Using GPS and GIS tools to monitor olive tree movements

Erosion is a problem that produces an important impact on the landscape, especially in agricultural areas. This process is accentuated by the effects of meteorological factors, tillage practices and the slope of the land. This latter effect is of greater importance because it leads to surface runoff which in turn causes the soil erosion. The properties of the land, such as the type of crop or the farm management practice, are also factors that determine the study of soil erosion. They must all be evaluated in order to obtain conclusions about the tillage erosion in a property. Nevertheless it is necessary to use spatial data to better quantify the changes that take place. In our study we quantify the eventual land movement and the subsequent displacement of olive trees produced by continuous tillage erosion. We analyse these movements on a property of olive orchards located on variable sloping land. Land movement monitoring has its methodological base in the repeated revision of the position of the object points, in this case the olive trees. The most suitable instrumentation for taking measurements in the zone we studied is GPS because of the lack of visibility through the trees. Data are integrated into GIS software in order to carry out a specific spatial analysis of this phenomenon. Our analysis provides accurate values of displacements which confirm that our olives trees have moved a few centimetres in a year. There is a relationship between olive tree movements and other spatial models such as elevation, slope or aspect. We have also observed that tillage practice causes complementary effects on tree movements.

[1]  M. C. Lacy,et al.  Establishment of a Non-Permanent GPS Network to Monitor the Recent NE-SW Deformation in the Granada Basin (Betic Cordillera, Southern Spain) , 2002 .

[2]  Deformation Analysis to Study Erosion in Sloped Olive Orchards. , 2006 .

[3]  S. D. Gregorio,et al.  A Cellular Automata model for soil erosion by water , 2001 .

[4]  K. G. Rao,et al.  A rule-based soil erosion model for a hilly catchment , 1999 .

[5]  J. V. Stafford,et al.  Implementing precision agriculture in the 21st century. , 2000 .

[6]  D. Shen,et al.  A new approach for simulating water erosion on hillslopes , 2003 .

[7]  G. R. Foster,et al.  A Process-Based Soil Erosion Model for USDA-Water Erosion Prediction Project Technology , 1989 .

[8]  F. Sansò,et al.  Geodetic deformation monitoring : from geophysical to engineering roles : IAG Symposium Jaen, Spain, March 17-19, 2005 , 2006 .

[9]  Naiqian Zhang,et al.  Development of a field-level geographic information system , 2001 .

[10]  Dengsheng Lu,et al.  Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using RUSLE, remote sensing and GIS , 2004 .

[11]  R. L. Clark,et al.  Evaluation of Sub-Meter and 2 to 5 Meter Accuracy GPS Receivers to Develop Digital Elevation Models , 2004, Precision Agriculture.

[12]  Peter Strauss,et al.  Modelling of event-based soil erosion in Costa Rica, Nicaragua and Mexico : evaluation of the EUROSEM model. , 2001 .

[13]  N. Zhang,et al.  Precision agriculture—a worldwide overview , 2002 .

[14]  M. Neményi,et al.  The role of GIS and GPS in precision farming. , 2003 .

[15]  M. Crespi,et al.  GPS sensitivity analysis applied to non-permanent deformation control networks , 1999 .