Assessing Forest Cover Dynamics and Forest Perception in the Atlantic Forest of Paraguay, Combining Remote Sensing and Household Level Data.

Da Ponte, Emmanuel, Mack, Benjamin, Wohlfart, Christian, Rodas, Oscar, Fleckenstein, Martina, Oppelt, Natascha, Dech, Stefan and Kuenzer, Claudia (2017) Assessing Forest Cover Dynamics and Forest Perception in the Atlantic Forest of Paraguay, Combining Remote Sensing and Household Level Data. Forests, 8 (10). DOI 10.3390/f8100389.

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Abstract

The Upper Parana Atlantic Forest (BAAPA) in Paraguay is one of the most threatened tropical forests in the world. The rapid growth of deforestation has resulted in the loss of 91% of its original cover. Numerous efforts have been made to halt deforestation activities, however farmers’ perception towards the forest and its benefits has not been considered either in studies conducted so far or by policy makers. This research provides the first multi-temporal analysis of the dynamics of the forest within the BAAPA region on the one hand, and assesses the way farmers perceive the forest and how this influences forest conservation at the farm level on the other. Remote sensing data acquired from Landsat images from 1999 to 2016 were used to measure the extent of the forest cover and deforestation rates over 17 years. Farmers’ influence on the dynamics of the forest was evaluated by combining earth observation data and household survey results conducted in the BAAPA region in 2016. Outcomes obtained in this study demonstrate a total loss in forest cover of 7500 km2. Deforestation rates in protected areas were determined by management regimes. The combination of household level and remote sensing data demonstrated that forest dynamics at the farm level is influenced by farm type, the level of dependency/use of forest benefits and the level of education of forest owners. An understanding of the social value awarded to the forest is a relevant contribution towards preserving natural resources.

Document Type: Article
Keywords: BAAPA; remote sensing; household survey; forest; farm types
Research affiliation: Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence
Kiel University
Refereed: Yes
Open Access Journal?: Yes
DOI etc.: 10.3390/f8100389
ISSN: 1999-4907
Projects: Future Ocean
Date Deposited: 19 Dec 2017 11:39
Last Modified: 19 Aug 2019 19:35
URI: http://oceanrep.geomar.de/id/eprint/40905

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