Institute Economia

Madrid, Spain

Institute Economia

Madrid, Spain

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Rescia A.J.,Complutense University of Madrid | Sanz-Canada J.,Institute Economia
Agronomy for Sustainable Development | Year: 2017

Agricultural intensification and farm abandonment in Europe have induced dramatic social, economic, and ecological issues. Sustainable management may solve these issues by providing a viable economic margin and preserving biodiversity. Specifically, we propose herein monetary compensation for farmers maintaining or restoring lands as non-agricultural areas. The mechanism for funding this compensation is based upon spatial analysis of two olive-grove landscapes. These exhibited different land-use patterns, a simple landscape and a complex one presenting a 50% higher diversity index and an 80% higher complexity index. We estimated olive-oil production and profitability. Results showed that the complex landscape contains three times more protected habitats. Neither landscape was economically viable, with the simple one showing values of 43% below the threshold, and the complex one 185%. The mechanism proposed to fund farmer subsidies was developed by means of the spatial and economic data estimated. This conservation payment system considers a non-linear relationship between the subsidies paid and the preserved area of agricultural use. The farmers of the simple landscape would receive a subsidy of 299, 394, and 464 €/ha for 10, 20, and 30% of preserved area, respectively. Inversely, the farmers of the complex landscape would be granted a reduction of 38 and 80 €/ha in their monetary incentives for the loss of 10 and 20%, respectively, of natural areas. Using this funding mechanism, conservation of biodiversity in agricultural areas would no longer constitute a factor limiting profitability, but would rather complement earnings. © 2017, INRA and Springer-Verlag France.

Pacheco-Labrador J.,Institute Economia | Gonzalez-Cascon R.,Instituto Nacional Of Investigacion Y Tecnologia Agraria Y Alimentaria Inia | Pilar Martin M.,Institute Economia | Riano D.,Institute Economia | Riano D.,University of California at Davis
International Journal of Applied Earth Observation and Geoinformation | Year: 2014

The direct estimation of nitrogen (N) in fresh vegetation is challenging due to its weak influence on leaf reflectance and the overlaps with absorption features of other compounds. Different empirical modelsrelate in this work leaf nitrogen concentration ([N]Leaf) on Holm oak to leaf reflectance as well as derivedspectral indices such as normalized difference indices (NDIs), the three bands indices (TBIs) and indices previously used to predict leaf N and chlorophyll. The models were calibrated and assessed their accuracy, robustness and the strength of relationship when other biochemicals were considered. Red edge was the spectral region most strongly correlated with [N]Leaf, whereas most of the published spectral indexesdid not provide accurate estimations. NDIs and TBIs based models could achieve robust and acceptableaccuracies (TBI1310,1720,730: R2= 0.76, [0.64,0.86]; RMSE (%) = 9.36, [7.04,12.83]). These models sometimesincluded indices with bands close to absorption features of N bonds or nitrogenous compounds, but also of other biochemicals. Models were independently and inter-annually validated using the bootstrap method, which allowed discarding those models non-robust across different years. Partial correlationanalysis revealed that spectral estimators did not strongly respond to [N]Leaf but to other leaf variablessuch as chlorophyll and water, even if bands close to absorption features of N bonds or compounds werepresent in the models. © 2013 Elsevier B.V.

Cheng T.,University of California at Davis | Riano D.,University of California at Davis | Riano D.,Institute Economia | Ustin S.L.,University of California at Davis
Remote Sensing of Environment | Year: 2014

Continuous wavelet analysis (CWA) has recently been applied to leaf-level spectroscopic data for quantifying foliar chemistry, but it is unclear how well or whether CWA can be applied to imaging spectroscopy data under the conditions of higher noise level and more complicating factors. This study evaluates the application of CWA to airborne imaging spectroscopy data for predicting diurnal and seasonal variation in canopy water content (CWC) for nut tree orchards. We collected CWC measurements and concurrent imagery from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) instrument twice a day (morning and afternoon) in spring and fall of 2011 in California, USA. Several robust wavelet features were determined and compared to four water-sensitive spectral indices, three existing in the literature and one optimized in this study, for the assessment of predictive performance. Results showed that the best prediction using CWA (R2=0.84 and root mean square error (RMSE)=0.027kg/m2) was produced by a combination of three wavelet features and it was considerably better than those by the existing water indices. While the best wavelet feature (1100nm, scale 6) characterized the water absorption in the near-infrared region, the optimized index ND850,720 used a red edge band at 720nm instead of a direct water absorption band. A bootstrap sampling of the validation data set indicated that ND850,720 predicted CWC significantly worse (p<0.0001) and exhibited greater sensitivity to seasonality. Both CWA and ND850,720 revealed statistically significant diurnal declines of CWC in two different seasons in the context of a substantial seasonal decline, but the former detected greater declines in diurnal CWC. Our results demonstrated the feasibility of applying CWA to airborne imaging spectroscopy data for CWC mapping and its superiority to spectral indices for improved prediction of CWC and understanding of spectral-chemical relations. © 2013 Elsevier Inc.

Yebra M.,CSIRO | Dennison P.E.,University of Utah | Chuvieco E.,University of Alcalá | Riano D.,Institute Economia | And 6 more authors.
Remote Sensing of Environment | Year: 2013

One of the primary variables affecting ignition and spread of wildfire is fuel moisture content (FMC). Live FMC (LFMC) is responsive to long term climate and plant adaptations to drought, requiring remote sensing for monitoring of spatial and temporal variations in LFMC. Liquid water has strong absorption features in the near- and shortwave-infrared spectral regions, which provide a physical basis for direct estimation of LFMC. Complexity introduced by biophysical and biochemical properties at leaf and canopy scales presents theoretical and methodological problems that must be addressed before remote sensing can be used for operational monitoring of LFMC. The objective of this paper is to review the use of remotely sensed data for estimating LFMC, with particular concern towards the operational use of LFMC products for fire risk assessment. Relationships between LFMC and fire behavior have been found in fuel ignition experiments and at landscape scales, but the complexity of fire interactions with fuel structure has prevented linking LFMC to fire behavior at intermediate scales. Changes in LFMC have both direct (liquid water absorption) and indirect (pigment and structural changes) impacts on spectral reflectance. The literature is dominated by studies that have used statistical (empirical) and physical model-based methods applied to coarse resolution data covering the visible, near infrared, and/or shortwave infrared regions of the spectrum. Empirical relationships often have the drawback of being site-specific, while the selection and parameterization of physically-based algorithms are far more complex. Challenges remain in quantifying error of remote sensing-based LFMC estimations and linking LFMC to fire behavior and risk. The review concludes with a list of priority areas where advancement is needed to transition remote sensing of LFMC to operational use. © 2013 Elsevier Inc.

Martin M.P.,Institute Economia | Barreto L.,CSIC - Institute of Agricultural Sciences | Fernandez-Quintanilla C.,CSIC - Institute of Agricultural Sciences
Crop Protection | Year: 2011

Site-specific weed management implies detecting the location of weeds in order to generate maps of their spatial distribution. This information facilitates a more accurate application of herbicides, spraying them in the exact areas of weed growth and in the required doses. In order to explore the potential of commercial satellites to discriminate and map weeds, we used the information contained in high spatial resolution images acquired by the QuickBird satellite to assess the density of sterile oat (Avena sterilis) present in a winter barley field at two different dates (March and June). Our results confirmed the potential of using satellite images in the spectral discrimination of weed patches in infested fields. The results of binary logistic regressions showed that the best matches in the classification of three categories (low, medium, or high sterile oat densities) corresponded to the March image. QuickBird's March image provided reliable estimates of sterile oat patches in barley crops when weed density was relatively high (between 86% and 94% of agreement between predicted and observed densities). However, when weed densities were lower than 10 plants/m2 there were serious difficulties to distinguish them from weed-free zones (between 72 and 75% of global agreement in the classification) with large underestimation of medium density weed patches (10 plants/m2). This is a potential limitation considering than the thresholds used for herbicide application decisions are generally close to this density. However, the information obtained may still be useful for producing field maps to describe the spatial distribution of this weed. Moreover, these studies have provided valuable information on the best spectral regions and/or vegetation indices for approaching discrimination between sterile oat and cereal crops and the most suitable period for it. © 2011 Elsevier Ltd.

Holl A.,Institute Politicas y Bienes Publicos IPP | Pardo R.,Fundacion BBVA | Rama R.,Institute Economia
Papers in Regional Science | Year: 2013

We study the spatial pattern of just-in-time (JIT) adoption for a sample of medium-sized and large Spanish manufacturing firms. JIT differs from other advanced manufacturing technologies because it relates directly to the spatial co-ordination of firms' internal production organisation with the external productive environment and depends on the quality of the transport system. Our results confirm the distinctive role of location for JIT adoption even after controlling for industry and plant-specific differences. We find that JIT adoption is greater in smaller cities but with higher transport accessibility indicating that urban congestion in larger urban areas likely reduces the benefits that firms may obtain from JIT implementation. © 2011 the author(s). Papers in Regional Science.

Cendon M.L.,Instituto Nacional de Tecnologia Agropecuaria | Sanz-Canada J.,Institute Economia | Lucena-Piquero D.,Independent researcher
Spanish Journal of Agricultural Research | Year: 2014

A relevant topic investigated in ‘Local Agro-Food Systems’ studies (LAFS) is the key role of collective action in the dissemination of innovations and knowledge aimed at the organization of quality on a local scale. The scope of this article deals with the methodological tools for typifying the relationships made, in LAFS hosting a Protected Designation of Origin (PDO), between the relational social capital and the differential quality of firms. The objective of this work is to categorize the agro-industrial firms into hierarchies for implementing rural development policies, with respect to their technical and managerial advice relationships and their score achieved in terms of product and process quality. The study takes into account the LAFS of “Estepa” and “Sierra de Segura”, Andalusia (S Spain), corresponding to two important olive oil PDOs. The methodological approach comprises, firstly, the elaboration of a quality synthetic indicator on processes and products of the mills. Secondly, social network analysis is applied to the technical/managerial advice networks of the mills. Thirdly, a mill typology was established by means of factor analysis which employs quality and relational indicators. It is proved that the Regulatory Boards, as well as the second-step cooperatives, can assume a role of integrating poles with respect to the collective action developed in the LAFS, particularly in terms of dissemination of knowledge and innovations, which enhances the process and product quality of local firms. The existence of networks is a necessary condition to improve and homogenize the quality in a diffuse local agro-food structure. © 2014 Ministerio de Agricultura Pesca y Alimentacion. All Rights Reserved.

Pacheco-Labrador J.,Institute Economia | Ferrero A.,Institute Optica Daza Of Valdes | Martin M.P.,Institute Economia
Applied Optics | Year: 2014

We report a nonlinearity effect related to the integration time in a double-beam spectroradiometer equipped with two negative-module metal-oxide semiconductor (NMOS) sensors. This effect can be explained by the addition of photoelectrons produced by the radiant flux on the sensors during the readout phase to the photoelectrons produced during the measurement phase. A new method is proposed to characterize and correct both gray-level and integration-time-related nonlinearities in NMOS sensors. This method is experimentally simple and outperforms other commonly used correction procedures. © 2014 Optical Society of America.

Care provided by relatives or friends to dependent people is a key process to promote wellbeing in Spanish society. This type of support has intense consequences over caregivers' lives. Comprehensive and multidisciplinary analyses are required to assess dependency effects over social network. In this paper we elaborate a classification of types of family care consequences over caregivers. We differentiate between positive or negative consequences, and between consequences affecting caregivers' health, economy and/or social relations. © 2010 Fundación Index.

The metropolitan region of Madrid has undergone significant changes in the last two decades, establishing it as the main economic centre with command functions in Southern Europe. This has resulted in a rapid increase in its rates of production and consumption, the size of its immigrant population and the processes of low-density suburbanisation (sprawl) becoming more common. But this trend, which can be linked to its prominent position in the world cities network, has been accompanied by significant social and environmental costs, an abrupt crisis since 2008 and the deepening of socio-spatial inequalities within. The progressive growth of the knowledge economy is a good indicator of this type of essentially contradictory process which signals the integration of megacities into global capitalism and the associated territorial changes.

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