Effects of climate, land cover and topography on soil erosion risk in a semiarid basin of the Andes

Ochoa, Pablo A.; Fries, Andreas; Mejia, Diego; Valdivieso, Juan Ignacio Burneo; Ruíz-Sinoga, José Damián; Cerdà, Artemi

doi:10.1016/j.catena.2016.01.011

Cited by 186 publications

(130 citation statements)

References 37 publications

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“…SOCag was strongly affected by the type of Bioclimate, increasing from 16.7 Mg ha −1 in the thermoMediterranean to 54.5 Mg ha −1 in the supra-Mediterranean Bioclimate. The impact of climate on soil development, runoff generation, soil erosion, and plant cover is well-known (Anaya-Romero et al, 2015; Buendia et al, 2016;Cerdà, 1998b;Ochoa et al, 2016), but little is known about its impact on soil organic carbon, and this is why the results shown here shed light into the environmental impact of land abandonment. Our findings confirm the results of other investigations that are summarised in Köchy et al (2015aKöchy et al ( , 2015b and quantified by Pabst et al (2016) in Africa or by Willaarts et al (2016) in the Mediterranean.…”

Section: Soc Stock and Soc After Abandonment In Each Soil Region And mentioning

confidence: 86%

Agricultural land abandonment in Mediterranean environment provides ecosystem services via soil carbon sequestration

Novara

Gristina

Sala

et al. 2017

Science of The Total Environment

127

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Section: Soc Stock and Soc After Abandonment In Each Soil Region And mentioning

confidence: 86%

Agricultural land abandonment in Mediterranean environment provides ecosystem services via soil carbon sequestration

Novara

Gristina

Sala

et al. 2017

Science of The Total Environment

127

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“…Land cover data are key inputs for modeling earth surface processes, such as climate, natural environment, ecology, food security, water resources, and soils [1][2][3][4][5][6][7]. Obtaining land cover information is difficult, however, because it is highly dynamic due to modification from not only human activity but also nature [8].…”

Section: Introductionmentioning

confidence: 99%

Feature Selection Solution with High Dimensionality and Low-Sample Size for Land Cover Classification in Object-Based Image Analysis

et al. 2017

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Land cover information extraction through object-based image analysis (OBIA) has become an important trend in remote sensing, thanks to the increasing availability of high-resolution imagery. Segmented objects have a large number of features that cause high-dimension and low-sample size problems in the classification process. In this study, on the basis of a partial least squares generalized linear regression (PLSGLR), we propose a group corrected PLSGLR, known as G-PLSGLR, that aims to reduce the redundancy of object features for land cover identifications. Using Gaofen-2 images, the area of interest was segmented and sampled to generate small sample-size training datasets with 51 object features. The features selected by G-PLSGLR were compared against a guided regularized random forest (GRRF) in metrics of reduction rate, feature redundancy, and accuracy assessment of classification. Three indicators of overall accuracy (OA), user's accuracy (UA), and producer's accuracy (PA) were applied for accuracy assessment in this paper. The result shows that the G-PLSGLR achieved a reduction rate of 9.27 with a feature redundancy of 0.29, and a value of OA 90.63%. The GRRF achieved a reduction rate of 1.61 with a feature redundancy of 0.42, and a value of OA 85.56%. The PA of each land cover category was more than 95% using features selected by G-PLSGLR, while the PA ranged from 77 to 96% using features selected by GRRF. The UA of G-PLSGLR-selected features ranged from 70 to 80% except for grass land and bare land, which achieved 10% higher UA than GRRF-selected features. The G-PLSGLR method we proposed has the advantages of a large reduction rate, low feature redundancy, and high classification performance, which can be applied in OBIA-based land cover classification.

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“…Worldwide loss of water and sediment due to soil erosion is a major environmental threat Pimentel, 1993). Soil erosion is accelerated due to high rainfall intensities , steep slopes (Beskow et al, 2009) and the fragile nature of topsoil (Lal, 1998;Rodrigo Comino et al, 2016;Ochoa et al, 2016). Many parts of the tropics in India have high annual rainfall confined to only 4 to 5 months (June-September).…”

Section: Introductionmentioning

confidence: 99%

Reversing land degradation through grasses: a systematic meta-analysis in the Indian tropics

et al. 2017

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Abstract. Although intensive agriculture is necessary to sustain the world's growing population, accelerated soil erosion contributes to a decrease in the environmental health of ecosystems at local, regional and global scales. Reversing the process of land degradation using vegetative measures is of utmost importance in such ecosystems. The present study critically analyzes the effect of grasses in reversing the process of land degradation using a systematic review. The collected information was segregated under three different land use and land management situations. Meta-analysis was applied to test the hypothesis that the use of grasses reduces runoff and soil erosion. The effect of grasses was deduced for grass strip and in combination with physical structures. Similarly, the effects of grasses were analyzed in degraded pasture lands. The overall result of the meta-analysis showed that infiltration capacity increased approximately 2-fold after planting grasses across the slopes in agricultural fields. Grazing land management through a cut-and-carry system increased conservation efficiencies by 42 and 63 % with respect to reduction in runoff and erosion, respectively. Considering the comprehensive performance index (CPI), it has been observed that hybrid Napier (Pennisetum purpureum) and sambuta (Saccharum munja) grass seem to posses the most desirable attributes as an effective grass barrier for the western Himalayas and Eastern Ghats, while natural grass (Dichanthium annulatum) and broom grass (Thysanolaena maxima) are found to be most promising grass species for the Konkan region of the Western Ghats and the northeastern Himalayan region, respectively. In addition to these benefits, it was also observed that soil carbon loss can be reduced by 83 % with the use of grasses. Overall, efficacy for erosion control of various grasses was more than 60 %; hence, their selection should be based on the production potential of these grasses under given edaphic and agro-ecological conditions. The present analysis also indicated that grass must be used as a vegetative strip to maintain soil quality in sloppy arable areas (8.5 Mha) of Indian hilly regions. Similarly, due attention should be paid for establishing grasses in 3 Mha of degraded pasture lands and 3.5 Mha of shifting cultivation areas in India to reverse the land degradation.

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Effects of climate, land cover and topography on soil erosion risk in a semiarid basin of the Andes

Cited by 186 publications

References 37 publications

Agricultural land abandonment in Mediterranean environment provides ecosystem services via soil carbon sequestration

Agricultural land abandonment in Mediterranean environment provides ecosystem services via soil carbon sequestration

Feature Selection Solution with High Dimensionality and Low-Sample Size for Land Cover Classification in Object-Based Image Analysis

Reversing land degradation through grasses: a systematic meta-analysis in the Indian tropics

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