Vegetation Dynamics Revealed by Remote Sensing and Its Feedback to Regional and Global Climate

This book focuses on some significant progress in vegetation dynamics and their response to climate change revealed by remote sensing data. The development of satellite remote sensing and its derived products offer fantastic opportunities to investigate vegetation changes and their feedback to regional and global climate systems. Special attention is given in the book to vegetation changes and their drivers, the effects of extreme climate events on vegetation, land surface albedo associated with vegetation changes, plant fingerprints, and vegetation dynamics in climate modeling

Use of TanDEM-X and Sentinel Products to Derive Gully Activity Maps in Kunene Region (Namibia) Based on Automatic Iterative Random Forest Approach

Gullies are landforms with specific patterns of shape, topography, hydrology, vegetation, and soil characteristics. Remote sensing products (TanDEM-X, Sentinel-1, and Sentinel-2) serve as inputs into an iterative algorithm, initialized using a micromapping simulation as training data, to map gullies in the northwestern of Namibia. A Random Forest Classifier examines pixels with similar characteristics in a pool of unlabeled data, and gully objects are detected where high densities of gully pixels are enclosed by an alpha shape. Gully objects are used in subsequent iterations following a mechanism where the algorithm uses the most reliable pixels as gully training samples. The gully class continuously grows until an optimal scenario in terms of accuracy is achieved. Results are benchmarked with manually tagged gullies (initial gully labeled area <0.3% of the total study area) in two different watersheds (408 and 302 km2, respectively) yielding total accuracies of >98%, with 60% in the gully class, Cohen Kappa >0.5, Matthews Correlation Coefficient >0.5, and receiver operating characteristic Area Under the Curve >0.89. Hence, our method outlines gullies keeping low false-positive rates while the classification quality has a good balance for the two classes (gully/no gully). Results show the most significant gully descriptors as the high temporal radar signal coherence (22.4%) and the low temporal variability in Normalized Difference Vegetation Index (21.8%). This research builds on previous studies to face the challenge of identifying and outlining gully-affected areas with a shortage of training data using global datasets, which are then transferable to other large (semi-) arid regions.This research is part of the DEM_HYDR2024 project sup ported by TanDEM-X Science Team, therefore the authors would like to express thanks to the Deutsches Zentrum für Luft und Raumfahrt (DLR) as the donor for the used TanDEM-X datasets. They acknowledge the financial support provided by the Namibia University of Science and Technology (NUST) within the IRPC research funding programme and to ILMI for the sponsorship of field trips to identify suitable study areas. Finally, they would like to express gratitude toward Heidelberg University and the Kurt-Hiehle-Foundation for facilitating the suitable work conditions during this research

Uncertainties in Digital Elevation Models: Evaluation and Effects on Landform and Soil Type Classification

Digital elevation models (DEMs) are a widely used source for the digital representation of the Earth's surface in a wide range of scientific, industrial and military applications. Since many processes on Earth are influenced by the shape of the relief, a variety of different applications rely on accurate information about the topography. For instance, DEMs are used for the prediction of geohazards, climate modelling, or planning-relevant issues, such as the identification of suitable locations for renewable energies. Nowadays, DEMs can be acquired with a high geometric resolution and over large areas using various remote sensing techniques, such as photogrammetry, RADAR, or laser scanning (LiDAR). However, they are subject to uncertainties and may contain erroneous representations of the terrain. The quality and accuracy of the topographic representation in the DEM is crucial, as the use of an inaccurate dataset can negatively affect further results, such as the underestimation of landslide hazards due to a too flat representation of relief in the elevation model. Therefore, it is important for users to gain more knowledge about the accuracy of a terrain model to better assess the negative consequences of DEM uncertainties on further analysis results of a certain research application. A proper assessment of whether the purchase or acquisition of a highly accurate DEM is necessary or the use of an already existing and freely available DEM is sufficient to achieve accurate results is of great qualitative and economic importance. In this context, the first part of this thesis focuses on extending knowledge about the behaviour and presence of uncertainties in DEMs concerning terrain and land cover. Thus, the first two studies of this dissertation provide a comprehensive vertical accuracy analysis of twelve DEMs acquired from space with spatial resolutions ranging from 5 m to 90 m. The accuracy of these DEMs was investigated in two different regions of the world that are substantially different in terms of relief and land cover. The first study was conducted in the hyperarid Chilean Atacama Desert in northern Chile, with very sparse land cover and high elevation differences. The second case study was conducted in a mid-latitude region, the Rur catchment in the western part of Germany. This area has a predominantly flat to hilly terrain with relatively diverse and dense vegetation and land cover. The DEMs in both studies were evaluated with particular attention to the influence of relief and land cover on vertical accuracy. The change of error due to changing slope and land cover was quantified to determine an average loss of accuracy as a function of slope for each DEM. Additionally, these values were used to derive relief-adjusted error values for different land cover classes. The second part of this dissertation addresses the consequences that different spatial resolutions and accuracies in DEMs have on specific applications. These implications were examined in two exemplary case studies. In a geomorphometric case study, several DEMs were used to classify landforms by different approaches. The results were subsequently compared and the accuracy of the classification results with different DEMs was analysed. The second case study is settled within the field of digital soil mapping. Various soil types were predicted with machine learning algorithms (random forest and artificial neural networks) using numerous relief parameters derived from DEMs of different spatial resolutions. Subsequently, the influence of high and low resolution DEMs with the respectively derived land surface parameters on the prediction results was evaluated. The results on the vertical accuracy show that uncertainties in DEMs can have diverse reasons. Besides the spatial resolution, the acquisition technique and the degree of improvements made to the dataset significantly impact the occurrence of errors in a DEM. Furthermore, the relief and physical objects on the surface play a major role for uncertainties in DEMs. Overall, the results in steeper areas show that the loss of vertical accuracy is two to three times higher for a 90 m DEM than for DEMs of higher spatial resolutions. While very high resolution DEMs of 12 m spatial resolution or higher only lose about 1 m accuracy per 10° increase in slope steepness, 30 m DEMs lose about 2 m on average, and 90 m DEMs lose more than 3 m up to 6 m accuracy. However, the results also show significant differences for DEMs of identical spatial resolution depending on relief and land cover. With regard to different land cover classes, it can be stated that mid-latitude forested and water areas cause uncertainties in DEMs of about 6 m on average. Other tested land cover classes produced minor errors of about 1 – 2 m on average. The results of the second part of this contribution prove that a careful selection of an appropriate DEM is more crucial for certain applications than for others. The choice of different DEMs greatly impacted the landform classification results. Results from medium resolution DEMs (30 m) achieved up to 30 % lower overall accuracies than results from high resolution DEMs with a spatial resolution of 5 m. In contrast to the landform classification results, the predicted soil types in the second case study showed only minor accuracy differences of less than 2 % between the usage of a spatial high resolution DEM (15 m) and a low resolution 90 m DEM. Finally, the results of these two case studies were compared and discussed with other results from the literature in other application areas. A summary and assessment of the current state of knowledge about the impact of a particular chosen terrain model on the results of different applications was made. In summary, the vertical accuracy measures obtained for each DEM are a first attempt to determine individual error values for each DEM that can be interpreted independently of relief and land cover and can be better applied to other regions. This may help users in the future to better estimate the accuracy of a tested DEM in a particular landscape. The consequences of elevation model selection on further results are highly dependent on the topic of the study and the study area's level of detail. The current state of knowledge on the impact of uncertainties in DEMs on various applications could be established. However, the results of this work can be seen as a first step and more work is needed in the future to extend the knowledge of the effects of DEM uncertainties on further topics that have not been investigated to date

Development of a 10-year (2001-2010) 0.1° data set of land-surface energy balance for mainland China

© Author(s) 2014. In the absence of high-resolution estimates of the components of surface energy balance for China, we developed an algorithm based on the surface energy balance system (SEBS) to generate a data set of land-surface energy and water fluxes on a monthly timescale from 2001 to 2010 at a 0.1 x 0.1° spatial resolution by using multi-satellite and meteorological forcing data. A remote-sensing-based method was developed to estimate canopy height, which was used to calculate roughness length and flux dynamics. The landsurface flux data set was validated against "ground-truth" observations from 11 flux tower stations in China. The estimated fluxes correlate well with the stations' measurements for different vegetation types and climatic conditions (average bias = 11.2 Wm-2, RMSE = 22.7 Wm-2). The quality of the data product was also assessed against the GLDAS data set. The results show that our method is efficient for producing a high-resolution data set of surface energy flux for the Chinese landmass from satellite data. The validation results demonstrate that more accurate downward long-wave radiation data sets are needed to be able to estimate turbulent fluxes and evapotranspiration accurately when using the surface energy balance model. Trend analysis of land-surface radiation and energy exchange fluxes revealed that the Tibetan Plateau has undergone relatively stronger climatic change than other parts of China during the last 10 years. The capability of the data set to provide spatial and temporal information on water-cycle and land-atmosphere interactions for the Chinese landmass is examined. The product is free to download for studies of the water cycle and environmental change in China

Remote Sensing of Land Surface Phenology

Land surface phenology (LSP) uses remote sensing to monitor seasonal dynamics in vegetated land surfaces and retrieve phenological metrics (transition dates, rate of change, annual integrals, etc.). LSP has developed rapidly in the last few decades. Both regional and global LSP products have been routinely generated and play prominent roles in modeling crop yield, ecological surveillance, identifying invasive species, modeling the terrestrial biosphere, and assessing impacts on urban and natural ecosystems. Recent advances in field and spaceborne sensor technologies, as well as data fusion techniques, have enabled novel LSP retrieval algorithms that refine retrievals at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. Meanwhile, rigorous assessment of the uncertainties in LSP retrievals is ongoing, and efforts to reduce these uncertainties represent an active research area. Open source software and hardware are in development, and have greatly facilitated the use of LSP metrics by scientists outside the remote sensing community. This reprint covers the latest developments in sensor technologies, LSP retrieval algorithms and validation strategies, and the use of LSP products in a variety of fields. It aims to summarize the ongoing diverse LSP developments and boost discussions on future research prospects

INVESTIGATING THE IMPACTS OF ANTHROPOGENIC AND CLIMATIC CHANGES ON THE STEPPE ECOSYSTEM IN CHINA’S LOESS PLATEAU AND THE MIXED-GRASS PRAIRIE REGION IN SOUTHWEST OKLAHOMA, USA

Grassland ecosystems occupy approximately 40% of the earth’s terrestrial area and represent one of most important ecosystems on Earth in terms of its impacts on global food supply, carbon sequestration and maintaining biodiversity. Grassland ecosystems are very sensitive to disturbances caused by either climatic or anthropogenic changes such as changes in precipitation regimes or management practices. The objective of this dissertation is to investigate the impacts imposed by grassland restoration activities and changes in precipitation anomalies on the steppe in China’s Loess Plateau and the mixed-grass prairie in southwest Oklahoma. In chapter two, I analyzed how large-scale vegetation conservation programs affected the grassland dynamics in China’s Loess Plateau by combining remotely sensed data with socio-economic statistics. The results of this study showed that the impact of vegetation conservation programs on vegetation change in the Loess Plateau is twofold. On the one hand, vegetation conservation programs target marginal lands. Thus, significant vegetation increases due to cropland conversion and afforestation can be found in these regions. On the other hand, intensified agricultural production can be found in croplands with suitable topography and well-established irrigation systems which were not enrolled in conservation programs to offset the agricultural production loss caused by vegetation conservation programs elsewhere. In chapter three, I demonstrated a new methodology on mapping the historical distribution of grassland species in southwest Oklahoma based on the Random Forest classification algorithm. In this study, elevation, soil pH and soil clay content were found to be significant variables for predicting the distribution of C3 and C4 grassland species. With the mapped distribution of grassland species between 1981 and 2010, in chapter four, I examined the relationship between changes in precipitation anomalies and the dynamics of relative abundance of C3 and C4 grassland species in southwest Oklahoma. In this study, significant decreases of C3/C4 ratio were identified in pasture/hay fields due to the increases in C4 abundance resulting from the decreases of sparsely vegetated area between 2005 and 2010. I suspect that the increase in C4 abundance was a drought adaptation strategy adopted by ranchers. Because C4 species are more tolerant of drought conditions and thus can help to maintain stable forage/hay production when negative precipitation anomalies prevailed during the growing season of C3 species

Afforestation and Reforestation: Drivers, Dynamics, and Impacts

Afforestation/reforestation (or forestation) has been implemented worldwide as an effective measure towards sustainable ecosystem services and addresses global environmental problems such as climate change. The conversion of grasslands, croplands, shrublands, or bare lands to forests can dramatically alter forest water, energy, and carbon cycles and, thus, ecosystem services (e.g., carbon sequestration, soil erosion control, and water quality improvement). Large-scale afforestation/reforestation is typically driven by policies and, in turn, can also have substantial socioeconomic impacts. To enable success, forestation endeavors require novel approaches that involve a series of complex processes and interdisciplinary sciences. For example, exotic or fast-growing tree species are often used to improve soil conditions of degraded lands or maximize productivity, and it often takes a long time to understand and quantify the consequences of such practices at watershed or regional scales. Maintaining the sustainability of man-made forests is becoming increasingly challenging under a changing environment and disturbance regime changes such as wildland fires, urbanization, drought, air pollution, climate change, and socioeconomic change. Therefore, this Special Issue focuses on case studies of the drivers, dynamics, and impacts of afforestation/reforestation at regional, national, or global scales. These new studies provide an update on the scientific advances related to forestation. This information is urgently needed by land managers and policy makers to better manage forest resources in today’s rapidly changing environments

Water Resource Variability and Climate Change

Climate change affects global and regional water cycling, as well as surficial and subsurface water availability. These changes have increased the vulnerabilities of ecosystems and of human society. Understanding how climate change has affected water resource variability in the past and how climate change is leading to rapid changes in contemporary systems is of critical importance for sustainable development in different parts of the world. This Special Issue focuses on “Water Resource Variability and Climate Change” and aims to present a collection of articles addressing various aspects of water resource variability as well as how such variabilities are affected by changing climates. Potential topics include the reconstruction of historic moisture fluctuations, based on various proxies (such as tree rings, sediment cores, and landform features), the empirical monitoring of water variability based on field survey and remote sensing techniques, and the projection of future water cycling using numerical model simulations

Impact of Land Use and Climate Change on Hydrological Ecosystem Services (Water Supply) in the Dryland Area of the Middle Reaches of the Yellow River

Driven by many factors, the water supply services (streamflow and groundwater) of many rivers in the dryland area of China have declined significantly. This aggravates the inherent severe water shortages and results in increased severity in the water use conflicts that are threatening sustainable development in the region. Innovative strategies towards more water-efficient land management are vital for enhancing water quantity to ensure water supply security. A key step in the successful development and implementation of such measures is to understand the response of hydrological processes and related services to changes in land management and climate. To this end, it was decided to investigate these processes and responses in the upper reaches of the Jing River (Jinghe), an important meso-scale watershed in the middle reaches of the Yellow River on the Loess Plateau (NW China). It has been shown that vegetation restoration efforts (planting trees and grass) are effective in controlling soil erosion on the Loess Plateau. Shifts in land cover/use lead to modifications of soil physical properties. Yet, it remains unclear if the hydraulic properties have also been improved by vegetation restoration. A better understanding of how vegetation restoration alters soil structure and related soil hydraulic properties, such as water conductivity and soil water storage capacity, is necessary. Three adjacent sites, with comparable soil texture, soil type, and topography but contrasting land cover (Black locust forest, grassland, and cropland), were investigated in a small catchment in the upstream Jinghe watershed (near Jingchuan, Gansu province). Seasonal variations of soil hydraulic properties in topsoil and subsoil were examined. Results revealed that the type of land use had a significant impact on field-saturated, near-saturated hydraulic conductivity, and soil water characteristics. Specifically, conversion from cropland to grass or forests promotes infiltration capacity as a result of increased saturated hydraulic conductivity, air capacity, and macroporosity. Moreover, conversion from cropland to forest tends to promote the formation of mesopores that increase soil water storage capacity. Tillage in cropland temporarily created well-structured topsoil, but also compacted subsoil, as indicated by low subsoil saturated hydraulic conductivity, air capacity, and plant available water capacity. An impact of land cover conversion on unsaturated hydraulic conductivities was not identified, indicating that changes in land cover do not affect functional meso- and microporosity. Changes in soil hydraulic properties and associated hydrological processes and services due to soil conservation efforts need to be considered, should soil conservation measures be implemented in water-limited regions for sustaining adequate water supply. To differentiate between the impacts of land management and climate change on streamflow, the variation of annual streamflow, precipitation, potential evapotranspiration, and climatic water balance in a small catchment of the upstream Jinghe watershed (near Pingliang, Gansu province) was examined during the period of 1955 – 2004. During this time the relative contributions of changes in land management and climate to the reduction of streamflow were estimated. A statistically significant decreasing trend of -1.14 mm y-1 in annual streamflow was detected. Furthermore, an abrupt streamflow reduction due to afforestation and construction of terraces and check-dams was identified around 1980. Remarkably, 74% of the total reduction in mean annual streamflow can be attributed to the soil conservation measures. Among various conservation measures, streamflow could be considerably reduced by afforestation and terracing (including damland creation), due to their low contribution to water yield. In contrast, slope farmland and grassland can maintain a certain level of water supply services due to higher runoff coefficients. According to a meta-analysis of the published studies on the Loess Plateau, the impact of changes in land management on annual streamflow appears to diminish with increasing catchment size while the impact of climate change appears uniform across space. This means that there is a dependency between the catchment size and the response of hydrological processes to environmental change. At least at the local scale, it appears that well-considered land management may help to ensure the water supply services. Due to limited surface water availability, groundwater is an essential water source for supporting ecosystem and socio-economic development in the dryland region. However, the groundwater process is susceptible and vulnerable to changes in climate and landscape (i.e., land cover and form) that in turn can result in profound adverse consequences on water supply services in water-limited regions. In addition, an improved understanding of the response of groundwater related processes to natural and artificial disturbances is likely to ensure more secure and more sustainable governance and management of such regions, as well as better options for adapting to climate change. Yet, this topic has seldom been researched, especially in areas that have already experienced large-scale alteration in landscape and are located in dryland regions, such as the Loess Plateau. Therefore, an investigation of the baseflow variation along the landscape change was conducted. The average annual baseflow has significantly decreased at catchment scale during the period of 1962 – 2002 without any obvious significant change in climate. At decadal scale, the reduction accounts for approximately 9% in the 1970s, 48% in the 1980s, and 92% in the 1990s, while the baseflow index declines averaging 5%, 16% and 67%, respectively. All of the monthly baseflow levels dropped at varying rates except in January, among which July was the most severe in terms of both magnitude (-4.17) and slope (-0.09 mm y-1). In perspective of landscape change, landform change (terrace and check-dam) tends to reduce baseflow by reallocation of surface fluxes and retention for crop growth causing limited deep drainage in other areas. Land cover change (i.e., afforestation) reduced the baseflow to a larger extent by enhanced evapotranspiration and thus hampered deep drainage as suggested by the soil moisture measurement underneath. The study indicates that knowledge about baseflow formation on catchment scale needs further improvement. Integrated soil conservation and water management for optimizing landscape structure and function in order to balance soil (erosion) and water (supply) related hydrological ecosystem services is vital. The governing processes to the changes of water-supply-services-related hydrological process (e.g., streamflow) are assumed to be different across space. To this end, the factors controlling streamflow were investigated on both a small and large scale. Streamflow in small catchments was found to be mainly controlled by precipitation and land cover type. On a larger scale, evaporative demand was found to be another additional major driving force. Hydrological modeling is a frequently used tool for the assessment of impacts of land use and climate change on water balance and water fluxes. However, application of the Soil and Water Assessment Tool (SWAT) model in the upstream Jinghe watershed was unsuccessful due to difficulties in calibration. The inability of the SWAT model to take the influence of terraces on steep slopes into consideration and the method how to calculate lateral flow were the main reasons for unsatisfactory calibration, at least for the current version of SWAT used in this study. Alternatively, Budyko’s frameworks were applied to predict the annual and long-term streamflow. However, the effect of changes in land management (e.g., afforestation) on streamflow could not be assessed due to a lack of vegetation factors. Therefore, an empirical analysis tool was derived based on an existing relationship for estimation. This method was found to be the most effective in reproducing the annual and long-term streamflow. The incorporation of temporal changes in land cover and form in the approach enables the estimation of the possible impact of soil conservation measures (e.g., afforestation or terracing). The importance of adaptive land management strategies for mitigating water shortage and securing the water supply services on the Loess Plateau was highlighted. A cross-sectoral view of the multiple services offered by managed ecosystems at different spatial scales under changing environments needs to be integrated to improve adaptive land management policy. In a water limited environment, such as the Loess Plateau, multiple ecosystem services including hydrological services need to be balanced with minimum trade-offs. This can only be achieved when management is based on a holistic understanding of the interdependencies among various ecosystem services and how they might change under alternative land management

Soil Water Erosion

The purpose of this book is to provide novel results related to soil water erosion that could help landowners and land-users, farmers, politicians, and other representatives of our global society to protect and, if possible, improve the quality and quantity of our precious soil resources. Published papers on the topics are related to new ways of mapping, maps with more detailed input data, maps about areas that have never been mapped before, sediment yield estimations, modelling sheets and gully erosion, USLE models, RUSLE models, dams which stop sediment runoff, sediment influx, solute transport, soil detachment capacities, badland morphology, freeze-thaw cycles, armed conflicts, use of rainfall simulators, rainfall erosivity, soil erodibility, etc