The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets

2017 ◽  
Author(s):  
Azin Wright
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Data Sets ◽  
Ebro Basin ◽  
Sensing Data

scholarly journals The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets

2017 ◽  
Vol 21 (9) ◽  
pp. 4747-4765 ◽  
Author(s):  
Clara Linés ◽  
Micha Werner ◽  
Wim Bastiaanssen
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Data Sets ◽  
Drought Management ◽  
Ebro Basin ◽  
Sensing Data ◽  
Drought Impacts ◽  
Management Plans ◽  
Drought Indicators ◽  
Selection Of

Abstract. The implementation of drought management plans contributes to reduce the wide range of adverse impacts caused by water shortage. A crucial element of the development of drought management plans is the selection of appropriate indicators and their associated thresholds to detect drought events and monitor the evolution. Drought indicators should be able to detect emerging drought processes that will lead to impacts with sufficient anticipation to allow measures to be undertaken effectively. However, in the selection of appropriate drought indicators, the connection to the final impacts is often disregarded. This paper explores the utility of remotely sensed data sets to detect early stages of drought at the river basin scale and determine how much time can be gained to inform operational land and water management practices. Six different remote sensing data sets with different spectral origins and measurement frequencies are considered, complemented by a group of classical in situ hydrologic indicators. Their predictive power to detect past drought events is tested in the Ebro Basin. Qualitative (binary information based on media records) and quantitative (crop yields) data of drought events and impacts spanning a period of 12 years are used as a benchmark in the analysis. Results show that early signs of drought impacts can be detected up to 6 months before impacts are reported in newspapers, with the best correlation–anticipation relationships for the standard precipitation index (SPI), the normalised difference vegetation index (NDVI) and evapotranspiration (ET). Soil moisture (SM) and land surface temperature (LST) offer also good anticipation but with weaker correlations, while gross primary production (GPP) presents moderate positive correlations only for some of the rain-fed areas. Although classical hydrological information from water levels and water flows provided better anticipation than remote sensing indicators in most of the areas, correlations were found to be weaker. The indicators show a consistent behaviour with respect to the different levels of crop yield in rain-fed areas among the analysed years, with SPI, NDVI and ET providing again the stronger correlations. Overall, the results confirm remote sensing products' ability to anticipate reported drought impacts and therefore appear as a useful source of information to support drought management decisions.

scholarly journals The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets

2017 ◽  
Author(s):  
Clara Linés ◽  
Micha Werner ◽  
Wim Bastiaanssen
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Data Sets ◽  
Drought Management ◽  
Ebro Basin ◽  
Sensing Data ◽  
Drought Impacts ◽  
Management Plans ◽  
Drought Indicators ◽  
Selection Of

Abstract. The implementation of drought management plans contributes to reduce the wide range of adverse impacts caused by water shortage. A crucial element of the development of drought management plans is the selection of appropriate indicators and their associated thresholds to detect drought events and monitor their evolution. Drought indicators should be able to detect emerging drought processes that will lead to impacts with sufficient anticipation to allow measures to be undertaken effectively. However, in the selection of appropriate drought indicators the connection to the final impacts is often disregarded. This paper explores the utility of remotely sensed data sets to detect early stages of drought at the river basin scale, and how much time can be gained to inform operational land and water management practices. Six different remote sensing data sets with different spectral origin and measurement frequency are considered, complemented by a group of classical in situ hydrologic indicators. Their predictive power to detect past drought events is tested in the Ebro basin. Qualitative (binary information based on media records) and quantitative (crop yields) data of drought events and impacts spanning a period of 12 years are used as a benchmark in the analysis. Results show that early signs of drought impacts can be detected up to some 6 months before impacts are reported in newspapers, with the best correlation-anticipation relationships for the Standard Precipitation Index (SPI), the Normalized Difference Vegetation Index (NDVI) and Evapotranspiration (ET). Soil Moisture (SM) and Land Surface Temperature (LST) offer also good anticipation, but with weaker correlations, while Gross Primary Production (GPP) presents moderate positive correlations only for some of the rainfed areas. Although classical hydrological information from water levels and water flows provided better anticipation than remote sensing indicators in most of the areas, correlations were found to be weaker. The indicators show a consistent behaviour with respect to the different levels of crop yield in rainfed areas among the analysed years, with SPI, NDVI and ET providing again the stronger correlations. Overall, the results confirm remote sensing products’ ability to anticipate reported drought impacts and therefore appear as a useful source of information to support drought management decisions.

scholarly journals Giovanni: The Bridge Between Data and Science

Eos ◽  
2017 ◽  
Author(s):  
Zhong Liu ◽  
James Acker
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Earth Science ◽  
Remote Sensing Data ◽  
Data Sets ◽  
Science Data ◽  
Web Based ◽  
Sensing Data ◽  
Daunting Task ◽  
Earth Science Data

Using satellite remote sensing data sets can be a daunting task. Giovanni, a Web-based tool, facilitates access, visualization, and exploration for many of NASA’s Earth science data sets.

scholarly journals Analyses of the Prądnik riverbed Shape Based on Archival and Contemporary Data Sets—Old Maps, LiDAR, DTMs, Orthophotomaps and Cross-Sectional Profile Measurements

2020 ◽  
Vol 12 (14) ◽  
pp. 2208 ◽  
Author(s):  
Stanisław Szombara ◽  
Paulina Lewińska ◽  
Anna Żądło ◽  
Marta Róg ◽  
Kamil Maciuk
Keyword(s):  
Remote Sensing ◽  
Survey Methods ◽  
Remote Sensing Data ◽  
Sufficient Information ◽  
Data Sets ◽  
Time Step ◽  
Mountain Areas ◽  
Cross Sectional ◽  
Sensing Data ◽  
Old Maps

Analyses of riverbed shape evolution are crucial for environmental protection and local water management. For narrow rivers located in forested, mountain areas, it is difficult to use remote sensing data used for large river regions. We performed a study of the Prądnik River, located in the Ojców National Park (ONP), Poland. A multitemporal analysis of various data sets was performed. Light detection and ranging (LiDAR)-based data and orthophotomaps were compared with classical survey methods, and 78 cross-sectional profiles were done via GNSS and tachymetry. In order to add an extra time step, the old maps of this region were gathered, and their content was compared with contemporary data. The analysis of remote sensing data suggests that they do not provide sufficient information on the state and changes of riverbanks, river course or river depth. LiDAR data sets do not show river bottoms, and, due to plant life, do not document riverbanks. The orthophotomaps, due to tree coverage and shades, cannot be used for tracking the whole river course. The quality of old maps allows only for general shape analysis over time. This paper shows that traditional survey methods provide sufficient accuracy for such analysis, and the resulted cross-sectional profiles can and should be used to validate other, remote sensing, data sets. We diagnosed problems with the inventory and monitoring of such objects and proposed methods to refine the data acquisition.

Evapotranspiration and soil moisture indexes derived from remote sensing data to identify and investigate the mechanisms of the spatio-temporal patterns of drought in the Ebro-Basin (NE Spain).

2020 ◽  
Author(s):  
Jaime Gaona ◽  
Pere Quintana-Seguí ◽  
Maria José Escorihuela
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Remote Sensing Data ◽  
Temporal Patterns ◽  
Surface Model ◽  
Ebro Basin ◽  
Sensing Data ◽  
Spatio Temporal

<p>The Mediterranean climate of the Iberian Peninsula defines high spatial and temporal variability of drought at multiple scales. These droughts impact human activities such as water management, agriculture or forestry, and may alter valuable natural ecosystems as well. An accurate understanding and monitoring of drought processes are crucial in this area. The HUMID project (CGL2017-85687-R) is studying how remote sensing data and models (Quintana-Seguí et al., 2019; Barella-Ortiz and Quintana-Seguí, 2019) can improve our current knowledge on Iberian droughts, in general, and in the Ebro basin, more specifically.</p><p>The traditional ground-based monitoring of drought lacks the spatial resolution needed to identify the microclimatic mechanisms of drought at sub-basin scale, particularly when considering relevant variables for drought such as soil moisture and evapotranspiration. In situ data of these two variables is very scarce.</p><p>The increasing availability of remote sensing products such as MODIS16 A2 ET and the high-resolution SMOS 1km facilitates the use of distributed observations for the analysis of drought patterns across scales. The data is used to generate standardized drought indexes: the soil moisture deficit index (SMDI) based on SMOS 1km data (2010-2019) and the evapotranspiration deficit index (ETDI) based on MODIS16 A2 ET 500m. The study aims to identify the spatio-temporal mechanisms of drought generation, propagation and mitigation within the Ebro River basin and sub-basins, located in NE Spain where dynamic Atlantic, Mediterranean and Continental climatic influences dynamically mix, causing a large heterogeneity in climates.</p><p>Droughts in the 10-year period 2010-2019 of study exhibit spatio-temporal patterns at synoptic and mesoscale scales. Mesoscale spatio-temporal patterns prevail for the SMDI while the ETDI ones show primarily synoptic characteristics. The study compares the patterns of drought propagation identified with remote sensing data with the patterns estimated using the land surface model SURFEX-ISBA at 5km.  The comparison provides further insights about the capabilities and limitations of both tools, while emphasizes the value of combining approaches to improve our understanding about the complexity of drought processes across scales.</p><p>Additionally, the periods of quick change of drought indexes comprise valuable information about the response of evapotranspiration to water deficits as well as on the resilience of soil to evaporative stress. The lag analysis ranges from weeks to seasons. Results show lags between the ETDI and SMDI ranging from days to weeks depending on the precedent drought status and the season/month of drought’s generation or mitigation. The comparison of the lags observed on remote sensing data and land surface model data aims at evaluating the adequacy of the data sources and the indexes to represent the nonlinear interaction between soil moisture and evapotranspiration. This aspect is particularly relevant for developing drought monitoring aiming at managing the impact of drought in semi-arid environments and improving the adaptation to drought alterations under climate change.</p>

Research on Technology of the Global Geographic Data Sets Generation Based on the Original Remote Sensing Data

2012 ◽  
Vol 433-440 ◽  
pp. 4229-4234
Author(s):  
Wen Quan Feng ◽  
Gan Zhou ◽  
Yong Fang
Keyword(s):  
Remote Sensing ◽  
Control System ◽  
Remote Sensing Data ◽  
Data Sets ◽  
Generation Process ◽  
Data Simulation ◽  
Sensing Data ◽  
Ground Station ◽  
Geographic Data ◽  
Operation Control

To meet the simulation and testing requirements of HY-1 Satellite ground operation control system simulation subsystem, a global geographic data sets based on original remote sensing data was proposed. This paper detailed the function and data processing methods of the data sets, mainly including data structure and the key algorithm of the satellite calibration and data filling required in the data sets generation process. At last, using the data simulation function of ground station, the generated raw data would be sent to real ground operation control system, and the processed images showing the data sets were filled with good results

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