SourCeBook oN remoTe SeNSiNg aND BioDiverSiTy iNDiCaTorS

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Sourcebook on Remote Sensing and Biodiversity Indicators Case Study 4.1: Forest Cover Change in Paraguay Author: Ben White, Global Land Cover Facility (GLCF), University of Maryland Indicator: tropical forest extent and change Potential monitoring scales: landscape, small and large nations Sensor: Landsat TM and Landsat Enhanced Thematic Mapper (ETM+) Imagery cost/hectare: free a. Introduction The moist tropical forests, tropical grasslands, and savannas that make up the Atlantic Forest are one of the world’s most diverse and endangered ecosystems. The forest has diminished to roughly 10 percent of its pre-Columbian extent, largely because of pressures from farming, logging, and population growth. Nevertheless, the remaining habitat is astonishingly diverse, with more than ,000 estimated vertebrate species and more than 0,000 plant species. By the early 1970s, the Brazilian interior Atlantic Forest was almost completely destroyed, while portions of the Atlantic Forest remained intact in Argentina and Paraguay. Although Brazil and Argentina established parks around Iguazú Falls to preserve portions of the forest, the majority of the Atlantic Forest in Paraguay has been almost entirely eliminated or fragmented. Today, the remaining Paraguayan Atlantic Forest is largely a function of accessibility and protected status. Although circumstances leading to the post-1970 deforestation are complex, three significant regional dynamics are recognized. The construction of a dam at the northern tip of the Paraná River substantially impacted the watershed, which was tied to traditional land dynamics throughout most of Paraguay. The Central Bank of Paraguay and the Inter-American Development Bank (IADB) have determined that in recent years, there has also been an increasing lack of governance throughout the border departments (states), making environmental management increasingly challenging. Perhaps the most significant driver of land cover change was the introduction of mechanized soy agriculture. In Alta Paraná and Itapua departments, the correlation of deforestation with soy production was particularly strong. b. Methods The methodology for the Paraguayan forest cover change mapping was initiated with the coregistration of orthorectified Landsat TM with ETM+ Level1G imagery. A data mask was then developed, incorporating only those pixels that need to be classified. The masking was followed by a standard ISODATA clustering of the multitemporal Landsat imagery. A binary training mask was created for each class. The spectral clusters resulting from the ISODATA clustering were then labeled using an automated application developed by GLCF. The masking/labelling routine was repeated until all pixels were classified. As needed, the GLCF personnel performed any required editing and filtering. The classified tiles were then mosaicked into a single country product. c. Results The GLCF became involved with the Paraguayan conservation organization, Guyra Paraguay, in an effort to map the changing land cover and to help guide local, national, and NGO managers and stakeholders. GLCF staff was able to map the vegetation changes by using Landsat satellite imagery and the methods outlined above, while Guyra Paraguay provided the ground-truthing necessary to validate the GLCF results (figure 4.1). Since then, Guyra Paraguay has conducted its own updating of these deforestation 40
�� Chapter 4. Trends in Selected Biomes, Habitats, and Ecosystems: Forests �� FIguRe 4.1 Forest change in Paraguay between 1990 and 2000. �� 41
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SourCeBook oN remoTe SeNSiNg aND BioDiverSiTy iNDiCaTorS

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