Mapping oak decline through long-term analysis of time series of satellite images in the forests of Malekshahi, Iran

2019 ◽  
pp. 1-22 ◽  
Author(s):  
Sadra Imanyfar ◽  
Mahdi Hasanlou ◽  
Vahid Mirzaei Zadeh
Keyword(s):  
Time Series ◽  
Satellite Images ◽  
Oak Decline ◽  
Term Analysis ◽  
Analysis Of Time Series

scholarly journals Phenological behavior of Atlas cedar (Cedrus atlantica) forest to snow and precipitation variability in Boutaleb and Babors Mountains, Algeria

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Khaled Missaoui ◽  
Rachid Gharzouli ◽  
Yamna Djellouli ◽  
Frençois Messner
Keyword(s):  
Time Series ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Descriptive Analysis ◽  
Precipitation Variability ◽  
Monthly Precipitation ◽  
Cedrus Atlantica ◽  
The Past

Abstract. Missaoui K, Gharzouli R, Djellouli Y, Messner F. 2020. Phenological behavior of Atlas cedar (Cedrus atlantica)  forest to snow and precipitation variability in Boutaleb and Babors Mountains, Algeria. Biodiversitas 21: 239-245. Understanding the changes in snow and precipitation variability and how forest vegetation response to such changes is very important to maintain the long-term sustainability of the forest. However, relatively few studies have investigated this phenomenon in Algeria. This study was aimed to find out the response of Atlas cedar (Cedrus atlantica (Endl.) G.Manetti ex Carrière) forest in two areas (i.e Boutaleb and Babors Mountains) and their response to the precipitation and snow variability. The normalized difference vegetation index (NDVI) generated from satellite images of MODIS time series was used to survey the changes of the Atlas cedar throughout the study area well as dataset of monthly precipitation and snow of the province of Setif (northeast of Algeria) from 2000 to 2018. Descriptive analysis using Standarized Precipitation Index (SPI) showed the wetter years were more frequent in the past than in the last two decades. The NDVI values changes in both areas with high values were detected in Babors Mountains with statistically significant differences. Our findings showed important difference in Atlas cedar phenology from Boutaleb mountains to Babors Mountains which likely related to snow factor.

scholarly journals Technical note: A procedure to clean, decompose and aggregate time series

2021 ◽  
Author(s):  
François Ritter
Keyword(s):  
Time Series ◽  
Earth Science ◽  
Technical Note ◽  
Screening Methods ◽  
Term Trend ◽  
Univariate Time Series ◽  
Processing Procedure ◽  
Long Term Trend ◽  
Analysis Of Time Series

Abstract. Errors, gaps and outliers complicate and sometimes invalidate the analysis of time series. While most fields have developed their own strategy to clean the raw data, no generic procedure has been promoted to standardize the pre-processing. This lack of harmonization makes the inter-comparison of studies difficult, and leads to screening methods that are usually ambiguous or case-specific. This study provides a generic pre-processing procedure (called past, implemented in R) dedicated to any univariate time series. Past is based on data binning and decomposes the time series into a long-term trend and a cyclic component (quantified by a new metric, the Stacked Cycles Index) to finally aggregate the data. Outliers are flagged with an enhanced Boxplot rule called Logbox. Three different Earth Science datasets (contaminated with gaps and outliers) are successfully cleaned and aggregated with past. This illustrates the robustness of this procedure that can be valuable to any discipline.

scholarly journals Historical trends of the ecotoxicological pesticide risk from the main grain crops in Rolling Pampa (Argentina)

2020 ◽  
Author(s):  
D.O. Ferraro ◽  
F Ghersa ◽  
R. de Paula ◽  
A.C. Duarte Vera ◽  
S. Pessah
Keyword(s):  
Time Series ◽  
Time Trends ◽  
Cropping System ◽  
Scaling Up ◽  
Pesticide Use ◽  
Historical Trends ◽  
Maize Crop ◽  
Sown Area ◽  
Term Analysis

AbstractWe showed the results of the first long-term analysis (1987-2019) of pesticide impact in the main agricultural area of Argentina. Using a clear and meaningful tool, based not only on acute toxicity but also on scaling up the results to total sown area, we identified time trends for both total pesticide impact and the ecoefficiency of modal pesticide profiles. By the end of the time series, soybean showed a pesticide impact four times greater than maize crop in the studied area. However, the time trend in the last years showed a sustainable pattern of pesticide use, with an improvement in the ecoefficiency. Oppositely, maize showed a relatively constant ecoefficiency value during most of the time series, suggesting a possible path towards an unsustainable cropping system. Findings from this study suggest that some efforts have to be made to improve the pest management decisions towards a more efficient pesticide profiles in maize crop and to keep improving the ecotoxicity pesticide profile in soybean crops because of its large sown area in the studied area.

scholarly journals Seagrass cover expansion off Caja de Muertos Island, Puerto Rico, as determined by long-term analysis of historical aerial and satellite images (1950–2014)

2020 ◽  
Vol 117 ◽  
pp. 106561 ◽  
Author(s):  
Mariana C. León-Pérez ◽  
Roy A. Armstrong ◽  
William J. Hernández ◽  
Alfonso Aguilar-Perera ◽  
Jill Thompson-Grim
Keyword(s):  
Puerto Rico ◽  
Satellite Images ◽  
Seagrass Cover ◽  
Term Analysis

Automated spaceborne detection of degraded vegetation around Monchegorsk, Kola Peninsula, Russia

Polar Record ◽  
2011 ◽  
Vol 48 (1) ◽  
pp. 107-112 ◽  
Author(s):  
W. G. Rees
Keyword(s):  
Time Series ◽  
Kola Peninsula ◽  
Industrial Pollution ◽  
Satellite Images ◽  
Vegetation Index ◽  
Simple Method ◽  
Data Analyst ◽  
Normalised Difference Vegetation Index ◽  
The Town ◽  
Analysis Of Time Series

ABSTRACTThis paper develops a simple method for the detection of ‘vegetation anomalies’, locations where the amount of vegetation, estimated through the use of the normalised difference vegetation index (NDVI), is significantly lower than expected on the basis of topographic factors alone. The method is developed and tested using satellite imagery from the area around the town of Monchegorsk on the Kola Peninsula, Russia. This area has been subject to heavy levels of airborne industrial pollution for many years and the intended purpose of the method is to allow the extent of pollution damaged vegetation to be estimated with as few operational decisions as possible by the data analyst, thus suiting it for automation and for the analysis of time-series of satellite images. While the work described in this paper is to some extent preliminary, it does establish that spatial variations in the NDVI of undisturbed vegetation can, at least in the study area, be modelled satisfactorily using topographic variables, and that negative departures from this modelled variation are very strongly associated with industrially mediated damage.

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