<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gutiérrez, Álvaro Gómez</style></author><author><style face="normal" font="default" size="100%">Schnabel, Susanne</style></author><author><style face="normal" font="default" size="100%">Contador, Francisco Lavado</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Gully erosion, land use and topographical thresholds during the last 60 years in a small rangeland catchment in SW Spain</style></title><secondary-title><style face="normal" font="default" size="100%">Land Degradation &amp; Development</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Gully erosion</style></keyword><keyword><style  face="normal" font="default" size="100%">land use</style></keyword><keyword><style  face="normal" font="default" size="100%">orthophotographs</style></keyword><keyword><style  face="normal" font="default" size="100%">Overgrazing</style></keyword><keyword><style  face="normal" font="default" size="100%">topographical thresholds</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><publisher><style face="normal" font="default" size="100%">John Wiley &amp; Sons, Ltd.</style></publisher><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">535-550</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Gully erosion plays an important role in degradation processes of Mediterranean environments. In this paper aerial orthophotographs were used for (i) analysing the evolution of a valley bottom gully and its relation with land use and vegetation cover, (ii) exploring the role of land use and vegetation cover on the coefficients of the equation S = aA−b (where S is slope at the headcut and A is drainage area), which is based on the topographical threshold concept and is commonly used to predict gully initiation. The study was carried out in a small catchment (99·5 ha) located in the southwest of the Iberian Peninsula. Gullies and headcuts were mapped together with land use and vegetation cover using aerial photographs for the years 1945, 1956, 1989, 1998, 2002 and 2006, which had to be digitized and orthorectified in advance. The results showed an increase of the area affected by gullying from 695 m2 in 1945–1009 m2 in 2006, reaching a maximum of 1560 m2 in 1956. Gullying was closely related with land use, especially with the amount of cultivated areas within the catchment and also with grazing intensity. No clear relationship was found between the evolution of the gullied area and rainfall amounts. Finally, the values of the exponent b obtained for different headcuts and different dates (close to 0·4) were similar to those proposed by other authors for gully erosion caused by Hortonian overland flow in semiarid environments. Copyright © 2009 John Wiley &amp; Sons, Ltd.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gutiérrez, Álvaro Gómez</style></author><author><style face="normal" font="default" size="100%">Schnabel, Susanne</style></author><author><style face="normal" font="default" size="100%">Lavado Contador, J. Francisco</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using and comparing two nonparametric methods (CART and MARS) to model the potential distribution of gullies</style></title><secondary-title><style face="normal" font="default" size="100%">Ecological Modelling</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CART</style></keyword><keyword><style  face="normal" font="default" size="100%">Gully erosion</style></keyword><keyword><style  face="normal" font="default" size="100%">MARS</style></keyword><keyword><style  face="normal" font="default" size="100%">Nonparametric modelling</style></keyword><keyword><style  face="normal" font="default" size="100%">Rangelands</style></keyword><keyword><style  face="normal" font="default" size="100%">ROC curve</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://linkinghub.elsevier.com/retrieve/pii/S0304380009004104</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">220</style></volume><pages><style face="normal" font="default" size="100%">3630 - 3637</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Gully erosion represents an important soil degradation process in rangelands. In order to take preventive or control measures and to reduce its environmental damages and economical costs it is useful to localize the points in the landscape where gullying takes place and to determine the importance of the different factors involved. The study is carried out in Extremadura, southwest Spain. The main objectives of this work are: (a) comparing two nonparametric schemes to model the potential distribution of gullies, (b) evaluating the importance of the different factors involved in gullying processes, (c) analyzing the role of prevalence in the success of the model and ﬁnally, (d) implementing and mapping the results with the help of a Geographical Information System (GIS). Two methods were used to model the response of a dependent variable (gullying) from a set of independent variables: Classiﬁcation And Regression Trees (CART) and Multivariate Adaptive Regression Splines (MARS). Three different datasets were used; the ﬁrst one for constructing the model (training dataset) and the others for validating the model (external datasets). These datasets are formed by a target variable (presence or absence of gullies) and a set of independent variables. The dependent variable was obtained by mapping the locations of gullies with the help of a GPS and high resolution aerial ortophotographs. A set of 32 independent variables reﬂecting topography, lithology, soil type, climate, land use and vegetation cover of each area were used. The performance of the models was evaluated using a non-dependent threshold method: the Receiver Operating Characteristic (ROC) curve. The results showed a better performance of MARS for predicting gullying with areas under the ROC curve of 0.98 and 0.97 for the validation datasets, while CART presented values of 0.96 and 0.66.</style></abstract><issue><style face="normal" font="default" size="100%">24</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gutiérrez, Álvaro Gómez</style></author><author><style face="normal" font="default" size="100%">Schnabel, Susanne</style></author><author><style face="normal" font="default" size="100%">Lavado Contador, J Francisco</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using and comparing two nonparametric methods (CART and MARS) to model the potential distribution of gullies</style></title><secondary-title><style face="normal" font="default" size="100%">Ecological Modelling</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CART</style></keyword><keyword><style  face="normal" font="default" size="100%">Gully erosion</style></keyword><keyword><style  face="normal" font="default" size="100%">MARS</style></keyword><keyword><style  face="normal" font="default" size="100%">Nonparametric modelling</style></keyword><keyword><style  face="normal" font="default" size="100%">Rangelands</style></keyword><keyword><style  face="normal" font="default" size="100%">ROC curve</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><volume><style face="normal" font="default" size="100%">220</style></volume><pages><style face="normal" font="default" size="100%">3630-3637</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Gully erosion represents an important soil degradation process in rangelands. In order to take preventive or control measures and to reduce its environmental damages and economical costs it is useful to localize the points in the landscape where gullying takes place and to determine the importance of the different factors involved. The study is carried out in Extremadura, southwest Spain. The main objectives of this work are: (a) comparing two nonparametric schemes to model the potential distribution of gullies, (b) evaluating the importance of the different factors involved in gullying processes, (c) analyzing the role of prevalence in the success of the model and ﬁnally, (d) implementing and mapping the results with the help of a Geographical Information System (GIS). Two methods were used to model the response of a dependent variable (gullying) from a set of independent variables: Classiﬁcation And Regression Trees (CART) and Multivariate Adaptive Regression Splines (MARS). Three different datasets were used; the ﬁrst one for constructing the model (training dataset) and the others for validating the model (external datasets). These datasets are formed by a target variable (presence or absence of gullies) and a set of independent variables. The dependent variable was obtained by mapping the locations of gullies with the help of a GPS and high resolution aerial ortophotographs. A set of 32 independent variables reﬂecting topography, lithology, soil type, climate, land use and vegetation cover of each area were used. The performance of the models was evaluated using a non-dependent threshold method: the Receiver Operating Characteristic (ROC) curve. The results showed a better performance of MARS for predicting gullying with areas under the ROC curve of 0.98 and 0.97 for the validation datasets, while CART presented values of 0.96 and 0.66.</style></abstract></record></records></xml>