The analyses of trends in vegetation dynamics require a profound knowledge of its seasonality. For the determination of the seasonality conventional methods of time series analyses often use a simple averaging of measured values of the identical time in different cycle of the whole time series (e.g. bfast). Then it is assumed that the resulting seasonal portion of a time series is constant and stable for the entire time series. However, analyses of vegetation time series show that trends in vegetation dynamics do not always run steadily, but show structural breaks, especially in regions with high potential for possible landscape changes. For such conversion areas, the assumption of a constant seasonality is not always ensured. The dynamic or variability of the seasonality can have temporal effects by a shift of the start of the season (SOS) or the end of the season (EOS) and therefore also on the length of the vegetation period. To show whether seasonal dynamics can be detected in vegetation time series, two requirements must be fulfilled. (1) High-temporal resolution vegetation information provided for example as MODIS-NDVI. (2) Indicators are needed which allows the description of the variability of seasonality. As a result these metrics allow a better modeling of long-term vegetation dynamics in the trend, taking into account the variability of the seasonality. But at the same time the metrics itself serve as indicators for long term vegetation dynamics. The aim of the present study is to analyse phenological and greenness metrics for the modelling of vegetation dynamics in the nature reserve Königsbrücker Heide. Detailed analyses of key metrics like SOS and EOS using different metric approaches and interpolation methods are applied and compared. The results show that it is dificult to determine consistent information for example for the trend of single phenology metrics.

Land use / land cover (LULC) change assessment is getting more consideration by global environmental change studies as land use change is exposing dryland environments for transitions and higher rates of resource depletion. The semiarid regions of northwestern Ethiopia are not different as land use transition is the major problem of the region. However, there is no satisfactory study to quantify the change process of the region up to now. Hence, spatiotemporal change analysis is vital for understanding and identification of major threats and solicit solutions for sustainable management of the ecosystem. LULC change studies focus on understanding the patterns, processes and dynamics of land use transitions and driving forces of change. The change processes in dryland ecosystems can be either seasonal, gradual or abrupt changes of random or systematic change processes that result in a pattern or permanent transition in land use. Identification of these processes of change and their type supports adoption of monitoring options and indicate possible measures to be taken to safeguard this dynamic ecosystem. This study examines the spatiotemporal patterns of LULC change, temporal trends in climate variables and the insights of the communities on change patterns of ecosystems. Landsat imagery, MODIS NDVI, CRU temperature, TAMSAT rainfall and socio-ecological field data were used in order to identify change processes. LULC transformation was monitored using support vector machine (SVM) algorithm. A cross-tabulation matrix assessment was implemented in order to assess the total change of land use categories based on net change and swap change. In addition, the pattern of change was identified based on expected gain and loss under a random process of gain and loss, respectively. Breaks For Additive Seasonal and Trend (BFAST) analysis was employed for determining the time, direction and magnitude of seasonal, abrupt and trend changes within the time series datasets. In addition, Man Kendall test statistic and Sen’s slope estimator were used for assessing long term trends on detrended time series data components. Distributed lag (DL) model was also adopted in order to determine the time lag response of vegetation to the current and past rainfall distribution. Over the study period of 1972- 2014, there is a significant change in LULC as evidenced by a significant increase in size of cropland of about 53% and a net loss of over 61% of woodland area. The period 2000-2014 has shown a sharp increase of cropland and a sharp decline of woodland areas. Proximate causes include agricultural expansion and excessive wood harvesting; and underlying causes of demographic factor, economic factors and policy contributed the most to an overuse of existing natural resources. In both the observed and expected proportion of random process of change and of systematic changes, woodland has shown the highest loss compared to other land use types. The observed transition and expected transition under random process of gain of woodland to cropland is 1.7%, implies that cropland systematically gains to replace woodland. The comparison of the difference between observed and expected loss under random process of loss also showed that when woodland loses cropland systematically replaces it. The assessment of magnitude and time of breakpoints on climate data and NDVI showed different results. Accordingly, NDVI analysis demonstrated the existence of breakpoints that are statistically significant on the seasonal and long term trends. There is a positive trend, but no breakpoints on the long term precipitation data during the study period. The maximum temperature also showed a positive trend with two breakpoints which are not statistically significant. On the other hand, there is no seasonal and trend breakpoints in minimum temperature, though there is an overall positive trend along the study period. The Man-Kendall test statistic for long term average Tmin and Tmax showed significant variation where as there is no significant trend within the long term rainfall distribution. The lag regression between NDVI and precipitation indicated a lag of up to forty days. This proves that the vegetation growth in this area is not primarily determined by the current precipitation rather with the previous forty days rainfall. The combined analysis showed declining vegetation productivity and a loss of vegetation cover that contributed for an easy movement of dust clouds during the dry period of the year. This affects the land condition of the region, resulting in long term degradation of the environment

Nowadays remote sensing is a well-established method and technique of providing data. The current development shows the availability of systems with very high geometric resolution for the monitoring of vegetation. At the same time, however, the value of temporally high-resolution data is underestimated, particularly in applications focusing on the detection of short-term changes. These can be natural processes like natural disasters as well as changes caused by anthropogenic interventions. These include economic activities such as forestry, agriculture or mining but also processes which are intended to convert previously used areas into natural or near-natural surfaces. The Königsbrücker Heide is a former military training site located about 30 km north of the Saxon state capitol Dresden. After the withdrawal of the Soviet forces in 1992 and after nearly 100 years of military use this site was declared as nature reserve in 1996. The management of the whole protection area is implemented in three different management zone. Based on MODIS-NDVI time series between 2000 and 2016 different developments are apparent in the nature development zone and the zone of controlled succession. Nevertheless, the analyses also show that short-term changes, so called breaks in the vegetation development cannot be described using linear trend models. The complete understanding of vegetation trends is only given if discontinuities in vegetation development are considered. Structural breaks in the NDVI time series can be found simultaneously in the whole study area. Hence it can be assumed that these breaks have a more natural character, caused for example by climatic conditions like temperature or precipitation. Otherwise, especially in the zone of controlled succession structural breaks can be detected which cannot be traced back to natural conditions. Final analyses of the spatial distribution of breakpoints as well as their frequency depending on the respective protection zone allow a detailed view to vegetation development in the Köonigsbrüucker Heide.

It seems to be obvious that precipitation has a major impact on greening during the rainy season in semi-arid regions. First results1 imply a strong dependence of NDVI on rainfall. Therefore it will be necessary to consider specific rainfall events besides the known ordinary annual cycle. Based on this fundamental idea, the paper will introduce the development of a rain adjusted vegetation index (RAVI). The index is based on the enhancement of the well-known normalized difference vegetation index (NDVI2) by means of TAMSAT rainfall data and includes a 3-step procedure of determining RAVI. Within the first step both time series were analysed over a period of 29 years to find best cross correlation values between TAMSAT rainfall and NDVI signal itself. The results indicate the strongest correlation for a weighted mean rainfall for a period of three months before the corresponding NDVI value. Based on these results different mathematical models (linear, logarithmic, square root, etc.) are tested to find a functional relation between the NDVI value and the 3-months rainfall period before (0.8). Finally, the resulting NDVI-Rain-Model can be used to determine a spatially individual correction factor to transform every NDVI value into an appropriate rain adjusted vegetation index (RAVI).

In 1989 about 1.5 million soldiers were stationed in Germany. With the political changes in the early 1990s a substantial decline of the staff occurred on currently 200,000 employees in the armed forces and less than 60,000 soldiers of foreign forces. These processes entailed conversions of large areas not longer used for military purposes, especially in the new federal states in the eastern part of Germany. One of these conversion areas is the former military training area Königsbrück in Saxony. For the analysis of vegetation and its development over time, the Normalized Difference Vegetation Index (NDVI) has established as one of the most important indicators. In this context, the questions arise whether MODIS NDVI products are suitable to determine conversion processes on former military territories like military training areas and what development processes occurred in the 'Königsbrücker Heide' in the past 15 years. First, a decomposition of each series in its trend component, seasonality and the remaining residuals is performed. For the trend component different regression models are tested. Statistical analysis of these trends can reveal different developments, for example in nature development zones (without human impact) and zones of controlled succession. The presented work ow is intended to show the opportunity to support a high temporal resolution monitoring of conversion areas such as former military training areas.

The value of remote sensing data is particularly evident where an areal monitoring is needed to provide information on the earth's surface development. The use of temporal high resolution time series data allows for detecting short-term changes. In Kogi State in Nigeria different vegetation types can be found. As the major population in this region is living in rural communities with crop farming the existing vegetation is slowly being altered. The expansion of agricultural land causes loss of natural vegetation, especially in the regions close to the rivers which are suitable for crop production. With regard to these facts, two questions can be dealt with covering different aspects of the development of vegetation in the Kogi state, the determination and evaluation of the general development of the vegetation in the study area (trend estimation) and analyses on a short-term behavior of vegetation conditions, which can provide information about seasonal effects in vegetation development. For this purpose, the GIMMS-NDVI data set, provided by the NOAA, provides information on the normalized difference vegetation index (NDVI) in a geometric resolution of approx. 8 km. The temporal resolution of 15 days allows the already described analyses. For the presented analysis data for the period 1981-2012 (31 years) were used. The implemented work flow mainly applies methods of time series analysis. The results show that in addition to the classical seasonal development, artefacts of different vegetation periods (several NDVI maxima) can be found in the data. The trend component of the time series shows a consistently positive development in the entire study area considering the full investigation period of 31 years. However, the results also show that this development has not been continuous and a simple linear modeling of the NDVI increase is only possible to a limited extent. For this reason, the trend modeling was extended by procedures for detecting structural breaks in the time series.

Les prairies supra-forestières sont des écosystèmes bien représentés dans les milieux de montagne et qui s’avèrent vulnérables aux changements climatiques et aux modalités d’utilisation des terres. Dans ce contexte, l’objectif principal de cette thèse a été d’évaluer l’effet des forçages climatiques et du pastoralisme sur la végétation des prairies supra-forestières à différentes échelles spatio-temporelles. En particulier, nous avons cherché à comprendre les réponses des prairies à la variabilité interannuelle du climat (température et précipitation), aux tendances sur le long terme (réchauffement) et aux évènements extrêmes (vagues de chaleur et sécheresses) ; ainsi qu’aux modalités de la gestion pastorale (charges et calendriers de pâturage). Pour cela, nous avons réalisé des analyses sur un nombre de métriques phénologiques, météorologiques et pastorales. Les premières, dérivées principalement de l’indice de différence normalisée de la végétation (NDVI) à partir d’images satellite de moyenne (MODIS) et de haute résolution (Landsat et SPOT), ainsi que des données acquises au sol à la volée et en continu sur cinq alpages. Les deuxièmes, calculées à partir des ré-analyses du modèle climatique SAFRAN de Météo-France. Les troisièmes, estimées à partir des données des Enquêtes Pastorales régionales (1996-1997 et 2012-2014), et des cahiers d’alpage du dispositif Alpages Sentinelles. Concernant la végétation des prairies supra-forestières, nos résultats mettent en évidence : (i) des tendances au verdissement assez généralisées, (ii) des tolérances plus importantes aux vagues de chaleur qu’aux périodes de sécheresse estivales, (iii) des sensibilités plus importantes aux facteurs climatiques qu’aux pressions de pâturage, (iv) des réponses légères mais positives aux modalités de gestion pastoral, et (v) un potentiel de repousse en fin de saison. L’originalité de nos résultats a été de montrer l’existence de relations plus fortes entre les facteurs climatiques et la végétation des prairies, qu’entre cette dernière et le pâturage. Ils ont également éclairé les apports de l’utilisation de la télédétection dans l’étude de ces milieux. / Mountain grasslands are wide distributed ecosystems which are particularly vulnerable to climate and land use changes. In this context, the main objective of this thesis was to assess the effect of climate and pastoral drivers on mountain grasslands vegetation at different spatiotemporal scales. In particular, we wanted to understand plant responses to annual variations of climate (temperature and precipitation), long term warming and extreme events (heat waves and droughts); as well as the land management impact (grazing intensity and calendars). Hence, we performed several analyses using phenological, meteorological and pastoral metrics. First, we derived phenological metrics mainly from the Normalized Difference Vegetation Index (NDVI) extracted from two sources: satellite remote sensing images at moderate (MODIS) and high (Landsat and SPOT) resolution and field remote sensing measures acquired with portable and fixed sensors over five mountain grasslands. Second, we estimated meteorological metrics from reanalysis of the climatic model SAFRAN provided by Météo France. Third, we estimated pastoral metrics from two regional pastoral surveys (1996-1997 and 2012-2014) and several local documents (“cahiers d’alpage”) produced within the project “Alpages Sentinelles”. Regarding mountain grasslands vegetation, our results showed: (i) widely distributed greening trends, (ii) higher tolerance to heat waves than to droughts, (iii) higher sensibility to climate factors than to grazing pressures, (iv) weak but positive responses to grazing, and (v) a regrowth potential at the end of the season. The originality of our results was to exhibit the stronger relationships between climate factors and vegetation phenology, than between the latter and grazing pressures. Moreover, we highlighted the important contributions of remote sensing data to study mountain ecosystems.

I takt med ett varmare klimat har behovet att kunna studera marktäckesförändringar, så som vegetationens utbredning och förändringar av trädgränsen i alpina klimat, ökat. Förändringar i vegetationen och trädgränsens förflyttning i den svenska fjällkedjan skulle kunna bidra till en negativ inverkan på de växter och djur som återfinns där, då deras utrymme att sprida sig minskas. Detta examensarbete syftar till att undersöka vegetations- och trädgränsförändringar i Sarek nationalpark under perioden 1990 – 2023, samt undersöka förändringar av årsmedeltemperaturen i området. Vidare undersöks om resultaten går att applicera på temperaturökningar som presenteras i RCP (Representative Concentration Pathways) scenarion. Indata för examensarbetet bestod av 18 Landsat-bilder tagna under perioden juni – augusti åren 1990 – 2023 och medeltemperatur- och vegetationsperiodsdata från SMHI:s väderstationer belägna i närheten av nationalparken. De satellitbilder som användes genomgick en förbearbetning i form av bandnormalisering då de var från tre olika Landsat-serier, 5, 7 och 8. Temperaturdata korrigerades för höjdskillnader mellan station och nationalparken, där temperaturen i snitt sjunker med 0,65 °C per 100 höjdmeter, vartefter medeltemperatur per år beräknades. De analyser som genomfördes under examensarbetet var NDVI-beräkningar, klassificering av NDVI och klassövergångsanalyser, analys av trädgränsen och den övre trädgränsekotonen, trendberäkning samt analys av klimatdata. Vidare beräknades en förväntad utveckling av medel-NDVI baserat på temperaturökningar från de fyra olika RCP-scenarierna. Under perioden 1990 – 2023 observeras ett signifikant högre medel-NDVI under perioden 2002 – 2023 jämfört med 1990 – 2001, vilket indikerar en ökning av vegetationen. Vidare observeras att områden med snö/vatten hade minskat med 46 % under hela perioden. Av de övergångar som observeras var den främsta förändringen under perioden 1990 – 2006 övergången från kalfjäll till låg vegetation, 7 % av totalytan. Under perioden 2006 - 2023 utgjorde övergången från snö/vatten till kalfjäll den största andelen (6 %). Trädgränsen och den övre trädgränsekotonen i området har förflyttats i snitt 118 höjdmeter respektive 16 höjdmeter under hela studieperioden.   Temperaturjämförelse mellan normalperioderna 1961 – 1990 och 1991 – 2020 visar på att den senare perioden var 1,51 °C varmare. Sambandet (r = 0,473) mellan stigande årsmedeltemperatur och medel-NDVI applicerades på de temperaturförändringar som presenteras i RCP-scenarion där en ökning av medel-NDVI kunde observeras i varje scenario. Resultaten i examensarbetet visar på att klimatförändringarna kan börjat ha en inverkan på vegetationen i Sarek nationalpark, där en ökande vegetation och förflyttningar kan observeras. Detta kan med en signifikant svag positiv korrelation härledas till stigande medeltemperaturer i området. / The period from 2011 to 2022 saw a 1.09°C increase in temperature compared to 1850-1900 (preindustrial time), highlighting the urgency to understand its impact on land cover changes, especially in alpine climates like Sweden’s mountain ranges. This thesis investigates vegetation and tree line dynamics in Sarek National Park from 1990 to 2023, alongside local temperature shifts. Utilizing Landsat imagery and weather station data, analyses encompass NDVI calculations, class transitions, and tree line ecotone assessments. Results show a notable rise in mean NDVI from 2002 to 2023 compared to 1990 to 2001, indicating increased vegetation, while snow/water coverage decreased by 46% over the whole period. Shifts in land cover types were observed, notably transitions from barren land to low vegetation. Tree line movements were also noted. Correlation analyses suggest a link between rising temperatures and vegetation changes. Overall, findings may suggest early signs of climate-induced vegetation shifts in Sarek National Park.

Master of Science / Department of Agronomy / Kraig Roozeboom / High soybean [Glycine max.] commodity prices in recent years have led to an increase in use of yield enhancing and protecting products. These products need to be evaluated to determine if the use of multiple inputs has a positive impact on yield and how these inputs interact with agronomic practices. The objectives of this study were to evaluate products individually and collectively in input systems, examine interactions between varieties and input systems (IS), seeding rates (SR) and IS, and row spacing (RS) and IS. Field experiments were conducted at high-yielding locations in Kansas and Minnesota in 2012 to 2014 to meet these objectives. Sixteen treatments consisting of individual inputs and inputs combined in systems were evaluated in one experiment. A second experiment evaluated the variety by IS interaction by constructing 18 treatments from a factorial combination of six glyphosate [N-(phosphonomethyl) glycine] resistant varieties and three IS’s: untreated control (UTC), SOYA (combination of possible yield-enhancing products representative of those currently being marketed), and SOYA minus foliar fungicide (SOYA – foliar F). A third experiment evaluated the SR by IS interaction by constructing 12 treatments from a factorial arrangement of six SR’s and two IS’s: UTC and SOYA. A fourth experiment evaluated the RS by IS interaction by constructing 12 treatments from a factorial arrangement of three RS’s and four IS’s: UTC, fungicide and insecticide seed treatment plus foliar fungicide (STFF), SOYA, and SOYA – foliar F. Very few interactions between IS and agronomic practices were detected in any of the experiments. Varieties had an effect on multiple growth parameters but yield differences were marginal; linear-plateau and non-linear models found that seeding rates that maximized yield in this study were similar to University recommendations; and in general, narrow rows produced the greatest yields. The use of inputs and IS’s typically increased seed mass and yield above the UTC across all experiments. However, given current costs and soybean prices, yield response to IS’s was not great enough to cover the additional costs. Overall, it appears producers would be better served by focusing on agronomic practices rather than implementing input systems.

Outdoor water use by single-family residences in the desert city of Tucson, Arizona is investigated as a multi-scaled coupled human-environment system, using remotely sensed images, GIS data, household water use records and survey responses. Like many desert cities, Tucson's municipal water system faces stresses at multiple spatial and temporal scales: rising demand, limited supplies, competition for distant resources and the likelihood of shortages due to regional climate change. Though the need for demand management is recognized, conflict between the long-term regional scale of the ecosystem that sustains Tucson's water supply and the short-term, local scale of the municipal utility results in a "lack of fit", shown here as the inability to reduce consumption to sustainable levels.While direct regulation of outdoor water use has not been successful, geographic research suggests that modification of the built environment, the focus of the three studies comprising this dissertation, holds promise as a demand management strategy. The first study is a spatial analysis of survey responses on outdoor water use practices during a drought. Next, the potential for substituting common amenities (irrigated landscapes and swimming pools) for private ones is investigated. Residential use was found to be sensitive to park proximity, greenness (proxied by the Normalized Difference Vegetation Index), size and presence of a park pool. Most small parks were net water savers; large parks offered the opportunity to substitute reclaimed water for potable supplies.The last study correlates long-term Landsat-based vegetation and water use trends and integrates these with a spatial analysis of kinetic temperatures. Findings indicate that despite reduced water use, Tucson became greener over the 1995 - 2008 period. This effect is attributed to a pulse of vegetation establishment in response to a shift in the El Niño - Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) around 1976 and to irrigation prior to the study period. I conclude that although the coupled human-environment system of Tucson's municipal water supply and use practices is complex, there are scale-dependent competitive advantages to be gained through thoughtful modification of the built environment.