Shifts in Vegetation Cover of Southern California Deserts in Response to Recent Climate Variations

In the deserts of Southern California, air temperatures have been rising and precipitation variability has been increasing over the past several decades. These recent climate shifts may have begun to threaten the survival of certain plant and animal species in these arid ecosystems. This study was designed to quantify and characterize variations in vegetation canopy density using more than 30 consecutive years of Landsat satellite image data across the western Lower Colorado (Sonoran) and southern Mojave Desert region. Mapping of the normalized difference vegetation index (NDVI) from Landsat images (1985 to 2017), which has been closely correlated with percent cover measurements of green vegetation canopies in a variety of arid ecosystems, was used to detect periodic upslope and downslope shifts in plant cover. The change in Landsat NDVI between 1985 and 2017 within the Santa Rosa Mountains Wilderness at four elevation zones between 500 m and 2500 m showed that vegetation green cover dropped notably in below-average precipitation periods, whereas green cover increased sharply in above-average precipitation years. This same temporal pattern of shifting in NDVI was detected along steep elevation gradients in the Anza-Borrego Desert State Park and in the Little San Bernardino Mountains of Joshua Tree National Park. Although the distribution of the dominant plant species along elevation gradients may have increased by more than 60 m over several decades (prior to 2007), we found no evidence that upslope shifts in percent plant cover have yet become a permanent pattern at these mountainous desert sites

Multiple-input multiple-output wireless communications with imperfect channel knowledge

In the first work a recurrent neural network (RNN) is employed for MIMO channel prediction. A novel PSO-EA-DEPSO off-line training algorithm is presented and is shown to outperform PSO, PSO-EA, and DEPSO. This predictor is shown to be robust to varying channel scenarios. New expressions for the received SNR, array gain, average probability of error, and diversity gain are derived. Next, a new expression for the outage capacity of a MIMO system with no CSI at the transmitter and an estimate at the receiver is presented. Since the outage capacity is a function of the first and second moments of the mutual information, new closed form approximations are derived at low and high effective SNR. Also at low effective SNR a new result for the outage capacity is presented. Finally, the outage capacity for a frequency selective channel is derived. This is followed by a MIMO RNN predictor that operates online. A single RNN is constructed to predict all of the MIMO sub-channels instantaneously. The extended Kalman filter (EKF) and real-time recurrent learning (RTRL) algorithms are applied to compare the MSE of the prediction error. A new expression for the channel estimation error of a continuously varying MIMO channel is derived next. The optimal amount of time to send training pilots is investigated for different channel scenarios. Special cases of the new expression for the channel estimation error lead to previously established results. The last work investigates the performance of a MIMO aeronautical system in a two- ray ground reflection scenario. The ergodic capacity is analyzed when the altitude, horizontal displacement, antenna separation, and aircraft velocity are varied --Abstract, page iv

Seismic analysis of a typical masonry building from Barcelona's Eixample district

The historic Eixample district of Barcelona is characterised by its beautiful avenues, laid out in grid across the city. At first impression, the buildings lining these avenues appear identical, an unending façade built to house the new Barcelona of the 20th Century. The unreinforced masonry buildings that typify the development remain in use today, largely unaltered since their construction. Unreinforced masonry buildings are among the most vulnerable structures to damage from seismic actions. For the masonry buildings of the Eixample that house over 15% of the population of Barcelona, this is no exception. This study performs a seismic analysis on a typical masonry building of the Eixample to estimate and assess this damage. By doing so, it aims to estimate the likely damage due to seismic actions, to identify critical elements of the structures and to quantify the need for seismic risk maintenance and response plans. The analysis uses the N2 Capacity Spectrum Method (Fajfar, 2000), adopted by Eurocode 8, to determine the displacement demand of possible earthquake scenarios. A seismic hazard analysis determines the seismic demand using deterministic, probabilistic and current European and Spanish code provisions. The seismic demand is then compared to the results of a non-linear pushover analysis completed using software DIANA (Version 9.4). The model geometry was based upon plans of a building that well represents the typical unreinforced masonry buildings of the Eixample. Results indicate a displacement demand to Spanish code provisions that corresponds to a substantial level of damage, in accordance with the European Macroseismic Scale (EMS 98) damage criteria. A moderate level of damage is derived from the probabilistic seismic scenario. Similar to previous studies, these results indicate a significant risk of seismic damage. The analysis has isolated critical structural elements that control the global response and damage during seismic action. This information can be used to develop inspection and maintenance plans to limit the risk of seismic damage. This study highlights the real risk of seismic damage to the typical unreinforced masonry buildings of the Eixample district. It determines appropriate building maintenance procedures, and reinforces the need for seismic response planning to best manage the significant expected social and infrastructure demands should such a disastrous event ever occur

Vegetation Cover Change in Yosemite National Park (California) Detected using Landsat Satellite Image Analysis

Landsat image analysis over the past 20+ years showed that consistent increases in the satellite normalized difference vegetation index (NDVI) during relatively dry years were confined to large wildfire areas that burned in the late 1980s and 1990s

Remote Sensing Monitoring Methods for Detecting Invasive Weed Coverage in Delta Waterways and Bay Marshlands

This presentation is part of the Independent Science Board of the State of California Delta Stewardship Council brown bag seminar series on the "How the Delta is Monitored", followed with a panel discussion. Various remote sensing approaches for aquatic vegetation will be reviewed. Key research and application issues with remote sensing monitoring in the Delta will be addressed

Changes in Vegetation Cover of the Arctic National Wildlife Refuge Estimated from MODIS Greenness Trends, 2000 to 2018

The Arctic National Wildlife Refuge (ANWR) was established in 1980 and covers 19 million acres (77,000 km2) in northeast Alaska. Wildlife habitats in the ANWR are vulnerable to long-lasting effects from any disturbance, in part because short growing seasons in the arctic provide limited time for species to recover. Trends and transitions in the growing season MODerate resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time-series at 250-m resolution were analyzed for the period from 2000 to 2018 to understand recent patterns of vegetation change in all ecoregions of the ANWR. Statistical analysis of changes in each MODIS pixel NDVI time series was conducted using the "Breaks for Additive Seasonal and Trend" method (BFAST) to map regional change rates. Results suggested that most negative NDVI anomalies in the tundra-covered river drainages of the Brooks Range Mountains and coastal plain have been associated with early spring thawing and elevated levels of surface moisture in low elevation drainages of the northern ANWR ecoregions

Mapping the Distribution and Biomass of Emergent Aquatic Plants in the Sacramento-San Joaquin River Delta of California Using Landsat Imagery Analysis

This study evaluated the cost-effective and timely use of Landsat imagery to map and monitor emergent aquatic plant biomass and to filter satellite image products for the most probable locations of water hyacinth coverage in the Delta based on field observations collected immediately after satellite image acquisition

Thirty Years of Change in Subalpine Forest Cover from Landsat Image Analysis in the Sierra Nevada Mountains of California

Landsat imagery was analyzed to understand changes in subalpine forest stands since the mid-1980s in the Sierra-Nevada region of California. At locations where long-term plot measurements have shown that stands are becoming denser in the number of small tree stems (compared to the early 1930s), the 30-year analysis of Landsat greenness index (NDVI) indicated that no consistent increases in canopy leaf cover have occurred at these same locations since the mid-1980s. Interannual variations in stand NDVI closely followed snow accumulation amounts recorded at nearby stations. In contrast, at eastern Sierra whitebark pine stand locations where it has been observed that widespread tree mortality has occurred, decreasing NDVI trends over the past 5-10 years were consistent with rapid loss of forest canopy cover. Landsat imagery was further analyzed to understand patterns of post-wildfire vegetation recovery, focusing on high burn severity (HBS) patches within burned areas dating from the late 1940s. Analysis of landscape metrics showed that the percentage of total HBS area comprised by the largest patch of recovered woody cover was relatively small in all fires that occurred since 1995, but increased rapidly with time since fire. Patch complexity of recovered woody cover decreased notably after more than 50 years of regrowth, but was not readily associated with time for fires that occurred since the mid 1990s. The aggregation level of patches with recovery of woody cover increased steadily with time since fire. The study approach using satellite remote sensing can be expanded to assess the consequences of stand-replacing wildfires in all forests of the region

Landscape Patterns of Burn Severity in the Soberanes Fire of 2016

The Soberanes Fire started on July 22, 2016 in Monterey County on the California Central Coast from an illegal campfire. This fire burned for 10 weeks at a record cost of more than $208 million for protection and control. A progressive analysis of the normalized burn ratio from the Landsat satellite showed that the final high burn severity (HBS) area for the Soberanes Fire comprised 22 percent of the total area burned, whereas final moderate burn severity (MBS) area comprised about 10 percent of the total area burned of approximately 53,470 ha (132,130 acres). The resulting landscape pattern of burn severity classes from the 2016 Soberanes Fire revealed that the majority of HBS area was located in the elevation zone between 500 and 1000 m, in the slope zone between 15 percent and 30 percent, or on south-facing aspects

Ten Years of Vegetation Change in Northern California Marshlands Detected using Landsat Satellite Image Analysis

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in perennial vegetation cover at marshland sites in Northern California reported to have undergone restoration between 1999 and 2009. Results showed extensive contiguous areas of restored marshland plant cover at 10 of the 14 sites selected. Gains in either woody shrub cover and/or from recovery of herbaceous cover that remains productive and evergreen on a year-round basis could be mapped out from the image results. However, LEDAPS may not be highly sensitive changes in wetlands that have been restored mainly with seasonal herbaceous cover (e.g., vernal pools), due to the ephemeral nature of the plant greenness signal. Based on this evaluation, the LEDAPS methodology would be capable of fulfilling a pressing need for consistent, continual, low-cost monitoring of changes in marshland ecosystems of the Pacific Flyway