Dbk: 1 revision imported

2021-07-26T14:35:41Z

1 revision imported

← Older revision	Revision as of 15:35, 26 July 2021
(No difference)

Geosource>Ajhil at 14:51, 7 July 2016

2016-07-07T14:51:23Z

New page

{| cellspacing="8" cellpadding="8"
|- style="vertical-align:top;"
| style="width: 1100px;" |
[[Image:CC_topbanner.jpg|frameless|center|800px|]]
----
|}

{| cellspacing="8" cellpadding="8"
|- style="vertical-align:top;"
| style="background-color: #404e7d; width: 250px" | '''Project Partner'''
'''Cornwall Council''' is the unitary authority for Cornwall, with a wide range of regulatory and public service provision responsibilities for a population of over half a million people. Cornwall Council succeeded Cornwall County Council in 2009 when it incorporated the previous Cornish district councils.
| ! scope="col" style="width: 850px;" | '''Project Rationale'''
The Cornish landscape contains considerable evidence of a rich and diverse history of human activity, ranging from prehistoric sites, medieval farming and historic mining, through to more recent industrial and military remains. Much of this evidence has been documented using information from a variety of sources, including published and unpublished literature, museum records, ﬁeldwork, aerial photographs and reports by members of the public. To date, over 57 000 historic buildings, sites and monuments have been recorded, and this database is constantly being updated as new information is acquired.

Over the years, a combination of both natural and anthropogenic factors have affected the landscape and made it more challenging to identify any remaining evidence of human activity. For instance, changes in land cover may have resulted in sites of past human activity becoming hidden beneath dense forest cover, or heavily degraded due to modern farming practices and erosion.
|}

{| cellspacing="8" cellpadding="8"
|- style="vertical-align:top;"
| ! scope="col" style="width: 600px;" | '''Historic Mining'''
Although LiDAR derived DTMs may be useful for revealing evidence of human activity in wooded areas, the quality of DTMs are somewhat degraded where the tree cover is very dense making it challenging to resolve topographic detail. This issue is primarily due to the airborne LiDAR survey being ﬂown while trees were in-leaf, and the processing algorithm used to separate ground from non-ground elevation measurements (i.e. trees, buildings) in the generation of the DTM. To assess whether the DTM could be improved in densely wooded areas, the raw LiDAR data were reprocessed. The reprocessed DTM has a signiﬁcant increase in the quality and detail of topographic information including evidence of mining activity that was not discernible in the original DTM. The reprocessing of the LiDAR data, would be beneﬁcial for the mapping of historic sites in wooded areas.
| style="width: 500px;" | [[Image:CC_fig1_b&w.jpg|frameless|center|500px| ]]
|}

{| cellspacing="8" cellpadding="8"
|- style="vertical-align:top;"
| style="width: 500px;" | [[Image:CCfig2.jpg|frameless|center|500px| ]]
| style="width: 600px;" |
Mining-related features, such as pits, quarries and spoil heaps, can be readily identiﬁed using DTM-derived hillshades. However, the visual interpretation of such features over vast areas is somewhat laborious. A semi-automated method was developed for rapidly mapping pits and quarries from the original regional DTM. This method involves ﬁlling depressions in the DTM using the ‘ﬁll’ hydrology tool in the ArcGIS. A depth map is then computed by subtracting the original DTM from the ﬁlled DTM, to which a minimum depth threshold is subsequently applied to extract depressions that correspond to pit and quarries. As well as highlighting the locations of pits and quarries, this relatively simple approach is capable of rapidly and accurately mapping their extent. Moreover, this method can also be adapted to map spoil heaps by ﬁrst inverting the DTM so that raised features become depressions.
|}
{| cellspacing="8" cellpadding="8"
|- style="vertical-align:top;"
| ! scope="col" style="width: 600px;" | '''Archaeological Mapping'''
Earthworks and monuments are generally smaller in size and more subtly expressed in the landscape than mining features. This can make them difﬁcult to recognise both in the ﬁeld and in LiDAR-derived data. In an attempt to overcome this, several topographic derivatives were generated to help enhance the appearance of subtle features. These comprised maps of slope, curvature, surface roughness and Topographic Position Index. Slope and curvature are measures of the steepness and roundness of the terrain, respectively, whereas surface roughness is a measure of the variability of the terrain. The Topographic Position Index (TPI) essentially measures the difference between the elevation of a particular point and the average elevation within a given neighbourhood, with positive TPI values indicating that the point is higher than its surroundings, and vice versa. Although not readily apparent in the hillshades, variations in the slope, curvature, TPI, and — to a lesser degree — surface roughness clearly reveal the presence of a circular earthwork. The method has been able to locate and map a feature that is not currently in the Cornwall Council's Historic Buildings, Sites and Monuments Record but bears a striking resemblance to that of known Iron Age/Romano-British enclosed settlements in region.
| style="width: 500px;" | [[Image:CCfig3.jpg|frameless|center|500px| ]]
|}

{| cellspacing="8" cellpadding="8"
|- style="vertical-align:top;"
| style="width: 500px;" | [[Image:CCfig4.jpg|frameless|center|500px| ]]
| style="width: 600px;" |
Barrows have a distinctive dome-shaped morphology that can be well-characterised with the aid of topographic variables — speciﬁcally the TPI. The TPI was derived from the DTM using a neighbourhood of slightly larger in size than the typical barrow diameter (i.e. 30 m). A threshold was then applied to extract positive TPI values that stand 0.4 m higher than their surrounding area. Individual polygons were created that deﬁne the outlines of the groups of adjoining pixels with positive TPI values greater than 0.4 m. The area and perimeter of each polygon was then calculated and used to compute a circularity index, which is a measure of how much a polygon's shape deviates from that of a perfect circle. Since barrows have a circular base, a low circularity threshold was used to extract near-circular polygons whilst eliminating all others. Accordingly, the extracted polygons highlight areas that have both a circular base and are elevated from the surroundings. The extract polygons coincide well with known barrow locations, and highlight a number of potential barrows that have not been previously recorded. Although the results clearly demonstrates the ability to identify barrows semi-automatically, some erroneous features are still mapped as potential barrows. These are mostly associated with artefacts in the DTM that arise as a result of the ﬁltering algorithm used to separate ground from non-ground LiDAR measurement during the generation of the original DTM. These false-positive features can be easily identiﬁed and removed from the dataset by overlaying the polygon layer on top of the DTM hillshade. Barrows that have been excavated may not be captured using this method if their dome-shape has been signiﬁcantly altered.
|}
{| cellspacing="8" cellpadding="8"
|- style="vertical-align:top;"
| colspan="2" style="width: 1100px;" | '''Future Opportunities'''
Ultimately, the Tellus South West airborne LiDAR data can help to establish a more comprehensive Historic Buildings, Sites and Monuments Record, which has important implications for advancing our knowledge and understanding of the historic environment, informed decision-making for planning, the preservation of historic sites and landscapes, and tourism and appreciation of such sites. Although speciﬁcally applied to Cornwall, the tools and techniques presented here can be readily applied to Devon and any other area for which high-resolution airborne LiDAR data exists.
 
{| cellspacing="8" cellpadding="8"
|- style="vertical-align:top;"
| style="width: 1100px;" |
[[Image:Logos_bottom.jpg|frameless|center|800px| ]]
|}
[[Category:Tellus How | ]]

Case study: Cornwall Council - Revision history

Dbk: 1 revision imported

Geosource>Ajhil at 14:51, 7 July 2016