ANALYSE THE VULNERABILITY IN THE MARANHÃO ILHA, BRAZIL, USING GIS TECHNIQUES AND GEOSPATIAL INFERENCE

Vulnerability and sustainability studies of an area help to assess both its level of exposure and capacity to support possible environmental impacts, and it is of primordial importance for proposals of the Legislation on Zoning, Allotment, Land Use/land cover, aiming to stimulate those areas indicated for urban growth, to discourage growth of overcrowded areas, to detect sections with restrictive use, as well as districts for permanent protection. This paper aims to analyze the vulnerability in the Maranhão Ilha, using GIS techniques, geospatial inference intersected with relevant social-environmental indicators.Estudos de vulnerabilidade e de sustentabilidade de uma área ajudam a avaliar o seu grau de exposição e sua capacidade de suporte a possíveis impactos ambientais, sendo fundamental para propostas de Lei de Zoneamento, Parcelamento, Uso e Ocupação do Solo, tendo por finalidade orientar as áreas onde deverá haver estímulo para o crescimento urbano; contenção da malha urbana; detecção de locais com possibilidade de uso restritivo, bem como locais de proteção permanente. Este trabalho propõe analisar o índice de vulnerabilidade a perda de solo da Ilha do Maranhão com base na metodologia proposta por (CREPANI, et al. 2001) e em técnicas de inferência espacial com apoio na AHP (Análise Hierárquica de Processo).

Field-oriented assessment of agricultural crops through temporal segmentation of modis VI data.

Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.

Earth, sea and sky, or, Marvels of the universe : being a full and graphic description of all that is wonderful in every continent of the globe, in the world of waters and the starry heavens; containing thrilling adventures on land and sea ...; embracing the striking physical features of the earth, the peculiar characteristics of the human race, of animals, birds, insects, etc., including a vivid description of the Atlantic, Pacific and Indian oceans and of the polar seas ...; together with the amazing phenomena of the solar and starry systems; the whole comprising a vast treasury of all that is marvelous and wonderful in the earth, sea, air, and skies /

Binding: blue cover, intricate illustrations in red and gilt on front cover and spine, marbled edges, floral endpapers

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Finland: the land of a thousand lakes a new holiday resort - [Cover]

Helsinki : The tourist society in Finland 1909 : Hull
Tarkemmat teoskuvat osoitteessa http://urn.fi/URN:NBN:fi-fd2011-pp00001592

An Intercomparison of Regional Atmospheric Circulation and the Melt Season Loss of Arctic Snow Cover and Sea Ice Extent Across the Land-Ocean Boundary

This study is designed to compare the monthly continental snow cover and sea ice extent loss in the Arctic with regional atmospheric conditions including: mean sea level pressure, 925 hPa air temperature, and mean wind direction among others during the melt season (March-August) over the 29-year study period 1979-2007. Little research has gone into studying the concurrent variations in the annual loss of continental snow cover and sea ice extent across the land-ocean boundary, since these data are largely stored in incompatible formats. However, the analysis of these data, averaged spatially over three autonomous study regions located in Siberia, North America, and Western Russia, reveals a distinct difference in the response of snow and sea ice to the atmospheric forcing. On average, sea ice extent is lost earlier in the year, in May, than snow cover, in June, although Arctic sea ice is located farther north than continental snow in all three study regions. Once the loss of snow and ice extent begins, snow cover is completely removed sooner than sea ice extent, even though ice loss begins earlier in the melt season. Further, the analysis of the atmospheric conditions surrounding loss of snow and ice cover over the independent study regions indicates that conditions of cool temperatures with strong northeasterly winds in the later melt season months are effective at removing sea ice cover, likely through ice divergence, as are warmer temperatures via southerly winds directly forcing melt. The results of this study set the framework for further analysis of the direct influence of snow cover loss on later melt season sea ice extents and the predictability of snow and sea ice extent responses to modeled future climate conditions

Land use/cover change using Remote Sensing and Geographic Information Systems : Pic Macaya National Park, Haiti

A post classification change detection technique based on a hybrid classification approach (unsupervised and supervised) was applied to Landsat Thematic Mapper (TM), Landsat Enhanced Thematic Plus (ETM+), and ASTER images acquired in 1987, 2000 and 2004 respectively to map land use/cover changes in the Pic Macaya National Park in the southern region of Haiti. Each image was classified individually into six land use/cover classes: built-up, agriculture, herbaceous, open pine forest, mixed forest, and barren land using unsupervised ISODATA and maximum likelihood supervised classifiers with the aid of field collected ground truth data collected in the field. Ground truth information, collected in the field in December 2007, and including equalized stratified random points which were visual interpreted were used to assess the accuracy of the classification results. The overall accuracy of the land classification for each image was respectively: 1987 (82%), 2000 (82%), 2004 (87%). A post classification change detection technique was used to produce change images for 1987 to 2000, 1987 to 2004, and 2000 to 2004. It was found that significant changes in the land use/cover occurred over the 17- year period. The results showed increases in built up (from 10% to 17%) and herbaceous (from 5% to 14%) areas between 1987 and 2004. The increase of herbaceous was mostly caused by the abandonment of exhausted agriculture lands. At the same time, open pine forest and mixed forest areas lost (75%) and (83%) of their area to other land use/cover types. Open pine forest (from 20% to 14%) and mixed forest (from18 to 12%) were transformed into agriculture area or barren land. This study illustrated the continuing deforestation, land degradation and soil erosion in the region, which in turn is leading to decrease in vegetative cover. The study also showed the importance of Remote Sensing (RS) and Geographic Information System (GIS) technologies to estimate timely changes in the land use/cover, and to evaluate their causes in order to design an ecological based management plan for the park.

Review of literature: pheasant nesting and production and the effect of weather, cover reduction, and agricultural land-use on nesting success.

Colorado Cooperative Wildlife Research Unit, Colorado A. & M College, Fort Collins, Colorado [and] Colorado Game and Fish Department, Denver, Colorado, cooperating.

Assessing the role of Mediterranean evergreen oaks canopy cover in land surface albedo and temperature using a remote sensing-based approach

Modifications in vegetation cover can have an impact on the climate through changes in biogeochemical and biogeophysical processes. In this paper, the tree canopy cover percentage of a savannah-like ecosystem (montado/dehesa) was estimated at Landsat pixel level for 2011, and the role of different canopy cover percentages on land surface albedo (LSA) and land surface temperature (LST) were analysed. A modelling procedure using a SGB machine-learning algorithm and Landsat 5-TM spectral bands and derived vegetation indices as explanatory variables, showed that the estimation of montado canopy cover was obtained with good agreement (R2 = 78.4%). Overall, montado canopy cover estimations showed that low canopy cover class (MT_1) is the most representative with 50.63% of total montado area. MODIS LSA and LST products were used to investigate the magnitude of differences in mean annual LSA and LST values between contrasting montado canopy cover percentages. As a result, it was found a significant statistical relationship between montado canopy cover percentage and mean annual surface albedo (R2 = 0.866, p < 0.001) and surface temperature (R2 = 0.942, p < 0.001). The comparisons between the four contrasting montado canopy cover classes showed marked differences in LSA (χ2 = 192.17, df = 3, p < 0.001) and LST (χ2 = 318.18, df = 3, p < 0.001). The highest montado canopy cover percentage (MT_4) generally had lower albedo than lowest canopy cover class, presenting a difference of −11.2% in mean annual albedo values. It was also showed that MT_4 and MT_3 are the cooler canopy cover classes, and MT_2 and MT_1 the warmer, where MT_1 class had a difference of 3.42 °C compared with MT_4 class. Overall, this research highlighted the role that potential changes in montado canopy cover may play in local land surface albedo and temperature variations, as an increase in these two biogeophysical parameters may potentially bring about, in the long term, local/regional climatic changes moving towards greater aridity.

The Amazon Frontier of Land-Use Change: Croplands and Consequences for Greenhouse Gas Emissions

The Brazilian Amazon is one of the most rapidly developing agricultural frontiers in the world. The authors assess changes in cropland area and the intensification of cropping in the Brazilian agricultural frontier state of Mato Grosso using remote sensing and develop a greenhouse gas emissions budget. The most common type of intensification in this region is a shift from single-to double-cropping patterns and associated changes in management, including increased fertilization. Using the enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, the authors created a green-leaf phenology for 2001-06 that was temporally smoothed with a wavelet filter. The wavelet-smoothed green-leaf phenology was analyzed to detect cropland areas and their cropping patterns. The authors document cropland extensification and double-cropping intensification validated with field data with 85% accuracy for detecting croplands and 64% and 89% accuracy for detecting single-and double-cropping patterns, respectively. The results show that croplands more than doubled from 2001 to 2006 to cover about 100 000 km(2) and that new double-cropping intensification occurred on over 20% of croplands. Variations are seen in the annual rates of extensification and double-cropping intensification. Greenhouse gas emissions are estimated for the period 2001-06 due to conversion of natural vegetation and pastures to row-crop agriculture in Mato Grosso averaged 179 Tg CO(2)-e yr(-1),over half the typical fossil fuel emissions for the country in recent years.

Using indicators of deforestation and land-use dynamics to support conservation strategies: A case study of central Rondonia, Brazil

In Rondonia State, Brazil, settlement processes have cleared 68,000 km 2 of tropical forests since the 1970s. The intensity of deforestation has differed by region depending on driving factors like roads and economic activities. Different histories of land-use activities and rates of change have resulted in mosaics of forest patches embedded in an agricultural matrix. Yet, most assessments of deforestation and its effects on vegetation, soil and water typically focus on landscape patterns of current conditions, yet historical deforestation dynamics can influence current conditions strongly. Here, we develop and describe the use of four land-use dynamic indicators to capture historical land-use changes of catchments and to measure the rate of deforestation (annual deforestation rate), forest regeneration level (secondary forest mean proportion), time since disturbance (mean time since deforestation) and deforestation profile (deforestation profile curvature). We used the proposed indices to analyze a watershed located in central Rondonia. Landsat TM and ETM+ images were used to produce historical land-use maps of the last 18 years, each even year from 1984 to 2002 for 20 catchments. We found that the land-use dynamics indicators are able to distinguish catchments with different land-use change profiles. Four categories of historical land-use were identified: old and dominant pasture cover on small properties, recent deforestation and dominance of secondary growth, old extensive pastures and large forest remnants and, recent deforestation, pasture and large forest remnants. Knowing historical deforestation processes is important to develop appropriate conservation strategies and define priorities and actions for conserving forests currently under deforestation. (C) 2009 Elsevier B.V. All rights reserved.