M. Eugenia Perez

Dr. M. Eugenia Perez

Complutense University of Madrid, Madrid, Spain
orcid

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2007 in Science of The Total Environment
Verified
Journal Article
Closed access
PRPilar García Rodríguez
Pilar García Rodríguez
MPM. Eugenia Perez
M. Eugenia Perez

1 February 2014 in Geoderma
Verified
Journal Article
Closed access
PGPilar García
Pilar García
MPM. Eugenia Perez
M. Eugenia Perez
AGAntonio Guerra
Antonio Guerra

29 April 2022 in Land
Verified
Journal Article
Open access
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MPM. Eugenia Perez
M. Eugenia Perez
JAJose María García Alvarado
Jose María García Alvarado
MRMARIA DEL PILAR GARCIA RODRIGUEZ
MARIA DEL PILAR GARCIA RODRIGUEZ
Raimundo Jimenez-BallestaRaimundo Jimenez-Ballesta
Raimundo Jimenez-Ballesta
Following a copious and famous snowfall in Madrid city (Spain) and its surrounding area, the tree masses were analysed to assess the impact of this snowfall. In this way, this paper proposes an approach towards urban forest impact inventory mapping as a consequence of the snowfall of January 2021, and the subsequent atmospheric stability, which kept surface temperatures in Madrid close to −10 °C. The study has been carried out using snowfall data from 1920 to 2020 and images from the Sentinel, Landsat and MODIS satellites. The results obtained by means of image changes in the NDVI reveal a clear impact on the trees, with 11% of the winter vegetation cover of the municipality being affected. Especially significant has been the damage detected both in the forest areas in the city and in the parks, gardens or urban roads.

30 January 2016 in Agriculture
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Journal Article
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MPM. Eugenia Perez
M. Eugenia Perez
MRMARIA DEL PILAR GARCIA RODRIGUEZ
MARIA DEL PILAR GARCIA RODRIGUEZ
This study analyzes soil sealing and its repercussions in the loss of fertile soils, which are more appropriate for agriculture use. Also, soil sealing increases flood risk. The main objective is to estimate soil loss by sealing in the Guadarrama River Basin (Madrid, Spain) between 1961 and 2011. The combination of digital processing (Normalized Difference Vegetation Index (NDVI), principal components and convolution filters) of satellite imagery with the digital terrain model helps to detect risk areas and allows quick updating of sealed soil mapping. The supervised classifications of the images were used to estimate the actual soil loss by sealing (9% in 2011) in the Guadarrama River Basin and the types and agrologic classes that have been lost. Soil loss occurs to a greater extent in highly permeable soils (sands) and in the most fertile soils. The main sealed soil associations are luvisols (alfisols), regosols (entisols) and cambisols (inceptisols).

24 May 2006 in Environmental Geology
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Journal Article
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MPM. Eugenia Perez
M. Eugenia Perez
MRMARIA DEL PILAR GARCIA RODRIGUEZ
MARIA DEL PILAR GARCIA RODRIGUEZ
VGVanesa González-Quiñones
Vanesa González-Quiñones
RBRaimundo Jiménez Ballesta
Raimundo Jiménez Ballesta

29 May 2007 in International Journal of Remote Sensing
Verified
Journal Article
Closed access
MRMARIA DEL PILAR GARCIA RODRIGUEZ
MARIA DEL PILAR GARCIA RODRIGUEZ
MPM. Eugenia Perez
M. Eugenia Perez
AZA. Guerra Zaballos
A. Guerra Zaballos
Landsat images supply significant information on the different aspects of the physical environment necessary to determine the distribution of salty soils. This work centres on the La Mancha area (Central Spain) which, due to its flat topography, exhibits ideal conditions to show surface and groundwater movement, as well as sediment distribution. Combination of these factors is essential for development. The main goal of this study is to derive information on the distribution of salt‐affected soils, as well as the area subject to flood risk. Multitemporal Landsat TM images selected from the 1990s have been used for this purpose. TM images are useful for delineation of mesozoic sediments rich in salts and/or areas with high humidity content. These images have been geo‐referenced to the UTM coordinate system and have been digitally enhanced. Principal components, NDVI and supervised classification were computed. Therefore, it is quite possible to predict with a high degree of probability the development of saline soils, but their precise classification is not always possible, owing to the fact that they are usually associated with other soil groups: calcisols, regosols, luvisols and kastanozems. Salt‐affected soils have been found to be associated with clayish mesozoic sediments, hollows, flood plain area and subsurface and groundwater movements. Complementary fieldwork is necessary in order to confirm digital values.