Abstract

Quantification of the direct impact of land use in the tropics on net biotic carbon flux relies on estimates of rates of deforestation, pre- and post-disturbance biomass, and fate of the cleared land. While existing remote sensing applications are providing estimates of the rates of deforestation and the fate of the cleared land (pasture, croplands, or secondary vegetation), techniques for estimating biomass of natural systems with remote sensing are needed. Synthetic Aperture Radar (SAR) presents a unique opportunity for imaging tropical forests under most cloud conditions and potentially provides information on vegetation biomass. Models for estimating above-ground biomass from SAR data have been developed. In this paper we examine the temporal and spatial variability of mean normalized radar cross-section across a chrono-sequence of secondary vegetation stands and clearings in Rondonia, Brazil. We also assess the impact of the observed temporal and spatial variability in normalized radar cross-section on estimating biomass of secondary vegetation stands. Results indicate that, while quantitative estimates of biomass are not stable due to intrinsic texture, system noise, and environmental effects, JERS-1 data are still useful for categorizing relative differences in development of secondary vegetation stands. Merging Japanese Earth Resources Satellite 1 (JERS-1) SAR data with Landsat Thematic Mapper (TM) derived age information data provide improved characterization of clearings and secondary vegetation in Rondonia.

Highlights

  • In this paper we examine the potential of using multitemporal Japanese Earth Resources Satellite 1 (JERS-1) Synthetic Aperture Radar (SAR) data for quantifying diVerences in rates of recovery of secondary vegetation for a site in central Rondonia

  • In an eVort to estimate the impact of residual slash on the overall radar backscatter from secondary vegetation stands, we examine the temporal changes in mean sigma naught with age of clearings

  • In a companion paper (Salas et al 2001 ) we develop a series of statistical models to evaluate, in an operational context, what level of changes in biomass one might be able to identify with JERS-1 SAR data for a given con dence level

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Summary

Introduction

DAcnonvuearl,cshpaantgiaellwyoeuxlpdlihcietlpesrteimsoalvteessoofmCeOo2f emissions the issues and discrepancies from the recent carbon model results based on annual atmospheric measurements. Over 30% of the deforested area in the Brazilian Amazon was in some form of secondary vegetation in 1986 and 1992 (Houghton et al 2000), areas of approximately 77 000 km and 98 000 km in secondary vegetation in 1986 and 1992, respectively The impact of these large secondary vegetation pools on the net biotic ux of carbon has yet to be quanti ed. The dynamics of the secondary vegetation pool and the rate of biomass accumulation needs to be understood in order to assess the impact of secondary vegetation on the global carbon cycle

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