Una metodología para la caracterización del uso del suelo mediante imágenes de media resolución espacial

Ochoa, Cristian Guevara; Lara, Bruno Daniel; Vives, Luis; Zimmermann, Erik; Gandini, Marcelo

doi:10.5154/r.rchscfa.2017.10.061

Cited by 8 publications

(12 citation statements)

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“…Particularly a negative trend in carbon gains (annual productivity) and a positive trend in seasonality would be indicating serious effects on biodiversity at ecosystem scale and for the provision of several ecosystem services (Paruelo et al, 2016;Vitousek et al, 1997). Land cover changes or the intensification of productive practices seem to be the responsible for the changes mentioned, or they indicate different works carried out at a more detailed scale (Baldi et al, 2006;Guevara-Ochoa et al, 2018;Lara and Gandini, 2014;Vazquez and Zulaica, 2013). These processes reveal a strong component of human control on seasonal carbon dynamics and on ecosystem functioning.…”

Section: Discussionmentioning

confidence: 99%

Trends and land surface phenological responses to climate variability in the Argentina Pampas

Lara

Gandini

Gantes

et al. 2020

CIG

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Understanding the interaction between land surface and atmosphere processes is fundamental for predicting the effects of future climate change on ecosystem functioning and carbon dynamics. The objectives of this work were to analyze the trends in land surface phenology (LSP) metrics from remote sensing data, and to reveal their relationship with precipitation and ENSO phenomenon in the Argentina Pampas. Using a time series of MODIS Normalized Difference Vegetation Index (NDVI) data from 2000 to 2014, the start of the growing season (SOS), the annual integral of NDVI (i-NDVI, linear estimator of annual productivity), the timing of the annual maximum NDVI (t-MAX) and the annual relative range of NDVI (RREL, estimator of seasonality) were obtained for the Argentina Pampas. Then, spatial and temporal relationships with the Multivariate ENSO Index (MEI) and precipitation were analyzed. Results showed a negative trend in annual productivity over a 53.6% of the study area associated to natural and semi-natural grassland under cattle grazing, whereas a 40.3% of Argentina Pampas showed a significant positive trend in seasonality of carbon gains. The study also reveals that climate variability has a significant impact on land surface phenology in Argentina Pampas, although the impact is heterogeneous. SOS and t-MAX showed a significant negative correlation with the precipitation indicating an earlier occurrence. 23.6% and 28.4% of the study area showed a positive correlation of the annual productivity with MEI and precipitation, respectively, associated to rangelands (in the first case) and to both rangeland and croplands, in the second case. Climate variability did not explain the seasonal variability of phenology. The relationships found between LSP metrics and climate variability could be important for implementation of strategies for natural resource management.

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Section: Discussionmentioning

confidence: 99%

Trends and land surface phenological responses to climate variability in the Argentina Pampas

Lara

Gandini

Gantes

et al. 2020

CIG

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“…The upper creek basin of Del Azul has an area of 1024 km 2 , see (Guevara Ochoa et al, 2018), and the altitude of the basin varies between 367 and 129m.…”

Section: Hydrological Datamentioning

confidence: 99%

Does determinism imply caos in hydrological variables?

Marotta

Rivas

Ochoa

et al. 2022

CURIHAM

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In this paper we present several hydrological time series from Argentina that include, evapotranspiration, precipitation, and stream flow. We survey previous results and apply the 0-1 test for chaos to classify the sequences as regular or chaotic. Previous studies have shown evidence of chaos in several observables from hydrology using the traditional phase space reconstruction method and the computation of Lyapunov exponents. The 0-1 test for chaos can be used as a first step to identify the type of time series, that later can be subjected to the more detailed analysis of the phase space reconstruction. Assuming that the systems that generated these time series are deterministic, the 0-1 test for chaos classifies all of them as chaotic

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“…In addition, among many other spectral vegetation indices, the NDVI has been proved to effectively detect seasonal and inter-annual changes in vegetation growth and activity, particularly at low or moderate vegetation amounts such as in grassland areas [41,42]; however, it tends to saturate under high biomass conditions and is very sensitive to canopy background variation [41]. In spite of its limitations, previous studies across the RPG region have shown that monthly NDVI time series data effectively discriminate temperate grasslands from other cover types (e.g., croplands, forested areas) based on their unique phenological characteristics [16,24,40,43,44]. It was therefore preferred in this scenario to other available spectral indices.…”

Section: Land Cover Characterizationmentioning

confidence: 99%

“…For each period, the NDVI datasets were stacked and resampled to 30 m pixel size using the nearest neighbor method in order to preserve the original image radiometric information. Given that ground-truth information was not available for annual periods prior to 2014, unsupervised classifications were performed to each annual NDVI dataset using the ISODATA algorithm (following a similar approach that was previously performed for the RPG region; see [16,43]. The ISODATA algorithm was set to generate a maximum of 20 classes using 100 iterations, a tolerance threshold of 5%, and maximum standard deviation of 1.…”

Section: Land Cover Characterizationmentioning

confidence: 99%

Temperate Grassland Afforestation Dynamics in the Aguapey Valuable Grassland Area between 1999 and 2020: Identifying the Need for Protection

2021

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Temperate grasslands are considered the most endangered terrestrial ecosystem worldwide; the existent areas play a key role in biodiversity conservation. The Aguapey Valuable Grassland Area (VGA), one of the most well-preserved temperate grassland areas within Argentina, is currently threatened by the anthropogenic expansion of exotic tree plantations. Little is known about the impacts of afforestation over temperate grassland landscape structures; therefore, the aim of this study is to characterize Aguapey VGA landscape structural changes between 1999 and 2020 based on remotely sensed data. This involves the generation of land cover maps for four annual periods based on unsupervised classification of Landsat 5 TM and 8 OLI images, the estimation of landscape metrics, and the transition analysis between land cover types and annual periods. The area covered by temperate grassland is shown to have decreased by almost 22% over the 20 year-period studied, due to the expansion of tree plantation cover. The afforestation process took place mainly between 1999 and 2007 in the northern region of the Aguapey VGA, which led first to grassland perforation and subsequently to grassland attrition; however, Aguapey’s cultural tradition of cattle ranching could have partially inhibited the expansion of exotic trees over the final years of the study. The evidence of grassland loss and fragmentation within the Aguapey VGA should be considered as an early warning to promote the development of sustainable land use policies, mainly focused towards the Aguapey VGA’s southern region where temperate grassland remains the predominant land cover type.

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Una metodología para la caracterización del uso del suelo mediante imágenes de media resolución espacial

Cited by 8 publications

References 0 publications

Trends and land surface phenological responses to climate variability in the Argentina Pampas

Trends and land surface phenological responses to climate variability in the Argentina Pampas

Does determinism imply caos in hydrological variables?

Temperate Grassland Afforestation Dynamics in the Aguapey Valuable Grassland Area between 1999 and 2020: Identifying the Need for Protection

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