A bi-directional strategy to detect land use function change using time-series Landsat imagery on Google Earth Engine:A case study of Huangshui River Basin in China

Constructed land, cropland, and ecological land are undergoing intense competition in many rapidly-developing regions. One of the major reasons to cause frequent land use (LU) conversions is the policy dynamics. The detection of such conversions is thus a prerequisite to understanding urban dynamics and how policies shape landscapes. This paper presents a bi-directional strategy to detect the LU change of the Huangshui River Basin of China from 1987 to 2018 using time-series Landsat imagery. We first initialized classification and optimization of remote sensing images using the Random Forest algorithm; We then detected bi-directional spatio-temporal changes based on the distribution probability of land-cover types. Our results reveal complicated dynamics underlying the net increase in urban and built-up land (UB) and the net decrease in cropland. In this area, due to the implementation of ecological compensation projects such as ecological migration and mine restoration, we found that on average 5.52 km2 of UB was converted into ecological land (forest, grassland and shrubland) every year, even though UB has expanded 3.6 times in the last 30 years with multiple conversions for cropland and ecological land. Meanwhile, 60% of lost cropland was converted to shrubland and grassland, and 40% was converted to UB. The accuracy of LU classification increases by 6.03% from 88.17%, and kappa coefficient increases by 2.41% from 85.16, compared to the existing initial results and uni-directional detection method. This study highlights the importance of the use of an effective remote sensing-based strategy for monitoring high-frequency LU changes in watershed areas with complicated human-nature interactions.</p

Preferential dust sources: a geomorphological classification designed for use in global dust-cycle models

We present a simple theoretical land-surface classification that can be used to determine the location and temporal behaviour of preferential sources of terrestrial dust emissions. The classification also provides information about the likely nature of the sediments, their erodibility and the likelihood that they will generate emissions under given conditions. The scheme is based on the dual notions of geomorphic type and connectivity between geomorphic units. We demonstrate that the scheme can be used to map potential modern-day dust sources in the Chihuahuan Desert, the Lake Eyre Basin and the Taklamakan. Through comparison with observed dust emissions, we show that the scheme provides a reasonable prediction of areas of emission in the Chihuahuan Desert and in the Lake Eyre Basin. The classification is also applied to point source data from the Sahara to enable comparison of the relative importance of different land surfaces for dust emissions. We indicate how the scheme could be used to provide an improved characterisation of preferential dust sources in global dust-cycle models

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

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

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

Aeolian dust deposition rates in south-western Iran

The annual atmospheric dust-load originating in the so-called Dust Belt ‎, which ranges from the ‎Sahara desert and the Arabian peninsula to the arid lowlands of Central Asia and the deserts of ‎northern China, impacts the air quality and the climate worldwide. Iran as a whole, and especially the ‎southwestern regions of the country, most affected by dust, with frequent dust storms characterized ‎by annual mean concentrations of more than 100 µg/m³ of suspended dust. Although aeolian dust is a ‎highly relevant problem in Iran, there is a lack of comprehensive regional studies on this topic. The ‎central aim of the study presented here is therefore the spatiotemporal analyses and classification of ‎dust events, the chemical composition of the dust, and the connections between regional and seasonal ‎climate variation and dust deposition rates in four sub-regions of Iran. This comprehensive approach is ‎based on the maximum mean dust concentration and the seasonality of dust events. The results are ‎provided new and valuable insights into the dust deposition and its related processes in the study area.‎ The study area covers 8.43% of Iran (about 117,000 km2), located between 45°30′00″ E 35°00′00″ N ‎and 49°30′00″ E 30°00′00″ N including Kermanshah, Lorestan and Khuzestan. The fieldwork area is ‎characterized by the rolling mountainous terrain about 4000 m above sea level (a.s.l) in the north and ‎east, plains and marshlands in the south. Study area has also located in dry climate and hot summer ‎conditions in the south, cold and hot desert climates in the west. The studies on aeolian dust in ‎southwestern Iran are based solely on ground deposition rates from 2014 to 2017‎‏.‏ To address the connections between the Ground observation of dust Deposition Rates (GDR), climate ‎zones, and weather patterns, a comparative analysis with various data sets was conducted. Both ‎gravimetric and directional dust samplers (10 each) were installed to record the monthly GDR between ‎‎2014 and 2017. The sampler design was deliberately kept simple to ensure long-term durability and ‎easy maintenance. The collected dust samples were analyzed for their chemical composition using ‎Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The ten sampling sites were also classified ‎by their land use / land cover (LULC) for a more detailed data interpretation. The observation data ‎during two typical dust cases (spring 2014 and winter 2015), have furthermore been compared with ‎the spatiotemporal dust concentration and dust load over the study area. Comparing the results of the ‎monthly mean Aerosol Optical Thickness (AOT) derived from the Moderate Resolution Imaging ‎Spectroradiometer (MODIS) and GDR data, using enhancement algorithms were applied in order to ‎investigate the spatiotemporal distribution of dust events. To demonstrate the aerosol movement, a ‎HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used for tracing the ‎investigated dust events. The time-space consistency between AOT and GDR, in agreement with the ‎HYSPLIT model output was the basis for an improved estimation of the dust deposition rate from ‎separate thickness layers. Finally, by comparing the high temporal and maximum seasonal deposition ‎rates, using MODIS and GDR data, the impact of the regional climate on the deposition rates of ‎aeolian dust was assessed, which allows insights in potential future dust emission scenarios in times of ‎climate change. ‎ A major finding shows the impact of dust events on the environment and considers the influence of ‎geographical factors, such as weathering, and climate pattern over aeolian dust deposition rates. In ‎more detail, finding to address the first objective suggested that contributors of the elemental ‎concentrations are associated with elements emanating from local industrial and commercial activities ‎‎(Cr, V, and Cd). The dominant variables (K, Zn) strongly influence the aerosol composition values and ‎represent the dust transport route. Inter –element relationships shows that the highest proportion (80%) ‎of dust samples subjected to Airborne Metals Regulations are formed under local and regional ‎conditions. Besides, the analyses indicate that the WRF-Chem model adequately simulates the ‎evolution, spatial distribution and load of dust over the study area. Hence, the model performance has ‎been evaluated by GDR. It showed different values of GDR highly depending on LULC pattern. Due to ‎the fact, that there is no way to isolate each individual area from the effects of either anthropogenic ‎sources or natural weathering processes, developing guidance on the priorities of expanding projects ‎and preventative actions towards potential dust deposition from natural and dominant sources may be ‎a subject of institutional interest. ‎ The results of direct measurements of dust deposition, which are typically made by passive sampling ‎techniques (ground-based observations), along with analyzed data from AOT, represent the second ‎objective to understand the spatiotemporal pattern of the points with the same variation. The ‎corresponding points headed to find moving air mass trajectories, using HYSPLIT were proven to be a ‎discriminator of their local and regional origin of aeolian dust. Furthermore, the seasonal deposition rate ‎varied from 8.4 g/m2/month in the summer to 3.5 g/m2/month in the spring. Despite all the advances ‎of AOT, under certain circumstances, the ground-based solutions were able to represent aerosol ‎conditions over the research area, tested in the southwestern regions of Iran. And that is when the low ‎number of observations is a commonly acknowledged drawback of GDR.‎ In addition, the peak of the seasonal deposition rates (t/km2/month) occurred in [arid desert hot-BWh, ‎‎8.4], [arid steppe hot-BSh, 6.6], and [hot and dry summer-Csa, 3.5] climate regions. Thus, the third ‎objective response was‏ ‏detected as the highest deposition rates of dust BWh >BSh >Csa throughout ‎the year, once the annual mean deposition rates (t/km2/year) are 100.80 for [BWh], 79.27 for [BSh], ‎and 39.60 for [Csa]. The knowledge gained on the dust deposition processes, together with the ‎feedback from the climate pattern, will provide insights into the records of data for developing new ‎sources, deposition rates and their climate offsets. Taking this in mind, having information about the ‎ground deposition rates in the study region could make the estimations more accurate, while finding an ‎appropriate algorithm is necessary to enhance the affected areas exposed to the dust. In order to ‎assess the impact of dust events on human health, environment and the damage to the various ‎business sectors of the country’s economy, additional studies with adequate modelling tools are ‎needed. ‎ Due to this date, the data holding organizations are somewhat reluctant to make their data available to ‎other parties. This work is also a step toward an institutional suggestion to gain benefit from information ‎exchange amongst data holding organizations, providers and users. The need for capacity building and ‎strong policy for implementing user-friendly geo information portal‏ ‏is essential.

Measuring, modelling and managing gully erosion at large scales: A state of the art

Soil erosion is generally recognized as the dominant process of land degradation. The formation and expansion of gullies is often a highly significant process of soil erosion. However, our ability to assess and simulate gully erosion and its impacts remains very limited. This is especially so at regional to continental scales. As a result, gullying is often overlooked in policies and land and catchment management strategies. Nevertheless, significant progress has been made over the past decades. Based on a review of >590 scientific articles and policy documents, we provide a state-of-the-art on our ability to monitor, model and manage gully erosion at regional to continental scales. In this review we discuss the relevance and need of assessing gully erosion at regional to continental scales (Section 1); current methods to monitor gully erosion as well as pitfalls and opportunities to apply them at larger scales (section 2); field-based gully erosion research conducted in Europe and European Russia (section 3); model approaches to simulate gully erosion and its contribution to catchment sediment yields at large scales (section 4); data products that can be used for such simulations (section 5); and currently existing policy tools and needs to address the problem of gully erosion (section 6). Section 7 formulates a series of recommendations for further research and policy development, based on this review. While several of these sections have a strong focus on Europe, most of our findings and recommendations are of global significance.info:eu-repo/semantics/publishedVersio