Abstract
Abstract. The current research aims at exploring the relationships between historical agricultural landscapes and sustainable tourism, by combining the potential of aerial and ground observation methods, that are able to detect the seasonal landscape changes. These phenomena are strongly interlaced with the annual cycle of plants, which have many implications for ecological processes, agriculture, health, tourism, regional/urban planning and economy. In many countries, similar phenomena as the timing of spring-blooming or the timing of autumn coloring foliage are of great visual value and can be of touristic interest, so to enhance the overall attractiveness of a territory. The research analyzes the case study of the historical agricultural landscape, localized in the in-between territories Turin and Milan, which is characterized by large portions of paddy-rice fields, which assume different aesthetical configurations over the year. This landscape, made up of an articulated system of waterways that support large portions of rice cultivation, protected natural areas, historical farmhouses, urban settlements, is the result of a long process of interaction between natural elements and human activities. Remote sensing and ground observations can play an important role in a high-accuracy mapping of the seasonal conditions of this kind of landscape. The flooding of paddy-rice fields determines a high scenic value of large portions of the rural landscape, that can be detected through remote sensing. The specificity of rice cultivation is that plants grow on flooded soils. Such a temporary condition of the landscape can become an unexpected tourist destination. From the methodological point of view, the research combines the potential of time series of satellite high-resolution imagery, for computing vegetation indexes (i.e. NDVI, NDWI etc.), and ground observations, through GIS mapping tools. This interpretation tools are useful to trace a network of slow scenic routes that allow perceiving such temporary landscape conditions and that support a territorial strategy aiming at a sustainable development of these fragile territories.
Highlights
The current research aims at integrating analysis techniques based on Remote Sensing (RS) and Geographic Information System (GIS) to create a platform where the seasonal changes of historical agricultural landscape can be mapped
The research refers to historical agricultural landscapes, that have been shaped over the centuries, according to the evolution of the agricultural techniques; they are fragile but vital resources for local economies, and they can be further enhanced in terms of sustainable tourism as a base for economic and spatial development
The research shows the effectiveness of the pixel-based recognition method for detecting flooded paddy-rice fields, which is confirmed by the ground observation survey
Summary
The current research aims at integrating analysis techniques based on Remote Sensing (RS) and Geographic Information System (GIS) to create a platform where the seasonal changes of historical agricultural landscape can be mapped. The seasonal landscape changes are strongly interlaced with the annual cycle of plants and with human activities, which intervene in their spatial organization. Many factors, both natural and anthropic, can influence the timing of these changeable phenomena (temperature, water availability, weather conditions, cultivation type, cultivation schedule etc.). Both natural and anthropic, can influence the timing of these changeable phenomena (temperature, water availability, weather conditions, cultivation type, cultivation schedule etc.) In this framework, RS and GIS can play a key role in highaccuracy tracking and mapping of seasonal landscape changes. In the field of agricultural landscape mapping, vegetation indices such as NDVI (Normalized Difference Vegetation Index), are sensitive indicators for monitoring the crop status, but they can be exploited for mapping the scenic conditions of large portions of rural landscapes (Xiao et al, 2002) (Xiao et al 2006)
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