Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Spatial Analysis of Degradation in the Reserve for San Rafael National Park, Period 2005-2019

Version 1 : Received: 16 May 2021 / Approved: 17 May 2021 / Online: 17 May 2021 (13:30:45 CEST)

How to cite: Llamas Franco, T.J.; Marín, L.J.V.; Rodríguez, S.M.A.; Molas, L.F.P.D.; Soria, L.G.; Bullock, E. Spatial Analysis of Degradation in the Reserve for San Rafael National Park, Period 2005-2019. Preprints 2021, 2021050389 (doi: 10.20944/preprints202105.0389.v1). Llamas Franco, T.J.; Marín, L.J.V.; Rodríguez, S.M.A.; Molas, L.F.P.D.; Soria, L.G.; Bullock, E. Spatial Analysis of Degradation in the Reserve for San Rafael National Park, Period 2005-2019. Preprints 2021, 2021050389 (doi: 10.20944/preprints202105.0389.v1).

Abstract

The goal of this study was to analyze the forest degradation in the Reserve for San Rafael National Park, Paraguay, during the period 2005-2019. This Reserve is one of the most important forest remnants of the Upper Paraná Atlantic Forest Ecoregion. A multitemporal analysis of degradation was carried out due to the occurrence of three disturbances: forest fires, a twister and illicit crops, using the Continuous Degradation Detection (CODED) algorithm, for which 3 factors were considered: variations due to pixel in the NDFI index values before, during and after every disturbance registered. In this context, the phenomenon with the greatest impact in terms of magnitude of degradation were the forest fires of 2005, being that year at the same time, the one that reported the highest degradation values. Secondly, there are the illicit crops established until the first semester of 2019, and lastly, the twister that occurred in 2017. Our findings demonstrate that CODED algorithm can detect multi-temporal degradation events in a Subtropical Broadleaf Forest, and the post-disturbance regeneration process after every disturbance tends to occur immediately. The response in terms of degradation-regeneration is highly variable, depending of the nature and severity of each disturbance and the vegetation recovery dynamics.

Subject Areas

forest degradation; NDFI index; multitemporal analysis; Continuous Degradation Detection; Google Earth Engine

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