scholarly journals Mineralization potential and integration of airborne magnetometric geophysical data data and EO-1, ASTER ester and Landsat-7 ETM + hyperspectral satellite data (Sheet 1: 100,000 Meshkinshahr)

2019 ◽  
Vol 11 (3) ◽  
pp. 113-142
Author(s):  
saeed Mojarad ◽  
Ali Nejati Kalate ◽  
Hamid Aghajani
Keyword(s):  
Satellite Data ◽  
Data Sheet ◽  
Geophysical Data ◽  
Mineralization Potential ◽  
Landsat 7

A comparative assessment of UK‐DMC and Landsat‐7 ETM+satellite data

Sensor Review ◽  
2013 ◽  
Vol 33 (2) ◽  
pp. 166-173 ◽  
Author(s):  
Ebenezer Yemi Ogunbadewa
Keyword(s):  
Satellite Data ◽  
Comparative Assessment ◽  
Landsat 7

A comparison of gap-filling approaches for Landsat-7 satellite data

2017 ◽  
Vol 38 (23) ◽  
pp. 6653-6679 ◽  
Author(s):  
Gaohong Yin ◽  
Gregoire Mariethoz ◽  
Ying Sun ◽  
Matthew F. McCabe
Keyword(s):  
Satellite Data ◽  
Gap Filling ◽  
Landsat 7

scholarly journals Can single empirical algorithms accurately predict inland shallow water quality status from high resolution, multi-sensor, multi-temporal satellite data?

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1511-1516 ◽  
Author(s):  
I. Theologou ◽  
M. Patelaki ◽  
K. Karantzalos
Keyword(s):  
Water Quality ◽  
High Resolution ◽  
Satellite Data ◽  
Landsat 8 ◽  
Landsat 7 ◽  
Multi Temporal ◽  
Water Quality Status ◽  
Quality Status ◽  
Empirical Algorithms

Assessing and monitoring water quality status through timely, cost effective and accurate manner is of fundamental importance for numerous environmental management and policy making purposes. Therefore, there is a current need for validated methodologies which can effectively exploit, in an unsupervised way, the enormous amount of earth observation imaging datasets from various high-resolution satellite multispectral sensors. To this end, many research efforts are based on building concrete relationships and empirical algorithms from concurrent satellite and in-situ data collection campaigns. We have experimented with Landsat 7 and Landsat 8 multi-temporal satellite data, coupled with hyperspectral data from a field spectroradiometer and in-situ ground truth data with several physico-chemical and other key monitoring indicators. All available datasets, covering a 4 years period, in our case study Lake Karla in Greece, were processed and fused under a quantitative evaluation framework. The performed comprehensive analysis posed certain questions regarding the applicability of single empirical models across multi-temporal, multi-sensor datasets towards the accurate prediction of key water quality indicators for shallow inland systems. Single linear regression models didn’t establish concrete relations across multi-temporal, multi-sensor observations. Moreover, the shallower parts of the inland system followed, in accordance with the literature, different regression patterns. Landsat 7 and 8 resulted in quite promising results indicating that from the recreation of the lake and onward consistent per-sensor, per-depth prediction models can be successfully established. The highest rates were for chl-a (r<sup>2</sup>=89.80%), dissolved oxygen (r<sup>2</sup>=88.53%), conductivity (r<sup>2</sup>=88.18%), ammonium (r<sup>2</sup>=87.2%) and pH (r<sup>2</sup>=86.35%), while the total phosphorus (r<sup>2</sup>=70.55%) and nitrates (r<sup>2</sup>=55.50%) resulted in lower correlation rates.

scholarly journals UTILIZATION OF LANDSAT DATA FOR WATER QUALITY OBSERVATION IN SMALL INLAND WATER BODIES

2016 ◽  
Vol XLI-B8 ◽  
pp. 373-377
Author(s):  
M. Pásler ◽  
J. Komárková
Keyword(s):  
Water Quality ◽  
Satellite Data ◽  
Quality Evaluation ◽  
Water Bodies ◽  
Landsat 8 ◽  
Landsat Data ◽  
Remotely Sensed Data ◽  
Water Quality Evaluation ◽  
Small Water ◽  
Landsat 7

Many studies deal with water quality evaluation using remotely sensed data. In the field of remote sensing, there have been proposed several procedures how to observe selected parameters of water quality and conditions. The majority of works use methods and procedures based on satellite data but they usually do not deal with suitability and practicability of the satellite data. This paper provides summary of determinants and limitations of satellite data utilization for water quality evaluation. Cloud cover and its influence on size of visible water surfaces is the most deeply evaluated determinants. Temporal resolution, spatial resolution and some other technical factors are discussed as next determinants. The case study demonstrates evaluation of the determinants for Landsat 7 and Landsat 8 data (level 1) and for area of small ponds in part of Pardubice region in the Czech Republic. It clearly demonstrates several limitations of Landsat data for evaluation of selected parameters of water quality and changes of small water bodies.

scholarly journals UTILIZATION OF LANDSAT DATA FOR WATER QUALITY OBSERVATION IN SMALL INLAND WATER BODIES

2016 ◽  
Vol XLI-B8 ◽  
pp. 373-377 ◽  
Author(s):  
M. Pásler ◽  
J. Komárková
Keyword(s):  
Water Quality ◽  
Satellite Data ◽  
Quality Evaluation ◽  
Water Bodies ◽  
Landsat 8 ◽  
Landsat Data ◽  
Remotely Sensed Data ◽  
Water Quality Evaluation ◽  
Small Water ◽  
Landsat 7

Many studies deal with water quality evaluation using remotely sensed data. In the field of remote sensing, there have been proposed several procedures how to observe selected parameters of water quality and conditions. The majority of works use methods and procedures based on satellite data but they usually do not deal with suitability and practicability of the satellite data. This paper provides summary of determinants and limitations of satellite data utilization for water quality evaluation. Cloud cover and its influence on size of visible water surfaces is the most deeply evaluated determinants. Temporal resolution, spatial resolution and some other technical factors are discussed as next determinants. The case study demonstrates evaluation of the determinants for Landsat 7 and Landsat 8 data (level 1) and for area of small ponds in part of Pardubice region in the Czech Republic. It clearly demonstrates several limitations of Landsat data for evaluation of selected parameters of water quality and changes of small water bodies.

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