Applications of remote sensing in the identification

and data basing of Ohio mine lands

Paul H. Lewis

5 Dec. 2006

ES 771, Remote Sensing

Table of Contents
Abstract Remote Sensing
History Conclusion
MineInfo Project References

ABSTRACT:

The Ohio Department of Natural Resources (ODNR) - Division of Mineral Resources Management (DMRM) has developed a mine location database based on permit maps. Many features of abandoned strip mines present risks to the public health and safety. Nearly 10,000 permits have been issued since the 1940s, yet only 35% of the permits have maps that can be used in the data basing endeavor. Current Landsat data would be a valuable asset in identifying old abandoned mines and reclaimed areas. Hyperspectral sensor data in the future will also be indispensable in identifying reclaimed mines based on unique vegetation identification techniques that these sensors will make possible.

HISTORY:

Over 300 million years ago, central Ohio was covered by an inland sea. The Appalachian Mountains slowly pushed upward to the east of the sea and streams formed that carried sediment down to the sea. Deltas and swamps formed along the coast which is now eastern Ohio. The ideal conditions existed in these swamps for dying plants to form layers of peat. Centuries of sedimentary deposits covered the peat, compressing it as it decomposed. This processing of the peat with heat and pressure helped form a ribbon of coal.

Figure 1: Map of inland sea of approximately 300 million years ago.
Taken from Hansen (1993)

Mining has been a part of the southeastern Ohio way of life since the mid 1800. Coal fueled much of the generation of electricity in the Northeast and Midwest. It was not until the 1940s that Ohio started issuing mining permits. During this time, strip mining increased in popularity as a means of retrieving the ribbon of coal that lay below the surface of much of southeastern Ohio. Strip mining is the practice of removing the earth above the layer of coal and then harvesting the coal.

The Strip Coal Mining Act of 1947 was Ohio’s first attempt at regulating coal mining. In particular this law was enacted to ensure that reclamation would be performed on lands that had been decimated by the strip mining process. In 1949, Ohio strengthened the regulations by establishing a reclamation enforcement office. Over the next few decades, Ohio continued refining and strengthening the mining laws, so that by 1972, Ohio had the most comprehensive strip mine laws in the nation. The 1972 law required mining companies restore mined lands to pre-mine contours, replace topsoil and the successful revegetation prior the return of their reclamation bond from the state.

The Federal Government enacted the Surface Mining Control and Reclamation Act (SMCRA) of 1977. This Act established stringent national standards for coal mining and reclamation and created the federal Department of the Interior's Office of Surface Mining Reclamation and Enforcement. Under this law, the Secretary of the Interior must approve any state program, which must meet or exceed the federal standards established with the act. The Secretary of Interior approved Ohio's regulatory and Abandoned Mined Lands (AML) programs in 1982.

The AML program was a reforestation program that aimed to providing low costs approaches to establish vegetation on mining sites that the mining companies had abandoned. Establishing vegetation on old mining sites is important for numerous reasons, such as reducing erosion, protecting watershed from toxic run-off and making sites safe for wildlife and recreational activities. Ohio’s AML program was particularly aimed at being economical so that the state could afford to affect low priority abandoned coal mine sites. Traditional strip mine reclamation practices which entail partial backfill to full backfill can run $6,500 to $8,000 per acre. Reforestation only, under the AML program, can run as little as $600 per acre.

Return to Table of Contents

MINEINFO PROJECT:

In 1999, ODNR-DMRM started developing a GIS database of mine lands based on the maps provided by the mining companies for the original licenses issued. This database is known as MineInfo Project. It is expected that the data can assist in the easy identification of reclaimed surface mine lands that might otherwise appear to be unmined, evaluating risks associated with abandoned mines and determining funding eligibility under SCMRA.

Figure 2: Sample mining permit map overlaid on DOQQ. Taken from ODNR-DMRM MineInfo Project Website

Permit maps that were submitted under requirements for attaining a mining license have been digitized to create shapefile organized by county. Available data includes permit boundary, affected boundary, test hole locations, and associated attributes. The shapefile information is then overlaid on DOQQ aerial image. The MineInfo data has some known deficiencies:

a) Early licenses did not requiring the companies to provide a map of the site.
b) Many licenses have been lost over the years.
c) Maps and location information were inaccurate because of limitations with surveying and mapping.

Specifically, the state issued 4800 mining licenses from 1940 thru 1966, but no maps of the mines are available. In the period from 1966 to 1973, Ohio issued 1111 licenses, but only 350 maps have been located for inclusion in the database. From 1973 to 1976, 1285 licenses were issued and of those, 414 maps have been recovered and digitized. The period from 1976 to 1981 was much better with 1581 licenses issued and only 82 maps missing. Since 1981, over 1200 licenses have been issued and all the maps have been digitized up to 2002. Thus, only 35% of the licenses issued are currently available in this database.

Return to Table of Contents

REMOTE SENSING:

With as many as 65% of Ohio mines going undocumented, additional data sources should be employed to aid in mine identification. The exploitation of Landsat imagery would be an excellent choice in this regard. Strip mines, depending on the stage of reclamation, can best be identified in the visible and near infra-red channels of Landsat. As lands are reclaimed through reforestation or turning into grass lands the red channel and near infra-red channel become more important.

Figure 3: 1973 Landsat MSS 421 false color image. Figure 4: 1985 Landsat MSS 421 false color image.
Figure 5: 1990 Landsat MSS 421 false color image. Figure 6: 1997 Landsat TM 432 false color image.

Figure 3-6 Taken from USGS Earthshots website.

This series of images depict the southward progress of mines in Muskingum County over a 24 year period. The forested areas appear in shades of red due to the higher reflectivity in the near infra-red. The mined land is blue-grey in appearance since there is higher reflectivity in the visible spectrum. As the mined land is reclaimed by forests and grass lands it transitions to from the blue-grey appearance to dark red in color since the vegetation boosts the reflectivity in the near infra-red and lowers the reflectivity in the red channel.

Hyperspectral sensors will be important in the future for documenting reclaimed mine lands. The AML reforestation program utilized in Ohio plants specific tree types. The tree selection is based principally for one reason. Barren abandon mine lands are typically highly acidic with pH readings of 3.0 to 4.0. Inoculating seedlings roots with Pisolithus tinctorius, a symbiotic fungus, helps with the absorption of water and nutrients. Only particular trees work successfully with this symbiotic fungus. The particular species are Virginia Pine, White Pine, Pitch-loblolly Pine, Red Pine, Scarlet Oak, Sawtooth Oak, Northern Red Oak, Chinkapin Oak, Burr Oak, Black Oak and American Chestnut. Utilizing hyperspectral imagery when it becomes more readily available, in conjunction with the USGS spectral library, should make identifying the mass plantings of these trees easy.

Return to Table of Contents

CONCLUSIONS:

The ODNR-DMRM MineInfo Project is a worthwhile database of mine lands, but with only 35% of all mines actually having detailed documentation this project might have little long-term utility. Like many record archives, valuable information is inadvertently lost or destroyed over time and if creative methodologies for filling the gaps are not employed projects like this will end up short lived. ODNR-DMRM would benefit greatly now from use of Landsat data in mine land identification and data basing. It is also quite possible that the MineInfo Project could make use of hyperspectral remote sensor data as it becomes more readily available to mark reclaimed locations through the spectral signals of the limited species of Pines and Oaks planted in the ODNR AML Reforestation Program.

Return to Table of Contents

REFERENCES:

Return to Table of Contents

Comments to plewis2@esumail.emporia.edu