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Temporal scale and spatial resolution effects on Amazon forest fragmentation assessment in Rondônia

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The Amazon has been under an intense deforestation process for the last 30 years, causing landscape fragmentation in many different regions and at distinct stages. The fragmentation process is commonly assessed by land-use maps derived from satellite sensor data and analysed at a landscape context. The analysis of fragmentation depends on an adequate choice of spatial resolution of land-use maps, and temporal scale in landscape dynamics studies. In this study, spatial–temporal resolution variation effects on fragmentation assessment were analysed in the Quatro Cachoeiras watershed, located at central Rondônia, Brazilian Amazon. Land-use maps derived from 1984 to 2002 satellite sensor data at 2-year intervals were used for landscape structure analysis on 12 samples randomly distributed along the watershed. In the spatial resolution variation analysis, landscape metrics obtained at 30 m resolution were compared with those obtained at coarser spatial resolutions. Effects of temporal scale variation were tested by comparison of landscape metrics calculated at 2-, 4- and 6-year intervals in the studied period. Results show that fragmentation stage influences sensitivity of landscape metrics for spatial resolution and at initial stages of fragmentation finer spatial resolution is required. Also, coarser resolutions up to 100 m could be used to assess landscape fragmentation at regions and the adequate time interval for landscape dynamics studies should be between 3 and 4 years.
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Document Type: Research Article

Affiliations: 1: Rural Engineering Department, ‘Luiz de Queiroz' School of Agriculture, University of São Paulo (USP), Av. Pádua Dias, 11, Caixa Postal 9, 13418‐900, Piracicaba, SP, Brazil 2: Statistics and Geographic Information Science Graduate Programme, Statistics and Information Management Institute (ISEGI), Universidade Nova de Lisboa, Campus de Campolide, 1070‐312, Lisbon, Portugal

Publication date: 2006-02-10

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