ENVIROMENTAL INFORMATION

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Raster Image Features table Report


DESCRIPTION:

We proposed a new methodology based on NDVI time series autocorrelation values and machine learning algorithms to assess fallowing temporal patterns across rainfed agricultural areas that were tested in mainland Spain. We found that approximately half of rainfed agricultural areas were regularly cultivated (RC) and distributed mainly in the north- western Spain whereas lands with crop-fallow rotation patterns every two (CF-2) and three years (CF-3) were distributed across northeast, center and south of Spain. You can see the spatial distribution in the map viewer below.

MOD
09Q1
NDVI 250
TS 2000 - 2012
FILTERED
TS
ACF
SPECIFIC ACF

FALLOW LANDS
REGIME

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GDB Report Features tables


DESCRIPTION:

The objective of the present study was to analyze the dynamics of the vegetation in ribera del Duero through the use of the NDVI index and to relate this index with climatic variables to study how the climate influences the development of crops. For this, the time series of the NDVI extracted from MODIS images of the different crops in the studied region in the period 2002-2020 were analyzed and this NDVI was related to the time series of two climatic variables such as temperature and precipitation, to evaluate the influence that these have on the dynamics of the vegetation of the area.
The stationarity of the time series was analyzed using the Dickey-Fuller test and, through the use of autocorrelation graphs and periodograms, their seasonality was analyzed. It was observed that none of the climatic and NDVI series studied had a trend and it was also observed that the NDVI series had a clear annual cycle.

MOD
09A1
NDVI 500 TS
FILTERED
ACF

CLIMATOLOGY
VEGETATION
DUERO

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Raster Image


DESCRIPTION:

This product provides the number of seasonal cycles of vegetation based on the periodogram of AVHRR-NDVI time series from 1982 to 2016 (NDVI3g product). Particularly, the highest ordinate value at 24, 12 or 8 AVHRR periods indicates the occurrence of one, two or three intra-annual cycles respectively. Most of pixels showed a clear dominance of one intra-annual cycle.

AVHRR
AVHRR NDVI
TS
PERIODOGRAM

NUMBER OF SEASONAL
CYCLES

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Raster Image


DESCRIPTION:

This product provides the amplitude of seasonal cycles of vegetation based on the periodogram of AVHRR-NDVI time series from 1982 to 2016 (NDVI3g product). It is generated using the value of the maximum periodogram’s ordinate (i.e., at 24, 12 or 8 periods). High values indicate high amplitude of the NDVI cycle at the dominant seasonality mode (one, two or three seasonal cycles per year). Higher values are located primarily north to the 50 parallel with some fluctuations depending probably on climate and orography whereas the lowest values are in arid regions and tropical areas.

AVHRR
AVHRR NDVI
TS
PERIODOGRAM

AMPLITUDE OF SEASONAL
CYCLES

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Raster Image


DESCRIPTION:

UThis product provides the amplitude of seasonal cycles of vegetation based on the periodogram of AVHRR-NDVI time series from 1982 to 2016 (NDVI3g product). It is calculated as the ratio between the value of the maximum amplitude (i.e., at 8, 12 or 24 periods) and the sum of the amplitudes at periods lower than or equal to 24 (annual term). Values are in percentage (0 -100). High values represent vegetation with high temporal stability whereas low values indicate that the number of seasonal cycles has changed during the study period. Higher values are mainly located in mid and high latitudes of the northern hemisphere and across the African savannas. In contrast, lower values are in drylands and in the Amazonian region.

AVHRR
AVHRR NDVI
TS
PERIODOGRAM

STABILITY OF SEASONAL
CYCLES

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Raster Image


DESCRIPTION:

This product provides an indicator of the presence of pluri-annual cycles based on the periodogram of AVHRR-NDVI time series from 1982 to 2016 (NDVI3g product). It is calculated as the ratio between the sum of all the amplitude values between period 24 (one year) and period 120 (5 years) and the sum of all the amplitudes. It represents the variance explained by the pluri-annual oscillations, from one to five-year cycles. Values are in percentage (0 – 100). High values indicate the presence of pluri-annual cycles and are mainly located in Australia.

AVHRR
AVHRR NDVI
TS
PERIODOGRAM

PRESENCE OF PLURIANNUAL
CYCLES

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Raster Image

DESCRIPTION:


Maps of different cropping patterns were derived from the spectral analysis of MODIS NDVI time series at a spatial resolution of 500 meters across maize and rice cultivated areas. This analysis identified single, double, and triple cropping patterns for the subperiods: 2001–2005, 2006–2010, 2011–2015, and 2016–2020.

Double- and triple-cropping systems are primarily situated in the areas surrounding the Daule and Babahoyo rivers, while croplands with a single seasonal cycle are found in regions farther from these watercourses.

MOD
09A1
NDVI 500
TS 2000 - 2023
FILTERED
TS
PERIODOGRAM

CROPLAND
INTENSIFICATION

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Raster Image

DESCRIPTION:


This product provides maps of maize and rice cultivated areas with a stable cropping pattern (one, two, or three crops per year) across four subperiods 2001–2005, 2006–2010, 2011–2015, and 2016–2020. Areas with a change in the cropping pattern during the entire period were also identified.

The different cropping patters were identified based on spectral analysis of MODIS NDVI time series at 500 meters spatial resolution.

MOD
09A1
NDVI 500
TS 2000 - 2023
FILTERED
TS
PERIODOGRAM

CROPLAND
INTENSIFICATION

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Raster Image

DESCRIPTION:


The main objective of this research was to assess cropland intensification by means of spectral analysis of MODIS NDVI time series in a high cloudiness tropical area such as Ecuador. A surface of 89,225 ha of the main staple crops in this country, which are rice and maize crops, was monitored to assess the evolution of the number of crop cycles.

Agricultural areas with an increasing trend of the number of crop growth cycles (cropland intensification).

MOD
09A1
NDVI 500
TS 2000 - 2023
FILTERED
TS
PERIODOGRAM

CROPLAND
INTENSIFICATION

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Copyright: Creative Commons Attribution 4.0 International

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Raster Image Features table Report

DESCRIPTION:


The study area includes four representative regions of the drylands cropping systems in Spain in the province of Soria
NDVI time series dynamics were analyzed to identify their characteristic components such as seasonality, cycles, trends, or structural changes, among others. With this information, a specific model was proposed for each series. The identification of the NDVI series has been carried out using the Box-Jenkins methodology in the selected 2584 pixels of Soria in which rainfed agriculture is practiced. According to this test, pixels have been divided into three levels.

In level 1, there were the pixels that showed low Q Ljung-Box test values at short and especially at medium and at long terms. In level three, there were the pixels that showed high Q Ljung-Box test values at short, medium, and/or long term. Therefore, the models of these pixels could be considered invalid. In level 2, there were the pixels classified as an intermediate situation

MOD
09A1
NDVI 500 TS
FILTERED
ACF

RAINFED CROPS DYNAMICS
IN SORIA

Copyright: Creative Commons Attribution 4.0 International