Submitted by Romulus Lima (romulus.lima@ufpe.br) on 2015-03-04T18:14:30Z No. of bitstreams: 2 DISSERTAÇÃO Bruna Patrícia Barbosa de Alencar.pdf: 2179196 bytes, checksum: 8c3cf557099a57319a7f100868e020c5 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-03-04T18:14:30Z (GMT). No. of bitstreams: 2 DISSERTAÇÃO Bruna Patrícia Barbosa de Alencar.pdf: 2179196 bytes, checksum: 8c3cf557099a57319a7f100868e020c5 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2013-02-26 / As imagens de RADAR são uma alternativa para a realização de mapeamentos em áreas de grande cobertura de nuvens, inerentes às imagens de sensores passivos. Entretanto, devido à variação de declive dos terrenos, que influência o ângulo de incidência do feixe emitido pelo RADAR, alguns erros geométricos ocorrem nas imagens. Esses erros são o encurtamento de rampa, inversão do relevo e o sombreamento. O objeto de estudo desta dissertação é a análise da ocorrência da sombra nas imagens ALOS/PALSAR, por ser uma área que não tem sinal de retorno e por gerar confusão no mapeamento de áreas como, por exemplo, as de vegetação. O sombreamento pode ocorrer em regiões de terreno movimentado e onde a face do relevo está voltada perpendicularmente ao pulso enviado pela antena ALOS/PALSAR. Para analisar a geração da sombra, são estudadas duas áreas de terreno movimentado. As áreas estão nos municípios de Petrolândia em Pernambuco e Glória na Bahia. Elas apresentam relevo ondulado controlado por zonas de cisalhamento, dobramentos e falhas geológicas. Uma metodologia de detecção da sombra ALOS/PALSAR é realizada, através da binarização da imagem ALOS/PALSAR supondo que para a área de sombra o retorno de sinal é muito baixo. Curvas de nível, mapa de orientação de vertentes e mapa de declividade foram adquiridos do projeto TOPODATA para verificar as características do terreno que influenciam na ocorrência do sombreamento, a escala utilizada foi de 1:100000. As imagens LANDSAT5/TM permitiram localizar as feições e compará-las com as regiões de sombra localizadas nas imagens ALOS/PALSAR. A área de sombra foi identificada na região de declividade, predominantemente, maior que 75% e nas orientações Sudeste e Sul. Os dados de orientação de vertentes e declividade serviram como dados fundamentais na identificação das áreas de sombra, juntamente com a imagem binarizada para identificar o baixo retorno do sinal que ocorre nas imagens de RADAR.

O presente estudo teve como objetivo principal avaliar o uso de diferentes algoritmos classificadores em imagens do satélite ALOS para mapeamento do uso do solo e classes de vegetação em um fragmento de Floresta Ombrófila Mista. Como objetivo secundário foram aplicadas e analisadas quatro diferentes técnicas de fusão para as imagens PRISM (2,5 metros de resolução espacial) e AVNIR-2 (10 metros), utilizando três e quatro bandas. As técnicas utilizadas foram as seguintes: HSV, Color normalized (CN), Gram-Schmidt Spectral Sharpening e Principal Components Spectral Sharpening. Para as classificações foram utilizados os algoritmos supervisionados Bhattacharya e Árvore de Decisão (C4.5). A área de estudo foi a Reserva Florestal Embrapa/Epagri localizada no Município de Caçador, SC. Na classificação por árvore de decisão foi utilizado um aplicativo para a geração do conjunto de regras da árvore, o software WEKA e um aplicativo de processamento de imagens, o software ENVI, para a classificação digital (RSI, 2005). Foram utilizadas 61 variáveis (13 espectrais e 48 de textura) representadas em 317 amostras de treinamento de 3 x 3 pixels cada uma. Quando da classificação por Bhattacharya (algoritmo de classificação por crescimento de regiões implementado no software SPRING) foi necessário primeiramente realizar a segmentação da imagem para posterior uso das regiões como amostras de treinamento para a classificação. Devido à limitação do software em processar 61 bandas conjuntamente no processo de segmentação, a técnica Análise de Cluster foi empregada para a seleção de seis bandas representativas do conjunto de dados. Na análise visual e no teste de fidelidade espectral, as técnicas de fusão que apresentaram melhores resultados foram as Componentes Principais e Gram-Schmidt. No teste de transferência de detalhes as quatro técnicas de fusão se mostraram apropriadas. No resultado das classificações o algoritmo que apresentou melhor acurácia foi a Árvore de Decisão, apresentando valor de coeficiente Kappa de 0,966 e acurácia geral de 97% em comparação com o Bhattacharya, que respectivamente apresentou os seguintes valores: 0,755 e 79%. Apesar da técnica Árvore de Decisão apresentar um coeficiente Kappa superior, sua classificação se mostrou com aparência de “salt and pepper”, com pixels isolados, assemelhando-se a uma imagem com ruído, ao contrário da classificação por regiões.

L’étude de la diffusion des ondes électromagnétiques par une surface rugueuse aléatoire est de première importance dans de nombreuses disciplines et conduit à diverses applications notamment pour le traitement des surfaces par télédétection. En connaissant les modes de rétrodiffusion, on peut détecter la présence de la rugosité aléatoire indésirable de la surface de réflection telle que le réflecteur d'antenne et par conséquent trouver un moyen de corriger ou compenser les erreurs de phase. Cette thèse porte sur l’obtention de l'humidité du sol de surface à partir de mesures radar. La description de la surface rugueuse de façon aléatoire est présentée, suivie par les interactions d'ondes électromagnétiques avec les média. En particulier, un modèle d'équation intégrale avancé (AIEM) est introduit. La validité du modèle AIEM, qui est adopté comme modèle de travail, se fait par une large comparaison avec des simulations numériques et des données expérimentales. On analyse également les caractéristiques des configurations radar bistatique et on étudie la sensibilité de la diffusion bistatique à l'humidité du sol et à la rugosité de surface et, dans le même temps, le cadre de la détermination de l'humidité du sol à partir de mesures radar utilisant un réseau de neurones à base de filtres de Kalman récurrents est présenté. La formation du réseau et l'inversion des données sont décrits. / Electromagnetic waves scattering from a randomly rough surface is of palpable importance in many fields of disciplines and bears itself in various applications spanned from surface treatment to remote sensing of terrain and sea. By knowing the backscattering patterns, one may detect the presence of the undesired random roughness of the reflection surface such as antenna reflector and accordingly devise a means to correct or compensate the phase errors. Therefore, it has been both theoretically and practically necessary to study the electromagnetic wave scattering from the random surfaces. This dissertation focuses on the retrieval of surface soil moisture from radar measurements. The description of the randomly rough surface is presented, followed by the electromagnetic wave interactions with the media. In particular, an advanced integral equation model (AIEM) is introduced. The validity of the AIEM model, which is adopted as a working model, is made by extensive comparison with numerical simulations and experimental data. Also analyzes the characteristics of the bistatic radar configurations and dissects the sensitivity of bistatic scattering to soil moisture and surface roughness of soil surfaces. Meanwhile presents a framework of soil moisture retrieval from radar measurements using a recurrent Kalman filter-based neural network. The network training and data inversion are described in detail.

Hydrological modelling is a powerful tool for hydrologists and engineers involved in the planning and development of integrated approach for the management of water resources. With the recent advent of computational power and the growing availability of spatial data, RS and GIS technologies can augment to a great extent the conventional methods used in rainfall runoff studies; it is possible to accurately describe watershed characteristics in particularly when determining runoff response to rainfall input. The main objective of this study is to apply the potential of spaceborne SAR data for soil moisture retrieval in order to improve the spatial input parameters required for hydrological modelling. For the spatial database creation, high resolution 2 m aerial laser scanning Digital Terrain Model (DTM), soil map, and landuse map were used. Rainfall records were transformed into a runoff through hydrological parameterisation of the watershed and the river network using HEC-HMS software for rainfall runoff simulation. The Soil Conservation Services Curve Number (SCS-CN) and Soil Moisture Accounting (SMA) loss methods were selected to calculate the infiltration losses. In microwave remote sensing, the study of how the microwave interacts with the earth terrain has always been interesting in interpreting the satellite SAR images. In this research soil moisture was derived from two different types of Spaceborne SAR data; TerraSAR-X and ALOS PALSAR (L band). The developed integrated hydrological model was applied to the test site of the Gottleuba Catchment area which covers approximately 400 sqkm, located south of Pirna (Saxony, Germany). To validate the model historical precipitation data of the past ten years were performed. The validated model was further optimized using the extracted soil moisture from SAR data. The simulation results showed a reasonable match between the simulated and the observed hydrographs. Quantitatively the study concluded that based on SAR data, the model could be used as an expeditious tool of soil moisture mapping which required for hydrological modelling.

Hydrological modelling is a powerful tool for hydrologists and engineers involved in the planning and development of integrated approach for the management of water resources. With the recent advent of computational power and the growing availability of spatial data, RS and GIS technologies can augment to a great extent the conventional methods used in rainfall runoff studies; it is possible to accurately describe watershed characteristics in particularly when determining runoff response to rainfall input. The main objective of this study is to apply the potential of spaceborne SAR data for soil moisture retrieval in order to improve the spatial input parameters required for hydrological modelling. For the spatial database creation, high resolution 2 m aerial laser scanning Digital Terrain Model (DTM), soil map, and landuse map were used. Rainfall records were transformed into a runoff through hydrological parameterisation of the watershed and the river network using HEC-HMS software for rainfall runoff simulation. The Soil Conservation Services Curve Number (SCS-CN) and Soil Moisture Accounting (SMA) loss methods were selected to calculate the infiltration losses. In microwave remote sensing, the study of how the microwave interacts with the earth terrain has always been interesting in interpreting the satellite SAR images. In this research soil moisture was derived from two different types of Spaceborne SAR data; TerraSAR-X and ALOS PALSAR (L band). The developed integrated hydrological model was applied to the test site of the Gottleuba Catchment area which covers approximately 400 sqkm, located south of Pirna (Saxony, Germany). To validate the model historical precipitation data of the past ten years were performed. The validated model was further optimized using the extracted soil moisture from SAR data. The simulation results showed a reasonable match between the simulated and the observed hydrographs. Quantitatively the study concluded that based on SAR data, the model could be used as an expeditious tool of soil moisture mapping which required for hydrological modelling.

The aim of this thesis is to evaluate the capability of radio detection and ranging (radar) data collected by the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture radar (PALSAR), supported by field measurements obtained through ground survey, to predict and map Above Ground Woody Biomass (AGWB) in the tropical savannas of the developing country of Belize, and to understand how the forest structure may influence the backscatter observed. Firstly, an extensive inventory of the woody vegetation of the tropical savannas of Belize was created by measuring the diameter at breast height (dbh), the total height (ht) and the location of 6547 trees in plots covering a total woodland area of 30.8 hectares, located within four protected areas (the Rio Bravo Conservation and Management Area (11×1ha), Deep River (108×0.1ha) and Manatee Forest Reserve (1ha) and the Bladen Nature Reserve (1ha) and also from plots located in unprotected areas (7×1ha). These measurements of forest structure, when combined with information about forest management practices obtained from local organisations revealed that different forms of protection and management may lead to the development of pine woodlands with different structural characteristics in these savannas. Secondly, a case-study was conducted to establish the sensitivity of the ALOS PALSAR backscatter data to AGWB and determine the effect of sample plot size to their relationship. The findings of this case-study show that the L-band backscatter in these low density pine woodlands is a possible predictor of AGWB and confirm that the appropriate sample plot size for predicting AGWB is one hectare; while the sensitivity degrades significantly with decreasing sample plot size. Taken together, the findings described above were combined to assess the capability of ALOS PALSAR backscatter to predict AGWB in these woodlands. A semi-empirical Water Cloud Model (WCM) describing the interaction between the backscatter and vegetation was re-arranged to enable the prediction of AGWB. Non-linear regression analysis revealed that the ALOS PALSAR backscatter predicted AGWB with an R2=0.92; an external validation conducted with additional ground reference data estimated this AGWB prediction to have an RMSE ~13 t/ha. The form of the regression model linking backscatter to AGWB appears to be particularly influenced by sample plots with higher tree numbers and by plots in which the trees were more homogeneous. The presence of many similar sized individuals within some plots is postulated as one explanation for the elevated saturation level for predictions in this study (> 100 t/ha) compared to other models. The model developed here predicts complete saturation in the backscatter - AGWB relationship to occur primarily as a result of increases in the tree number density and often concurrently in basal area, two parameters which are usually strongly correlated with AGWB in these woodlands. Thirdly, the locally validated relationship between ALOS PALSAR backscatter and AGWB is used to map AGWB for the lowland pine savannas of Belize at a spatial resolution of 100m. The mapping estimates that over 90% of these pine woodlands have an AGWB below 60 t/ha, with the average woody biomass estimated at 23.5 t/ha. When these new predictions are mapped and aggregated over the extents of two protected areas (Rio Bravo and Deep River), the totals obtained agree closely (error ≤20%) with previous estimates of AGWB obtained from ground data and previous research. The combined evidence suggests that woodland protection may produce a small, positive effect upon AGWB, with the mean of the AGWB/ha predictions higher in areas that are protected and managed for biodiversity (29.55 ± 0.84 t/ha) than in other areas that are not protected (23.29 ± 0.19 t/ha). When the fine scale local AGWB mapping produced using ALOS PALSAR is compared cell-by-cell with global biomass products at coarser spatial resolutions (500m and 1000m), the AGWB differences observed range from 115-120%. When the coarser AGWB estimates are aggregated over the extents of Deep River and Rio Bravo, the AGWB totals obtained differ significantly (~280 – 300%) from AGWB estimates from ground data and previous research. Overall, these findings suggest that where sufficient ground data exists to build a reliable local relationship to radar backscatter, more detailed biomass mapping can be produced from ALOS and similar satellite sensor data at resolutions of ~100m. This more accurate and spatially detailed information about the distribution of woody biomass within tropical lowland savannas is more appropriate for monitoring local changes in forest cover and for supporting management decisions for forested areas of around ~10,000ha than estimates based upon previously available, but coarser scale, global biomass products.

The boreal forest covers 11% of the earth’s land surface and contains 37 percent of the planet’s terrestrial carbon, which is more than the combined total of both the tropical and the temperate forests [1]. This estimate translates to 703 Pg of carbon with the vast majority contained within the organic soils and peat layers [2-4]. The western-north American boreal forest is a fire ecosystem [2, 5-7] where fires typically occur every 50 to 200 years [8, 9], allowing vast quantities of carbon to re-enter the atmosphere. Understanding and estimating past fire history and the related changes in carbon budget [3, 4, 7, 10] in this biome is of significant importance for climate researchers as they attempt to model for future changes in the planet’s climate [2, 4, 11-14]. Many techniques are available to remotely sense wildfires - using optical, thermal and passive microwave remote sensors - during and immediately after an event - although resolution and availability of images due to cloud cover can make these techniques operationally challenging. Radar remote sensing can provide a complement to these optical and passive microwave techniques, since radar is not affected by cloud cover and solar illumination levels. The Advanced Land Observatory Satellite (ALOS) operates a phased array L band synthetic aperture radar (PALSAR) and Canada’s Radarsat-2 contains a C-Band (SAR) instrument. These radar satellites can be used to detect information about the boreal forest environment including the effects of wildfire. Polarimetric radar is an emerging technology whose full potential is still being actively explored and discovered. More specifically, this research is ground-breaking since very little work has been performed investigating the relationship between polarimetric radar data and historical boreal wildfire events. This area of investigation is a complex marriage of forestry, geospatial information and radar engineering that requires an extensive array of data sets to facilitate analysis. This research has demonstrated that both PALSAR L-Band and Canada’s Radarsat-2 C-Band full polarimetric radars can be used to detect and classify wildfire scars within individual images. The boreal forest is a dynamic ecosystem where both the level of burn severity and the subsequent regeneration of the forest is affected by many factors that can vary widely across small distances. This work contributes to the understanding of the relationships between remotely sensed quad-pol radar signals and both the boreal ecosystem and how wildfire interacts in this environment. / Graduate / 0478 / 0538 / 0984 / ghobart@nrcan.gc.ca

O objetivo deste trabalho foi a geração e avaliação de ortoimagens ALOS/PRISM, utilizandose para isso MDEs (Modelos Digitais de Elevação) obtidos através das diferentes combinações de visadas desse sensor de uma imagem com nível de processamento 1B1. Na primeira etapa foram gerados os MDEs a partir das combinações das três visadas, utilizando-se para isso pontos de controle obtidos através de levantamento de campo, onde foram testados a quantidade mínima necessária de pontos de controle para geração de MDE e outros parâmetros tais como nível de processamento, tamanho de janela, entre outros. Na etapa seguinte, comparou-se o resultado da extração com os Modelos Digitais de Elevação do ASTER (GDEM) e o SRTM (Shuttle Radar Topographic Mission), este gerado a partir do Projeto TOPODATA do INPE (Instituto Nacional de Pesquisas Espaciais). Na etapa final avaliaram-se os MDEs com os pontos de checagem. Através de análises estatísticas selecionaram-se os melhores MDEs para ortorretificação. Os resultados demonstraram que, para este caso específico, todos os MDES da combinação de visada Backward – Foward (gerados a partir de 6 pontos de controle) seriam aprovados por apresentarem os menores valores de RMS (entre 2,94 e 3m) e que, ao se utilizar outros MDEs oriundos de outras combinações, as ortoimagens obtidas também atendem ao Padrão de Exatidão Cartográfica (PEC) Classe A para escala 1:25.000, bem como as ortoimagens geradas com os Modelos de Elevação Globais SRTM e GDEM. A área de estudo escolhida foi uma região rural do município de São Gabriel – RS, que possui relevo com média altimétrica de 160m, podendo ser considerado plano, o que justifica o bom desempenho do SRTM em conjunto com os MDEs gerados a partir do PRISM. / The aim of this work was the generation and evaluation of orthoimages ALOS / PRISM, using the MDEs (Digital Elevation Models) obtained using different combinations of sensor views of an image with 1B1 processing level. In the first step the MDEs were created from combinations of three views, using for it the ground control points obtained by field survey, where the minimum amount necessary of control points for DEM generation and other parameters as processing level, size of the windows, among others were tested. In the further step, the result of extraction was compared to Digital Elevation Models from ASTER (GDEM) and SRTM (Shuttle Radar Topographic Mission), this one generated from the Project TOPODATA from INPE (National Institute for Space Research). In the final step, the MDEs were evaluated with the checkpoints. Through statistical analysis the best MDEs were selected for orthorectification. The results showed that, for this specific case, all MDEs combination of Backward - Foward (generated from 6 control points) would be approved by submitting the lowest values of RMS (between 2.94 and 3 m) and, when using other MDEs from another combinations, obtained orthoimages also satisfies the Cartographic Accuracy Standard (PEC) for Class A 1:25,000 scale, as the orthoimages generated from the SRTM and GDEM. The chosen study area was a rural region of São Gabriel - RS, which has average altitude of 160 m, can be considered plane, which explains the good performance of the SRTM in conjunction with the MDEs generated from PRISM.

O objetivo deste trabalho foi a geração e avaliação de ortoimagens ALOS/PRISM, utilizandose para isso MDEs (Modelos Digitais de Elevação) obtidos através das diferentes combinações de visadas desse sensor de uma imagem com nível de processamento 1B1. Na primeira etapa foram gerados os MDEs a partir das combinações das três visadas, utilizando-se para isso pontos de controle obtidos através de levantamento de campo, onde foram testados a quantidade mínima necessária de pontos de controle para geração de MDE e outros parâmetros tais como nível de processamento, tamanho de janela, entre outros. Na etapa seguinte, comparou-se o resultado da extração com os Modelos Digitais de Elevação do ASTER (GDEM) e o SRTM (Shuttle Radar Topographic Mission), este gerado a partir do Projeto TOPODATA do INPE (Instituto Nacional de Pesquisas Espaciais). Na etapa final avaliaram-se os MDEs com os pontos de checagem. Através de análises estatísticas selecionaram-se os melhores MDEs para ortorretificação. Os resultados demonstraram que, para este caso específico, todos os MDES da combinação de visada Backward – Foward (gerados a partir de 6 pontos de controle) seriam aprovados por apresentarem os menores valores de RMS (entre 2,94 e 3m) e que, ao se utilizar outros MDEs oriundos de outras combinações, as ortoimagens obtidas também atendem ao Padrão de Exatidão Cartográfica (PEC) Classe A para escala 1:25.000, bem como as ortoimagens geradas com os Modelos de Elevação Globais SRTM e GDEM. A área de estudo escolhida foi uma região rural do município de São Gabriel – RS, que possui relevo com média altimétrica de 160m, podendo ser considerado plano, o que justifica o bom desempenho do SRTM em conjunto com os MDEs gerados a partir do PRISM. / The aim of this work was the generation and evaluation of orthoimages ALOS / PRISM, using the MDEs (Digital Elevation Models) obtained using different combinations of sensor views of an image with 1B1 processing level. In the first step the MDEs were created from combinations of three views, using for it the ground control points obtained by field survey, where the minimum amount necessary of control points for DEM generation and other parameters as processing level, size of the windows, among others were tested. In the further step, the result of extraction was compared to Digital Elevation Models from ASTER (GDEM) and SRTM (Shuttle Radar Topographic Mission), this one generated from the Project TOPODATA from INPE (National Institute for Space Research). In the final step, the MDEs were evaluated with the checkpoints. Through statistical analysis the best MDEs were selected for orthorectification. The results showed that, for this specific case, all MDEs combination of Backward - Foward (generated from 6 control points) would be approved by submitting the lowest values of RMS (between 2.94 and 3 m) and, when using other MDEs from another combinations, obtained orthoimages also satisfies the Cartographic Accuracy Standard (PEC) for Class A 1:25,000 scale, as the orthoimages generated from the SRTM and GDEM. The chosen study area was a rural region of São Gabriel - RS, which has average altitude of 160 m, can be considered plane, which explains the good performance of the SRTM in conjunction with the MDEs generated from PRISM.

O objetivo deste trabalho foi a geração e avaliação de ortoimagens ALOS/PRISM, utilizandose para isso MDEs (Modelos Digitais de Elevação) obtidos através das diferentes combinações de visadas desse sensor de uma imagem com nível de processamento 1B1. Na primeira etapa foram gerados os MDEs a partir das combinações das três visadas, utilizando-se para isso pontos de controle obtidos através de levantamento de campo, onde foram testados a quantidade mínima necessária de pontos de controle para geração de MDE e outros parâmetros tais como nível de processamento, tamanho de janela, entre outros. Na etapa seguinte, comparou-se o resultado da extração com os Modelos Digitais de Elevação do ASTER (GDEM) e o SRTM (Shuttle Radar Topographic Mission), este gerado a partir do Projeto TOPODATA do INPE (Instituto Nacional de Pesquisas Espaciais). Na etapa final avaliaram-se os MDEs com os pontos de checagem. Através de análises estatísticas selecionaram-se os melhores MDEs para ortorretificação. Os resultados demonstraram que, para este caso específico, todos os MDES da combinação de visada Backward – Foward (gerados a partir de 6 pontos de controle) seriam aprovados por apresentarem os menores valores de RMS (entre 2,94 e 3m) e que, ao se utilizar outros MDEs oriundos de outras combinações, as ortoimagens obtidas também atendem ao Padrão de Exatidão Cartográfica (PEC) Classe A para escala 1:25.000, bem como as ortoimagens geradas com os Modelos de Elevação Globais SRTM e GDEM. A área de estudo escolhida foi uma região rural do município de São Gabriel – RS, que possui relevo com média altimétrica de 160m, podendo ser considerado plano, o que justifica o bom desempenho do SRTM em conjunto com os MDEs gerados a partir do PRISM. / The aim of this work was the generation and evaluation of orthoimages ALOS / PRISM, using the MDEs (Digital Elevation Models) obtained using different combinations of sensor views of an image with 1B1 processing level. In the first step the MDEs were created from combinations of three views, using for it the ground control points obtained by field survey, where the minimum amount necessary of control points for DEM generation and other parameters as processing level, size of the windows, among others were tested. In the further step, the result of extraction was compared to Digital Elevation Models from ASTER (GDEM) and SRTM (Shuttle Radar Topographic Mission), this one generated from the Project TOPODATA from INPE (National Institute for Space Research). In the final step, the MDEs were evaluated with the checkpoints. Through statistical analysis the best MDEs were selected for orthorectification. The results showed that, for this specific case, all MDEs combination of Backward - Foward (generated from 6 control points) would be approved by submitting the lowest values of RMS (between 2.94 and 3 m) and, when using other MDEs from another combinations, obtained orthoimages also satisfies the Cartographic Accuracy Standard (PEC) for Class A 1:25,000 scale, as the orthoimages generated from the SRTM and GDEM. The chosen study area was a rural region of São Gabriel - RS, which has average altitude of 160 m, can be considered plane, which explains the good performance of the SRTM in conjunction with the MDEs generated from PRISM.