Environmental Monitoring Commons^™

Time Series Decomposition Of Land Surface Temperature For Long-Term Trend Forecasting And Impact On Nesting Sea Turtle Habitats In The Arabian Gulf, Sachi Perera, Rommel H. Maneja, Mohamed Allali, Cyril Rakovski, Erik Linstead, Daniele Struppa, Ali Qasem, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Improving land surface temperature (LST) modeling is vital for mitigating climate change effects on various ecosystems and marine habitats such as important sea turtle habitats. Over the past decade, extreme temperatures have likely significantly affected nesting sea turtle habitats in the Arabian Gulf, with predominantly female hatchlings creating an imbalance in the sex ratio. Such shifts have profound implications for these habitats’ long-term survival and conservation management. This study leverages statistical machine learning models to measure ongoing temporal variations in LST. We break down the LST time series into trend, seasonal, and noise components using classical decomposition methods like X11, …

Multi-Temporal Analysis Of Urbanization-Driven Slope And Ecological Impact Using Machine-Learning And Remote Sensing Techniques, Zhang Hao, Muhammad Haseeb, Zheng Xiangtian, Zainab Tahir, Syed Amer Mahmood, Aqil Tariq, Rana Waqar Aslam, M. Abdullah-Al-Wadud, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Rapid urbanization in Lahore, Pakistan, has led to significant ecological and thermal challenges, particularly the intensification of Urban Heat Island (UHI) effects and increased thermal stress as measured by the Urban Thermal Field Variance Index (UTFVI). This study employs a multi-temporal evaluation of Landsat satellite imagery and GIS-based analysis to investigate the Spatio-temporal trends in land-use and land-cover (LULC) changes from 1994 to 2024. We detected substantial changes in urban growth, vegetation cover, and barren areas using supervised classification (Random Forest) methods and remote sensing indices such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), NDBI (Normalized …

Spatial Gap-Filling Of Himawari-8 Hourly Aod Products Using Machine Learning With Model-Based Aod And Meteorological Data: A Focus On The Korean Peninsula, Youjeong Youn, Seoyeon Kim, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

Given the complex spatiotemporal variability of aerosols, high-frequency satellite observations are essential for accurately mapping their distribution. However, optical remote sensing encounters difficulties in detecting Aerosol Optical Depth (AOD) over cloud-covered regions, creating data gaps that limit comprehensive environmental analysis. This study introduces a spatial gap-filling method for Himawari-8/Advanced Himawari Imager (AHI) hourly AOD data, using a Random Forest (RF) model that integrates meteorological variables and model-based AOD data. Developed and validated over South Korea from 1 January to 31 December 2019, the model effectively improved data coverage from 6% to 100%. The approach demonstrated high performance in blind tests, …

Changing Characteristics Of Land Cover, Landscape Pattern And Ecosystem Services In The Bohai Rim Region Of China, Jiaqi Liu, Wei Chen, Hu Ding, Zhanhang Liu, Min Xu, Ramesh P. Singh, Congqiang Liu

Mathematics, Physics, and Computer Science Faculty Articles and Research

Since the Anthropocene, ecosystems have been continuously deteriorating due to global climate change and human intervention. Exploring the changing characteristics of land use/land cover (LULC), landscape pattern and ecosystem service (ES) and their drivers is crucial for regional ecosystem management and sustainable development. Taking the Bohai Rim region of China as an example, we used the land use transfer matrix, landscape pattern index and InVEST model to analyze the changing characteristics of LULC, landscape pattern and six key ESs [crop production (CP), water yield (WY), carbon storage (CS), soil conservation (SC), habitat quality (HQ), landscape aesthetics (LA)] during 2000–2020. Detailed …

Coupling Between Evapotranspiration, Water Use Efficiency, And Evaporative Stress Index Strengthens After Wildfires In New Mexico, Usa, Ryan C. Joshi, Annalise Jensen, Madeleine Pascolini-Campbell, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Aim

Methods

Results …

Examining Wildfire Dynamics Using Ecostress Data With Machine Learning Approaches: The Case Of South-Eastern Australia's Black Summer, Yuanhui Zhu, Shakthi B. Murugesan, Ivone K. Masara, Soe W. Myint, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Wildfires are increasing in risk and prevalence. The most destructive wildfires in decades in Australia occurred in 2019–2020. However, there is still a challenge in developing effective models to understand the likelihood of wildfire spread (susceptibility) and pre-fire vegetation conditions. The recent launch of NASA's ECOSTRESS presents an opportunity to monitor fire dynamics with a high resolution of 70 m by measuring ecosystem stress and drought conditions preceding wildfires. We incorporated ECOSTRESS data, vegetation indices, rainfall, and topographic data as independent variables and fire events as dependent variables into machine learning algorithms applied to the historic Australian wildfires of 2019–2020. …

Roaded Catchments In Wa, Department Of Primary Industries And Regional Development, Western Australia

Natural resources factsheets

Roaded catchments are earthwork structures designed to increase the amount of run-off from the catchment above a receiving farm dam.

Roaded catchments are lined with clay and compacted to make a smooth surface that reduces infiltration and increases run-off. Roaded catchments should discharge into a silt trap and then into a dam (excavated earth tank). This combined structure should be fenced to exclude livestock.

The Department of Primary Industries and Regional Development recommends that roaded catchments are part of an integrated water and salinity management program.

The information in this page is only a guide – seek expert advice before …

Greenhouse Gas Accounting For Western Australian Agriculture 2022, Johnny Machon, Mandy Curnow, Christophe D'Abbadie

Climate Science Published Reports

This report presents new modelling of the greenhouse gas emissions attributable to Western Australia’s agricultural industries and provides an overview of sequestration at the state level. The report improves and expands on the estimates from previous technical reports by the Department of Primary Industries and Regional Development (DPIRD), most notably Curnow et al. (2022). The report presents a new, much broader picture, capturing not only emissions from agricultural activities in Western Australia (WA), but also the emissions associated with the production of agricultural inputs and the sequestration that occurs on agriculturally managed lands. This broader picture of emissions aligns with …

Carbon Restoration Potential On Global Land Under Water Resource Constraints, Shouzhang Peng, César Terrer, Benjamin Smith, Philippe Ciais, Qinggong Han, Jialan Nan, Joshua B. Fisher, Liang Chen, Lei Deng, Kailiang Yu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Ecosystem restoration is a critical nature-based solution to mitigate climate change. However, the carbon sequestration potential of restoration, defined as the maximum achievable carbon storage, has likely been overestimated because previous studies have not adequately accounted for the competition between ecosystem water demands for maximizing carbon sequestration and human water needs. Here we used a comprehensive process-based model combined with extensive land-use data and evaporation recycling accounting for land–atmosphere feedback to estimate the water requirements associated with ecosystem restoration. We found that achieving the carbon sequestration potential of restoration would significantly reduce global water availability per capita by 26%, posing …

Challenges Of Using More Precise Temporal And Spatial Resolution Of Remote Sensing Data For Surface Water Quality Monitoring, Ivan Rykin

Dartmouth College Master’s Theses

Monitoring river suspended sediment concentration (SSC) is critical for environmental challenges such as understanding the fate of thawed permafrost sediment and its impact on global carbon cycling. However, traditional SSC monitoring using Landsat imagery is limited by spatial and temporal constraints, particularly for narrow rivers in cloudy and/or snowy regions.

This study investigates the use of higher spatial (3 m) and temporal (daily) resolution satellite imagery from the PlanetScope constellation to estimate SSC in remote rivers such as those in the Arctic. I compare the performance of PlanetScope’s spectral resolution (4 and 8 bands) with Landsat 7. Merging data from …

Seasonal Dynamics In Land Surface Temperature In Response To Land Use Land Cover Changes Using Google Earth Engine, Lei Feng, Sajjad Hussain, Narcisa G. Pricope, Sana Arshad, Aqil Tariq, Li Feng, Muhammad Mubeen, Rana Waqar Aslam, Mohammed S. Fnais, Wenzhao Li, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Changes in land use and land cover (LULC) are critical for evaluating global spatiotemporal trends, especially regarding climate change and urbanization. This study investigates the dynamics of Landsat surface temperature (LST) in response to LULC changes and their effects on the seasonal microclimate in Kasur District, Pakistan. Using the Google Earth Engine platform, we employed a random forest algorithm to detect LULC changes (cropland, forest, built-up, fallow, barren, and water) and analyze seasonal spectral indices from Landsat imagery for 1988, 2002, and 2022. Significant LULC changes were observed, including a 9.8% increase in built-up areas, a 4.2% decrease in cropland, …

A Generalized Machine Learning Model For Long-Term Coral Reef Monitoring In The Red Sea, Justin J. Gapper, Surendra Maharjan, Wenzhao Li, Erik Linstead, Surya Prakash Tiwari, Mohamed A. Qurban, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Coral reefs, despite covering less than 0.2 % of the ocean floor, harbor approximately 35 % of all known marine species, making their conservation critical. However, coral bleaching, exacerbated by climate change and phenomena such as El Niño, poses a significant threat to these ecosystems. This study focuses on the Red Sea, proposing a generalized machine learning approach to detect and monitor changes in coral reef cover over an 18-year period (2000–2018). Using Landsat 7 and 8 data, a Support Vector Machine (SVM) classifier was trained on depth-invariant indices (DII) derived from the Gulf of Aqaba and validated against ground …

Growing Oaten Hay On Frost Prone Paddocks, Department Of Primary Industries And Regional Development, Western Australia

Grains and other field crops factsheets

Growing oaten hay on frost-prone paddocks minimises the frost risk because it is cut soon after flowering, avoiding the frost sensitive period. If severe frost damage occurs to other crops, baling them for hay may reduce economic loss.

Oats are much more tolerant than other cereals to frost events that occur during vegetative growth and flowering.

Balloon Borne Gps-Enabled Radiosondes That Enable Simultaneous Multi-Point Atmospheric Sensing With A Single Ground Station, Peter A. Ribbens

Doctoral Dissertations and Master's Theses

Radiosondes are balloon borne atmospheric instruments that are a critical tool for understanding dynamics in the lower layers of the atmosphere. The low-cost radiosondes developed in the Space and Atmospheric Instrumentation Lab have been further developed to improve the system's use as a science-quality atmospheric instrument that is unique in its ability to simultaneously track multiple sondes with a single ground station. Sensors to measure temperature and pressure were added to improve measurements of the atmospheric state. A printed circuit board shield and 3D-printed shell were designed to make mass manufacturing possible. A thermistor-based temperature sensor was developed and tested …

Linkages Of The 2022 Unprecedented Global Heatwave Events To Triple-Dip La Niña, Sachi Perera, Joshua B. Fisher, Mohamed Allali, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Heatwaves are influenced significantly by El Niño-Southern Oscillation (ENSO), which alters temperature and precipitation patterns throughout the world. Since 2020, we have witnessed a "triple dip" La Niña conditions persisting for three consecutive years resulting in severe weather and climate driven events globally. In this study, we identified the dominant frequency of Niño 3.4 Sea Surface Temperature (SST) signals and correlated them with regions experiencing unprecedented heat waves in 2022, namely, the Indian Ocean, the North Atlantic around England and Spain, and the Mediterranean Sea. The signal's power spectrum and its three highest power components are determined based on the …

Enhancing Sustainable Development Goals Through Future Vapor Pressure Deficit Analysis In The Nile River Basin, Surendra Maharjan, Wenzhao Li, Shahryar Fazli, Hani Sewilam, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Vapor Pressure Deficit (VPD) is crucial in meteorology and agriculture for understanding plant-environment interactions. Its application as an indicator in agricultural practices notably advances Sustainable Development Goals such as Zero Hunger (SDG 2) and Climate Action (SDG 13). This research focuses on the impact of climate change on agricultural productivity and food security in the Nile River Basin (NRB), emphasizing the role of VPD, temperature, and precipitation. Utilizing Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets from NEX-GDDP-CMIP6, the study analyzes key climatic variables that influence agricultural conditions. The study applies the Mann-Kendall test to evaluate VPD trends from 2000 …

Assessment And Prediction Of Meteorological Drought Using Machine Learning Algorithms And Climate Data, Khalid En-Nagre, Mourad Aqnouy, Ayoub Ouarka, Syed Ali Asad Naqvi, Ismail Bouizrou, Jamal Eddine Stitou El Messari, Aqil Tariq, Walid Soufan, Wenzhao Li, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Monitoring drought in semi-arid regions due to climate change is of paramount importance. This study, conducted in Morocco’s Upper Drâa Basin (UDB), analyzed data spanning from 1980 to 2019, focusing on the calculation of drought indices, specifically the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at multiple timescales (1, 3, 9, 12 months). Trends were assessed using statistical methods such as the Mann-Kendall test and the Sen’s Slope estimator. Four significant machine learning (ML) algorithms, including Random Forest, Voting Regressor, AdaBoost Regressor, and K-Nearest Neighbors Regressor, were evaluated to predict the SPEI values for both three …

Identifying High-Value Tactical Livestock Decisions On A Mixed Enterprise Farm In A Variable Environment, Michael Young, John Young, Ross S. Kingwell, Philip E. Vercoe

Animal production and livestock research articles

Context

Australia is renowned for its climate variation, featuring years with drought and years with floods, which result in significant production and profit variability. Accordingly, to maximise profitability, dryland farming systems need to be dynamically managed in response to unfolding weather conditions.

Aims

The aim of this study is to identify and quantify optimal tactical livestock management for different weather-years.

Methods

This study employed a whole-farm optimisation model to analyse a representative mixed enterprise farm located in the Great Southern region of Western Australia. Using this model, we investigated the economic significance of five key livestock management tactics. These included …

Glacier Lake Inventory And Lake Outburst Flood Hazard Assessment In Kanchenjunga Conservation Area, Nepal, Prabish Khadka Chhetri

Theses

This study presents a comprehensive assessment of glacial lakes and land surface temperature (LST) dynamics within the Kanchenjunga Conservation Area (KCA) from 2010 to 2023. The KCA holds significant ecological importance, serving as a critical habitat for diverse flora and fauna, while also playing a vital role in regional hydrological systems. Additionally, its stunning landscapes attract tourists and mountaineers from around the world, further emphasizing the need for understanding environmental changes within the area. Utilizing medium to high-resolution satellite imagery from PlanetScope for glacial mapping and Landsat for LST analysis, the research aimed to achieve two primary objectives: creating an …

Understanding The Zonal Variability In Cmip6 Projections Of Sahelian Precipitation, Emmanuel Ogwuche Audu

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

The uncertainty in model projections of future precipitation across the Sahel has persisted across many generations of Earth System Models (ESMs), with some models predicting drying and others moistening across this region. These discrepancies in future projections pose a challenge for stakeholders and decision makers. Many projections of Sahel precipitation found in the ESMs participating in the sixth phase of Coupled Model Intercomparison Project (CMIP6) show a zonal dipole in precipitation trend, with moistening across the Central and Eastern Sahel and drying projected for the Western Sahel. Previous studies have connected precipitation variability across the Sahel to changes in various …

Polarimetric Radar Signatures In Significant Severe Left-Moving Supercells, Raychel Nelson

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Left-moving (LM) supercells, though rarer than right-moving (RM) supercells, may produce significant severe weather. However, there are very few existing studies on LM supercells, particularly polarimetric radar analyses. The upgrade of the nationwide Weather Surveillance Radar-1988 Doppler (WSR-88D) network to polarimetric capability and subsequent studies vastly improved understanding of RM supercells, but similar efforts have largely not been made for LM supercells. This study employs an automated polarimetric radar signature detection algorithm to examine a dataset of significant severe (hail ≥ 2.00”, wind ≥ 65 kts) LM supercells to quantify their polarimetric signatures. Comparisons are made with RM supercells to …

A Dual-Polarimetric Analysis Of A Large Sample Of Left-Moving Supercells, Ben Schweigert

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Supercells have been researched extensively since they were first described over 50 years ago. They are prolific severe weather producers, responsible for the most severe hail, severe wind gusts, and tornadoes. These rotating thunderstorms require attention from forecasters to protect life and property from their threats, most effectively done with Doppler radars. While extensive amounts of radar-based investigations have been completed, they focused almost exclusively on right-moving (RM) supercells, resulting in a knowledge gap surrounding their counter-rotating (left-moving, LM) partners. This study works to fill the void by developing a dataset of LM supercells and analyzing the dual-polarimetric features observed …

Net Fluxes Of Broadband Shortwave And Photosynthetically Active Radiation Complement Ndvi And Near Infrared Reflectance Of Vegetation To Explain Gross Photosynthesis Variability Across Ecosystems And Climate, Kanishka Mallick, Joseph Verfaillie, Tianxin Wang, Ariane Arias Ortiz, Daphne Szutu, Koong Yi, Yanghui Kang, Robert Shortt, Tian Hu, Mauro Sulis, Zoltan Szantoi, Gilles Boulet, Joshua B. Fisher, Dennis Baldocchi

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

A significant challenge in global change research is understanding how vegetation interacts with the environment to influence ecosystem gross primary productivity (GPP) through carbon assimilation. One emerging objective is to consistently predict GPP fluctuations worldwide by establishing a robust scaling relationship between GPP measured at flux towers and satellite spectral reflectance data. However, a major hurdle in achieving this goal is the discrepancy in spatial resolution between early satellite measurements and eddy flux measurements. By using a large set of growing season data covering 100 site-years in North and Central America, we explored the potential of transforming incident and reflected …

The Role Of Geomorphological Context In Vegetative Succession Within The Breiðamerkurjökull Glacial Foreland, Lucas Nerbonne

Independent Study Project (ISP) Collection

As glaciers retreat worldwide at an accelerating pace, understanding primary succession in these newly exposed landscapes becomes increasingly critical. This study examines the initial vegetative colonization patterns in glacial forelands, focusing on the influence of geomorphological formations of resulting plant communities. By analyzing vegetative communities in glaciofluvial and push moraine deposits, this study highlights how the more varied, channelized morphologies of fluvial deposits create potential microclimates better conducive to heterogenous plant colonization than the homogenous terrain of the nearby push moraine. Vegetative coverage, sediment size, and species abundance was collected at 480 sites across 6 different historical glacial extents across …

Ground Electric Field, Atmospheric Weather And Electric Grid Variations In Northeast Greece Influenced By The March 2012 Solar Activity And The Moderate To Intense Geomagnetic Storms, Georgios Anagnostopoulos, Anastasios Karkanis, Athanasios Kampatagis, Panagiotis Marhavilas, Sofia-Anna Menesidou, Dimitrios Efthymiadis, Stefanos Keskinis, Dimitar Ouzounov, Nick Hatzigeorgiu, Michael Danakis

Mathematics, Physics, and Computer Science Faculty Articles and Research

In a recent paper, we extended a previous study on the solar solar influence to the generation of the March 2012 heatwave in the northeastern USA. In the present study we check the possible relationship of solar activity with the early March 2012 bad weather in northeast Thrace, Greece. To this end, we examined data from various remote sensing instrumentation monitoring the Sun (SDO satellite), Interplanetary space (ACE satellite), the Earth’s magnetosphere (Earth-based measurements, NOAA-19 satellite), the top of the clouds (Terra and Aqua satellites), and the near ground atmosphere. Our comparative data analysis suggests that: (i) the winter-like weather …

Evaluating Future Water Availability In Texas Through The Lens Of A Data-Driven Approach Leveraged With Cmip6 General Circulation Models, Wenzhao Li, Dongfeng Li, Hesham El-Askary, Joshua B. Fisher, Zheng N. Fang

Mathematics, Physics, and Computer Science Faculty Articles and Research

Climate change is escalating the frequency and intensity of extreme precipitation events, significantly influencing the spatial and temporal distributions of water resources. This is particularly evident in Texas, a rapidly growing state with a pronounced west-east gradient in water supply. This study utilizes Coupled Model Intercomparison Project Phase 6 (CMIP6) data and data-driven methodology to improve projections of Texas's future water resources, focusing on actual evapotranspiration (AET) and water availability through enhanced Multi-Model Ensembles. The results reveal that the data-driven model significantly outperforms the CMIP5 and CMIP6 models across all skill metrics, underscoring the potential of data-driven methodologies in advancing …

Water Whiplash In Mediterranean Regions Of The World, Citlalli Madrigal, Rama Bedri, Thomas Piechota, Wenzhao Li, Glenn Tootle, Hesham El-Askary

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The presence of weather and water whiplash in Mediterranean regions of the world is analyzed using historical streamflow records from 1926 to 2023, depending on the region. Streamflow from the United States (California), Italy, Australia, Chile, and South Africa is analyzed using publicly available databases. Water whiplash—or the rapid shift of wet and dry periods—are compared. Wet and dry periods are defined based on annual deviations from the historical record average, and whiplash occurs when there is an abrupt change that overcomes an accommodated deficit or surplus. Of all the stations, there are more dry years (56%) than wet years …

Evaluation Of Seven Satellite-Based And Two Reanalysis Global Terrestrial Evapotranspiration Products, Zijing Xie, Yunjun Yao, Qingxin Tang, Meng Liu, Joshua B. Fisher, Jiquan Chen, Xiaotong Zhang, Kun Jia, Yufu Li, Ke Shang, Bo Jiang, Junming Yang, Ruiyang Yu, Xueyi Zhang, Xiaozheng Guo, Lu Liu, Jing Ning, Jiahui Fan, Lilin Zhang

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Although comprehensive evaluation of different types of global terrestrial evapotranspiration (ET) products has been conducted, the satellite remote sensing techniques have prompted the development of several available global ET products, warranting a reassessment as products continue to evolve. Recently, we produced the long-term Global LAnd Surface Satellite (GLASS) ET product, but there is a lack of comparison and evaluation with other ET products and EC observations on a global scale. In this study, we evaluated the accuracy and uncertainty of seven satellite-based (GLASS-AVHRR, GLASS-MODIS, BESS, FLUXCOM, GLEAM, MOD16, and PML_V2) and two reanalysis (ERA5 and MERRA2) global terrestrial ET products …

Estimation Of Sugarcane Yield Using Multi-Temporal Sentinel 2 Satellite Imagery And Random Forest Regression, Alireza Taravat, Gebeyehu Abebe, Berhan Gessesse, Tsegaye Tadesse

National Drought Mitigation Center: Faculty Publications

Advancements in remote sensing techniques have greatly enhanced crop monitoring and yield estimation, with spectral vegetation indices (VIs) serving as a key component. Our study investigates the use of Sentinel-2 data, notable for its red-edge bands, in estimating sugarcane yield in Ethiopia's Awash Basin. Utilizing 22 VIs from S2 imagery, our approach combines Random Forest (RF) regression with the Recursive Feature Elimination (RFE) algorithm to improve the accuracy of sugarcane yield predictions. The results demonstrate the superior performance of the RF-RFE method over traditional RF with full datasets and Stepwise Multiple Regression (SMR). Particularly, VIs focusing on the red-edge spectral …

Carbon Neutral By 2030 - Katanning Research Station, Department Of Primary Industries And Regional Development, Western Australia

Climate Science Published Reports

The Department of Primary Industries and Regional Development's (DPIRD) Katanning Research Station (KRS) is developing practical techniques and methods for mitigating carbon emissions from the livestock industry.

This research will help the livestock industry in Western Australia (WA) access anticipated future markets for carbon neutral food and fibre products.