scholarly journals Empirical Absolute Calibration Model for Multiple Pseudo-Invariant Calibration Sites

2019 ◽  
Vol 11 (9) ◽  
pp. 1105 ◽  
Author(s):  
Bipin Raut ◽  
Morakot Kaewmanee ◽  
Amit Angal ◽  
Xiaoxiong Xiong ◽  
Dennis Helder
Keyword(s):  
Region Of Interest ◽  
Image Data ◽  
Sensor Calibration ◽  
Absolute Calibration ◽  
Landsat 8 ◽  
Calibration Model ◽  
General Applicability ◽  
Landsat 7 ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sentinel 2A

This work extends an empirical absolute calibration model initially developed for the Libya 4 Pseudo-Invariant Calibration Site (PICS) to five additional Saharan Desert PICS (Egypt 1, Libya 1, Niger 1, Niger 2, and Sudan 1), and demonstrates the efficacy of the resulting models at predicting sensor top-of-atmosphere (TOA) reflectance. It attempts to generate absolute calibration models for these PICS that have an accuracy and precision comparable to or better than the current Libya 4 model, with the intent of providing additional opportunities for sensor calibration. In addition, this work attempts to validate the general applicability of the model to other sites. The method uses Terra Moderate Resolution Imaging Spectroradiometer (MODIS) as the reference radiometer and Earth Observing-1 (EO-1) Hyperion image data to provide a representative hyperspectral reflectance profile of the PICS. Data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the PICS are used for developing the model. The developed models were used to simulate observations of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), Landsat 8 (L8) Operational Land Imager (OLI), Sentinel 2A (S2A) MultiSpectral Instrument (MSI) and Sentinel 2B (S2B) MultiSpectral Instrument (MSI) from their respective launch date through 2018. The models developed for the Egypt 1, Libya 1 and Sudan 1 PICS have an estimated accuracy of approximately 3% and precision of approximately 2% for the sensors used in the study, comparable to the current Libya 4 model. The models developed for the Niger 1 and Niger 2 sites are significantly less accurate with similar precision.

scholarly journals Hyperspectral Empirical Absolute Calibration Model Using Libya 4 Pseudo Invariant Calibration Site

2021 ◽  
Vol 13 (8) ◽  
pp. 1538
Author(s):  
Manisha Das Chaity ◽  
Morakot Kaewmanee ◽  
Larry Leigh ◽  
Cibele Teixeira Teixeira Pinto
Keyword(s):  
Zenith Angle ◽  
Spectral Resolution ◽  
Region Of Interest ◽  
Image Data ◽  
Absolute Calibration ◽  
Landsat 8 ◽  
Calibration Model ◽  
View Zenith Angle ◽  
Satellite Sensors ◽  
Terra Modis

The objective of this paper is to find an empirical hyperspectral absolute calibration model using Libya 4 pseudo invariant calibration site (PICS). The approach involves using the Landsat 8 (L8) Operational Land Imager (OLI) as the reference radiometer and using Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm as a hyperspectral source. This model utilizes data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the Libya 4 PICS. It uses an improved, simple, empirical, hyperspectral Bidirectional Reflectance Distribution function (BRDF) model accounting for four angles: solar zenith and azimuth, and view zenith and azimuth angles. This model can perform absolute calibration in 1 nm spectral resolution by predicting TOA reflectance in all existing spectral bands of the sensors. The resultant model was validated with image data acquired from satellite sensors such as Landsat 7, Sentinel 2A, and Sentinel 2B, Terra MODIS, Aqua MODIS, from their launch date to 2020. These satellite sensors differ in terms of the width of their spectral bandpass, overpass time, off-nadir viewing capabilities, spatial resolution, and temporal revisit time, etc. The result demonstrates the efficacy of the proposed model has an accuracy of the order of 3% with a precision of about 3% for the nadir viewing sensors (with view zenith angle up to 5) used in the study. For the off-nadir viewing satellites with view zenith angle up to 20, it can have an estimated accuracy of 6% and precision of 4%.

scholarly journals Using Window Regression to Gap-Fill Landsat ETM+ Post SLC-Off Data

2018 ◽  
Vol 10 (10) ◽  
pp. 1502 ◽  
Author(s):  
Evan Brooks ◽  
Randolph Wynne ◽  
Valerie Thomas
Keyword(s):  
Computation Time ◽  
Window Size ◽  
Landsat 8 ◽  
Ancillary Data ◽  
Data Intensive ◽  
Landsat 7 ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Temporal Dimensions ◽  
Data Layers

The continued development of algorithms using multitemporal Landsat data creates opportunities to develop and adapt imputation algorithms to improve the quality of that data as part of preprocessing. One example is de-striping Enhanced Thematic Mapper Plus (ETM+, Landsat 7) images acquired after the Scan Line Corrector failure in 2003. In this study, we apply window regression, an algorithm that was originally designed to impute low-quality Moderate Resolution Imaging Spectroradiometer (MODIS) data, to Landsat Analysis Ready Data from 2014–2016. We mask Operational Land Imager (OLI; Landsat 8) image stacks from five study areas with corresponding ETM+ missing data layers, using these modified OLI stacks as inputs. We explored the algorithm’s parameter space, particularly window size in the spatial and temporal dimensions. Window regression yielded the best accuracy (and moderately long computation time) with a large spatial radius (a 7 × 7 pixel window) and a moderate temporal radius (here, five layers). In this case, root mean square error for deviations from the observed reflectance ranged from 3.7–7.6% over all study areas, depending on the band. Second-order response surface analysis suggested that a 15 × 15 pixel window, in conjunction with a 9-layer temporal window, may produce the best accuracy. Compared to the neighborhood similar pixel interpolator gap-filling algorithm, window regression yielded slightly better accuracy on average. Because it relies on no ancillary data, window regression may be used to conveniently preprocess stacks for other data-intensive algorithms.

scholarly journals Riesgo en estructuras hidráulicas asociado al cambio de uso del suelo en cuencas hidrográficas

2018 ◽  
Vol 26 (1) ◽  
pp. 157-162
Author(s):  
Edmundo Canchari Gutiérrez
Keyword(s):  
Landsat 8 ◽  
Landsat 7 ◽  
Sentinel 2A

La finalidad del trabajo es determinar el riesgo de las estructuras hidráulicas asociado al cambio del uso de suelo en cuencas hidrográficas, para la evaluación del cambio de uso del suelo y la variación en el tiempo se obtiene en base al registro disponibles de los proyectos LANDSAT 5, LANDSAT 7 y LANDSAT 8, además del proyecto SENTINEL 2A; como fundamento teórico se trata la teledetección, índice de vegetación de diferencia normalizada, transformación de la precipitación en escorrentía, riesgo, vulnerabilidad y resiliencia. El índice de vegetación de diferencia normalizada se asocia al cambio de uso del suelo y éste con la capacidad de abstracción de la precipitación, obteniendo así los caudales de máxima avenida para los periodos analizados.

scholarly journals Two decades of dynamic change and progressive destabilization on the Thwaites Eastern Ice Shelf

2021 ◽  
Vol 15 (11) ◽  
pp. 5187-5203
Author(s):  
Karen E. Alley ◽  
Christian T. Wild ◽  
Adrian Luckman ◽  
Ted A. Scambos ◽  
Martin Truffer ◽  
...  
Keyword(s):  
Shear Zone ◽  
Structural Integrity ◽  
Dynamic Change ◽  
Image Data ◽  
Landsat 8 ◽  
Ice Shelf ◽  
Ice Flow ◽  
Landsat 7 ◽  
Rapid Pace ◽  
Elevation Model

Abstract. The Thwaites Eastern Ice Shelf (TEIS) buttresses the eastern grounded portion of Thwaites Glacier through contact with a pinning point at its seaward limit. Loss of this ice shelf will promote further acceleration of Thwaites Glacier. Understanding the dynamic controls and structural integrity of the TEIS is therefore important to estimating Thwaites' future sea-level contribution. We present a ∼ 20-year record of change on the TEIS that reveals the dynamic controls governing the ice shelf's past behaviour and ongoing evolution. We derived ice velocities from MODIS and Sentinel-1 image data using feature tracking and speckle tracking, respectively, and we combined these records with ITS_LIVE and GOLIVE velocity products from Landsat-7 and Landsat-8. In addition, we estimated surface lowering and basal melt rates using the Reference Elevation Model of Antarctica (REMA) DEM in comparison to ICESat and ICESat-2 altimetry. Early in the record, TEIS flow dynamics were strongly controlled by the neighbouring Thwaites Western Ice Tongue (TWIT). Flow patterns on the TEIS changed following the disintegration of the TWIT around 2008, with a new divergence in ice flow developing around the pinning point at its seaward limit. Simultaneously, the TEIS developed new rifting that extends from the shear zone upstream of the ice rise and increased strain concentration within this shear zone. As these horizontal changes occurred, sustained thinning driven by basal melt reduced ice thickness, particularly near the grounding line and in the shear zone area upstream of the pinning point. This evidence of weakening at a rapid pace suggests that the TEIS is likely to fully destabilize in the next few decades, leading to further acceleration of Thwaites Glacier.

scholarly journals Impact of land use change on hydrological conditions in the Karajae watershed, South Sulawesi Province

2021 ◽  
Vol 886 (1) ◽  
pp. 012079
Author(s):  
Chairil A ◽  
Syamsu Rijal ◽  
Munajat Nursaputra ◽  
Muh. Faisal Mappiase
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Image Data ◽  
Water Source ◽  
Assessment Tools ◽  
Landsat 8 ◽  
Dryland Agriculture ◽  
Land Use Patterns ◽  
Hydrological Conditions ◽  
Landsat 7

Abstract Land use is a representation of activities and utilization of land resources by the community. Land use has a big influence on the hydrological condition of a watershed. One of the small watersheds, in general, is the Karajae watershed, but it has a very large impact on the City of Pare-Pare, and the surrounding community. The Karajae watershed is the main water source for the people of Pare-Pare and agriculture. This study aims to analyze land use patterns that have a major impact on hydrological conditions in the Karajae watershed. The analysis begins with remote sensing methods to interpret land use using Landsat 7 image data in 2010 and Landsat 8 imagery in 2020. Next, analyze the pattern of land use change in detail in each forest area with a geographic information system approach. Analysis of hydrological conditions using the Soil and Water Assessment Tools approach with the input of the land use data. Land use Change 2010-2020 in the Karajae watershed shows additional land use in the form of settlements, rice fields, and dryland agriculture as a form of community activity. There are two forest areas in the Karajae watershed, namely production forest and protected forest. Production forest is dominated by dryland agriculture in the form of corn, beans, and horticulture, while the protected forest is dominated by and secondary dryland forest. This has an impact on hydrological conditions that there are fluctuations in discharge and an increase in sediment a decade ago. Optimal application of forest functions reduces discharge and sediment. Different forest planning for each forest function and land use within. Production forest with many activities directed towards community-based forest management such as community forest and village forest. As for the Protected Forest, which is dominated by grassland and shrubs, forest rehabilitation is carried out.

scholarly journals Utilisation De L’image Multispectrale Pour L’exploration Et La Recherche Des Ressources Minérales : État Des Connaissances Et Proposition D’un Modèle De Traitement

2018 ◽  
Vol 14 (24) ◽  
pp. 350
Author(s):  
Abdessamad El Atillah ◽  
Zine El Abidine El Morjani ◽  
Mustapha Souhassou
Keyword(s):  
Remote Sensing ◽  
Principal Component ◽  
Geological Mapping ◽  
Landsat 8 ◽  
Geological Maps ◽  
Landsat 7 ◽  
Sentinel 2A ◽  
Terrestrial Globe ◽  
The Cost ◽  
Methods Of Treatment

Multiband space remote sensing is an indirect tool for prospecting the Earth's surface. It is very powerful especially in its applications related to the field of geology including geological mapping, mining and oil exploration. It can also significantly reduce the cost of exploration, reach inaccessible areas, guide mining research to favorable regions and reach a large surface. In this article, we highlight in details the state of knowledge in this field of research by citing the different methods and approaches carried out by several specialists who generally define the use of remote sensing for lithostructural and mineralogical mapping and particularly for the exploration and research of mineral substances. We also create methods derived from the aforementioned methods of treatment by means of a logical analogy between the different bands of several satellites of observation of the terrestrial globe, particularly between : Landsat 7 ETM +; Landsat 8 OLI / TIRS; Aster and Sentinel 2A. At the end, we synthesize these results by proposing a multispectral image-processing model that can be applied directly. This model starts with the calculation of Optimum Index Factor (OIF), which allows us to detect only the most important colored composites; and the reports of the bands, rations, the principal component analysis, ACI and the classification that allow the realization of a lithological and mineralogical mapping as well as maps of lineaments by means of directional filters. The validity of the models is tested by comparison with field data and geological maps of the studied site.

scholarly journals Spatial Temporal Analysis of Coral Reefs in Belitung Tourism Destination Islands

2018 ◽  
Vol 73 ◽  
pp. 03024
Author(s):  
Pavita Raudina Sari ◽  
Ratna Saraswati ◽  
Adi Wibowo
Keyword(s):  
Coral Reefs ◽  
Image Data ◽  
Temporal Analysis ◽  
Landsat 8 ◽  
Tourism Destination ◽  
Natural Factor ◽  
Tourist Attractions ◽  
Natural Factors ◽  
Landsat 7 ◽  
Landsat Satellite

One of the world’s most spectacular ecosystems in this world is the coral reef. In Indonesia, Bangka Belitung is one province which has beautiful coral reefs and has become one of the tourist attractions. However, there might be a loss of the coral reefs area that can be caused by natural factors and human activities. This study aims to analyze the distribution and the changing of coral reefs that occurred in the islands of tourist destination in Belitung Regency from 2005 to 2018 and to analyze its factors. Landsat satellite imageries used in this study are Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI/TIRS. The distribution of coral reefs will be determined by image data processing. Then, overlay methods are used to analyze the changes and its factors. Based on the analysis, in the year of 2005-2018, there are 3.93 km2 areas of coral reefs that have decreased. On the top of that, there are 1.34 km2 or about 34.04% of coral reefs areas have decreased that caused by non-natural factors. It can be concluded that the decreased of the coral reefs occurred in Belitung tourism destination islands, are still dominated by natural factors rather than a non-natural factor.

scholarly journals New Approach for Temporal Stability Evaluation of Pseudo-Invariant Calibration Sites (PICS)

2019 ◽  
Vol 11 (12) ◽  
pp. 1502 ◽  
Author(s):  
Fatima Tuz Zafrin Tuli ◽  
Cibele Teixeira Pinto ◽  
Amit Angal ◽  
Xiaoxiong Xiong ◽  
Dennis Helder
Keyword(s):  
Temporal Stability ◽  
Kendall Test ◽  
Sensor Calibration ◽  
Landsat 8 ◽  
Radiometric Calibration ◽  
Calibration Source ◽  
Blue Band ◽  
New Approach ◽  
Monotonic Trend ◽  
Moderate Resolution Imaging Spectroradiometer

Pseudo-Invariant Calibration Sites (PICS) are one of the most popular methods for in-flight vicarious radiometric calibration of Earth remote sensing satellites. The fundamental question of PICS temporal stability has not been adequately addressed. However, the main purpose of this work is to evaluate the temporal stability of a few PICS using a new approach. The analysis was performed over six PICS (Libya 1, Libya 4, Niger 1, Niger 2, Egypt 1 and Sudan 1). The concept of a “Virtual Constellation” was developed to provide greater temporal coverage and also to overcome the dependence limitation of any specific characteristic derived from one particular sensor. TOA reflectance data from four sensors consistently demonstrating “stable” calibration to within 5%—the Landsat 7 ETM+ (Enhanced Thematic Mapper Plus), Landsat 8 OLI (Operational Land Imager), Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and Sentinel-2A MSI (Multispectral Instrument)–were merged into a seamless dataset. Instead of using the traditional method of trend analysis (Student’s T test), a nonparametric Seasonal Mann-Kendall test was used for determining the PICS stability. The analysis results indicate that Libya 4 and Egypt 1 do not exhibit any monotonic trend in six reflective solar bands common to all of the studied sensors, indicating temporal stability. A decreasing monotonic trend was statistically detected in all bands, except SWIR 2, for Sudan 1 and the Green and Red bands for Niger 1. An increasing trend was detected in the Blue band for Niger 2 and the NIR band for Libya 1. These results do not suggest abandoning PICS as a viable calibration source. Rather, they indicate that PICS temporal stability cannot be assumed and should be regularly monitored as part of the sensor calibration process.

scholarly journals IDENTIFICATION OF MANGROVE FORESTS USING MULTI-RESOLUTION SATELLITE IMAGERY

Jurnal Segara ◽  
2020 ◽  
Vol 16 (2) ◽  
Author(s):  
Anang Dwi Purwanto
Keyword(s):  
Remote Sensing ◽  
Mangrove Forest ◽  
Image Data ◽  
Field Measurements ◽  
Landsat 8 ◽  
Mangrove Forests ◽  
Remote Sensing Technology ◽  
Red Edge ◽  
Sensing Technology ◽  
Sentinel 2A

The development of remote sensing technology for identifying various of coastal and marine ecosystems which one of them is mangrove forest increasing rapidly. Identification of mangrove forests visually is constrained by much of combinations of RGB composite. The aims of this research is to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using Optimum Index Factor (OIF) method. The image data used represents 3 levels of intermediate to high resolution spatial resolution including Landsat 8 imagery (30 m) acquisition on 30 May 2013, Sentinel 2A image (10 m) acquisition on 18 March 2018 and SPOT 6 image (6 m) acquisition on 10 January 2015. Data of mangrove distributions used were the results of field measurements in the period 2013-2015. The results showed that the band composites of 564 (NIR+SWIR+Red) of Landsat 8 image and the band composites of 8a114 (Vegetation Red Edge+SWIR+Red) of Sentinel 2A are the best RGB composites for identifying mangrove forest, while the band composites of 341 (Red+NIR+Blue) of SPOT 6 image is  also the best colour composites (R-G-B) for identifying mangrove forest in Segara Anakan, Cilacap. The RGB composites of images developed from Landsat 8 and Sentinel 2A image are able to distinguish objects of mangrove forest from surrounding objects more clearly, but image composites from SPOT 6 image still require additional of association elements to identify mangrove objects.The development of remote sensing technology for identifying various of coastal and marine ecosystems which one of them is mangrove forest increasing rapidly. Identification of mangrove forests visually is constrained by much of combinations of RGB composite. The aims of this research is to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using Optimum Index Factor (OIF) method. The image data used represents 3 levels of intermediate to high resolution spatial resolution including Landsat 8 imagery (30 m) acquisition on 30 May 2013, Sentinel 2A image (10 m) acquisition on 18 March 2018 and SPOT 6 image (6 m) acquisition on 10 January 2015. Data of mangrove distributions used were the results of field measurements in the period 2013-2015.The results showed that the band composites of 564 (NIR+SWIR+Red) of Landsat 8 image and the band composites of 8a114 (Vegetation Red Edge+SWIR+Red) of Sentinel 2A are the best RGB composites for identifying mangrove forest, while the band composites of 341 (Red+NIR+Blue) of SPOT 6 image is  also the best colour composites(R-G-B) for identifying mangrove forest in Segara Anakan, Cilacap. The RGB composites of images developed from Landsat 8 and Sentinel 2A image are able to distinguish objects of mangrove forest from surrounding objects more clearly, but imagecomposites from SPOT 6 image still require additional of association elements to identify mangrove objects.

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