Student Number : 0216831W - MSc research report - School of Environmental Sciences - Faculty of Science / This report deals with the relationship between the NDVI obtained from the NOAA AVHRR sensor and that obtained from the MODIS sensor. The relationship is quantitatively assessed for distinct polygons over various land-cover types in the northeastern Kwa-Zulu Natal Province of South Africa. Spatial and temporal variations in the relationships are addressed and discussed with reference to spectral response, sunsensor- target geometries and atmospheric factors. Specifically, various methods are investigated to estimate a MODIS-equivalent NDVI from the AVHRR NDVI and in so doing create the potential to develop a self-consistent NDVI between the historically available AVHRR NDVI dataset and the relatively new MODIS NDVI dataset. NOAA-16 AVHRR NDVI data and AQUA MODIS NDVI data for the two-year period from January 2002 to December 2003 are used to develop the method. A linear relationship exists between the AVHRR and MODIS NDVI. However, spatial variations in the relationship in terms of land-cover and mean NDVI are pointed out. The potential of atmospheric corrections applied to AVHRR data through a radiative transfer atmospheric correction model to improve the relationship between the two NDVI datasets is also investigated. The importance of geo-location accuracy of the AVHRR NDVI dataset is assessed in the light of the accuracy obtainable with the proposed method to estimate a MODIS-equivalent NDVI from the AVHRR NDVI. A method to estimate the MODIS NDVI from the AVHRR NDVI that takes the mean AVHRR NDVI value into account, as opposed to a constant linear relationship over all the points, is proposed. Atmospheric correction is shown not to improve the accuracy of the method in a statistically significant way. The root-mean-square error of the proposed method is in the order of 0.05 NDVI units and varies between 0.5 and 2 standard deviations of the MODIS NDVI over an entire season.

The Caspian Region includes the Caspian Sea and five littoral states: Azerbaijan, Iran, Turkmenistan, Kazakhstan and Russian. 40% of the Caspian coastal zone is arid, 69% of this territory undergone desertification according to international reports. Among the reasons are soil erosion caused by water, wind and irrigation, the salinization of soil, intense bioresources usage, and soil pollution due to oil extraction and production. Desertification is a serious problem, at global, national and local scales. It is important to know what should be sustained or developed in order to protect land from desertification. The generalization of data over desertification processes in Caspian countries, studying the dynamics of this process in space and time could help facilitate measures to counter regional desertification. To understand Caspian Region coastal desertification phenomenon, vegetation cover satellite images for the years 1982 – 2006 were investigated to give map vegetation changes over time. The Normalized Difference Vegetation Index (NDVI) data for this study was derived from the Global Inventory Modeling and Mapping Studies (GIMMS) dataset, with the spatial resolution of 8 km. A coastal strip 160 km from the coast, divided by countries, was investigated. Theanalyses were focused on extent and severity of vegetation cover degradation, and possible causes such as landscape, land use history and culture, climatic changes and policies. The aim was to address questions related to desertification phenomenon, by focusing on Caspian Region time-series of vegetation cover data and investigation patterns of desertification in the region. In this study evidence of land degradation in the Caspian Region countries was found to occur on local scales or sub-national scales rather than across the regional as a whole. Changes in vegetation cover revealed by AVHRR NDVI appeared to be reversible in character and were dependent on the climate conditions, and anthropogenic impact in approximately equal proportions.

Esse trabalho tem como objetivo compreender as relações entre a Land Surface Temperature (LST), Normalized Difference Vegetation Índex (NDVI) e os padrões do uso da terra do município de São Paulo no período de 1985 a 2010. Analisou-se 15 bairros, nos quais foram extraídas 45 amostras aleatórias de diferentes padrões de uso da terra; subdivididas em baixo padrão, médio padrão e médio alto padrão. Com o aporte de geotecnologia, foi feita a extração dos dados das imagens de satélite Landsat 5 (TM) e das Ortofotos do ano de 2010. O comportamento das amostras variou de acordo como os diferentes perfis dos grupos analisados. O grupo de baixo padrão foi o que apresentou as maiores amplitudes térmicas, ausência de arborização urbana atreladas a um baixo padrão construtivo. O grupo de médio padrão é caracterizado pela predominância de área verticalizada e apresenta uma arborização urbana escassa em meio a uma malha urbana consolidada. O grupo de médio alto padrão foi o que mais apresentou arborização urbana, distribuída de forma homogênea na maioria das amostras, portanto foi o grupo que teve baixas amplitudes térmicas e o índice de Normalized Difference Vegetation Index (NDVI) com pouca variação. Os testes mostraram fortes correlações negativas entre as amostras de Land Surface Temperature (LST) e o índice de Normalized Difference Vegetation Index (NDVI), sendo -0,58 em 1985, -0,43 em 2004 e -0,82 em 2010. Os diferentes padrões de uso da terra, relacionados à temperatura de superfície, e o índice de vegetação, aliado à preocupação com o planejamento ambiental, deve resultar na melhoria da qualidade de vida da população. Esta pesquisa faz parte do Projeto Temático processo FAPESP 08/58161 -1, \"Assessment of Impacts and Vulnerability to Climate Change in Brazil and strategies for Adaptation options\", Component 5: Vulnerability of the metropolitan region of São Paulo to climate Change. / This study aims to understand the relationship between Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) and the patterns of land use in the municipality of São Paulo, from 1985 to 2010. A totoal of 45 random samples were extracted from the 15 districts used in this study, with different patterns of land use which were subdivided into three different clases: low-end, middle and middle-high. Geospatial approaches allowed the extraction of satellite image data from Landsat 5 data (TM) and from Orthophotos from 2010. The behavior of the samples varied accordingly to the different group profiles. The low-end group presented the highest thermal amplitudes and more significant absence of urban vegetation linked, both to low urbanization and construction standards. The average standard group is characterized by the predominance of vertical buildings and lacks urban trees amidst a consolidated urban landscape. The average-high standard group displayed the highest concentration of green urban areas, distributed homogeneously in most samples, so this group presented low variations both in temperature amplitude and in the Normalized Difference Vegetation Index (NDVI). The correlation tests showed strong negative correlations between samples of Land Surface Temperature (LST) and the NDVI samples, of -0.58 in 1985, -0.43 in 2004 and -0.82 in 2010. Understanding the relations between the different patterns of land use, surface temperature and the NDVI (with due concern for environmental planning) is an important step in the identification and rehabilitation of enviromentally. This research is part of the Thematic Project FAPESP 08/58161 -1 process, \"Assessment of Impacts and Vulnerability to Climate Change in Brazil and strategies for Adaptation options\", Component 5: Vulnerability of the metropolitan region of São Paulo to climate Change.

Esse trabalho tem como objetivo compreender as relações entre a Land Surface Temperature (LST), Normalized Difference Vegetation Índex (NDVI) e os padrões do uso da terra do município de São Paulo no período de 1985 a 2010. Analisou-se 15 bairros, nos quais foram extraídas 45 amostras aleatórias de diferentes padrões de uso da terra; subdivididas em baixo padrão, médio padrão e médio alto padrão. Com o aporte de geotecnologia, foi feita a extração dos dados das imagens de satélite Landsat 5 (TM) e das Ortofotos do ano de 2010. O comportamento das amostras variou de acordo como os diferentes perfis dos grupos analisados. O grupo de baixo padrão foi o que apresentou as maiores amplitudes térmicas, ausência de arborização urbana atreladas a um baixo padrão construtivo. O grupo de médio padrão é caracterizado pela predominância de área verticalizada e apresenta uma arborização urbana escassa em meio a uma malha urbana consolidada. O grupo de médio alto padrão foi o que mais apresentou arborização urbana, distribuída de forma homogênea na maioria das amostras, portanto foi o grupo que teve baixas amplitudes térmicas e o índice de Normalized Difference Vegetation Index (NDVI) com pouca variação. Os testes mostraram fortes correlações negativas entre as amostras de Land Surface Temperature (LST) e o índice de Normalized Difference Vegetation Index (NDVI), sendo -0,58 em 1985, -0,43 em 2004 e -0,82 em 2010. Os diferentes padrões de uso da terra, relacionados à temperatura de superfície, e o índice de vegetação, aliado à preocupação com o planejamento ambiental, deve resultar na melhoria da qualidade de vida da população. Esta pesquisa faz parte do Projeto Temático processo FAPESP 08/58161 -1, \"Assessment of Impacts and Vulnerability to Climate Change in Brazil and strategies for Adaptation options\", Component 5: Vulnerability of the metropolitan region of São Paulo to climate Change. / This study aims to understand the relationship between Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) and the patterns of land use in the municipality of São Paulo, from 1985 to 2010. A totoal of 45 random samples were extracted from the 15 districts used in this study, with different patterns of land use which were subdivided into three different clases: low-end, middle and middle-high. Geospatial approaches allowed the extraction of satellite image data from Landsat 5 data (TM) and from Orthophotos from 2010. The behavior of the samples varied accordingly to the different group profiles. The low-end group presented the highest thermal amplitudes and more significant absence of urban vegetation linked, both to low urbanization and construction standards. The average standard group is characterized by the predominance of vertical buildings and lacks urban trees amidst a consolidated urban landscape. The average-high standard group displayed the highest concentration of green urban areas, distributed homogeneously in most samples, so this group presented low variations both in temperature amplitude and in the Normalized Difference Vegetation Index (NDVI). The correlation tests showed strong negative correlations between samples of Land Surface Temperature (LST) and the NDVI samples, of -0.58 in 1985, -0.43 in 2004 and -0.82 in 2010. Understanding the relations between the different patterns of land use, surface temperature and the NDVI (with due concern for environmental planning) is an important step in the identification and rehabilitation of enviromentally. This research is part of the Thematic Project FAPESP 08/58161 -1 process, \"Assessment of Impacts and Vulnerability to Climate Change in Brazil and strategies for Adaptation options\", Component 5: Vulnerability of the metropolitan region of São Paulo to climate Change.

Hurricane Hugo struck the coast of South Carolina on September 21, 1989 as a category 4 hurricane on the Saffir-Simpson Scale. Landsat Thematic mapper was utilized to determine the extent of damage experienced at the Santee Experimental Forest (SEF) (a part of Francis Marion National Forest) in South Carolina. Normalized Difference Vegetation Index (NDVI) and the change detection techniques were used to determine initial forest damage and to monitor the recovery over a 22-year period following Hurricane Hugo. According to the results from the NDVI analysis the SEF made a full recovery after a 10-year period. The remote sensing techniques used were effective in identifying the damage as well as the recovery.

The feasibility of using optical sensors and non-nitrogen limiting reference crops to determine post-emergent nitrogen fertilizer requirements of canola was evaluated. Normalized difference vegetation index was well suited for estimating yield potential and nitrogen status. Although sensor-based nitrogen management was generally agronomically feasible for canola, the economic benefits of doing so remain uncertain because of the added cost of applying post-emergent nitrogen. / February 2008

Alluvial groundwater systems are an important source of water for communities and biodiverse riparian corridors throughout the arid and semi-arid Basin and Range Geological Province of western North America. These aquifers and their attendant desert streams have been depleted to support a growing population, while projected climate change could lead to more extreme episodes of drought and precipitation in the future. The only source of replenishment to these aquifers is recharge. This dissertation builds upon previous work to characterize and quantify recharge in arid and semi-arid basins by characterizing the intra-annual seasonality of recharge across the Basin and Range Province, and considering how climate change might impact recharge seasonality and volume, as well as fragile riparian corridors that depend on these hydrologic processes. First, the seasonality of recharge in a basin in the sparsely-studied southern extent of the Basin and Range Province is determined using stable water isotopes of seasonal precipitation and groundwater, and geochemical signatures of groundwater and surface water. In northwestern Mexico in the southern reaches of the Basin and Range, recharge is dominated by winter precipitation (69% ± 42%) and occurs primarily in the uplands. Second, isotopically-based estimates of seasonal recharge fractions in basins across the region are compared to identify patterns in recharge seasonality, and used to evaluate a simple water budget-based model for estimating recharge seasonality, the normalized seasonal wetness index (NSWI). Winter precipitation makes up the majority of annual recharge throughout the region, and North American Monsoon (NAM) precipitation has a disproportionately weak impact on recharge. The NSWI does well in estimating recharge seasonality for basins in the northern Basin and Range, but less so in basins that experience NAM precipitation. Third, the seasonal variation in riparian and non-riparian vegetation greenness, represented by the normalized difference vegetation index (NDVI), is characterized in several of the study basins and climatic and hydrologic controls are identified. Temperature was the most significant driver of vegetation greenness, but precipitation and recharge seasonality played a significant role in some basins at some elevations. Major contributions of this work include a better understanding of recharge in a monsoon-dominated basin, the characterization of recharge seasonality at a regional scale, evaluation of an estimation method for recharge seasonality, and an interpretation of the interaction of seasonal hydrologic processes, vegetation dynamics, and climate change.

No description available.

The feasibility of using optical sensors and non-nitrogen limiting reference crops to determine post-emergent nitrogen fertilizer requirements of canola was evaluated. Normalized difference vegetation index was well suited for estimating yield potential and nitrogen status. Although sensor-based nitrogen management was generally agronomically feasible for canola, the economic benefits of doing so remain uncertain because of the added cost of applying post-emergent nitrogen.

The feasibility of using optical sensors and non-nitrogen limiting reference crops to determine post-emergent nitrogen fertilizer requirements of canola was evaluated. Normalized difference vegetation index was well suited for estimating yield potential and nitrogen status. Although sensor-based nitrogen management was generally agronomically feasible for canola, the economic benefits of doing so remain uncertain because of the added cost of applying post-emergent nitrogen.