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In the context of increased pressures on land for food and non-food production, it is relevant to understand better, which land resources have become unused and abandoned and where these lands are. Data on where these lands are and what their extend is are not collected in regular statistics. In this paper, we present an approach to detect signs of abandonment in cropping land using radar coherence data. The methodology was tested in the Spanish regions of Albacete and Soria where agricultural land abandonment is a common process. The results show that land abandonment detection using radar coherence data works well for the region of Albacete in arable lands. The radar-based analysis is a relatively simple method to detect land abandonment in an early to longer term state and can therefore be applied once developed and tested further in other regions to larger areas of the EU where land abandonment is serious and needs monitoring and policy response. The applicability of the method to Soria and Emilia Romagna (Italy) regions shows that there are still challenges to overcome to make the method more widely applicable for detecting land abandonment in other environmental zones of Europe. Lack of reliable training and validation data, like Land Parcel Identification Systems data, in regions is one of the challenges in this respect.

Carbon neutrality in the transport sector is a key challenge for the growing bioeconomy as the share of biofuels has stagnated over the past decade. This can be attributed to basic economics and a lack of a robust market for these technologies. Consequently, more sustainable biomass supply concepts are required that reduce negative impacts on the environment and at the same time promote environmental services for sustainable agricultural cropping systems including erosion prevention, soil fertility improvement, greenhouse gas mitigation, and carbon sequestration. One promising concept is the cultivation of perennial biomass crops such as Miscanthus (Miscanthus Andersson) as biofuel feedstock. In this study, the multiple environmental services provided by Miscanthus are first explored and subsequently monetized. Then the integration of Miscanthus cultivation for biomass production into European agricultural systems is assessed. One hectare of Miscanthus provides society with environmental services to a value of 1,200 to 4,183 € a−1. These services are even more pronounced when cultivation takes place on marginal agricultural land. The integration of Miscanthus into existing agricultural practices aids both conservation and further optimization of socio-economic welfare and landscape diversification. As these environmental services are more beneficial to the public than the Miscanthus farmers, subsidies are required to close the gap between biofuels and biodiversity that are calculated based on the provision of environmental services. Similar approaches to that developed in this study may be suitable for the implementation of other biomass cropping systems and therefore help foster the transition to a bioeconomy.

Geo-engineering

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods D random forest and gradient boosting and/or multinomial logistic regression D as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10 -fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of method

Land degradation is a global concern. In tropical areas it primarily concerns the conversion of forest into non-forest lands and the associated losses of environmental services. Defining such degradation is not straightforward hampering effective reduction in degradation and use of already degraded lands for more productive purposes. To facilitate the processes of avoided degradation and land rehabilitation, we have developed a methodology in which we have used international environmental and social sustainability standards to determine the suitability of lands for sustainable agricultural expansion. The method was developed and tested in one of the frontiers of agricultural expansion, West Kalimantan province in Indonesia. The focus was on oil palm expansion, which is considered as a major driver for deforestation in tropical regions globally. The results suggest that substantial changes in current land-use planning are necessary for most new plantations to comply with international sustainability standards. Through visualizing options for sustainable expansion with our methodology, we demonstrate that the link between oil palm expansion and degradation can be broken. Application of the methodology with criteria and thresholds similar to ours could help the Indonesian government and the industry to achieve its pro-growth, pro-job, pro-poor and pro-environment development goals. For sustainable agricultural production, context specific guidance has to be developed in areas suitable for expansion. Our methodology can serve as a template for designing such commodity and country specific tools and deliver such guidance. © 2013 Smit et al.

Vorlageform des Erscheinungsvermerks: Gedruckt zu Marpurg/ durch Paulum Egenolff/|| Jm Jahr/ M.D.XCIII.

Vorlageform des Erscheinungsvermerks: Gedruckt zu Marpurg/ durch Paulum Egenolff/|| Jm Jahr/ M.D.XCIII.