Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products

Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties – the sill and the mean length scale metric – provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R2 = 0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R2 = 0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets.

Interpretação integrada de sísmica de alta-resolução e da morfologia submarina da costa de fiordes na patagônia central - Chile

Este estudo apresenta o uso integrado da sísmica de alta resolução e da morfologia submarina para interpretar a evolução do ambiente glacimarinho da costa de fiordes da Patagônia Central, Chile. Foram analisados registros de perfilador de fundo e subfundo 3,5 kHz e modelos submarinos 3D de sete fiordes adjacentes ao campo de gelo Patagônico Sul (Eyre, Falcon, Penguin, Europa Peel, Calvo e Amalia) e parte do canal Icy. Os registros, com cerca de 300 km de levantamento acústico, foram obtidos pelo Servicio Hidrográfico y Oceanográfico de la Armada de Chile (SHOA), durante o cruzeiro de investigação científica Campo de Hielo Sur, realizado em 1995. Foram identificadas as principais fácies acústicas e geoformas sedimentares. A morfologia submarina e das bacias subaéreas adjacentes foi analisada com a elaboração de modelos tridimensionais subaéreos e submarinos e de perfis batimétricos longitudinais a partir de cartas náuticas, também do SHOA. Foram utilizadas imagens Landsat ETM+ na interpretação da geomorfologia glacial da área de entorno subaérea dos fiordes. O eixo longitudinal dos fiordes exibe morfologia irregular com bacias profundas e mostra fácies acústicas associadas ao sistema de depósitos de zonas de linha de encalhe (grounding line), às línguas de gelos flutuantes, e aos icebergs e ao gelo marinho. Refletores acústicos distinguem duas fácies principais, segundo sua configuração interna e geometria externa: caóticas e estratificadas. A geometria dos depocentros e as características dos refletores acústicos indicam a importante influência da batimetria e da topografia pré-existentes na dinâmica das geleiras e nos conseqüentes processos de sedimentação. Devido às grandes profundidades das bacias, as frentes das geleiras poderiam ser flutuantes ou aterradas ao fundo marinho. Em todo o caso, predomina um regime glacial onde o gelo está perto do ponto de fusão. É sugerido que os fiordes estudados resultam de um continuum de formas e de processos, que vão dos lineamentos e sistemas de falhas pré-existentes e controlados tectonicamente desde o Mioceno Inferior (ca. 25 milhões de anos AP), processos de denudação fluvial e de vertentes, vales fluviais modificados glacialmente e, finalmente, canais e fiordes erodidos pela ação do gelo. A tectônica originou uma topografia favorável para o desenvolvimento das geleiras, ocorreram processos de retroalimentação positiva entre aumento o da precipitação e expansão do campo de gelo no lado oeste da cordilheira. Provavelmente, as geleiras durante o Último Máximo Glacial não foram suficientemente espessas para aprofundar os fiordes, tampouco para dragar seus depósitos sedimentares para fora deles. Os processos de deposição de sedimentos caóticos acusticamente visíveis ocorreram durante o recuo das geleiras, já no Holoceno, onde elas alcançaram pontos de estabilidade, ajudadas pela morfologia dos fiordes, mesmo em águas profundas. Os depósitos estratificados localizados nas bacias intra-sills e em maiores profundidades, por sua vez, tiveram sua origem, provavelmente, das partes flutuantes do gelo, onde predominam os processos de desprendimento de icebergs (calving) e também do gelo marinho. Nessas mesmas bacias, depósitos mais profundos, não visíveis ao sistema de alta-resolução, poderiam estar preservados no fundo, pois não foram erodidos pelos sucessivos ciclos de avanço e recuo das geleiras, contendo assim informações sobre a evolução do campo de gelo ao longo do Quaternário.

Carta de Aptidão para a implantação de rodovias e avaliação de alternativas de traçado com uso de geotecnologias

This study discuss the use of the geotechnologies to aid the planners on the terrain aptness definition for highways implantation and on the different trace evaluation to the extention of the Governador Carvalho Pinto highway, between Taubaté-SP and Aparecida do Norte-SP. Fratures on the area were mapping using Landsat ETM+, band Pan. In order to elaborate the phisical aptness chart for highway implantation was used the Analitical Hierarchy Process (AHP) operation, in on geographical information system (GIS). Using GIS were realized a ponderate middle with the soils, rocks, relief, slope, fractures and land use/cover maps. Using this physical aptness chart and joinning it with urban and restrict areas (that was inserted by the Boolean operation), were obtained a viability chart for highway implantation. Based on it were proposed three aleatory traces for the Carvalho Pinto highway. This traces were evaluated with the cross tabulation operation. The integration of the restrict areas, land use and phisical aptness in digital media can offer for the planners the cartography of the viability for the highway implantation. The evaliation of these three traces, based on the viability chart, can subsidyse the decision by the planners.

Reconhecimento e mapeamento dos ambientes costeiros para geração de mapas de ISA ao derramamento de óleo, Amazônia oriental

Acidentes relacionados ao transporte de petróleo constituem uma ameaça às zonas costeiras de todo o mundo, pois se trata de um evento ecologicamente desastroso podendo causar sérios danos ao meio ambiente. Na costa nordeste do Pará ocorre intenso fluxo de navios e balsas transportando petróleo e derivados, daí a necessidade de estabelecer estratégias de prevenção e gestão dos impactos ambientais ao derrame de óleo para elaboração de planos de emergência. O objetivo deste trabalho é gerar o mapa dos ambientes costeiros e o mapa de índice de sensibilidade ambiental ao derrame de óleo dos ambientes costeiros de uma porção da costa nordeste do Pará. A metodologia consistiu no processamento digital de imagens Landsat ETM+7, associadas aos dados do MDE do SRTM (shuttle radar topography mission) e aos dados de campo, em ambiente de SIG (sistema de informação geográfica). Os resultados permitiram o reconhecimento e a descrição de cinco unidades geomorfológicas e de ambientes sedimentares; identificação e hierarquização de nove índices de sensibilidade ambiental (ISA); além da geração do mapa de índice de sensibilidade ambiental ao derramamento de óleo. As técnicas de sensoriamento remoto e SIG mostraram ser importantes ferramentas no reconhecimento dos ambientes costeiros e geração dos mapas propostos.

Multitemporal assessment of the geomorphologic evolution of the Restinga of Marambaia, Rio de Janeiro, Brazil

The Restinga of Marambaia is an emerged sand bar located between the Sepetiba Bay and the South Atlantic Ocean, on the south-east coast of Brazil. The objective of this study was to observe the geomorphologic evolution of the coastal zone of the Restinga of Marambaia using multitemporal satellite images acquired by multisensors from 1975 to 2004. The images were digitally segmented by a region growth algorithm and submitted to an unsupervised classification procedure (ISOSEG) followed by a raster edit based on visual interpretation. The image time-series showed a general trend of decrease in the total sand bar area with values varying from 80.61km(2) in 1975 to 78.15km(2) in 2004. The total area calculation based on the 1975 and 1978 Landsat MSS data was shown to be super-estimated in relation to the Landsat TM, Landsat ETM+, and CBERS-2 CCD data. These differences can also be associated to the relatively poorer spatial resolution of the MSS data, nominally 79m, against the 20m of the CCD data and 30m of the TM and ETM+ data. For the estimates of the width in the central portion of the sand bar the variation was from 158m (1975) to 100m (2004). The formation of a spit in the northern region of the study area was visually observed. The area of the spit was estimated, with values varying from 0.82km(2) (1975) to 0.55km(2) (2004).

A comparison of pixel and object-based land cover classification. A case study of the Asmara region, Eritrea

In this paper we compare the performance of two image classification paradigms (object- and pixel-based) for creating a land cover map of Asmara, the capital of Eritrea and its surrounding areas using a Landsat ETM+ imagery acquired in January 2000. The image classification methods used were maximum likelihood for the pixel-based approach and Bhattacharyya distance for the object-oriented approach available in, respectively, ArcGIS and SPRING software packages. Advantages and limitations of both approaches are presented and discussed. Classifications outputs were assessed using overall accuracy and Kappa indices. Pixel- and object-based classification methods result in an overall accuracy of 78% and 85%, respectively. The Kappa coefficient for pixel- and object-based approaches was 0.74 and 0.82, respectively. Although pixel-based approach is the most commonly used method, assessment and visual interpretation of the results clearly reveal that the object-oriented approach has advantages for this specific case-study.

Central Darfur

The present map sheet is one of two overview maps of the Darfur Map Series Release II (1:500'000). Map features, composed of six field maps 1:250'000, were slightly generalised and referenced to Landsat ETM+ data. The maps and the geodatabase were preparded by the Centre for Development and Environment (CDE) of the University of Berne with funding from the Swiss Federal Department of Foreign Affairs. The map is being released as a technical contribution to support the humanitarian, peace-keeping and reconstruction efforts in Darfur, Western Sudan.

Glacial geomorphology of the Altai and Western Sayan Mountains, Central Asia

In this article, we present a map of the glacial geomorphology of the Altai andWestern Sayan Mountains, covering an area of almost 600,000 km2. Although numerous studies provide evidence for restricted Pleistocene glaciations in this area, others have hypothesized the past existence of an extensive ice sheet. To provide a framework for accurate glacial reconstructions of the Altai and Western Sayan Mountains, we present a map at a scale of 1:1,000,000 based on a mapping from 30 m resolution ASTER DEM and 15 m/30 mresolution Landsat ETM+ satellite imagery. Four landform classes have been mapped: marginal moraines, glacial lineations, hummocky terrain, and glacial valleys. Our mapping reveals an abundance of glacial erosional and depositional landforms. The distribution of these glacial landforms indicates that the Altai and Western Sayan Mountains have experienced predominantly alpine-style glaciations, with some small ice caps centred on the higher mountain peaks. Large marginal moraine complexes mark glacial advances in intermontane basins. By tracing the outer limits of present-day glaciers, glacial valleys, and moraines, we estimate that the past glacier coverage have totalled to 65,000 km2 (10.9% of the mapped area), whereas present-day glacier coverage totals only 1300 km2 (0.2% of the mapped area). This demonstrates the usefulness of remote sensing techniques for mapping the glacial geomorphology in remote mountain areas and for quantifying the past glacier dimensions. The glacial geomorphological map presented here will be used for further detailed reconstructions of the paleoglaciology and paleoclimate of the region.

The integration of multi-source data to improve the classification of remotely sensed images

The number of remote sensing platforms and sensors rises almost every year, yet much work on the interpretation of land cover is still carried out using either single images or images from the same source taken at different dates. Two questions could be asked of this proliferation of images: can the information contained in different scenes be used to improve the classification accuracy and, what is the best way to combine the different imagery? Two of these multiple image sources are MODIS on the Terra platform and ETM+ on board Landsat7, which are suitably complementary. Daily MODIS images with 36 spectral bands in 250-1000 m spatial resolution and seven spectral bands of ETM+ with 30m and 16 days spatial and temporal resolution respectively are available. In the UK, cloud cover may mean that only a few ETM+ scenes may be available for any particular year and these may not be at the time of year of most interest. The MODIS data may provide information on land cover over the growing season, such as harvest dates, that is not present in the ETM+ data. Therefore, the primary objective of this work is to develop a methodology for the integration of medium spatial resolution Landsat ETM+ image, with multi-temporal, multi-spectral, low-resolution MODIS \Terra images, with the aim of improving the classification of agricultural land. Additionally other data may also be incorporated such as field boundaries from existing maps. When classifying agricultural land cover of the type seen in the UK, where crops are largely sown in homogenous fields with clear and often mapped boundaries, the classification is greatly improved using the mapped polygons and utilising the classification of the polygon as a whole as an apriori probability in classifying each individual pixel using a Bayesian approach. When dealing with multiple images from different platforms and dates it is highly unlikely that the pixels will be exactly co-registered and these pixels will contain a mixture of different real world land covers. Similarly the different atmospheric conditions prevailing during the different days will mean that the same emission from the ground will give rise to different sensor reception. Therefore, a method is presented with a model of the instantaneous field of view and atmospheric effects to enable different remote sensed data sources to be integrated.

Separabilidade espectral das coberturas de cana-de-açúcar e de pastagem na Mesorregião do Leste Alagoano.

As imagens de satélite constituem o material básico mais utilizado para o mapeamento da cobertura vegetal. No entanto, a localização, o número de bandas e a época do imageamento influenciam na diferenciação de classes de cobertura. Tal fato se aplica à distinção entre classes de cobertura com características espectrais parecidas como é o caso das áreas com cobertura de cana-de-açúcar e de pastagem. O objetivo deste trabalho foi verificar a possibilidade de distinção dessas classes a partir de imagens dos sensores Landsat TM e ETM+ e do sensor CCD-CBERS obtidas nos períodos chuvoso e seco. O estudo foi realizado na região úmida do Estado de Alagoas. As coberturas de cana- de- açúcar e de pastagem foram obtidas no contexto do mapeamento do uso e da cobertura das terras de Alagoas, como parte do projeto de zoneamento agroecológico. Utilizou-se a classificação supervisionada pelo método da máxima verossimilhança. A separabilidade espectral das classes foi avaliada pelo método da divergência transformada. A presença de bandas sensíveis aos teores de umidade da planta na região do espectro do infravermelho médio nos sensores Landsat TM e ETM+ possibilitou a separação das duas classes em imagens da época seca. Nas imagens da época úmida a resposta espectral da cana-de-açúcar e da pastagem foi semelhante em todas as bandas desses sensores. A ausência de bandas nesta região do espectro para o sensor CBERS impede a diferenciação desses alvos.

Biomassa nas florestas de caatinga nas microrregiões do Seridó Oriental (RN) e Seridó Ocidental (PB).

A remoção parcial ou total da vegetação de caatinga provoca redução na produção de biomassa aérea afetando a cobertura dos solos e aumentando os riscos de degradação das terras do semiárido nordestino. O objetivo deste trabalho foi avaliar a biomassa aérea da caatinga arbustiva e arbórea das microrregiões do Seridó Oriental (RN) e Seridó Ocidental Paraibano. Foram utilizadas imagens do sensor Landsat ETM+, mosaicadas e realçadas utilizando-se o índice de vegetação da diferença normalizada (IVDN). Na estimativa da fitomassa foram utilizadas equações obtidas em trabalhos anteriores que relacionam a biomassa aérea da caatinga com o IVDN. A fitomassa aérea total foi estimada em 4,51 x 107 Mg, com uma média de 9 Mg ha-1. Esta média é extremamente baixa quando comparada aos valores encontrados por outro autores para outras áreas de caatinga. Cerca de 60% da área apresenta valor de produtividade de fitomassa aérea menor que 10 Mg ha-1 e 12% da área tem produtividade média inferior a 5 Mg ha-1. Observações de campo relacionadas à remoção do solo por erosão mostraram que essas áreas estiveram associadas a severos problemas de degradação.

Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images

Algae bloom is one of the major consequences of the eutrophication of aquatic systems, including algae capable of producing toxic substances. Among these are several species of cyanobacteria, also known as blue-green algae, that have the capacity to adapt themselves to changes in the water column. Thus, the horizontal distribution of cyanobacteria harmful algae blooms (CHABs) is essential, not only to the environment, but also for public health. The use of remote sensing techniques for mapping CHABs has been explored by means of bio-optical modeling of phycocyanin (PC), a unique inland waters cyanobacteria pigment. However, due to the small number of sensors with a spectral band of the PC absorption feature, it is difficult to develop semi-analytical models. This study evaluated the use of an empirical model to identify CHABs using TM and ETM+ sensors aboard Landsat 5 and 7 satellites. Five images were acquired for applying the model. Besides the images, data was also collected in the Guarapiranga Reservoir, in São Paulo Metropolitan Region, regarding the cyanobacteria cell count (cells/mL), which was used as an indicator of CHABs biomass. When model values were analyzed excluding calibration factors for temperate lakes, they showed a medium correlation (R²=0.81, p=0.036), while when the factors were included the model showed a high correlation (R²=0.96, p=0.003) to the cyanobacteria cell count. The empirical model analyzed proved useful as an important tool for policy makers, since it provided information regarding the horizontal distribution of CHABs which could not be acquired from traditional monitoring techniques.

A comparison for a multiscale study of structural lineaments in southern Brazil: LANDSAT-7 ETM+ and shaded relief images from SRTM3-DEM

This paper presents a comparison of descriptive statistics obtained for brittle structural lineaments extracted manually from LANDSAT images and shaded relief images from SRTM 3 DEM at 1:100, 000 and 1:500, 000 scales. The selected area is located in the southern of Brazil and comprises Precambrian rocks and stratigraphic units of the Paraná Basin. The application of this methodology shows that the visual interpretation depends on the kind of remote sensing image. The resulting descriptive statistics obtained for lineaments extracted from the images do not follow the same pattern according to the scale adopted. The main direction obtained for Proterozoic rocks using both image types at a 1:500, 000 scale are close to NS±10, whereas at a 1:100, 000 scale N45E was obtained for shaded relief images from SRTM 3 DEM and N10W for LANDSAT images. The Paleozoic sediments yielded the best results for the different images and scales (N50W). On the other hand, the Mesozoic igneous rocks showed greatest differences, the shaded relief images from SRTM 3 DEM images highlighting NE structures and the LANDSAT images highlighting NW structures. The accumulated frequency demonstrated high similarity between products for each image type no matter the scale, indicating that they can be used in multiscale studies. Conversely, major differences were found when comparing data obtained using shaded relief images from SRTM 3 DEM and Landsat images at a 1:100, 000 scale.

Mapping indicators of riparian vegetation health using IKONOS and Landsat-7 ETM+ image data in Australian tropical savannas

Government agencies responsible for riparian environments are assessing the utility of remote sensing for mapping and monitoring environmental health indicators. The objective of this work was to evaluate IKONOS and Landsat-7 ETM+ imagery for mapping riparian vegetation health indicators in tropical savannas for a section of Keelbottom Creek, Queensland, Australia. Vegetation indices and image texture from IKONOS data were used for estimating percentage canopy cover (r2=0.86). Pan-sharpened IKONOS data were used to map riparian species composition (overall accuracy=55%) and riparian zone width (accuracy within 4 m). Tree crowns could not be automatically delineated due to the lack of contrast between canopies and adjacent grass cover. The ETM+ imagery was suited for mapping the extent of riparian zones. Results presented demonstrate the capabilities of high and moderate spatial resolution imagery for mapping properties of riparian zones, which may be used as riparian environmental health indicators

The Lena River Delta - Land cover classification of tundra environments based on Landsat 7 ETM+ data and its application for upscaling of methane emissions

The Lena River Delta, situated in Northern Siberia (72.0 - 73.8° N, 122.0 - 129.5° E), is the largest Arctic delta and covers 29,000 km**2. Since natural deltas are characterised by complex geomorphological patterns and various types of ecosystems, high spatial resolution information on the distribution and extent of the delta environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was conducted and used for the quantification of methane emissions from the delta ecosystems on the regional scale. The applied supervised minimum distance classification was very effective with the few ancillary data that were available for training site selection. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena Delta was calculated with 10.35 mg CH4/m**2/d. Taking our multi-scale approach into account we find that the methane source strength of certain tundra wetland types is lower than calculated previously on coarser scales.