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Full-Text Articles in Remote Sensing

Studying Factors Of Environmental Injustice And Ways To Achieve Equity, Arham Hussain, Reginald Metellus Dec 2022

Studying Factors Of Environmental Injustice And Ways To Achieve Equity, Arham Hussain, Reginald Metellus

Publications and Research

In today's day of age, the biggest concern for current and future generations: the environment. The urban heat island (UHi) with its significant energy, health, and societal impacts is among the major environmental issues in urban regions, especially in historically underserved and socially vulnerable communities (HUSVCs). In the 1930s, the former federal agency, Homeowners' Loan Corporation (H0Lq, created ''Residential Security" maps of major cities, known today as "redlined" areas. These neighborhoods were often designated as "hazardous" due to the high percentages of people of color living there, leading to systematic disinvestment based on race. While the program ended in 1968, …


Titaniferous-Vanadiferous, Magnetite-Ilmenite Mineralization In A Mafic Suite Within The Chhotanagpur Gneissic Complex, Bihar, India, Ashmeer Mohammad, Anup K. Prasad, Kehe-U Wetsah, Mohammad Azad, Vivek Aryan, Hesham El-Askary Jul 2022

Titaniferous-Vanadiferous, Magnetite-Ilmenite Mineralization In A Mafic Suite Within The Chhotanagpur Gneissic Complex, Bihar, India, Ashmeer Mohammad, Anup K. Prasad, Kehe-U Wetsah, Mohammad Azad, Vivek Aryan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Titanium or vanadium metals or their alloys are important industrial metals/alloys. Because these resources are in short supply, the investigation of potential titaniferous-vanadiferous deposits needs special attention to bridge the supply-demand gap. The study integrates geological, geochemical, remote sensing, and geophysical data for assessing the potentiality of titaniferous-vanadiferous, magnetite-ilmenite mineralization in and around the Sudamakund and Paharpur areas, Gaya and Jehanabad districts, Bihar, India, and delineation of specific targets for detailed exploration. Field visits for large scale mapping on (1:12,500 scale) were used to conduct a reconnaissance survey for magnetite-ilmenite mineralization in parts of toposheet number 72G/04 in the Gaya …


Using Lidar To Estimate Carbon Sequestration Of Evergreen Trees At Eastern Washington University (Ewu) Campus, Cheney, Washington, Kristy A. Snyder May 2022

Using Lidar To Estimate Carbon Sequestration Of Evergreen Trees At Eastern Washington University (Ewu) Campus, Cheney, Washington, Kristy A. Snyder

2022 Symposium

EWU contains a variety of deciduous and evergreen trees across its campus, providing several benefits. However, no comprehensive record exists of the total number, location, species, or ages of these trees. This knowledge can inform facilities of proper care for individual trees and can be used to estimate carbon sequestration on campus. Traditional on-the-ground methods for assessing trees require tree cores or clinometers, making trees susceptible to pests or disease and leading to inaccurate results. Remote sensing using lidar data is a noninvasive, more precise method to measure tree height and subsequently assess tree age. This poster explores using point …


Lake Satellite Temperature Data Validation, Mamadou Balde, Pascal Kouogang May 2022

Lake Satellite Temperature Data Validation, Mamadou Balde, Pascal Kouogang

Publications and Research

In environmental remote sensing, satellite data isn't absolutely conclusive, for that reason, there is a natural need to verify the data acquired from the satellite. The most suitable tool to achieve such verification is on ground sensors that have the advantage of proximity. Addressing any possible discrepancies between the satellite data and the ground sensor data is sure to yield ways to come up with improvements of satellite band calibration and sensing capabilities. This research focused on correlating temperature data from the MODIS satellite with the data obtained from the In Situ sensor located in Lake Sunapee. Doing the latter …


Multi-Criteria Evaluation Model For Classifying Marginal Cropland In Nebraska Using Historical Crop Yield And Biophysical Characteristics, Andrew Laws May 2022

Multi-Criteria Evaluation Model For Classifying Marginal Cropland In Nebraska Using Historical Crop Yield And Biophysical Characteristics, Andrew Laws

School of Natural Resources: Dissertations, Theses, and Student Research

Marginal cropland is suboptimal due to historically low and variable productivity and limiting biophysical characteristics. To support future agricultural management and policy decisions in Nebraska, U.S.A, it is important to understand where cropland is marginal for its two most economically important crops: corn (Zea mays) and soybean (Glycine max). As corn and soybean are frequently planted in a crop rotation, it is important to consider if there is a relationship with cropland marginality. Based on the current literature, there exists a need for a flexible yet robust methodology for identifying marginal land at different scales, which …


Landslide Detection In The Himalayas Using Machine Learning Algorithms And U-Net, Sansar Raj Meena, Lucas Pedrosa Soares, Carlos H. Grohmann, Cees Van Westen, Kushanav Bhuyan, Ramesh P. Singh, Mario Floris, Filippo Catani Feb 2022

Landslide Detection In The Himalayas Using Machine Learning Algorithms And U-Net, Sansar Raj Meena, Lucas Pedrosa Soares, Carlos H. Grohmann, Cees Van Westen, Kushanav Bhuyan, Ramesh P. Singh, Mario Floris, Filippo Catani

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Event-based landslide inventories are essential sources to broaden our understanding of the causal relationship between triggering events and the occurring landslides. Moreover, detailed inventories are crucial for the succeeding phases of landslide risk studies like susceptibility and hazard assessment. The openly available inventories differ in the quality and completeness levels. Event-based landslide inventories are created based on manual interpretation, and there can be significant differences in the mapping preferences among interpreters. To address this issue, we used two different datasets to analyze the potential of U-Net and machine learning approaches for automated landslide detection in the Himalayas. Dataset-1 is composed …