11.1Introduction

The spatial dimension of terraced landscapes currently represents a challenge to perform a synoptic observation of such peculiar agricultural ecosystems. The terraced landforms are paramount not only in terms of cartographic representation but also in understanding and valuing their environmental, social, and economic complexity that range from change of agricultural practices to geo-hydrological hazards. Hence, locating and mapping agricultural terraced landforms are gaining even more attention both in the academic and in the policy-making spheres, especially for agricultural terraces that are still not represented in official maps or for those which are disappeared from the physical and cultural landscape. Within such framework, the University of Padova launched the MAPTER project, by providing an overview of the terraced systems on the national territory. In Italy, terraced systems are widely diffused as documented in the first geographical survey at national scale which was developed by ISPRA (2013) and Bonardi and Varotto (2016). The MAPTER project was developed in preparation of the Third International Meeting “Terraced Landscapes: choosing the future,” held in Italy (Venice-Padua, October 6–15, 2016). Due to different data sources, MAPTER project adopted a multi-scale approach comparing different methodologies to investigate characteristics about the morphology of the terrace systems. The aims of the MAPTER project are (i) identifying and mapping agricultural terraces; (ii) extracting terraced features such as terrace risers, especially dry-stone walls; and (iii) quantifying the extension of the agricultural, or abandoned, terrace system areas. During the project, different methods were tested, according to data source availability: LiDAR Digital Terrain Model (DTM), high-resolution satellite images, participatory mapping and Voluntary Geography spatial data, and the use of unmanned aerial vehicle (UAV) . Finally, terraced systems were analyzed in order to calculate some geographical parameters such as intensity and extension indexes and to perform a specific classification according to altitude, slope, lithology, and agricultural use (see Varotto et al. in this book).

11.2Materials and Methods

To map and to survey terraced systems, different methodologies were tested and implemented in the last 20 years, according to geospatial technologies evolution and data availability.

11.2.1 Traditional Cartographic and Photo Analysis

The first and the long-standing methodology is based on traditional cartography analyses, often supported by aerial photos study and field survey. Aerial photos usually are made with an overlap that allows a three-dimensional view—by mean of stereoscope—that could enhance the understanding of the terrace risers. To note that the geometric distortion in aerial photos often leads to relief displacements (Lillesand et al. 2015). These spatial errors required a huge amount of field surveys in order to perform data validation and ground truth to complete the terrace system mapping. This method is strongly related to the geographic acquisition processes which include the analogical use of both aerial photos and field data survey, manually transferred on static paper maps and, sometime, georeferenced and processed in geographic information system (GIS) environment by the use of a digitizer.

11.2.2 Orthophoto

In the early 2000s, high-resolution orthophotos at 1.0 or 0.5 m were available and they could just improve the survey in order to have more accuracy both in geometry and radiometry of data. At the time of this paper, this geospatial information presents the advantage of ortho-rectification and high geometric resolution (sometimes under 0.2 m cell size). Therefore, mapping and extracting terraced systems by visual analysis, or supervised/unsupervised classification, are not affected by position errors. Moreover, orthophotos often make more detectable dry-stone walls from different types of terrace risers.

11.2.3 WMS and Geobrowser

Important geospatial data are at present also provided by Web Map Services (WMS) and Geobrowsers, which currently represent important resources to acquire and process high resolution, georeferenced, and ortho-rectified satellite images, which are mostly freely available to any Web users. These Web-based services are very useful whereby no other kind of spatial data are available or in case of terraced systems located in remote areas which would require field survey in situ. WMS are usually provided by institutional Geoportals from Regions, Ministry of Environment, and Geographical Military Institute (Istituto Geografico Militare, IGM) as well as no profit organizations; Geobrowsers are usable by Google EarthTM, Bing MapTM, QGIS and ESRITM platforms. Geobrowser and WMS service are particularly useful for participatory and voluntary geography that has usually less skill of a GIS analyst.

11.2.4 LiDAR Survey

In the early 2000s, a new remote sensing technology based on laser light (Light Detection and Ranging: LiDAR) boosts a worldwide revolution in high-resolution geomorphometry analysis and landform survey (Jasiewicz et al. 2015). LiDAR DTM is a powerful set of elevation data that could represent dry-stone walls and terraced systems with a high level of accuracy at local scale. Scientific literature documented several morphometric studies about methodologies to identify, extract, and measure agricultural terraced landforms (Ninfo 2008; Passalacqua et al. 2010; Ore and Bruins 2012; Sas et al. 2012; Sofia et al. 2014; Tarolli et al. 2015). In addition to the cited literature about terrace features extraction, it is worth to also consider Hengl and Reuter (2009), Jasiewicz et al. (2015) since their works offer a wide and complete overview of morphometric analysis and feature extraction proper of DEMs and DTMs. The greatest strength of LiDAR data is related to terrain morphology detection under the canopy, enabling mapping surveys in wider areas and allowing further analyses to verify presence and geometry of agricultural terraces previously mapped only by traditional methodology. LiDAR detection has also the capability to obtain different surface models: Digital Surface Model (DSM, the earth surface with tree canopies, building, aerial wires, etc.) and Digital Terrain Model (DTM: the bare soil surface). LiDAR data require specific software for their management: first to pre-elaborating raw data (as TerrascanTM) and then for data elaboration (as GIS software). In GIS environment is extremely performing the tools of surface processing—that allow the calculation of parameters such slope, aspect, curvature—and the tools of spatial analysis, for the calculation of drainage channels and direction, or for smoothing and filtering noise from DTM surface.

11.2.5 UAV Survey

Another more recent methodology to map and extract terrace landforms is the use of optical sensors on unmanned aerial vehicles (UAVs). The main advantages in using UAV are based (i) on the very high spatial resolution of aerial photos (0.05– 0.3 m) due to the low altitude of the survey flight that give a strong accuracy of details and (ii) the temporal resolution which allows monitoring the biophysical, the hydraulic, and the land use status. On the contrary, if the very high spatial resolution is one of the strengths of this mapping methodology, it could also represent its same weakness, due to timeand resource-consuming, obstruction of vegetation and costs to survey wide areas. UAV data require specific software (as Pix4DTM) for the elaboration of orthophotos and DTM and DSM. Then, digital models and orthophotos could be analyzed in GIS environment.