models on satellite imagery from Sentinel-2, Landsat 8, and Landsat 5 to derive turbidity change in 2007–2017. Our results revealed an overall decreasing spatial trend from the upper to lower streams. Seasonal variations were observed with high turbidity from July to September and low turbidity from October to May. Annual turbidity showed a temporally slightly declining trend from 2007 to 2017. The pattern of turbidity change is affected by the confluence of tributaries and the changes in precipitation and vegetation along the river. These findings provide important insights into the responses of riverine turbidity to climate and environmental changes on the Tibetan Plateau.

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