Edson Eyji Sano

Land cover mapping of the tropical savanna region in Brazil

The Brazilian tropical savanna (Cerrado), encompassing more than 204 million hectares in the central part of the country, is the second richest biome in Brazil in terms of biodiversity and presents high land use pressure. The objective of this study was to map the land cover of the Cerrado biome based on the segmentation and visual interpretation of 170 Landsat Enhanced Thematic Mapper Plus satellite scenes acquired in 2002. The following land cover classes were discriminated: grasslands, shrublands, forestlands, croplands, pasturelands, reforestations, urban areas, and mining areas. The results showed that the remnant natural vegetation is still covering about 61% of the biome, however, on a highly asymmetrical basis. While natural physiognomies comprise 90% of the northern part of the biome, only 15% are left in its southern portions. Shrublands were the dominant natural land cover class, while pasturelands were the dominant land use class in the Cerrado biome. The final Cerrado’s land cover map confirmed the intensive land use pressure in this unique biome. This paper also showed that Landsat-like sensors can provide feasible land cover maps of Cerrado, although ancillary data are required to help image interpretation.

Mapeamento semidetalhado do uso da terra do Bioma Cerrado

O objetivo deste trabalho foi mapear o uso da terra do Bioma Cerrado na escala de 1:250.000. As seguintes classes de uso da terra foram consideradas: culturas agricolas, pastagens cultivadas, reflorestamentos, areas urbanas e areas de mineracao. A metodologia envolveu a segmentacao de imagens do satelite Landsat, a classificacao visual dos segmentos e a analise da exatidao global do mapa final. Aproximadamente 39,5% do Cerrado apresentaram algum tipo de uso de terra. Pastagens cultivadas e culturas agricolas foram as classes predominantes, com 26,5 e 10,5%, respectivamente.

Spatial and temporal probabilities of obtaining cloud-free Landsat images over the Brazilian tropical savanna

Remotely sensed data are the best and perhaps the only possible way for monitoring large‐scale, human‐induced land occupation and biosphere‐atmosphere processes in regions such as the Brazilian tropical savanna (Cerrado). Landsat imagery has been intensively employed for these studies because of their long‐term data coverage (>30 years), suitable spatial and temporal resolutions, and ability to discriminate different land‐use and land‐cover classes. However, cloud cover is the most obvious constraint for obtaining optical remote sensing data in tropical regions, and cloud cover analysis of remotely sensed data is a requisite step needed for any optical remote sensing studies. This study addresses the extent to which cloudiness can restrict the monitoring of the Brazilian Cerrado from Landsat‐like sensors. Percent cloud cover from more than 35 500 Landsat quick‐looks were estimated by the K‐means unsupervised classification technique. The data were examined by month, season, and El Niño Southern Oscillation event. Monthly observations of any part of the biome are highly unlikely during the wet season (October–March), but very possible during the dry season, especially in July and August. Research involving seasonality is feasible in some parts of the Cerrado at the temporal satellite sampling frequency of Landsat sensors. There are several limitations at the northern limit of the Cerrado, especially in the transitional area with the Amazon. During the 1997 El Niño event, the cloudiness over the Cerrado decreased to a measurable but small degree (5% less, on average). These results set the framework and limitations of future studies of land use/land cover and ecological dynamics using Landsat‐like satellite sensors.

A derivation of roughness correlation length for parameterizing radar backscatter models

Surface roughness is a key parameter of radar backscatter models designed to retrieve surface soil moisture (θS) information from radar images. This work offers a theory‐based approach for estimating a key roughness parameter, termed the roughness correlation length (L c). The L c is the length in centimetres from a point on the ground to a short distance for which the heights of a rough surface are correlated with each other. The approach is based on the relation between L c and h RMS as theorized by the Integral Equation Model (IEM). The h RMS is another roughness parameter, which is the root mean squared height variation of a rough surface. The relation is calibrated for a given site based on the radar backscatter of the site under dry soil conditions. When this relation is supplemented with the site specific measurements of h RMS, it is possible to produce estimates of L c. The approach was validated with several radar images of the Walnut Gulch Experimental Watershed in southeast Arizona, USA. Results showed that the IEM performed well in reproducing satellite‐based radar backscatter when this new derivation of L c was used as input. This was a substantial improvement over the use of field measurements of L c. This new approach also has advantages over empirical formulations for the estimation of L c because it does not require field measurements of θS for iterative calibration and it accounts for the very complex relation between L c and h RMS found in heterogeneous landscapes. Finally, this new approach opens up the possibility of determining both roughness parameters without ancillary data based on the radar backscatter difference measured for two different incident angles.

Identificação de impurezas e misturas em pó de café por meio de comportamento espectral e análise de imagens digitais

Para eliminar divergencias na interpretacao dos resultados e agilizar os atuais metodos de deteccao de fraudes em cafe torrado e moido, foi estabelecido um metodo baseado na analise por imagem e fundamentado no principio de que diferentes materiais de origem orgânica, como o po de cafe, podem apresentar reflectâncias distintas em diferentes comprimentos de onda do espectro eletromagnetico. Partiu-se da hipotese de que o po de cafe adulterado, quando submetido a uma fonte artificial de iluminacao, apresenta uma reflectância, nos canais vermelho (R), verde (G) e azul (B), diferente em relacao a do po de cafe nao-adulterado. Apos as etapas de limpeza, secagem e homogeneizacao, foram geradas imagens multiespectrais das amostras de cafe, por meio de uma lupa acoplada a uma câmara CCD (Charge Coupled Device). A quantificacao das impurezas na amostra foi obtida utilizando-se curvas de calibracao entre a area relativa obtida pela classificacao supervisionada de imagens e a porcentagem de impurezas presentes nas amostras. Esse novo metodo permite agilidade da resposta, ausencia de subjetividade nos resultados e nao-destruicao das amostras analisadas, e assegura um patamar minimo de deteccao de 95% das impurezas do produto.

Modelo matemático para estimativa da temperatura média diária do ar no Estado de Goiás

The objective of this work was to develop a mathematical model to predict the daily average of air temperature in Goias, Brazil. The model was developed through a linear combination of altitude, latitude, longitude, and the incomplete trigonometric Fourier series using the first three harmonic coefficients. The parameters of the model were adjusted with data from 21 weather stations, using multiple linear regression. The resulting correlation coefficient of the model was 0.91, and the Willmotts index of agreement was close to 1. The model was tested with data from three additional weather stations at different altitudes: high (1,100 m), medium (554 m), and low (431 m). The performance of the model was reasonable for both high and low altitude stations, and very good for the medium altitude station.

Biophysical characteristics and fire occurrence of cultivated pastures in the Brazilian savanna observed by moderate resolution satellite data

Cultivated pastures are the dominant land-use unit in Brazil, with the cattle raising sector representing ∼50% of the total Brazilian emissions of greenhouse gases. About 44% of the Brazilian cattle herd is located in the 204 million ha Cerrado, the Brazilian savanna biome and one of the worlds hotspots for conservation, where pasture is still the major driving force behind the ongoing land clearance. In the face of the environmental challenges posed by the Cerrado cultivated pastures, 50% of which are estimated to be already severely degraded and where most of the pasture-related fires in Brazil occur, in this study we report the findings on the use of key Moderate Resolution Imaging Spectroradiometer (MODIS) Land (MODLAND) products for retrieving biophysical patterns and trends of cultivated pastures over the entire Brazilian savanna biome. The areas of Cerrado covered by cultivated pastures were analysed by the following 2008 MODIS products: MOD13Q1 enhanced vegetation index, MOD11A2 land-surface temperature, MOD15A2 leaf area index, and MCD45A1 fire-affected areas. Specifically, 23 MOD13Q1 composites for the whole year of 2008 were used as a net primary productivity proxy. Our results indicate the ability of moderate resolution orbital imagery to consistently depict the main characteristics and regional variation in the biophysical properties of the Cerrado pastures, which clearly depend on management practices, usage, and environmental conditions. In particular, these results corroborate the feasibility of an operational MODIS-based monitoring system providing early fire warnings and overall quality assessments in support of a more efficient and sustainable herd occupation and more appropriate land-use destination.

MAPEAMENTO DE ÁREAS DE CAMPO LIMPO ÚMIDO NO DISTRITO FEDERAL A PARTIR DE FUSÃO DE IMAGENS MULTIESPECTRAIS

Wetlands are among the most important ecosystems on the earth. Despite the importance of these eco- systems, there are few studies and data regarding their location, extent and other basic characteristics. In this study, the mapping of these ecosystems was realized by means of multispectral image fusion - Landsat5/TM and CBERS2B/HRC. Images from May to October of 2008 (dry season) were merged by IHS enhancement technique. Results showed that there was an improvement in the identifi cation of areas occupied by humid grasslands since there was an gain in the discrimination of targets once there was an integration of higher spatial resolution of panchromatic band with higher spectral resolution of other bands. The map of distribution of humid grasslands indicated a total of 8,46 km 2 located essentially in conservation units.

Discriminação da cobertura vegetal do Cerrado matogrossense por meio de imagens MODIS

The objective of the present work was to evaluate the potential of the spectral linear mixture model (SLMM), applied to Moderate Resolution Imaging Spectroradiometer (MODIS) images, to discriminate natural and anthropic classes of vegetation in the portion of Mato Grosso state covered by Cerrado vegetation. The monitoring of the Cerrado biome is becoming very important due to its strong human disturbance, especially in the last four decades. In this context, the MODIS sensor appears as an option due to its high temporal resolution. However, considering its moderate spatial resolution, the decomposition of its spectral response is indicated. The SLMM appears to be a viable technique, since it permits estimating the percentage of components within the pixel. The data used in the temporal class profiles corresponded to the following fraction images derived from SLMM: vegetation, soil, and shade. Discrimination of natural and anthropogenic classes was determined through the Mahalanobis distance, presented by dendrograms. The fraction images allow time series analyses for spatial and temporal characterization of the classes. Soil and shade fraction images, in the dry season, present better results in the discrimination of selected classes. For the discrimination of classes with similar floristic composition, fraction images from the rainy season are indicated.

Polarimetric signatures and classification of tropical land covers

Polarimetric signatures for different tropical land covers were extracted from RADARSAT-2 data. Subsequently, the data were classified. The objective of this work was to assess the potential of RADARSAT-2 polarimetric C band data on land cover mapping. RADARSAT-2 data were acquired over Tapajos National Forest, a tropical forest reserve in Brazil, and surroundings, in September 2008. A field campaign was conducted during the same week of the SAR data recording. Polarimetric signatures for the different land covers were extracted for co- and cross-polarised bands and results indicated the variety of scattering mechanisms in the study area. Following that, the coherence and covariance matrices were used for the Freeman-Durden target decomposition, which decomposed the image targets in new bands representing the main scattering mechanism in the resolution cells — corner reflection, volumetric and superficial. Data were later classified by a k-means-Wishart classifier. The bands representing volumetric and superficial scattering helped discriminating vegetated and non-vegetated areas. Classification accuracy reached around 80% for forest and pasture/bare soil classes. For the remaining classes, the classification accuracy results did not reach 50%.