J. A. Martínez-Casasnovas

A spatial information technology approach for the mapping and quantification of gully erosion

Abstract In contrast to the effort during the last decades to investigate sheet (interrill) and rill soil erosion processes, relatively few studies have been focused on quantifying and/or predicting gully erosion. The extension of the use of modern spatial information technologies, such as geographical information systems (GIS), digital elevation modelling (DEM) and remote sensing, have created new possibilities for research in this field. A key issue to be addressed, as the basis for predicting the effects of global changes such as land use and climate changes, is the mapping and quantification of gully erosion rates, including rate of retreat of gully walls and rate of sediment production. This research work presents a method to compute the rate of retreat of gully walls and the associated rate of sediment production caused by gully erosion. The proposed method uses multitemporal aerial photographs and multitemporal digital elevation models, both of which have been processed using GIS techniques. The research was applied to a sample catchment of 25 km2 located in Catalonia, Spain. Aerial photographs at scale of 1:30,000 from 1957 and orthophotos from 1993 were used to map gully erosion and determine erosion rates between 1957 and 1993. The rates of channel incision and sediment production were computed from the subtraction of multitemporal digital elevation models. The rate of gully walls retreat was 0.2 m year−1, representing a rate of 0.9‰ m2 year−1. The maximum rate of channel incision (0.7–0.8 m year−1) occurred at the head of the gully and at meandering zones. The rate of sediment production caused by gully erosion was 1322±142 ton ha−1 year−1. In comparison with other methods to compute sediment production caused by gully erosion processes, the proposed method integrates the losses due to overland flow, mass movements and gully deepening and supposes an improvement to locate the areas within the gullies with higher erosional activity.

Soil erosion caused by extreme rainfall events: mapping and quantification in agricultural plots from very detailed digital elevation models

This paper presents a method that can be used to quantify and map soil losses at field scale produced by extreme rainfall events. The amounts of sediment produced by overland flow and Ž. concentrated overland flow inter-rill, rill and gully erosion at the agricultural plot scale are evaluated from elevation differences computed from very high resolution digital elevation models Ž. DEMs , from before and just after an extreme rainfall event. Geographical Information Systems Ž. GIS techniques are used to analyse the multi-temporal spatial data. The research case study presented makes reference to a mechanised vineyard plot located in the Alt Penedes-Anoia region `

Impact assessment of changes in land use/conservation practices on soil erosion in the Penedès–Anoia vineyard region (NE Spain)

Abstract Soil erosion by water is one of the most important land degradation processes in the Mediterranean basin. In comparison with other typical crops in this region, vineyards are the agricultural land use that cause the highest soil losses. The changes in land use types and management that have involved the intensification of agriculture from the 1950s have contributed to the increase of soil erosion. This paper presents an assessment of this impact in a vineyard region of fundamental concern in the NE Spain, the Penedes–Anoia, mainly dedicated to the production of high quality wines and “cavas”. The analysis is based on the comparison of the estimated soil loss rates in the period just before the mechanisation (1950s) and in the most recent past (1990s). Multitemporal data (aerial photographs and digital terrain models), the revised universal soil loss equation and GIS analysis were used for that purpose. The results show a clear negative soil loss balance, with 12.6% of the agricultural land having experienced major negative changes. This negative balance is associated with the increase of the area dedicated to vineyards, the transformation of old traditional vineyard plantations to modern trained plantations and to the removing of conservation practices to adopt plots to crop mechanisation. This leads to an unsustainable viticulture and soil degradation in medium- to long-term periods.

Nutrient losses from a vineyard soil in Northeastern Spain caused by an extraordinary rainfall event

Vineyards are one of the lands that incur the highest soil losses in Mediterranean environments. Most of the studies that report about this problem only focus on soil losses and few investigations have addressed the nutrient losses associated with erosion processes during the storms. The present research evaluates the loss of nitrogen, phosphorus and potassium in vineyard soils located in a Mediterranean area (NE Spain), after an extreme rainfall event recorded on 10 June 2000. The total rainfall of this event was 215 mm, 205 mm of which fell in 2 h 15 min. The maximum intensity in 30-min periods reached 170 mm h−1. This rainfall produced a large amount of sediments both inside and outside the plots, with the consequent soil mobilisation and loss of nutrients. The estimate of soil loss was based on the subtraction of two very accurate digital elevation models (DEMs) of different dates in GIS, and measures of the nutrient content of sediment collected in the plot. Soil loss in the study plot reached 207 mg ha−1. Most sediment was produced by concentrated surface runoff. Nutrient losses amounted as 108.5 kg ha−1 of N, 108.6 kg ha−1 of P and 35.6 kg ha−1 of K. The proposed method allowed mapping the sediment contribution and deposition areas and the distribution of the nutrient load and losses within the plot.

Prediction of existing gully erosion in vineyard parcels of the NE Spain: a logistic modelling approach

This paper presents a study of determining factors and a method to predict the existence of gully erosion in vineyard parcels. The Alt Penedes-Anoia region (Catalonia, NE Spain), mainly dedicated to the cropping of vineyards for high quality wine production, was selected as the case study area. Single factors related to the existence of gully erosion were determined by means of statistical tests (Students t-test and chi-square). The existence of gully erosion was predicted by means of a multivariate procedure. A stepwise selection of variables (relief, soil, land use/management characteristics) was performed, which allowed the identification of factors that present a significant relationship with the existence of gully erosion. The selected factors, slope degree and planar slope form, were considered as independent variables in a logistic regression of binary response. The model computes the probability that gullies exist in given vineyard parcels, and it can be implemented in a raster-based geographical information system (GIS). The assessment of the model in 52 parcels, different from the training data set, yielded an overall accuracy of 84.6%. The predictive model can be applied for areas with similar conditions, but the modelling approach can be applied in other different areas.

Spatial variability in grape yield and quality influenced by soil and crop nutrition characteristics

Knowledge of spatial variability of soil fertility and plant nutrition is critical for planning and implementing site-specific vineyard management. To better understand the key drivers behind vineyard variability, yield mapping from 2002 to 2005 and 2007 (the monitor broke down in 2006) was used to identify zones of different productive potential in a Pinot Noir field located in Raimat (Lleida, Spain). Simultaneously, the vineyard field was sampled in 2002, 2003 and 2007, applying three different schemes (depending on the number of target vines in different grape yield zones). The sampling carried out in 2002, which involved different soil, topographic and crop properties (mineral contents in petiole), made it possible to evaluate the influence of these parameters on the grape yield variability. The zones of lowest yield coincided with locations in which the nutritional status of the crop exhibited the lowest values, particularly with respect to petiole contents of calcium and manganese. Sampling systems adopted in 2003 and 2007 (grape quality and soil attributes) confirmed the inverse spatial correlation between grape yield and some grape quality parameters and, more importantly, showed that the percentage of soil carbonates had a great influence on grape quality probably due to the reduced availability of manganese in calcareous soils. Site-specific vineyard management could therefore be considered using two different strategies: variable-rate application of foliar fertilizers to increase the yield in areas with low production and also foliar or soil fertilizers to improve the quality specifications in some areas.

Mapping land cover from detailed aerial photography data using textural and neural network analysis

Automated mapping of land cover using black and white aerial photographs, as an alternative method to traditional photo‐interpretation, requires using methods other than spectral analysis classification. To this end, textural measurements have been shown to be useful indicators of land cover. In this work, a neural network model is proposed and tested to map historical land use/land cover (LUC) from very detailed panchromatic aerial photographs (5 m resolution) using textural measurements. The method is used to identify different land use and management types (e.g. traditional versus mechanized vineyard systems). These have been tested with known ground reference data. The results show the potential of the methodology to obtain automatic, historic, and very detailed cartography information from a complex landscape such as the mountainous and Mediterranean region to which it is applied here, and the advantages that this method has over traditional methods.

Seasonal temperature and precipitation variability during the last 60 years in a Mediterranean climate area of Northeastern Spain: a multivariate analysis

This paper presents the analysis of mean daily temperature and precipitation from 1950 to 2010 in an area with Mediterranean climate of NE Spain including some coastal areas near Barcelona and the Penedès and Camp de Tarragona Depressions located between the Coastal Mountain Range and the Mediterranean Sea. Their variability, with especial attention to the frequency of extreme events, was analysed by using 18 indexes: seven for temperature and 11 for precipitation were analysed for four meteorological observatories. A multivariate analysis was performed in order to analyse the temperature and precipitation trends. During the analysed period, an increase in mean annual maximum temperature was observed in all observatories ranging between 1.5 and 2.2°C associated with an increase in the number of days with high extreme temperatures. Minimum temperature only increased significantly in the coast observatories (about 1.4°C). By seasons, temperature trends were greater at Vilafranca del Penedès and Barcelona observatories and lower at Reus airport. Maximum spring temperature increased between 1.5 and 2.5°C, summer temperature increased between 1.6 and 2.5°C and autumn temperature increased by up to 2.2°C. Precipitation presented a high variability from year to year, without significant trends. The most significant results were related to the dry conditions observed in spring 2000s, the wet conditions recorded in summer 2000s and 1980s and the longer dry periods in autumn 2000s. The increase of temperatures determined the increase of evapotranspiration, and due to the higher irregular distribution, water deficits for crop development were recorded. An advance of phenological dates and a reduction of grape yield are associated to climate trends.

Analysis of Vegetation Indices to Determine Nitrogen Application and Yield Prediction in Maize (Zea mays L.) from a Standard UAV Service

The growing use of commercial unmanned aerial vehicles (UAV) and the need to adjust N fertilization rates in maize (Zea mays L.) currently constitute a key research issue. In this study, different multispectral vegetation indices (green-band and red-band based indices), SPAD and crop height (derived from a multispectral compact camera mounted on a UAV) were analysed to predict grain yield and determine whether an additional sidedress application of N fertilizer was required just before flowering. Seven different inorganic N rates (0, 100, 150, 200, 250, 300, 400 kg·N·ha−1), two different pig slurry manure rates (Ps) (150 or 250 kg·N·ha−1) and four different inorganic-organic N combinations (N100Ps150, N100Ps250, N200Ps150, N200Ps250) were applied to maize experimental plots. The spectral index that best explained final grain yield for the N treatments was the Wide Dynamic Range Vegetation Index (WDRVI). It identified a key threshold above/below 250–300 kg·N·ha−1. WDRVI, NDVI and crop height showed no significant response to extra N application at the economic optimum rate of fertilization (239.8 kg·N·ha−1), for which a grain yield of 16.12 Mg·ha−1 was obtained. This demonstrates their potential as yield predictors at V12 stage. Finally, a ranking of different vegetation indices and crop height is proposed to overcome the uncertainty associated with basing decisions on a single index.

A cartographic and database approach for land cover/use mapping and generalization from remotely sensed data

Classification of remotely sensed data involves a set of generalization processes, i.e. reality is simplified to a set of a few classes that are relevant to the application under consideration. This article introduces an approach to image classification that uses a class hierarchy structure for mapping unit definition at different generalization levels. This structure is implemented as an operational relational database and allows querying of more detailed land cover/use information from a higher abstraction level, which is that viewed by the map user. Elementary mapping units are defined on the basis of an unsupervised classification process in order to determine the land cover/use classes registered in the remotely sensed data. Mapping unit composition at different generalization levels is defined on the basis of membership values of sampled pixels to land cover/use classes. Unlike fuzzy classifications, membership values are presented to the user at mapping unit level.