Tatiana Mora Kuplich

Modeling small watersheds in Brazilian Amazonia with shuttle radar topographic mission-90 m data

This work presents a methodology for the refinement of shuttle radar topographic mission (SRTM-90 m) data available for South America to enable detailed watershed studies in Amazonia. The original data were pre-processed to properly map detailed low-order drainage features and allowed digital estimates of morphometric variables. Spatial-resolution refinement (3″ to 1″, or ∼90 to ∼30 m) through data kriging was found to be an interesting solution to construct digital elevation models (DEMs) with more adequate presentation of landforms than the original data. The refinement of spatial resolution by kriging interpolation overcame the main constraints for drainage modeling with original SRTM-90 m, such as spatial randomness, artifacts and unrealistic presentation due to pixel size. Kriging with a Gaussian semivariogram model caused a smoothing of the resulting DEM, but the main features for drainage modeling were preserved. Canopy effects on the modeled surface represented the main remaining limitation for terrain analysis after pre-processing. Data regarding a small watershed in Amazonas (∼38 km2), Brazil, were evaluated through visualization techniques, morphometric analyses and plot diagrams of the results. The data showed limitations for use in the original form, but could be applied for watershed modeling at relatively detailed scales after the described pre-processing.

Relating SAR image texture to the biomass of regenerating tropical forests

An accurate global carbon budget requires information on terrestrial carbon sink strength. Regenerating tropical forests are known to be important terrestrial carbon sinks but information on their location, extent and biomass (from which carbon content can be estimated) is incomplete. The use of remotely sensed data in optical wavelengths has been of limited use due to both the weak relationship between optical radiation and forest biomass and near‐constant cloud cover in the tropics. L‐band Synthetic Aperture Radar (SAR) backscatter, however, is related positively to biomass (but only up to an asymptote of around 40–90 T ha−1) and can be obtained independently of cloud cover. Both canopy structure and biomass change over time as pioneer species are replaced by early and late regenerating species. These structural changes are related to an increase in (i) tree height, (ii) tree species richness and (iii) canopy thickness and influence the roughness of the canopy surface and consequently SAR image texture. Therefore, we investigated the degree to which textural information could be used to increase the correlation between image tone (backscatter) and biomass. Field data were used to estimate the biomass of 37 regenerating forests plots in Brazilian Amazonia. Texture measures derived from local statistics, the grey level co‐occurrence matrix (GLCM) and the variogram were evaluated using simulated images on the basis of their ability to identify significant differences in image texture independently of image contrast. The selected texture measures were applied to L‐band JERS‐1 (Japanese Earth Resources Satellite) SAR images and the correlation between backscatter and biomass was determined for regenerating tropical forests. A strong correlation was found for the texture measures and biomass. The r a 2 (adjusted coefficient of determination), measuring the correlation between backscatter and biomass, increased from 0.74 to 0.82 with the addition of GLCM‐derived contrast. The addition of image texture (GLCM‐derived contrast) to image tone (backscatter) potentially increases the accuracy with which JERS‐1 SAR data can be used to estimate biomass in tropical forests.

Bamboo-dominated forests of the southwest Amazon: detection, spatial extent, life cycle length and flowering waves.

We map the extent, infer the life-cycle length and describe spatial and temporal patterns of flowering of sarmentose bamboos (Guadua spp) in upland forests of the southwest Amazon. We first examine the spectra and the spectral separation of forests with different bamboo life stages. False-color composites from orbital sensors going back to 1975 are capable of distinguishing life stages. These woody bamboos flower produce massive quantities of seeds and then die. Life stage is synchronized, forming a single cohort within each population. Bamboo dominates at least 161,500 km2 of forest, coincident with an area of recent or ongoing tectonic uplift, rapid mechanical erosion and poorly drained soils rich in exchangeable cations. Each bamboo population is confined to a single spatially continuous patch or to a core patch with small outliers. Using spatial congruence between pairs of mature-stage maps from different years, we estimate an average life cycle of 27–28 y. It is now possible to predict exactly where and approximately when new bamboo mortality events will occur. We also map 74 bamboo populations that flowered between 2001 and 2008 over the entire domain of bamboo-dominated forest. Population size averaged 330 km2. Flowering events of these populations are temporally and/or spatially separated, restricting or preventing gene exchange. Nonetheless, adjacent populations flower closer in time than expected by chance, forming flowering waves. This may be a consequence of allochronic divergence from fewer ancestral populations and suggests a long history of widespread bamboo in the southwest Amazon.

Mapping forest successional stages following deforestation in Brazilian Amazonia using multi-temporal Landsat images

Tropical forest successional stages have been mapped previously with multi‐temporal satellite sensor imagery. The precise identification and classification of such stages, however, has proved difficult. This Letter presents a new method for the classification of forest successional stages following deforestation in Brazilian Amazonia. Multi‐temporal Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) and derived fraction images and field data were used in a semi‐automatic classification approach. The results were encouraging and signal the application of the method for the entire Brazilian Amazonia.

Variáveis geomorfométricas locais e sua relação com a vegetação da região do interflúvio Madeira-Purus (AM-RO)

The objective of this work was to assess the potential of geomorphometric variables, derived from SRTM (Shuttle Radar Topographic Mission) data, to help identify vegetation types in the Amazonian Madeira-Purus interfluvio region. A RADAMBRASIL project vegetation map was used as a reference and the geomorphometric variables (elevation, slope, aspect and profile and plan curvatures) were compared to the mapped units. Analyses indicated vegetation types easily discriminated, depending on the topographic position. The variables of elevation, slope and aspect were the most important for their high discrimination power of the vegetation types. Although geomorphometric data are recognized as having strong potential for characterizing vegetation, this was not shown in the results, due to the mismatching of variability scales between the two sources of data; large units tend to exhibit similar distribution patterns of geomorphometry, and comprise classes with different responses for geomorphometric constraints. Discriminant analyses of geomorphometric variables permitted vegetation mapping up to the sub-physiognomy levels.

Quantifying optical and SAR image relationships for tropical landscape features in the Amazônia

This paper discusses the relationship between SAR and optical data for an Amazonian test‐site with different land cover types. L‐band HH JERS‐1 SAR and Landsat TM images acquired few days apart from each other in 1994 and 1997 were analyzed. Landsat TM fraction images (vegetation, soil, and shade) were used to characterize the terrain features in the study area. Based on 220 samples randomly distributed over different land cover types in the fraction and SAR bands, a regression analysis was performed. Consistent results between SAR data and fraction images suggest that L‐band SAR data may be a complementary source of information for mapping land cover changes in Amazônia, especially to monitor deforestation in areas frequently blurred by cloud cover in optical images.

Tropical land cover change detection with polarimetric SAR data

There is an increasing need for fast and accurate data on tropical land cover status, and a baseline for land cover monitoring. Remotely sensed SAR data are not sensitive to cloud cover and can be useful for such purpose. Polarimetric SAR data are available in orbital systems, such as RADARSAT-2, and still have to be tested for the classification of tropical land cover and the detection of land cover change, particularly forest conversion. This work presents a study of RADARSAT-2 polarimetric images, acquired in two different dates (September 2008 and October 2009), to assess their potential in classifying forest and non-forest classes in Brazilian Amazonia. SAR images were acquired following different orbit and incidence angles, which anticipated varied conditions for images interpretation and classes discrimination. The complex SAR data were classified based on the distance of Wishart, and information from field campaigns was used for the training and test samples. Classification results were compared to evaluate possibilities for change detection in the forest cover. Classification accuracy figures were around 80%. The use of RADARSAT-2 images allowed the mapping of land cover and land cover change, considering forest and non-forest classes.

Série temporal de índice de vegetação sobre diferentes tipologias vegetais no Rio Grande do Sul

The objective of this study was the identification of the phenology dynamics of the main types of vegetation of Rio Grande do Sul state, for the period from 2000 to 2010, using Enhanced Vegetation Index data through the wavelet transform. The identification of cycles or seasonal patterns in time series of vegetation indices obtained by orbital sensors allows the observation of anomalies and effects of climate and environmental change. A temporal profile of Enhanced Vegetation Index was built for the Rio Grande do Sul region, where samples of the four main plant typologies were selected: native grassland, mixed ombrophilous forest, soybean and rice crop. These samples were submitted to the wavelet transform, which allowed the decomposition of the series and presentation of data in relation to time and frequency with which the phenological events have occurred. The data showed regularity in the dynamics of vegetation types tested, with annual cycles of plant growth and higher Enhanced Vegetation Index values in spring and summer and lower Enhanced Vegetation Index values in autumn and winter.

Relação entre as variáveis morfométricas extraídas de dados SRTM (Shuttle Radar Topography Mission) e a vegetação do Parque Nacional de Brasília

Este trabalho visa ao estudo da relacao entre a distribuicao de fitofisionomias do Parque Nacional de Brasilia (PNB) e variaveis topograficas, para avaliar o potencial de dados SRTM isoladamente, como complemento aos dados tradicionalmente aplicados no sensoriamento remoto da vegetacao. Esta relacao foi verificada atraves de analises discriminantes entre o mapa de vegetacao referencia do PNB e as seguintes variaveis morfometricas: elevacao, declividade, orientacao de vertente, curvatura vertical e curvatura horizontal. Tais analises indicaram as classes de vegetacao que podem ser separadas com base nas condicoes topograficas do terreno. As variaveis morfometricas mais importantes na distincao entre os tipos vegetacionais foram a elevacao, a declividade e a orientacao de vertente. Apesar de os dados morfometricos mostrarem potencial indicativo das classes de vegetacao, as analises resultaram em discriminacao em um nivel aquem do detalhamento tematico do mapa referencia. Tal desempenho pode ser explicado pela incompatibilidade das escalas de variacao exibidas entre os dados morfometricos em relacao ao tamanho das unidades de mapeamento da vegetacao. Alem disso, a variacao de tipos de vegetacao do cerrado pode ser explicada por uma serie de outros fatores alem da topografia. Com base nas analises discriminantes das variaveis morfometricas, foi possivel o mapeamento experimental da vegetacao ao nivel de subfisionomias.

Relação da vegetação de caatinga com a condição geomorfométrica local

The objective of this work was to assess the potential of geomorphometric variables, derived from SRTM (Shuttle Radar Topographic Mission) data, to help in identifying vegetation types in the Serra das Almas National Park (CE). A 1:100.000 survey vegetation map was used as reference and the geomorphometric variables (elevation, slope, aspect and profile and plan curvatures) were compared to the mapped units. The variables elevation, slope and profile curvature were shown as the most important for their high discrimination power of the vegetation types. Although geomorphometric data had strong potential for characterizing vegetation through map comparisons, the achieved thematic detail levels were under those of the reference map when data was analyzed under a numerical approach. It was concluded that geomorphometric data were important input for vegetation mapping, and should be employed together with currently used data.