WorldCereal: a dynamic open-source system for global-scale, seasonal, and reproducible crop and irrigation mapping

The challenge of global food security in the face of population growth, conflict and climate change requires a comprehensive understanding of cropped areas, irrigation practices and the distribution of major commodity crops like maize and wheat. However, such understanding should preferably be updated at seasonal intervals for each agricultural system rather than relying on a single annual assessment. Here we present the European Space Agency funded WorldCereal system, a global, seasonal, and reproducible crop and irrigation mapping system that addresses existing limitations in current global-scale crop and irrigation mapping. WorldCereal generates a range of global products, including temporary crop extent, seasonal maize and cereals maps, seasonal irrigation maps, seasonal active cropland maps, and confidence layers providing insights into expected product quality. The WorldCereal product suite for the year 2021 presented here serves as a global demonstration of the dynamic open-source WorldCereal system. The presented products are fully validated, e.g., global user's and producer's accuracies for the annual temporary crop product are 88.5 % and 92.1 %, respectively. The WorldCereal system provides a vital tool for policymakers, international organizations, and researchers to better understand global crop and irrigation patterns and inform decision-making related to food security and sustainable agriculture. Our findings highlight the need for continued community efforts such as additional reference data collection to support further development and push the boundaries for global agricultural mapping from space. The global products are available at https://doi.org/10.5281/zenodo.7875104 (Van Tricht et al., 2023)

Good practices for estimating area and assessing accuracy of land change

The remote sensing science and application communities have developed increasingly reliable, consistent, and robust approaches for capturing land dynamics to meet a range of information needs. Statistically robust and transparent approaches for assessing accuracy and estimating area of change are critical to ensure the integrity of land change information. We provide practitioners with a set of “good practice” recommendations for designing and implementing an accuracy assessment of a change map and estimating area based on the reference sample data. The good practice recommendations address the three major components: sampling design, response design and analysis. The primary good practice recommendations for assessing accuracy and estimating area are: (i) implement a probability sampling design that is chosen to achieve the priority objectives of accuracy and area estimation while also satisfying practical constraints such as cost and available sources of reference data; (ii) implement a response design protocol that is based on reference data sources that provide sufficient spatial and temporal representation to accurately label each unit in the sample (i.e., the “reference classification” will be considerably more accurate than the map classification being evaluated); (iii) implement an analysis that is consistent with the sampling design and response design protocols; (iv) summarize the accuracy assessment by reporting the estimated error matrix in terms of proportion of area and estimates of overall accuracy, user's accuracy (or commission error), and producer's accuracy (or omission error); (v) estimate area of classes (e.g., types of change such as wetland loss or types of persistence such as stable forest) based on the reference classification of the sample units; (vi) quantify uncertainty by reporting confidence intervals for accuracy and area parameters; (vii) evaluate variability and potential error in the reference classification; and (viii) document deviations from good practice that may substantially affect the results. An example application is provided to illustrate the recommended process

Detection and Modelling of 3D Trees from Mobile Laser Scanning Data

Mobile laser scanning acquires massive point clouds in urban areas to provide high resolution data for 3D city modelling. A workflow for detecting and modelling trees from point clouds is presented. Emphasis lies on data reduction using an alpha shape approach. From the reduced point cloud the parameters are extracted to model the 3D trees using the Weber and Penn (1995) approach. The workflow is applied on two different sample data sets which were acquired with different mobile mapping systems and thus vary in quality and point density. The applied data reduction approach reduces the amount of data to process by about 95%. The tree models generated are consisting of a realistic trunk and branch structure of the tree crown. However, the inner branch structure of the tree crown is parameterised. Only the outer shape of the tree matches with the reality, which is sufficient for the requirements of visualization applications. For the tested areas the tree detection reaches a quality rate of 85 % and 78 % respectively. The comparison of the generated tree models against photographs and the original point cloud shows that the level of abstraction is sufficient for the integration of the tree models into 3D city models. 1

Differences in lower limb muscle activation patterns during Sit to Stand Task for different heel heights

© 2017 IEEE. The purpose of this study was to investigate differences in lower limb muscle activation patterns for females wearing shoes with different heel heights during Sit to Stand Task (STS). Ten female participants with no prior history of neurological disorders participated in this study. Surface electromyography (sEMG) characteristics were recorded for four different heel heights (ranging from 4cm to 10cm) while performing the STS task. Signal processing analysis suggests that muscle activities increases on elevated heel heights, which may induce muscle imbalance for frequent STS tasks. In addition, results of muscle utilisation (percentage) for different heel heights suggest that lower limb muscles tend to compensate in order to maintain postural balance

WorldCereal open global harmonized reference data repository (CC-BY-SA licensed data sets)

Within the ESA funded WorldCereal project we have built an open harmonized reference data repository at global extent for model training or product validation in support of land cover and crop type mapping. Data from 2017 onwards were collected from many different sources and then harmonized, annotated and evaluated. These steps are explained in the harmonization protocol (10.5281/zenodo.7584463). This protocol also clarifies the naming convention of the shape files and the WorldCereal attributes (LC, CT, IRR, valtime and sampleID) that were added to the original data sets. This publication includes those harmonized data sets of which the original data set was published under the CC-BY-SA license or a license similar to CC-BY-SA. See document "_In-situ-data-World-Cereal - license - CC-BY-SA.pdf" for an overview of the original data sets