Skip to main content

Person

Marissa A Alessi

Cartographer
Florence Bascom Geoscience Center

Email: malessi@usgs.gov
Office Phone: 703-648-6905

Location
John W Powell FB
12201 Sunrise Valley Drive
Reston , VA 20192-0002
US

Supervisor: Pete G Chirico
thumbnail
This dataset was created as part of the USGS Afghanistan Project investigating artisanal and small-scale mining activity. Clay mining for brick making purposes represents a small but important segment of the mineral extraction industry in Kabul, Afghanistan. Over the past several decades Kabul has grown from a relatively small city, with a 1970 population of less than 500,000 people, to a sprawling urban center with approximately 4.2 million people in 2020 (CIA 2020). Population growth has expanded the need for housing, commercial, and industrial buildings, and associated infrastructure. This has greatly increased demand for bricks, the primary construction material of the region. In this study, very high-resolution...
thumbnail
This data release publishes datasets within and surrounding the Piney Branch watershed located in the Washington, D.C. metropolitan suburb of Vienna, Virginia. This dataset was utilized in studies that investigated the accuracy and application of geospatial modeling techniques, structure-from-motion (SfM) photogrammetric methods, and digital elevation model (DEM) differencing to assess and quantify geomorphic and anthropogenic landform change. The United States Geological Survey’s (USGS) three-dimensional digital elevation program (3DEP) light detection and ranging (LiDAR) digital terrain models (DTMs) were used together with and as a means for comparison to DTMs created from historical aerial imagery. The creation...
thumbnail
Cobalt, designated a critical mineral by the European Union and the United States, is a crucial component of the lithium-ion batteries found in cell phones, electric vehicles, and personal computing devices. Over half of the world’s cobalt supply is produced in the Democratic Republic of the Congo (DRC), where cobalt is mined in both large-scale and artisanal or small-scale operations. This dataset focuses on Africa’s mineral-rich Copperbelt region, an area mined for both copper and cobalt, that extends south across the DRC boundary into neighboring Zambia. Existing geoscientific data and remote sensing analysis were investigated to build a comprehensive dataset describing cobalt mining extent and technique (large-...
thumbnail
Spatial data of artisanal mining riverine dredges using three different Synthetic Aperture Radar detection approaches on the Madeira River, Brazil
Three semi-automated detection approaches using Sentinel-1 Synthetic Aperture Radar (SAR) have been performed to identify artisanal and small-scale mining (ASM) riverine dredges on the Madeira River in Brazil. The methods are: i) Search for Unidentified Maritime Objects (SUMO), an established method for large ocean ship detection; and two techniques specifically developed for riverine environments: ii) a local detection method; and iii) a global threshold method. The results from each method are contained on this landing page along with the visual interpretation dataset of SAR data used as the validation dataset. The pre-processed SAR data used to produce these results are found also found on this page.
thumbnail
This data release catalogs the locations of small-scale diamond and gold mining dredges on the Kadéï (Sangha) River, Central African Republic from the years 2015 to 2019. The Kadéï river flows through the Nola prefecture in the CAR and is known to host placer diamond deposits. The dataset was developed through visual interpretation of 387 Synthetic Aperture Radar (SAR) scenes. The point shapefile contains 1,747 locations of vessels, identified by type as either a dredge, idle vessel, or ferry.
ScienceBase brings together the best information it can find about USGS researchers and offices to show connections to publications, projects, and data. We are still working to improve this process and information is by no means complete. If you don't see everything you know is associated with you, a colleague, or your office, please be patient while we work to connect the dots. Feel free to contact sciencebase@usgs.gov.