scholarly journals Surface water extent dynamics from three periods of continuous Landsat time series; subregional differences across Argentine plains

2021 ◽  
pp. 131
Author(s):  
Vanina S. Aliaga ◽  
María C. Piccolo ◽  
Gerardo M. E. Perillo
Keyword(s):  
Remote Sensing ◽  
Shallow Lakes ◽  
Dominant Role ◽  
Positive Association ◽  
Lake Area ◽  
Surface Hydrology ◽  
Social Functions ◽  
Pampean Region ◽  
Remote Sensing Techniques ◽  
Lake Number

<p>The Pampean region in Argentina is an extensive plain characterized by abundant shallow lakes that fulfill many environmental, ecological, and social functions. This study aims to detect the multiannual lake area changes in this region during 2001-2009 using remote sensing, including lakes as small as ≥10,000 m<sup>2</sup> or 1 ha. Landsat scenes of the wet (2008-2009), normal (2006), and dry (2008-2009) seasons were obtained, and using remote sensing techniques, the number and area of shallow lakes were calculated. The spatiotemporal variation of shallow lakes was studied in different climate periods in eight singular subregions. Spatial associations between annual precipitation and lake number and area were analyzed through the development of a Geographic Information System (GIS) at a subregional scale. During the study period the total lake area in the Pampean region decreased by 5257.39 km<sup>2 </sup>(62 %), but each subregion showed different responses to climatic events. In seven of them, the differences between climate periods prove to be statistically significant (P&gt;0.01). The relationship between precipitation and lake number and area revealed the domain of positive association. We conclude that climate factors play a dominant role in lake changes across the Pampean plains. However, other factors such as origin, topographic and edaphic characteristics intensify or mitigate changes in surface hydrology.</p>

scholarly journals Assessment of Imja Glacier Lake outburst Flood (GLOF) Risk in Dudh Koshi River Basin using Remote Sensing Techniques

1970 ◽  
Vol 7 (1) ◽  
pp. 75-91 ◽  
Author(s):  
Kamal P Budhathoki ◽  
OR Bajracharya ◽  
BK Pokharel
Keyword(s):  
Remote Sensing ◽  
Risk Assessment ◽  
Statistical Methods ◽  
Linear Regression Analysis ◽  
Coefficient Of Determination ◽  
Lake Area ◽  
Decision Criteria ◽  
Outburst Flood ◽  
Hazard Potential ◽  
Remote Sensing Techniques

Glacier lakes are common phenomena in the Himalaya region of Nepal. Glacier lake outburst floods have repeatedly caused the death tolls and severe damage to downstream infrastructures. In Himalayas, a vital uncertainty about the glacier lake hazard potential still exists, thereby the effects of accelerating rates of glacier retreat and expansion of Glacier Lake could be the wake of recent global warming and resulting climatic changes. The paper, first describes the general different-level approach upon which the study is based. Then, in the methodological part, applicable remote sensing techniques, geographic information system (GIS) and statistical methods are presented. Observed data of lake area, volume, and depth having similar lake characteristics reported in the different literature are used to develop empirical equations by using statistical methods. The values of r2 (coefficient of determination) - obtained are very high (r2=0.939 for depth – area relationship and r2= 0.990 for volume – area relationship). The comparison of the empirical expression clearly indicated that there is more than 90% variation in the dependent variable, lake volume,as explained by the linear regressions in both cases. Area of Imja glacier lake for different years are determined from the available satellite imagery and volume of the Imja glacier lake are estimated using the expression: V = 0.094A1.453.developed from linear regression analysis of the observed data. Similarly, mean depth can be estimated by using the expression: D = 0.94A0.452. After the preparation of maps and data, a scheme of decision criteria for the evaluation of hazard potential of Imja glacier lake is established. A list of decision criteria is a documented set of factors that are used to examine and compare for evaluating the hazard potential of a glacier lake. The empirical scores are given in terms of hazard magnitude for hazard rating. Analysis of Imja glacier lake based on the empirical scoring system clearly indicated that GLOF risk of the possible outburst from Imja glacier lake is MODERATE. A systematic application of remote sensing based methods for glacier lake outburst flood risk assessment is applicable and thus recommended. Keywords: Glacier lake outburst; remote sensing; risk assessment; hazard potential; empirical parameters; climate change DOI: http://dx.doi.org/10.3126/jhm.v7i1.5618 JHM 2010; 7(1): 75-91

scholarly journals Estimation of Water Coverage in Permanent and Temporary Shallow Lakes and Wetlands by Combining Remote Sensing Techniques and Genetic Programming: Application to the Mediterranean Basin of the Iberian Peninsula

2021 ◽  
Vol 13 (4) ◽  
pp. 652
Author(s):  
Carolina Doña ◽  
Daniel Morant ◽  
Antonio Picazo ◽  
Carlos Rochera ◽  
Juan Manuel Sánchez ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Shallow Lakes ◽  
Near Infrared ◽  
Salt Ponds ◽  
Infrared Band ◽  
Landsat 7 ◽  
Global Change Scenarios ◽  
Remote Sensing Techniques ◽  
Ecological Types ◽  
Sentinel 2

This work aims to validate the wide use of an algorithm developed using genetic programing (GP) techniques allowing to discern between water and non-water pixels using the near infrared band and different thresholds. A total of 34 wetlands and shallow lakes of 18 ecological types were used for validation. These include marshes, salt ponds, and saline and freshwater, temporary and permanent shallow lakes. Furthermore, based on the spectral matching between Landsat and Sentinel-2 sensors, this methodology was applied to Sentinel-2 imagery, improving the spatial and temporal resolution. When compared to other techniques, GP showed better accuracy (over 85% in most cases) and acceptable kappa values in the estimation of water pixels (κ ≥ 0.7) in 10 of the 18 assayed ecological types evaluated with Landsat-7 and Sentinel-2 imagery. The improvements were especially achieved for temporary lakes and wetlands, where existing algorithms were scarcely reliable. This shows that GP algorithms applied to remote sensing satellite imagery can be a valuable tool to monitor water coverage in wetlands and shallow lakes where multiple factors cause a low resolution by commonly used water indices. This allows the reconstruction of hydrological series showing their hydrological behaviors during the last three decades, being useful to predict how their hydrological pattern may behave under future global change scenarios.

scholarly journals Análisis del efecto de variables ambientales en la estimación de la erosionabilidad (Factor K) = Analysis of the Effect of Environmental Variables on the Soil Erodibility Estimation (K Factor)

2018 ◽  
pp. 195
Author(s):  
Pedro Perez Cutillas ◽  
Gonzalo G. Barberá ◽  
Carmelo Conesa García
Keyword(s):  
Remote Sensing ◽  
Environmental Variables ◽  
Input Data ◽  
Vegetation Index ◽  
Mineralogical Composition ◽  
Soil Erodibility ◽  
Estimation Algorithms ◽  
K Factor ◽  
Remote Sensing Techniques

El objetivo principal de este trabajo se centra en la determinación y análisis de las variables ambientales que influyen en las divergencias de las estimaciones de erosionabilidad a partir de dos métodos, aplicando tres algoritmos de estimación del Factor K. La exploración de esta información permite conocer el peso que ejerce el origen de los datos de entrada a los modelos en el cómputo de erosionabilidad y qué importancia tiene en función del algoritmo elegido para la estimación del Factor K. Los resultados muestran que las pendientes, así como los índices de vegetación (NDVI) y de composición mineralógico (IOI) obtenidos mediantes técnicas de teledetección han   mostrado los valores de asociación más elevados entre ambos métodos.The main goal of this work is to determine and analyze the influence of environmental variables on the changes of two erodibility methods, through the application of three estimation algorithms of K Factor. The analysis of this information allows knowing the significance of the input data to the models in the erodibility estimation, and likewise the consequence of the algorithm selected for the estimation of K Factor. The results show that the slopes, as well as the vegetation index (NDVI) and the mineralogical composition index (IOI), generated both by remote sensing techniques, have shown the highest values of association between methods.

scholarly journals Monitoring Changes in the Transparency of the Largest Reservoir in Eastern China in the Past Decade, 2013–2020

2021 ◽  
Vol 13 (13) ◽  
pp. 2570
Author(s):  
Teng Li ◽  
Bozhong Zhu ◽  
Fei Cao ◽  
Hao Sun ◽  
Xianqiang He ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mean Squared Error ◽  
Eastern China ◽  
Water Environment ◽  
Relative Difference ◽  
Boreal Summer ◽  
Support Vector ◽  
Lake Area ◽  
The Past ◽  
Remote Sensing Reflectance

Based on characteristics analysis about remote sensing reflectance, the Secchi Disk Depth (SDD) in the Qiandao Lake was predicted from the Landsat8/OLI data, and its changing rates on a pixel-by-pixel scale were obtained from satellite remote sensing for the first time. Using 114 matchups data pairs during 2013–2019, the SDD satellite algorithms suitable for the Qiandao Lake were obtained through both the linear regression and machine learning (Support Vector Machine) methods, with remote sensing reflectance (Rrs) at different OLI bands and the ratio of Rrs (Band3) to Rrs (Band2) as model input parameters. Compared with field observations, the mean absolute relative difference and root mean squared error of satellite-derived SDD were within 20% and 1.3 m, respectively. Satellite-derived results revealed that SDD in the Qiandao Lake was high in boreal spring and winter, and reached the lowest in boreal summer, with the annual mean value of about 5 m. Spatially, high SDD was mainly concentrated in the southeast lake area (up to 13 m) close to the dam. The edge and runoff area of the lake were less transparent, with an SDD of less than 4 m. In the past decade (2013–2020), 5.32% of Qiandao Lake witnessed significant (p < 0.05) transparency change: 4.42% raised with a rate of about 0.11 m/year and 0.9% varied with a rate of about −0.09 m/year. Besides, the findings presented here suggested that heavy rainfall would have a continuous impact on the Qiandao Lake SDD. Our research could promote the applications of land observation satellites (such as the Landsat series) in water environment monitoring in inland reservoirs.

Sign in / Sign up

Export Citation Format

Share Document