Assessment of relationships between precipitation and satellite derived vegetation condition in South Australia

The normalised difference vegetation index (NDVI) has evolved as a primary tool for monitoring continental-scale vegetation changes and interpreting the impact of short to long-term climatic events on the biosphere. The objective of this research was to assess the nature of relationships between precipitation and vegetation condition, as measured by the satellite-derived NDVI within South Australia. The correlation, timing and magnitude of the NDVI response to precipitation were examined for different vegetation formations within the State (forest, scrubland, shrubland, woodland and grassland). Results from this study indicate that there are strong relationships between precipitation and NDVI both spatially and temporally within South Australia. Differences in the timing of the NDVI response to precipitation were evident among the five vegetation formations. The most significant relationship between rainfall and NDVI was within the forest formation. Negative correlations between NDVI and precipitation events indicated that vegetation green-up is a result of seasonal patterns in precipitation. Spatial patterns in the average NDVI over the study period closely resembled the boundaries of the five classified vegetation formations within South Australia. Spatial variability within the NDVI data set over the study period differed greatly between and within the vegetation formations examined depending on the location within the state. ACRONYMS AVHRR Advanced Very High Resolution Radiometer ENVSAEnvironments of South Australia EOS Terra-Earth Observing System EVIEnhanced Vegetation Index MODIS Moderate Resolution Imaging Spectro-radiometer MVC Maximum Value Composite NDVINormalised Difference Vegetation Index NIRNear Infra-Red NOAANational Oceanic and Atmospheric Administration SPOT Systeme Pour l’Observation de la Terre. [ABSTRACT FROM AUTHOR]

Remote Sensing of Vegetation Change Across a Latitudinal Gradient in the Canadian Arctic

Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.

Evaluation of vegetation recovery after fire: a case study in Calde, central region of Portugal

Remote Sensing has been used for decades, and more and more applications are added to its repertoire. With this study we aim to show the use of Remote Sensing in the field of vegetation recovery monitoring in burned areas and the added value of data with a high spatial resolution. This was done by analysing both Landsat 7 and 8 scenes, after the forest fire of summer 2012 in the parish of Calde, in the central region of Portugal, as well as an orthophoto produced with images acquired by an unmanned aerial vehicle.

Above ground biomass functions with vegetation indices for multiple use systems of two evergreen oaks

Remote sensing is a promising approach for above ground biomass estimation, as forest parameters can be obtained indirectly. The analysis in space and time is quite straight forward due to the flexibility of the method to determine forest crown parameters with remote sensing. It can be used to evaluate and monitoring for example the development of a forest area in time and the impact of disturbances, such as silvicultural practices or deforestation. The vegetation indices, which condense data in a quantitative numeric manner, have been used to estimate several forest parameters, such as the volume, basal area and above ground biomass. The objective of this study was the development of allometric functions to estimate above ground biomass using vegetation indices as independent variables. The vegetation indices used were the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Simple Ratio (SR) and Soil-Adjusted Vegetation Index (SAVI). QuickBird satellite data, with 0.70 m of spatial resolution, was orthorectified, geometrically and atmospheric corrected, and the digital number were converted to top of atmosphere reflectance (ToA). Forest inventory data and published allometric functions at tree level were used to estimate above ground biomass per plot. Linear functions were fitted for the monospecies and multispecies stands of two evergreen oaks (Quercus suber and Quercus rotundifolia) in multiple use systems, montados. The allometric above ground biomass functions were fitted considering the mean and the median of each vegetation index per grid as independent variable. Species composition as a dummy variable was also considered as an independent variable. The linear functions with better performance are those with mean NDVI or mean SR as independent variable. Noteworthy is that the two better functions for monospecies cork oak stands have median NDVI or median SR as independent variable. When species composition dummy variables are included in the function (with stepwise regression) the best model has median NDVI as independent variable. The vegetation indices with the worse model performance were EVI and SAVI.

Perfis temporais NDVI MODIS, na cana-soca, de maturação tardia

This paper describes the development of a relational database and a tool for viewing MODIS NDVI temporal profile, using data from MOD09Q1 product, specifically the surface bidirectional reflectance factor relative to the RED and NIR wavelength, mosaic of 8-day temporal composition, and the quality band, in sugarcane fields in the state of São Paulo, for analysis of the late stubble-cane maturation. From sugarcane farms were obtained the historical data about yield, soil, variety, location of the each pixel for each subregion monitored. All data were integrated in a database developed in PostgreSQL. The tool was implemented using Java language and allowed a fast and automatic way of analyzing sugarcane phenological patterns. It concluded that the MODIS NDVI temporal profile using data from MOD09Q1 product is able to subsidize the monitoring of phenological changes in the sugarcane.

Spatial patterns of malaria in a land reform colonization project, Juruena municipality, Mato Grosso, Brazil

Background: In Brazil, 99% of malaria cases are concentrated in the Amazon, and malaria's spatial distribution is commonly associated with socio-environmental conditions on a fine landscape scale. In this study, the spatial patterns of malaria and its determinants in a rural settlement of the Brazilian agricultural reform programme called ""Vale do Amanhecer"" in the northern Mato Grosso state were analysed. Methods: In a fine-scaled, exploratory ecological study, geocoded notification forms corresponding to malaria cases from 2005 were compared with spectral indices, such as the Normalized Difference Vegetation Index (NDVI) and the third component of the Tasseled Cap Transformation (TC_3) and thematic layers, derived from the visual interpretation of multispectral TM-Landsat 5 imagery and the application of GIS distance operators. Results: Of a total of 336 malaria cases, 102 (30.36%) were caused by Plasmodium falciparum and 174 (51.79%) by Plasmodium vivax. Of all the cases, 37.6% (133 cases) were from residents of a unique road. In total, 276 cases were reported for the southern part of the settlement, where the population density is higher, with notification rates higher than 10 cases per household. The local landscape mostly consists of open areas (38.79 km(2)). Training forest occupied 27.34 km(2) and midsize vegetation 7.01 km(2). Most domiciles with more than five notified malaria cases were located near areas with high NDVI values. Most domiciles (41.78%) and malaria cases (44.94%) were concentrated in areas with intermediate values of the TC_3, a spectral index representing surface and vegetation humidity. Conclusions: Environmental factors and their alteration are associated with the occurrence and spatial distribution of malaria cases in rural settlements.

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.

Lignin phenols used to infer organic matter sources to Sepetiba Bay - RJ, Brasil

Lignin phenols were measured in the sediments of Sepitiba Bay, Rio de Janeiro, Brazil and in bedload sediments and suspended sediments of the four major fluvial inputs to the bay: Sao Francisco and Guandu Channels and the Guarda and Cacao Rivers. Fluvial suspended lignin yields (Sigma 8 3.5-14.6 mgC 10 g dw(-1)) vary little between the wet and dry seasons and are poorly correlated with fluvial chlorophyll concentrations (0.8-50.2 mu gC L(-1)). Despite current land use practices that favor grassland agriculture or industrial uses, fluvial lignin compositions are dominated by a degraded leaf-sourced material. The exception is the Guarda River, which has a slight influence from grasses. The Lignin Phenol Vegetation Index, coupled with acid/aldehyde and 3.5 Db/V ratios, indicate that degraded leaf-derived phenols are also the primary preserved lignin component in the bay. The presence of fringe Typha sp. and Spartina sp. grass beds surrounding portions of the Bay are not reflected in the lignin signature. Instead, lignin entering the bay appears to reflect the erosion of soils containing a degraded signature from the former Atlantic rain forest that once dominated the watershed, instead of containing a significant signature derived from current agricultural uses. A three-component mixing model using the LPVI, atomic N:C ratios, and stable carbon isotopes (which range between -26.8 and -21.8 parts per thousand) supports the hypothesis that fluvial inputs to the bay are dominated by planktonic matter (78% of the input), with lignin dominated by leaf (14% of the input) over grass (6%). Sediments are composed of a roughly 50-50 mixture of autochthonous material and terrigenous material, with lignin being primarily sourced from leaf. (C) 2010 Elsevier Ltd. All rights reserved.

MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass

The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m(3)/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. (C) 2011 Elsevier Inc. All rights reserved.

Integração de imagens NOAA/AVHRR: rede de cooperação para monitoramento nacional da safra de soja

Uma avaliação inicial das condições do desenvolvimento da safra nacional, enquanto as plantas ainda estão nos campos, é altamente necessária para o cálculo correto das projeções na tomada de decisão e políticas relacionadas com o planejamento governamental e segurança alimentar. O objetivo deste trabalho foi avaliar a adequação dos dados NOAA/AVHRR (National Oceanic and Atmospheric Administration / Advanced Very High Resolution Radiometer) em detectar mudanças nas condições da vegetação, devidas à ocorrência de estresse hídrico, na soja, por meio de uma combinação do índice NDVI (Normalized Difference Vegetation Index) e da LST (Land Surface Temperature). Os dados LST e NDVI foram combinados e comparados pixel a pixel, sobre uma área de cultivo de soja, no Rio Grande do Sul. A relação teórica inversa prevista na combinação de LST e NDVI foi detectada. Foi observado que ocorre um aumento médio na LST em uma safra de ciclo normal (de 301,02 K para 308,36 K), quando comparada a uma safra sob condição de estresse hídrico, no desenvolvimento da cultura. Uma redução média do NDVI foi observada no ciclo normal (de 0,65 para 0,53), comparada com uma safra sob efeitos ocasionados pela estiagem no desenvolvimento da cultura. Foi observado maior correlação da produtividade municipal com LST (R2=0,78) do que com o NDVI (R2 = 0,59). Os resultados obtidos indicam que a integração de imagens do sensor AVHRR, proveniente de diferentes instituições, proporciona a adequada combinação espacial e temporal dos dados LST e NDVI, a fim de detectar a ocorrência de estresse hídrico, bem como sua intensidade, caracterizando as condições do ciclo de desenvolvimento da soja.

Análise dos impactos das mudanças do uso do solo na futura gestão e conservação da Reserva da Chimanimani - Moçambique

Dissertação de Mestrado, Gestão e Conservação da Natureza, 27 de Outubro de 2015, Universidade dos Açores.

Integrated analysis of climate, soil, topography and vegetative growth in Iberian viticultural regions

The Iberian viticultural regions are convened according to the Denomination of Origin (DO) and present different climates, soils, topography and management practices. All these elements influence the vegetative growth of different varieties throughout the peninsula, and are tied to grape quality and wine type. In the current study, an integrated analysis of climate, soil, topography and vegetative growth was performed for the Iberian DO regions, using state-of-the-art datasets. For climatic assessment, a categorized index, accounting for phenological/thermal development, water availability and grape ripening conditions was computed. Soil textural classes were established to distinguish soil types. Elevation and aspect (orientation) were also taken into account, as the leading topographic elements. A spectral vegetation index was used to assess grapevine vegetative growth and an integrated analysis of all variables was performed. The results showed that the integrated climate-soil-topography influence on vine performance is evident. Most Iberian vineyards are grown in temperate dry climates with loamy soils, presenting low vegetative growth. Vineyards in temperate humid conditions tend to show higher vegetative growth. Conversely, in cooler/warmer climates, lower vigour vineyards prevail and other factors, such as soil type and precipitation acquire more important roles in driving vigour. Vines in prevailing loamy soils are grown over a wide climatic diversity, suggesting that precipitation is the primary factor influencing vigour. The present assessment of terroir characteristics allows direct comparison among wine regions and may have great value to viticulturists, particularly under a changing climate.

Detecção automática de alterações do coberto florestal com imagens de satélite de grande e muito grande resolução espacial

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Utilização de imagem LISS III para análise de espaços verdes em Lisboa

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Leishmaniasis transmission: distribution and coarse-resolution ecology of two vectors and two parasites in Egypt

Introduction: In past decades, leishmaniasis burden has been low across Egypt; however, changing environment and land use has placed several parts of the country at risk. As a consequence, leishmaniasis has become a particularly difficult health problem, both for local inhabitants and for multinational military personnel. Methods: To evaluate coarse-resolution aspects of the ecology of leishmaniasis transmission, collection records for sandflies and Leishmania species were obtained from diverse sources. To characterize environmental variation across the country, we used multitemporal Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for 2005-2011. Ecological niche models were generated using MaxEnt, and results were analyzed using background similarity tests to assess whether associations among vectors and parasites (i.e., niche similarity) can be detected across broad geographic regions. Results: We found niche similarity only between one vector species and its corresponding parasite species (i.e., Phlebotomus papatasi with Leishmania major), suggesting that geographic ranges of zoonotic cutaneous leishmaniasis and its potential vector may overlap, but under distinct environmental associations. Other associations (e.g., P. sergenti with L. major) were not supported. Mapping suitable areas for each species suggested that northeastern Egypt is particularly at risk because both parasites have potential to circulate. Conclusions: Ecological niche modeling approaches can be used as a first-pass assessment of vector-parasite interactions, offering useful insights into constraints on the geography of transmission patterns of leishmaniasis.