Assessing the capabilities of high-resolution spectral, altimetric, and textural descriptors for mapping the status of citrus parcels

[EN] Agricultural land abandonment is an increasing phenomenon around the world with relevant environmental and socio-economic implications. In the European Union about 11 % of agricultural land is at high risk of abandonment. The Comunitat Valenciana region (Spain) is the most important citrus producer in Europe suffering from this problem. Identifying the status of citrus crops at the parcel level is essential for policymakers in agriculture. This work assessed the use of WorldView-3 data, Very High-Resolution Airborne Images, and Structure from Motion point clouds to identify the status of citrus parcels using two machine learning algorithms: Random Forest and Support Vector Machines. Different analyses involving combinations of the three data sources were carried out to assess the impact on classification accuracy. The results showed the high potential of airborne imagery (OA ¿ 0.967) and WorldView-3 (OA ¿ 0.936) to detect parcel status using a single image. The SfM data showed a lower potential (OA ¿ 0.825). Adding SfM point cloud to the multispectral information produced small improvements (0.4¿2.0 %) in classification accuracy. The class separability analysis showed the importance of WV-3 SWIR bands to detect abandoned parcels as they produce more spectral separability over the productive parcels in the 1570 nm ¿ 2330 nm spectrum. The results also show the importance of GLCM texture features extracted from sub-metric images due to their ability to model spatial planting patterns typical of fruit cropsThis research was funded by regional government of Spain, Generalitat Valenciana, within the framework of the research project AICO/2020/246. Funding for open access charge: CRUE-Universitat Politecnica de Valencia.Morell-Monzó, S.; Estornell Cremades, J.; Sebastiá-Frasquet, M. (2023). Assessing the capabilities of high-resolution spectral, altimetric, and textural descriptors for mapping the status of citrus parcels. Computers and Electronics in Agriculture. 204:1-11. https://doi.org/10.1016/j.compag.2022.10750411120

Land Use Classification of VHR Images for Mapping Small-Sized Abandoned Citrus Plots by Using Spectral and Textural Information

[EN] Agricultural land abandonment is an increasing problem in Europe. The Comunitat Valenciana Region (Spain) is one of the most important citrus producers in Europe suffering this problem. This region characterizes by small sized citrus plots and high spatial fragmentation which makes necessary to use Very High-Resolution images to detect abandoned plots. In this paper spectral and Gray Level Co-Occurrence Matrix (GLCM)-based textural information derived from the Normalized Difference Vegetation Index (NDVI) are used to map abandoned citrus plots in Oliva municipality (eastern Spain). The proposed methodology is based on three general steps: (a) extraction of spectral and textural features from the image, (b) pixel-based classification of the image using the Random Forest algorithm, and (c) assignment of a single value per plot by majority voting. The best results were obtained when extracting the texture features with a 9 x 9 window size and the Random Forest model showed convergence around 100 decision trees. Cross-validation of the model showed an overall accuracy of the pixel-based classification of 87% and an overall accuracy of the plot-based classification of 95%. All the variables used are statistically significant for the classification, however the most important were contrast, dissimilarity, NIR band (720 nm), and blue band (620 nm). According to our results, 31% of the plots classified as citrus in Oliva by current methodology are abandoned. This is very important to avoid overestimating crop yield calculations by public administrations. The model was applied successfully outside the main study area (Oliva municipality); with a slightly lower accuracy (92%). This research provides a new approach to map small agricultural plots, especially to detect land abandonment in woody evergreen crops that have been little studied until now.This research was funded by regional government of Spain, Generalitat Valenciana, within the framework of the research project AICO/2020/246 and the APC was also funded by the research project AICO/2020/246.Morell-Monzó, S.; Sebastiá-Frasquet, M.; Estornell Cremades, J. (2021). Land Use Classification of VHR Images for Mapping Small-Sized Abandoned Citrus Plots by Using Spectral and Textural Information. Remote Sensing. 13(4):1-18. https://doi.org/10.3390/rs13040681S11813

Comparison of Sentinel-2 and High-Resolution Imagery for Mapping Land Abandonment in Fragmented Areas

[EN] Agricultural land abandonment is an important environmental issue in Europe. The proper management of agricultural areas has important implications for ecosystem services (food production, biodiversity, climate regulation and the landscape). In the coming years, an increase of abandoned areas is expected due to socio-economic changes. The identification and quantification of abandoned agricultural plots is key for monitoring this process and for applying management measures. The Valencian Region (Spain) is an important fruit and vegetable producing area in Europe, and it has the most important citrus industry. However, this agricultural sector is highly threatened by diverse factors, which have accelerated land abandonment. Landsat and MODIS satellite images have been used to map land abandonment. However, these images do not give good results in areas with high spatial fragmentation and small-sized agricultural plots. Sentinel-2 and airborne imagery shows unexplored potential to overcome this thanks to higher spatial resolutions. In this work, three models were compared for mapping abandoned plots using Sentinel-2 with 10 m bands, Sentinel-2 with 10 m and 20 m bands, and airborne imagery with 1 m visible and near-infrared bands. A pixel-based classification approach was used, applying the Random Forests algorithm. The algorithm was trained with 144 plots and 100 decision trees. The results were validated using the hold-out method with 96 independent plots. The most accurate map was obtained using airborne images, the Enhanced Vegetation Index (EVI) and Thiam's Transformed Vegetation Index (TTVI), with an overall accuracy of 88.5%. The map generated from Sentinel-2 images (10 m bands and the EVI and TTVI spectral indices) had an overall accuracy of 77.1%. Adding 20 m Sentinel-2 bands and the Normalized Difference Moisture Index (NDMI) did not improve the classification accuracy. According to the most accurate map, 4310 abandoned plots were detected in our study area, representing 32.5% of its agricultural surface. The proposed methodology proved to be useful for mapping citrus in highly fragmented areas, and it can be adapted to other crops.Morell-Monzó, S.; Estornell Cremades, J.; Sebastiá-Frasquet, M. (2020). Comparison of Sentinel-2 and High-Resolution Imagery for Mapping Land Abandonment in Fragmented Areas. Remote Sensing. 12(12):1-18. https://doi.org/10.3390/rs12122062S1181212MacDonald, D., Crabtree, J. ., Wiesinger, G., Dax, T., Stamou, N., Fleury, P., … Gibon, A. (2000). Agricultural abandonment in mountain areas of Europe: Environmental consequences and policy response. Journal of Environmental Management, 59(1), 47-69. doi:10.1006/jema.1999.0335Kosmas, C., Kairis, O., Karavitis, C., Acikalin, S., Alcalá, M., Alfama, P., … Solé-Benet, A. (2015). An exploratory analysis of land abandonment drivers in areas prone to desertification. CATENA, 128, 252-261. doi:10.1016/j.catena.2014.02.006Corbelle Rico, E., & Crecente Maseda, R. (2018). Estudio da evolución da superficie agrícola na comarca da Terra Chá a partir de fotografía aérea histórica e mapas de usos, 1956-2004. Recursos Rurais, (4), 57-65. doi:10.15304/rr.id5312Gellrich, M., Baur, P., Koch, B., & Zimmermann, N. E. (2007). Agricultural land abandonment and natural forest re-growth in the Swiss mountains: A spatially explicit economic analysis. Agriculture, Ecosystems & Environment, 118(1-4), 93-108. doi:10.1016/j.agee.2006.05.001Rey Benayas, J. M. (2007). Abandonment of agricultural land: an overview of drivers and consequences. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 2(057). doi:10.1079/pavsnnr20072057Árgyelán, T. (2015). Abandonment phenomenon in Europe. Acta Universitatis Sapientiae, Agriculture and Environment, 7(1), 89-97. doi:10.1515/ausae-2015-0008Citricultura Valenciana: Gestión Integrada de Plagas y Enfermedades en Cítricoshttp://gipcitricos.ivia.es/citricultura-valencianaRounsevell, M. D. A., Reginster, I., Araújo, M. B., Carter, T. R., Dendoncker, N., Ewert, F., … Tuck, G. (2006). A coherent set of future land use change scenarios for Europe. Agriculture, Ecosystems & Environment, 114(1), 57-68. doi:10.1016/j.agee.2005.11.027Verburg, P. H., Schulp, C. J. E., Witte, N., & Veldkamp, A. (2006). Downscaling of land use change scenarios to assess the dynamics of European landscapes. Agriculture, Ecosystems & Environment, 114(1), 39-56. doi:10.1016/j.agee.2005.11.024Dubinin, M., Potapov, P., Lushchekina, A., & Radeloff, V. C. (2010). Reconstructing long time series of burned areas in arid grasslands of southern Russia by satellite remote sensing. Remote Sensing of Environment, 114(8), 1638-1648. doi:10.1016/j.rse.2010.02.010Ruiz-Flan˜o, P., Garci´a-Ruiz, J. M., & Ortigosa, L. (1992). Geomorphological evolution of abandoned fields. A case study in the Central Pyrenees. CATENA, 19(3-4), 301-308. doi:10.1016/0341-8162(92)90004-uFischer, J., Hartel, T., & Kuemmerle, T. (2012). Conservation policy in traditional farming landscapes. Conservation Letters, 5(3), 167-175. doi:10.1111/j.1755-263x.2012.00227.xPenov, I. (2004). The Use of Irrigation Water in Bulgaria’s Plovdiv Region During Transition. Environmental Management, 34(2), 304-313. doi:10.1007/s00267-004-0019-8Novara, A., Gristina, L., Sala, G., Galati, A., Crescimanno, M., Cerdà, A., … La Mantia, T. (2017). Agricultural land abandonment in Mediterranean environment provides ecosystem services via soil carbon sequestration. Science of The Total Environment, 576, 420-429. doi:10.1016/j.scitotenv.2016.10.123Cerdà, A., Ackermann, O., Terol, E., & Rodrigo-Comino, J. (2019). Impact of Farmland Abandonment on Water Resources and Soil Conservation in Citrus Plantations in Eastern Spain. Water, 11(4), 824. doi:10.3390/w11040824Rey Benayas, J. M., & Bullock, J. M. (2012). Restoration of Biodiversity and Ecosystem Services on Agricultural Land. Ecosystems, 15(6), 883-899. doi:10.1007/s10021-012-9552-0Shrivastava, R. J., & Gebelein, J. L. (2007). Land cover classification and economic assessment of citrus groves using remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 61(5), 341-353. doi:10.1016/j.isprsjprs.2006.10.003Löw, F., Prishchepov, A., Waldner, F., Dubovyk, O., Akramkhanov, A., Biradar, C., & Lamers, J. (2018). Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series. Remote Sensing, 10(2), 159. doi:10.3390/rs10020159Alcantara, C., Kuemmerle, T., Prishchepov, A. V., & Radeloff, V. C. (2012). Mapping abandoned agriculture with multi-temporal MODIS satellite data. Remote Sensing of Environment, 124, 334-347. doi:10.1016/j.rse.2012.05.019Estel, S., Kuemmerle, T., Alcántara, C., Levers, C., Prishchepov, A., & Hostert, P. (2015). Mapping farmland abandonment and recultivation across Europe using MODIS NDVI time series. Remote Sensing of Environment, 163, 312-325. doi:10.1016/j.rse.2015.03.028Dara, A., Baumann, M., Kuemmerle, T., Pflugmacher, D., Rabe, A., Griffiths, P., … Hostert, P. (2018). Mapping the timing of cropland abandonment and recultivation in northern Kazakhstan using annual Landsat time series. Remote Sensing of Environment, 213, 49-60. doi:10.1016/j.rse.2018.05.005Müller, D., Leitão, P. J., & Sikor, T. (2013). Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees. Agricultural Systems, 117, 66-77. doi:10.1016/j.agsy.2012.12.010Yin, H., Prishchepov, A. V., Kuemmerle, T., Bleyhl, B., Buchner, J., & Radeloff, V. C. (2018). Mapping agricultural land abandonment from spatial and temporal segmentation of Landsat time series. Remote Sensing of Environment, 210, 12-24. doi:10.1016/j.rse.2018.02.050Kuemmerle, T., Hostert, P., Radeloff, V. C., van der Linden, S., Perzanowski, K., & Kruhlov, I. (2008). Cross-border Comparison of Post-socialist Farmland Abandonment in the Carpathians. Ecosystems, 11(4), 614-628. doi:10.1007/s10021-008-9146-zGrădinaru, S. R., Kienast, F., & Psomas, A. (2019). Using multi-seasonal Landsat imagery for rapid identification of abandoned land in areas affected by urban sprawl. Ecological Indicators, 96, 79-86. doi:10.1016/j.ecolind.2017.06.022Prishchepov, A. V., Radeloff, V. C., Dubinin, M., & Alcantara, C. (2012). The effect of Landsat ETM/ETM + image acquisition dates on the detection of agricultural land abandonment in Eastern Europe. Remote Sensing of Environment, 126, 195-209. doi:10.1016/j.rse.2012.08.017Baumann, M., Kuemmerle, T., Elbakidze, M., Ozdogan, M., Radeloff, V. C., Keuler, N. S., … Hostert, P. (2011). Patterns and drivers of post-socialist farmland abandonment in Western Ukraine. Land Use Policy, 28(3), 552-562. doi:10.1016/j.landusepol.2010.11.003Szostak, M., Hawryło, P., & Piela, D. (2017). Using of Sentinel-2 images for automation of the forest succession detection. European Journal of Remote Sensing, 51(1), 142-149. doi:10.1080/22797254.2017.1412272Kanjir, U., Đurić, N., & Veljanovski, T. (2018). Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring. ISPRS International Journal of Geo-Information, 7(10), 405. doi:10.3390/ijgi7100405Proisy, C., Viennois, G., Sidik, F., Andayani, A., Enright, J. A., Guitet, S., … Suhardjono. (2018). Monitoring mangrove forests after aquaculture abandonment using time series of very high spatial resolution satellite images: A case study from the Perancak estuary, Bali, Indonesia. Marine Pollution Bulletin, 131, 61-71. doi:10.1016/j.marpolbul.2017.05.056Thanh Noi, P., & Kappas, M. (2017). Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery. Sensors, 18(2), 18. doi:10.3390/s18010018Maxwell, A. E., Warner, T. A., & Fang, F. (2018). Implementation of machine-learning classification in remote sensing: an applied review. International Journal of Remote Sensing, 39(9), 2784-2817. doi:10.1080/01431161.2018.1433343https://rdrr.io/cran/raster/https://cran.r-project.org/web/packages/rgdal/index.htmlHuete, A., Justice, C., & Liu, H. (1994). Development of vegetation and soil indices for MODIS-EOS. Remote Sensing of Environment, 49(3), 224-234. doi:10.1016/0034-4257(94)90018-3Wilson, E. H., & Sader, S. A. (2002). Detection of forest harvest type using multiple dates of Landsat TM imagery. Remote Sensing of Environment, 80(3), 385-396. doi:10.1016/s0034-4257(01)00318-2Silleos, N. G., Alexandridis, T. K., Gitas, I. Z., & Perakis, K. (2006). Vegetation Indices: Advances Made in Biomass Estimation and Vegetation Monitoring in the Last 30 Years. Geocarto International, 21(4), 21-28. doi:10.1080/10106040608542399Huete, A. . (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), 295-309. doi:10.1016/0034-4257(88)90106-xGitelson, A. A., Kaufman, Y. J., & Merzlyak, M. N. (1996). Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment, 58(3), 289-298. doi:10.1016/s0034-4257(96)00072-7Breiman, L. (2001). Machine Learning, 45(1), 5-32. doi:10.1023/a:1010933404324Gislason, P. O., Benediktsson, J. A., & Sveinsson, J. R. (2006). Random Forests for land cover classification. Pattern Recognition Letters, 27(4), 294-300. doi:10.1016/j.patrec.2005.08.011Breiman, L. (1996). Bagging predictors. Machine Learning, 24(2), 123-140. doi:10.1007/bf00058655Pal, M. (2005). Random forest classifier for remote sensing classification. International Journal of Remote Sensing, 26(1), 217-222. doi:10.1080/01431160412331269698Olofsson, P., Foody, G. M., Herold, M., Stehman, S. V., Woodcock, C. E., & Wulder, M. A. (2014). Good practices for estimating area and assessing accuracy of land change. Remote Sensing of Environment, 148, 42-57. doi:10.1016/j.rse.2014.02.015Whiteside, T. G., Maier, S. W., & Boggs, G. S. (2014). Area-based and location-based validation of classified image objects. International Journal of Applied Earth Observation and Geoinformation, 28, 117-130. doi:10.1016/j.jag.2013.11.009Morell Monzó, S., & Membrado-Tena, J. C. (2019). Causas y consecuencias del crecimiento urbanístico en el litoral valenciano a través de la evolución de los usos del suelo. El caso de Oliva. Cuadernos de Turismo, (44), 303-326. doi:10.6018/turismo.44.404861Smith, P., House, J. I., Bustamante, M., Sobocká, J., Harper, R., Pan, G., … Pugh, T. A. M. (2015). Global change pressures on soils from land use and management. Global Change Biology, 22(3), 1008-1028. doi:10.1111/gcb.1306

Periphyton and phytoplankton assessment in a shrimp nursery: signature pigments analysis

[EN] Understanding microalgae composition is key for an improved aquaculture system management. The primary objective of this research was to estimate microalgae community structure in a Marsupenaeus japonicus nursery. The secondary objective was to analyze the environmental parameters (salinity, pH, dissolved oxygen, total dissolved ammonia, nitrites, nitrates and phosphates) and shrimp density effect on abundance, composition and development of microalgae in a shrimp nursery. Periphyton and phytoplankton composition and abundance were determined using HPLC signature pigment analysis coupled with CHEMTAX software. Environmental parameters were measured in the tanks with probes or in the laboratory following standard procedures of water quality analysis. A nonparametric repeated-measures ANOVA statistical analysis was done to test differences between treatments. Spearman rank correlation analyses were performed on environmental and biological variables with phytoplankton or periphyton groups in order to examine significant relationship. The results showed diatoms were significantly higher than any other groups in both phytoplankton and periphyton communities. Shrimp density effect on periphyton, phytoplankton composition and environmental parameters was minor. Nutrients played a key role on phytoplankton development, but had a minor effect on periphyton, which was more affected by colonization processes and other environmental variables. The analysis of signature pigments allowed to report the presence of previously undetected groups on periphyton, prasinophytes and prymnesiophytes, which are characterized by high nutritional value. This is especially important in nurseries because shrimp grazing on periphyton can increase post-larvae survival.Financial support for this research was provided by Conselleria d'Educacio, Investigacio, Cultura i Esport of the Generalitat Valenciana, through the program VALi+D, file Number ACIF/2014/244. The authors want to thank the anonymous reviewer for the accurate revision and useful comments which helped to improve the original manuscript.Llario, F.; Rodilla, M.; Falco, S.; Escrivá, J.; Sebastiá-Frasquet, M. (2020). Periphyton and phytoplankton assessment in a shrimp nursery: signature pigments analysis. International Journal of Environmental Science and Technology. 17(2):857-868. https://doi.org/10.1007/s13762-019-02515-zS85786817

Remote Sensing Temporal Reconstruction of the Flooded Area in "Tablas de Daimiel" Inland Wetland 2000-2021

[EN] Tablas de Daimiel National Park (TDNP) is a unique inland wetland located in the Mancha plain (Spain). It is recognized at the international level, and it is protected by different figures, such as Biosphere Reserve. However, this ecosystem is endangered due to aquifer overexploitation, and it is at risk of losing its protection figures. The objective of our study is to analyze the evolution of the flooded area between the year 2000 and 2021 by Landsat (5, 7 and 8) and Sentinel-2 images, and to assess the TDNP state through an anomaly analysis of the total water body surface. Several water indices were tested, but the NDWI index for Sentinel-2 (threshold -0.20), the MNDWI for Landsat-5 (threshold -0.15), and the MNDWI for Landsat-8 (threshold -0.25) showed the highest accuracy to calculate the flooded surface inside the protected area's limits. During the period 2015-2021, we compared the performance of Landsat-8 and Sentinel-2 and an R2 value of 0.87 was obtained for this analysis, indicating a high correspondence between both sensors. Our results indicate a high variability of the flooded areas during the analyzed period with significant peaks, the most notorious in the second quarter of 2010. Minimum flooded areas were observed with negative precipitation index anomalies since fourth quarter of 2004 to fourth quarter of 2009. This period corresponds to a severe drought that affected this region and caused important deterioration. No significant correlation was observed between water surface anomalies and precipitation anomalies, and the significant correlation with flow and piezometric anomalies was moderate. This can be explained because of the complexity of water uses in this wetland, which includes illegal wells and the geological heterogeneity.Pena-Regueiro, J.; Estornell Cremades, J.; Aguilar-Maldonado, J.; Sebastiá-Frasquet, M. (2023). Remote Sensing Temporal Reconstruction of the Flooded Area in "Tablas de Daimiel" Inland Wetland 2000-2021. Sensors. 23(8). https://doi.org/10.3390/s2308409623

COMPARISON OF GAMIFICATION TOOLS FOR EVALUATING THE ETHICAL, ENVIRONMENTAL AND PROFESSIONAL RESPONSIBILITY SKILLS IN SCIENCE DEGREES

In the last two years the Universitat Politècnica de València (UPV) has implemented the evaluation of key transversal competences in its degrees. The objective is to offer an added value both for UPV s graduates and their employers. Nowadays, labour market is demanding not only professional skills but also personal and transversal competences development. However, evaluating these skills may require evaluation methods and techniques different to traditional ones. The authors have worked with gamification tools to help assessing student s performance in Ethical, environmental and professional responsibility skill. The experiences described have been developed in the frame of an Innovative Educational Project Improvement during the academic years 2014/2015 and 2015/2016. The aim of this paper is to compare the performance of two gamification applications, Socrative and Quizbean, for evaluating the above mentioned skill. Both applications can be used in the classroom with different devices such as laptops, tablets or mobile phones, and are based on creating questionnaires. These applications also share other characteristics such as high number of questions allowed, relatively high number of students in the classroom, instant results, etc. Socrative was used in Thermodynamics and Chemical Kinetics course in the first year of the Bachelor s degree in Biotechnology. Quizbean was used in Groundwater management subject in the fourth year of the Bachelor s degree in Environmental Sciences. To increase student motivation, game rules were included to encourage competition. The questionnaires were designed and classified according to 3 possible levels of acquisition of the key competence, these levels are fully described in a specific rubric that was explained beforehand to the students. Both applications performed successfully and the specificities of each gamification tool are described in the results. Students were satisfactorily involved in the activity, and some examples are included to show different levels of competence acquisition.The authors would like to thank the Vice-Rectorate for Studies, Quality and Acreditation of the Universitat Politècnica de València for funding the lnnovation and Educational Improvement Project A005: “Experiencia piloto de evaluación en distintas titulaciones de la UPV de la competencia transversal UPV Responsabilidad ética, medioambiental y profesional”Sebastiá-Frasquet, M.; Vargas Colás, MD.; Asensio Cuesta, S.; Pascual-Seva, N. (2016). COMPARISON OF GAMIFICATION TOOLS FOR EVALUATING THE ETHICAL, ENVIRONMENTAL AND PROFESSIONAL RESPONSIBILITY SKILLS IN SCIENCE DEGREES. IATED. https://doi.org/10.21125/iceri.2016.1855

Active methodologies for deep learning in sustainable development goals

[EN] The general objective of this project was to improve the quality of student learning, from the point of view of a global objective, sustainable development, and therefore aligned with the SDGs (Sustainable Development Goals). It is intended that students achieve deep learning in this area, favouring the transfer of the knowledge acquired to their future professional and social life. This deep learning promotes the integral development of the student, not only from an academic point of view, but also social and ecological. Project Based Learning (PBL), as an active learning methodology, is being widely used as a deep learning strategy. In this project, it has been used in several subjects, from different degrees, schools, and campus. The learning strategies have been evaluated by means of a learning evaluation questionnaire (CEVEAPEU) before and after the application of the PBL. In addition, student satisfaction and generic skills (i.e. ethical, environmental and professional responsibility) have been assessed. The project aims to find a solution a specific real case, such as an environmental or social problem. The results show that PBL has favoured the cooperative work of students and has increased their motivation. The students could select the topics that interest them the most and that they consider important in their professional future. They have worked collaboratively and actively, planning the project, making decisions, implementing it, and evaluating it. The students have ¿acted¿ and the teachers have been advisors or guides, thus promoting intrinsic motivation. This active methodology has allowed students to learn in a collaborative and cooperative way, fostering their motivation and achieving deep learning in environmental aspects.The project of innovation and educational improvement in which this communication is framed has received financial support from the Institute of Education Sciences (ICE) of the Universitat Politècnica de València (UPV) Proyecto de Innovación y Mejora Educativa (PIME/19-20/174 ), Objetivo Agenda 2030 y UPV 2020: Aprendizaje ambiental profundo en la UPV.Romero Gil, I.; Paches Giner, MAV.; Sebastiá-Frasquet, M.; Hernández Crespo, C. (2021). Active methodologies for deep learning in sustainable development goals. IATED Academy. 5506-5513. https://doi.org/10.21125/inted.2021.1115S5506551

Turbidity patterns in the Albufera lake, Spain, and their relation to irrigation cycles

[EN] The Albufera Natural Park (Valencia, Spain) is one of the most representative coastal wetlands in the Mediterranean basin. It holds several protection designations at national and international level, such as Spanish Natural Park, Special Protection Areas (SPAs) for birds, Sites of Community Importance (SCIs) and Ramsar Site. Both the park and its main lake, Albufera¿s lake, face several environmental problems. One of them is reduced transparency and lake clogging. The lake is highly dependent on the rice cycle and on irrigation returns, mainly from the Acequia Real. In this study, we analyse the monthly transparency and turbidity patterns during year 2018, and we relate them to irrigation cycles. We used Sentinel 2A satellite images from the European Space Agency, which have an atmospheric correction. Remote sensing results were compared with in situ data from the monitoring program of the Environment General Subdivision of the regional government. This monitoring program samples five points on a monthly basis, and analyses Secchi disk depth, suspended solids and chlorophyll a. Our results show the temporal and spatial pattern of turbidity in the Albufera lake which offers relevant information for water resources management.María-Teresa Sebastiá-Frasquet was beneficiary of the CAS18/00107 post-doctoral research grant, supported by the Spanish Ministry of Education Culture and Sports during her stay at the Universidad Autónoma de Baja California (Mexico), image processing was partially developed during the staySebastiá-Frasquet, M.; Aguilar-Maldonado, JA.; Santamaría-Del-Ángel, E.; Altur Grau, VJ. (2019). Turbidity patterns in the Albufera lake, Spain, and their relation to irrigation cycles. WIT Transactions on Ecology and the Environment (Online). 239:173-180. https://doi.org/10.2495/WS190151S17318023

Adaptation of urban uses of environmental characteristics: A case study of La Safor, Valencia, Spain

[EN] In the 1990s a methodology was developed to apply the concept of land aptitude to urban plans. This methodology was based on the concepts of capacity and vulnerability in the face of different urban uses (e.g. residential use, industrial use and strategic facilities). The methodology was implemented thanks to geographical information systems (GIS) mapping of available cartography. In recent years, the available cartography has increased in quantity and in spatial resolution. Also, urban planning and environmental legislation have evolved. In this study, we propose a methodological update to incorporate all these changes. The updated methodology is applied to La Safor (Valencia, Spain), which is a region composed of 31 municipalities. La Safor is a model case study because of its characteristics that makes it representative of both coastal and inner areas. Our results point out the need to incorporate legal constraints to the methodology. Including climate adaptation is also essential for strategic urbanism and to accomplish environmental requirements. The methodology presented can be defined as an integrated assessment tool necessary for sustainable development and minimizing environmental risks.Altur Grau, VJ.; Aguilar-Maldonado, JA.; Sebastiá-Frasquet, M.; Miralles García, JL. (2019). Adaptation of urban uses of environmental characteristics: A case study of La Safor, Valencia, Spain. WIT Transactions on Ecology and the Environment (Online). 238:187-198. https://doi.org/10.2495/SC190171S18719823

Mapping Satellite Inherent Optical Properties Index in Coastal Waters of the Yucatán Peninsula (Mexico)

[EN] The Yucatan Peninsula hosts worldwide-known tourism destinations that concentrate most of the Mexico tourism activity. In this region, tourism has exponentially increased over the last years, including wildlife oriented tourism. Rapid tourism development, involving the consequent construction of hotels and tourist commodities, is associated with domestic sewage discharges from septic tanks. In this karstic environment, submarine groundwater discharges are very important and highly vulnerable to anthropogenic pollution. Nutrient loadings are linked to harmful algal blooms, which are an issue of concern to local and federal authorities due to their recurrence and socioeconomic and human health costs. In this study, we used satellite products from MODIS (Moderate Resolution Imaging Spectroradiometer) to calculate and map the satellite Inherent Optical Properties (IOP) Index. We worked with different scenarios considering both holiday and hydrological seasons. Our results showed that the satellite IOP Index allows one to build baseline information in a sustainable mid-term or long-term basis which is key for ecosystem-based management.This research was funded by CONACYT with a doctorate scholarship to Jesús A. Aguilar-Maldonado,with the announcement number 251025 in 2015. María-Teresa Sebastiá-Frasquet was a beneficiary of the BEST/2017/217 post-doctoral research grant, supported by the Valencian Conselleria d’Educació, Investigació,Cultura i Esport (Spain) during her stay at the Universidad Autónoma de Baja California (Mexico). The Secretariat of Public Education of Mexico (SEP) under the Program for Professional Development Teacher, covered the costs of publication in open access.Aguilar-Maldonado, J.; Santamaría-Del-Ángel, E.; González-Silvera, A.; Cervantes-Rosas, OD.; Sebastiá-Frasquet, M. (2018). Mapping Satellite Inherent Optical Properties Index in Coastal Waters of the Yucatán Peninsula (Mexico). Sustainability. 10(6). https://doi.org/10.3390/su10061894S1894106Bentz, J., Lopes, F., Calado, H., & Dearden, P. (2016). Sustaining marine wildlife tourism through linking Limits of Acceptable Change and zoning in the Wildlife Tourism Model. Marine Policy, 68, 100-107. doi:10.1016/j.marpol.2016.02.016Jarvis, D., Stoeckl, N., & Liu, H.-B. (2016). The impact of economic, social and environmental factors on trip satisfaction and the likelihood of visitors returning. Tourism Management, 52, 1-18. doi:10.1016/j.tourman.2015.06.003Ziegler, J., Dearden, P., & Rollins, R. (2012). But are tourists satisfied? Importance-performance analysis of the whale shark tourism industry on Isla Holbox, Mexico. Tourism Management, 33(3), 692-701. doi:10.1016/j.tourman.2011.08.004Duffus, D. A., & Dearden, P. (1990). Non-consumptive wildlife-oriented recreation: A conceptual framework. Biological Conservation, 53(3), 213-231. doi:10.1016/0006-3207(90)90087-6Aguilar-Trujillo, A. C., Okolodkov, Y. B., Herrera-Silveira, J. A., Merino-Virgilio, F. del C., & Galicia-García, C. (2017). Taxocoenosis of epibenthic dinoflagellates in the coastal waters of the northern Yucatan Peninsula before and after the harmful algal bloom event in 2011–2012. Marine Pollution Bulletin, 119(1), 396-406. doi:10.1016/j.marpolbul.2017.02.074Ulloa, M. J., Álvarez-Torres, P., Horak-Romo, K. P., & Ortega-Izaguirre, R. (2017). Harmful algal blooms and eutrophication along the mexican coast of the Gulf of Mexico large marine ecosystem. Environmental Development, 22, 120-128. doi:10.1016/j.envdev.2016.10.007Henrichs, D. W., Hetland, R. D., & Campbell, L. (2015). Identifying bloom origins of the toxic dinoflagellate Karenia brevis in the western Gulf of Mexico using a spatially explicit individual-based model. Ecological Modelling, 313, 251-258. doi:10.1016/j.ecolmodel.2015.06.038Murray, G. (2007). Constructing Paradise: The Impacts of Big Tourism in the Mexican Coastal Zone. Coastal Management, 35(2-3), 339-355. doi:10.1080/08920750601169600Heisler, J., Glibert, P. M., Burkholder, J. M., Anderson, D. M., Cochlan, W., Dennison, W. C., … Suddleson, M. (2008). Eutrophication and harmful algal blooms: A scientific consensus. Harmful Algae, 8(1), 3-13. doi:10.1016/j.hal.2008.08.006Smayda, T. J. (2008). Complexity in the eutrophication–harmful algal bloom relationship, with comment on the importance of grazing. Harmful Algae, 8(1), 140-151. doi:10.1016/j.hal.2008.08.018Klemas, V. (2012). Remote Sensing of Algal Blooms: An Overview with Case Studies. Journal of Coastal Research, 278, 34-43. doi:10.2112/jcoastres-d-11-00051.1COFEPRIS (Comisión Federal para la Protección contra Riesgos Sanitarios/Federal Commission for Protection against Health Risks)https://www.gob.mx/cofepris/acciones-y-programas/antecedentes-en-mexico-76707Antoine, D., & Morel, A. (1996). Oceanic primary production: 1. Adaptation of a spectral light-photosynthesis model in view of application to satellite chlorophyll observations. Global Biogeochemical Cycles, 10(1), 43-55. doi:10.1029/95gb02831Barocio-León, Ó. A., Millán-Núñez, R., Santamaría-del-Ángel, E., González-Silvera, A., & Trees, C. C. (2006). Spatial variability of phytoplankton absorption coefficients and pigments off Baja California during November 2002. Journal of Oceanography, 62(6), 873-885. doi:10.1007/s10872-006-0105-zSmith, V. H., Tilman, G. D., & Nekola, J. C. (1999). Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environmental Pollution, 100(1-3), 179-196. doi:10.1016/s0269-7491(99)00091-3Limoges, A., Londeix, L., & de Vernal, A. (2013). Organic-walled dinoflagellate cyst distribution in the Gulf of Mexico. Marine Micropaleontology, 102, 51-68. doi:10.1016/j.marmicro.2013.06.002Jiang, L., Xia, M., Ludsin, S. A., Rutherford, E. S., Mason, D. M., Marin Jarrin, J., & Pangle, K. L. (2015). Biophysical modeling assessment of the drivers for plankton dynamics in dreissenid-colonized western Lake Erie. Ecological Modelling, 308, 18-33. doi:10.1016/j.ecolmodel.2015.04.004Aguilar-Maldonado, J., Santamaría-del-Ángel, E., González-Silvera, A., Cervantes-Rosas, O., López, L., Gutiérrez-Magness, A., … Sebastiá-Frasquet, M.-T. (2018). Identification of Phytoplankton Blooms under the Index of Inherent Optical Properties (IOP Index) in Optically Complex Waters. Water, 10(2), 129. doi:10.3390/w10020129Wei, G., Tang, D., & Wang, S. (2008). Distribution of chlorophyll and harmful algal blooms (HABs): A review on space based studies in the coastal environments of Chinese marginal seas. Advances in Space Research, 41(1), 12-19. doi:10.1016/j.asr.2007.01.037Urquhart, E. A., Schaeffer, B. A., Stumpf, R. P., Loftin, K. A., & Werdell, P. J. (2017). A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing. Harmful Algae, 67, 144-152. doi:10.1016/j.hal.2017.06.001Harvey, E. T., Kratzer, S., & Philipson, P. (2015). Satellite-based water quality monitoring for improved spatial and temporal retrieval of chlorophyll-a in coastal waters. Remote Sensing of Environment, 158, 417-430. doi:10.1016/j.rse.2014.11.017Malthus, T. J., & Mumby, P. J. (2003). Remote sensing of the coastal zone: An overview and priorities for future research. International Journal of Remote Sensing, 24(13), 2805-2815. doi:10.1080/0143116031000066954Matthews, M. W. (2011). A current review of empirical procedures of remote sensing in inland and near-coastal transitional waters. International Journal of Remote Sensing, 32(21), 6855-6899. doi:10.1080/01431161.2010.512947Miller, R. L., & McKee, B. A. (2004). Using MODIS Terra 250 m imagery to map concentrations of total suspended matter in coastal waters. Remote Sensing of Environment, 93(1-2), 259-266. doi:10.1016/j.rse.2004.07.012Loisel, H., Vantrepotte, V., Norkvist, K., Mériaux, X., Kheireddine, M., Ras, J., … Moutin, T. (2011). Characterization of the bio-optical anomaly and diurnal variability of particulate matter, as seen from scattering and backscattering coefficients, in ultra-oligotrophic eddies of the Mediterranean Sea. Biogeosciences, 8(11), 3295-3317. doi:10.5194/bg-8-3295-2011Werdell, P. J., Franz, B. A., Bailey, S. W., Feldman, G. C., Boss, E., Brando, V. E., … Mangin, A. (2013). Generalized ocean color inversion model for retrieving marine inherent optical properties. Applied Optics, 52(10), 2019. doi:10.1364/ao.52.002019Brezonik, P. L., Olmanson, L. G., Finlay, J. C., & Bauer, M. E. (2015). Factors affecting the measurement of CDOM by remote sensing of optically complex inland waters. Remote Sensing of Environment, 157, 199-215. doi:10.1016/j.rse.2014.04.033Odermatt, D., Gitelson, A., Brando, V. E., & Schaepman, M. (2012). Review of constituent retrieval in optically deep and complex waters from satellite imagery. Remote Sensing of Environment, 118, 116-126. doi:10.1016/j.rse.2011.11.013Enriquez, C., Mariño-Tapia, I., Jeronimo, G., & Capurro-Filograsso, L. (2013). Thermohaline processes in a tropical coastal zone. Continental Shelf Research, 69, 101-109. doi:10.1016/j.csr.2013.08.018Estadísticas del Agua en México. Secretaría de Medio Ambiente y Recursos Naturaleshttp://201.116.60.25/publicaciones/EAM_2016.pdfArcega-Cabrera, F., Garza-Pérez, R., Noreña-Barroso, E., & Oceguera-Vargas, I. (2014). Impacts of Geochemical and Environmental Factors on Seasonal Variation of Heavy Metals in a Coastal Lagoon Yucatan, Mexico. Bulletin of Environmental Contamination and Toxicology, 94(1), 58-65. doi:10.1007/s00128-014-1416-1Lopez-Maldonado, Y., Batllori-Sampedro, E., Binder, C. R., & Fath, B. D. (2017). Local groundwater balance model: stakeholders’ efforts to address groundwater monitoring and literacy. Hydrological Sciences Journal, 62(14), 2297-2312. doi:10.1080/02626667.2017.1372857Derrien, M., Cabrera, F. A., Tavera, N. L. V., Kantún Manzano, C. A., & Vizcaino, S. C. (2015). Sources and distribution of organic matter along the Ring of Cenotes, Yucatan, Mexico: Sterol markers and statistical approaches. Science of The Total Environment, 511, 223-229. doi:10.1016/j.scitotenv.2014.12.053INEGIhttp://www.beta.inegi.org.mx/temas/agua/Ramírez, R., Seeliger, L., & Di Pietro, F. (2016). Price, Virtues, Principles: How to Discern What Inspires Best Practices in Water Management? A Case Study about Small Farmers in the Yucatan Peninsula of Mexico. Sustainability, 8(4), 385. doi:10.3390/su8040385Null, K. A., Knee, K. L., Crook, E. D., de Sieyes, N. R., Rebolledo-Vieyra, M., Hernández-Terrones, L., & Paytan, A. (2014). Composition and fluxes of submarine groundwater along the Caribbean coast of the Yucatan Peninsula. Continental Shelf Research, 77, 38-50. doi:10.1016/j.csr.2014.01.011Álvarez-Góngora, C., & Herrera-Silveira, J. A. (2006). Variations of phytoplankton community structure related to water quality trends in a tropical karstic coastal zone. Marine Pollution Bulletin, 52(1), 48-60. doi:10.1016/j.marpolbul.2005.08.006Carruthers, T. J. B., van Tussenbroek, B. I., & Dennison, W. C. (2005). Influence of submarine springs and wastewater on nutrient dynamics of Caribbean seagrass meadows. Estuarine, Coastal and Shelf Science, 64(2-3), 191-199. doi:10.1016/j.ecss.2005.01.015Monterrubio, J. C., Sosa, A. P., & Josiam, B. M. (2014). Spring break e impacto social en Cancún, México. Un estudio para la gestión del turismo. Turismo y Sociedad, 15, 149. doi:10.18601/01207555.n15.09Lee, Z.-P. (2005). A model for the diffuse attenuation coefficient of downwelling irradiance. Journal of Geophysical Research, 110(C2). doi:10.1029/2004jc002275Gordon, H. R., Brown, O. B., Evans, R. H., Brown, J. W., Smith, R. C., Baker, K. S., & Clark, D. K. (1988). A semianalytic radiance model of ocean color. Journal of Geophysical Research, 93(D9), 10909. doi:10.1029/jd093id09p10909Roesler, C. S., Perry, M. J., & Carder, K. L. (1989). Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters. Limnology and Oceanography, 34(8), 1510-1523. doi:10.4319/lo.1989.34.8.1510SMN (Servicio Meteorológico Nacional/National Metereological Service)http://smn.cna.gob.mx/es/climatologia/temperaturas-y-lluvias/resumenes-mensuales-de-temperaturas-y-lluviasCarstensen, J., Klais, R., & Cloern, J. E. (2015). Phytoplankton blooms in estuarine and coastal waters: Seasonal patterns and key species. Estuarine, Coastal and Shelf Science, 162, 98-109. doi:10.1016/j.ecss.2015.05.005Winder, M., & Cloern, J. E. (2010). The annual cycles of phytoplankton biomass. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1555), 3215-3226. doi:10.1098/rstb.2010.0125Cloern, J. E., & Jassby, A. D. (2008). Complex seasonal patterns of primary producers at the land-sea interface. Ecology Letters, 11(12), 1294-1303. doi:10.1111/j.1461-0248.2008.01244.xAthie, G. (2011). Yucatan Current variability through the Cozumel and Yucatan channels. Ciencias Marinas, 37(4A), 471-492. doi:10.7773/cm.v37i4a.1794Pérez, R., Muller-Karger, F. E., Victoria, I., Melo, N., & Cerdeira, S. (1999). Cuban, Mexican, U.S. Researchers probing mysteries of Yucatan Current. Eos, Transactions American Geophysical Union, 80(14), 153-158. doi:10.1029/99eo00104Merino, M. (1997). Upwelling on the Yucatan Shelf: hydrographic evidence. Journal of Marine Systems, 13(1-4), 101-121. doi:10.1016/s0924-7963(96)00123-6Beusen, A. H. W., Slomp, C. P., & Bouwman, A. F. (2013). Global land–ocean linkage: direct inputs of nitrogen to coastal waters via submarine groundwater discharge. Environmental Research Letters, 8(3), 034035. doi:10.1088/1748-9326/8/3/034035Pacheco Castro, R., Pacheco Ávila, J., Ye, M., & Cabrera Sansores, A. (2017). Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer. Groundwater, 56(1), 62-72. doi:10.1111/gwat.12546Muñoz, J., Freile-Pelegrín, Y., & Robledo, D. (2004). Mariculture of Kappaphycus alvarezii (Rhodophyta, Solieriaceae) color strains in tropical waters of Yucatán, México. Aquaculture, 239(1-4), 161-177. doi:10.1016/j.aquaculture.2004.05.043Sebastiá, M.-T., Rodilla, M., Sanchis, J.-A., Altur, V., Gadea, I., & Falco, S. (2012). Influence of nutrient inputs from a wetland dominated by agriculture on the phytoplankton community in a shallow harbour at the Spanish Mediterranean coast. Agriculture, Ecosystems & Environment, 152, 10-20. doi:10.1016/j.agee.2012.02.006Enriquez, C., Mariño-Tapia, I. J., & Herrera-Silveira, J. A. (2010). Dispersion in the Yucatan coastal zone: Implications for red tide events. Continental Shelf Research, 30(2), 127-137. doi:10.1016/j.csr.2009.10.00