A method for predicting large-area missing observations in Landsat time series using spectral-temporal metrics

Combined with increasing computing ability, the free and open access to Landsat archive has enabled the changes on the Earth’s surface to be monitored for almost 50 years. However, due to missing observations that result from clouds, cloud shadows, and scan line corrector failure, the Landsat data record is neither a continuous nor consistent time series. We present a new gap-filling method, Missing Observation Prediction based on Spectral-Temporal Metrics (MOPSTM), which uses spectral-temporal metrics computed from Landsat one-year time series and the k-Nearest Neighbor (k-NN) regression. Herein, we demonstrate the performance of MOPSTM by using five, nearly cloud-free, full scene Landsat images from Kenya, Finland, Germany, the USA, and China. Cloud masks from the images with extensive cloud cover were used to simulate large-area gaps, with the highest value we tested being 92% of missing data. The gap-filling accuracy was assessed quantitatively considering all five sites and different land use/land cover types, and the MOPSTM algorithm performed better than the spectral angle-mapper based spatiotemporal similarity (SAMSTS) gap-filling algorithm. The mean RMSE values of MOPSTM were 0.010, 0.012, 0.025, 0.012, and 0.018 for the five sites, while those of SAMSTS were 0.011, 0.017, 0.038, 0.014, and 0.023, respectively. Furthermore, MOPSTM had mean coefficient of determination (R2) values of 0.90, 0.86, 0.78, 0.92, and 0.89, which were higher than those for SAMSTS (0.84, 0.75, 0.55, 0.89, and 0.83). The performance of MOPSTM was not considerably affected by image gap sizes as images ranging from gap sizes of 51% of the image all the way to 92% of the image yielded similar gap-filling accuracy. Also, MOPSTM does not require local parametertuning except for the k values in the k-NN regression, and it can make a gap-free image from any acquisition date. MOPSTM provides a new spectral-temporal approach to generate the gap-free imagery for typical Landsat applications, such as land use, land cover, and forest monitoring.Peer reviewe

Spatial-Spectral Radial Basis Function-Based Interpolation for Landsat ETM+ SLC-Off Image Gap Filling

The scan-line corrector (SLC) of the Landsat 7 ETM+ failed permanently in 2003, resulting in about 22% unscanned gap pixels in the SLC-off images, affecting greatly the utility of the ETM+ data. To address this issue, we propose a spatial-spectral radial basis function (SSRBF)-based interpolation method to fill gaps in SLC-off images. Different from the conventional spatial-only radial basis function (RBF) that has been widely used in other domains, SSRBF also integrates a spectral RBF to increase the accuracy of gap filling. Concurrently, global linear histogram matching is applied to alleviate the impact of potentially large differences between the known and SLC-off images in feature space, which is demonstrated mathematically in this article. SSRBF fully exploits information in the data themselves and is user-friendly. The experimental results on five groups of data sets covering different heterogeneous regions show that the proposed SSRBF method is an effective solution to gap filling, and it can produce more accurate results than six popular benchmark methods. CCB

Remote Sensing and Modeling of Stressed Aquifer Systems and the Associated Hazards

abstract: Aquifers host the largest accessible freshwater resource in the world. However, groundwater reserves are declining in many places. Often coincident with drought, high extraction rates and inadequate replenishment result in groundwater overdraft and permanent land subsidence. Land subsidence is the cause of aquifer storage capacity reduction, altered topographic gradients which can exacerbate floods, and differential displacement that can lead to earth fissures and infrastructure damage. Improving understanding of the sources and mechanisms driving aquifer deformation is important for resource management planning and hazard mitigation. Poroelastic theory describes the coupling of differential stress, strain, and pore pressure, which are modulated by material properties. To model these relationships, displacement time series are estimated via satellite interferometry and hydraulic head levels from observation wells provide an in-situ dataset. In combination, the deconstruction and isolation of selected time-frequency components allow for estimating aquifer parameters, including the elastic and inelastic storage coefficients, compaction time constants, and vertical hydraulic conductivity. Together these parameters describe the storage response of an aquifer system to changes in hydraulic head and surface elevation. Understanding aquifer parameters is useful for the ongoing management of groundwater resources. Case studies in Phoenix and Tucson, Arizona, focus on land subsidence from groundwater withdrawal as well as distinct responses to artificial recharge efforts. In Christchurch, New Zealand, possible changes to aquifer properties due to earthquakes are investigated. In Houston, Texas, flood severity during Hurricane Harvey is linked to subsidence, which modifies base flood elevations and topographic gradients.Dissertation/ThesisDoctoral Dissertation Geological Sciences 201

Relleno de datos de velocidades de viento mediante la aplicación de método de Hot Deck para la estimación de producción de energía eléctrica en base al recurso eólico

Durante las campañas de medición de viento en las estaciones meteorológicas, pueden sucederse condiciones atípicas que producen la pérdida de datos ya sea por falla del equipo, por falla en el suministro eléctrico de respaldo, por saturación de espacio de almacenamiento, entre otras. Por tanto, es necesario que las series de datos sean completadas, tratando de reducir la incertidumbre en el proceso. En el presente trabajo se trabaja con datos de velocidades de viento proporcionadas por la estación meteorológica instalada en la Universidad Politécnica Salesiana. Sede Quito – Campus Sur. Los datos registrados de forma horaria se encuentran completos y validados por el método de las Rachas. En base a la serie completa se obtienen 3 series de datos adicionales quitando de manera aleatoria el 10, 40 y 70% de datos. Aplicando el método de Hot-Deck se completan las series construidas y se realizan comparaciones con la serie de datos original completa. Para la estimación de producción de energía eléctrica se utiliza la Distribución de Weibull. Finalmente, se muestran los resultados en los que se analizan la efectividad del llenado de datos conforme a los escenarios propuestos. Para el desarrollo del trabajo se ha empleado las ayudas computacionales RStudio y Matlab.During the wind measurement campaigns in the weather stations, atypical conditions can occur that produce the loss of data either by equipment failure, by backup power supply failure, by storage space saturation, among others. Therefore, it is necessary that the data series be complete, try to reduce the uncertainty in the process. In this work we work with wind speed data provided by the weather station installed at the Salesian Polytechnic University. Quito Headquarters - South Campus. The data recorded on an hourly basis is complete and validated by the Rachas method. Based on the complete series, 3 additional data series will be needed, randomly citing 10, 40 and 70% of data. Applying the Hot-Deck method, the constructed series are completed and comparisons are made with the complete original data series. Weibull Distribution is used for the modification of electric energy production. Finally, there are the results in which the effectiveness of data submission is analyzed according to the proposed scenarios. RStudio and Matlab computational aids have been used for the development of the work

Mountain Glacier Change Across Regions and Timescales

Mountain glaciers have influenced the surface of our planet throughout geologic time. These large reservoirs of water ice sculpt alpine landscapes, regulate downstream river flows, perturb climate-tectonic feedbacks, contribute to sea level change, and guide human migration and settlement patterns. Glaciers are especially relevant in modern times, acting as buffers which supply seasonal meltwater to densely populated downstream communities and support economies via hydropower generation. Anthropogenic warming is accelerating ice loss in most glacierized regions of the world. This has sparked concerns regarding water resources and natural hazards, and placed glaciers at the forefront of climate research. Here we provide new observations of glacier change in key mountain regions to quantify rates of ice loss, better understand climate drivers, and help establish a more unified framework for studying glacier change across timescales. In Chapter 1 we use seismic observations, numerical modeling, and geomorphic analysis to investigate a destructive glacial lake outburst flood (GLOF) which occurred in Bhutan. GLOFs are a substantial hazard for downstream communities in many vulnerable regions. Yet key aspects of GLOF dynamics remain difficult to quantify, as in situ measurements are scarce due to the unpredictability and remote source locations of these events. Here we apply cross-correlation based seismic analyses to track the evolution of the GLOF remotely (~100 km from the source region), use the seismic observations along with eyewitness reports and a downstream gauge station to constrain a numerical flood model, then assess geomorphic change and current state of the unstable lakes via satellite imagery. Coherent seismic energy is evident from 1 to 5 Hz beginning approximately 5 hours before the flood impacted Punakha village, which originated at the source lake and advanced down the valley during the GLOF duration. Our analysis highlights potential benefits of using real-time seismic monitoring to improve early warning systems. The next two chapters in this work focus on quantifying multi-decadal glacier ice loss in the Himalayas. Himalayan glaciers supply meltwater to densely populated catchments in South Asia, and regional observations of glacier change are needed to understand climate drivers and assess impacts on glacier-fed rivers. Here we utilize a set of digital elevation models derived from cold war–era spy satellite film and modern stereo satellite imagery to evaluate glacier responses to changing climate over the last four decades. In Chapter 2 we focus on the eastern Himalayas, centered on the Bhutan–China border. The wide range of glacier types allows for the first mass balance comparison between clean, debris, and lake-terminating (calving) glaciers in the area. Measured glaciers show significant ice loss, with statistically similar mass balance values for both clean-ice and debris-covered glacier groups. Chapter 3 extends the same methodology to quantify glacier change across the entire Himalayan range during 1975–2000 and 2000–2016. We observe consistent ice loss along the entire 2000-km transect for both intervals and find a doubling of the average loss rate during 2000–2016 compared to 1975–2000. The similar magnitude and acceleration of ice loss across the Himalayas suggests a regionally coherent climate forcing, consistent with atmospheric warming and associated energy fluxes as the dominant drivers of glacier change. Chapter 4 investigates millennial-scale glacier changes during the Late Glacial period (15-11 ka). Here we present a high-precision beryllium-10 chronology and geomorphic map from a sequence of well-preserved moraines in the Nendaz valley of the western European Alps, with the goal to shed light on the timing and magnitude of glacier responses during an interval of dramatic natural climate variability. Our chronology brackets a coherent glacier recession through the Younger Dryas stadial into the early Holocene, similar to glacier records from the southern hemisphere and a new chronology from Arctic Norway. These results highlight a general agreement between mountain glacier changes and atmospheric greenhouse gas records during the Late Glacial. In Chapter 5 we use a numerical glacier model to simulate glacier change across a typical alpine region in the European Alps. Model results suggest that shorter observational timespans focused on modern periods (when glaciers are far from equilibrium and undergoing rapid change) exhibit greater spatial variability of mean annual ice thickness changes, compared to intervals which extend further back in time (to include decades when climate was more stable). The model agrees with multi-decadal satellite observations of glacier change, and clarifies the positive correlation between glacier disequilibrium and spatial variability of glacier mass balance. This relationship should be taken into account in regional glacier studies, particularly when analyzing recent spatial patterns of ice loss. Advances made in this work are of practical value for societies vulnerable to glacier change. This includes potential improvements to GLOF early warning systems via seismic monitoring, better constraints on glacier-sourced water scenarios in South Asia, strengthened understanding of long-term glacier responses to baseline natural climate variability, and a clarified relationship between glacier disequilibrium and spatial variability of ice loss. When placed within a global context, our observations highlight the correlation between regional mountain glacier change and greenhouse gas forcing through time

Applications of Unmanned Aerial Systems (UASs) in Hydrology: A Review

In less than two decades, UASs (unmanned aerial systems) have revolutionized the field of hydrology, bridging the gap between traditional satellite observations and ground-based measurements and allowing the limitations of manned aircraft to be overcome. With unparalleled spatial and temporal resolutions and product-tailoring possibilities, UAS are contributing to the acquisition of large volumes of data on water bodies, submerged parameters and their interactions in different hydrological contexts and in inaccessible or hazardous locations. This paper provides a comprehensive review of 122 works on the applications of UASs in surface water and groundwater research with a purpose-oriented approach. Concretely, the review addresses: (i) the current applications of UAS in surface and groundwater studies, (ii) the type of platforms and sensors mainly used in these tasks, (iii) types of products generated from UAS-borne data, (iv) the associated advantages and limitations, and (v) knowledge gaps and future prospects of UASs application in hydrology. The first aim of this review is to serve as a reference or introductory document for all researchers and water managers who are interested in embracing this novel technology. The second aim is to unify in a single document all the possibilities, potential approaches and results obtained by different authors through the implementation of UASs

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production