An Exploration of Some Pitfalls of Thematic Map Assessment Using the New Map Tools Resource

A variety of metrics are commonly employed by map producers and users to assess and compare thematic maps’ quality, but their use and interpretation is inconsistent. This problem is exacerbated by a shortage of tools to allow easy calculation and comparison of metrics from different maps or as a map’s legend is changed. In this paper, we introduce a new website and a collection of R functions to facilitate map assessment. We apply these tools to illustrate some pitfalls of error metrics and point out existing and newly developed solutions to them. Some of these problems have been previously noted, but all of them are under-appreciated and persist in published literature. We show that binary and categorical metrics, including information about true-negative classifications, are inflated for rare categories, and more robust alternatives should be chosen. Most metrics are useful to compare maps only if their legends are identical. We also demonstrate that combining land-cover classes has the often-neglected consequence of apparent improvement, particularly if the combined classes are easily confused (e.g., different forest types). However, we show that the average mutual information (AMI) of a map is relatively robust to combining classes, and reflects the information that is lost in this process; we also introduce a modified AMI metric that credits only correct classifications. Finally, we introduce a method of evaluating statistical differences in the information content of competing maps, and show that this method is an improvement over other methods in more common use. We end with a series of recommendations for the meaningful use of accuracy metrics by map users and producer

The striatal dopamine transporter in first-episode, drug-naive schizophrenic patients: evaluation by the new SPECT-ligand[99mTc]TRODAT-1

Following the current hypothesis that acute schizophrenic psychotic illness is associated with a triatal ‘hyperdopaminergic state’, presynaptic integrity and dopamine transporter (DAT) density in first-episode, neuroleptic-naive schizophrenic patients was measured by single-photonemission- tomography (SPECT) and compared with that in healthy control subjects. A new SPECT-ligand for assessment of the striatal DAT, the Technetium-99m-labelled tropane TRODAT-1 ([99mTc]TRODAT-1), was used. Ten inpatients suffering from a first acute schizophrenic episode and 10 age- and sex-matched healthy control subjects underwent SPECT with [99mTc]TRODAT-1. On the day of SPECT, psychopathological ratings were performed with the Brief Psychiatric Rating Scale (BPRS), the Positive and Negative Syndrome Scale (PANSS) and Schedule for Assessment of Negative Symptoms (SANS). Patients had not previously received any neuroleptic or antidepressant medication. Mean specific TRODAT-1 binding in the striatum did not differ significantly between the patient and the age- and sex-matched control group (1.25 vs. 1.28). Variance was significantly higher in the patient group. The data obtained with the new ligand in first-episode, drug-naive schizophrenic patients are in line with the PET results from the group of Laakso et al. in a comparable patient sample. [99mTc]TRODAT-1 seems to be a valuable new SPECTligand in the evaluation of the presynaptic site of the striatal dopaminergic synapse in schizophrenia

LACO-Wiki: A land cover validation tool and a new, innovative teaching resource for remote sensing and the geosciences

The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.lacowiki.net

LACO-Wiki: A New Online Land Cover Validation Tool Demonstrated Using GlobeLand30 for Kenya

Accuracy assessment, also referred to as validation, is a key process in the workflow of developing a land cover map. To make this process open and transparent, we have developed a new online tool called LACO-Wiki, which encapsulates this process into a set of four simple steps including uploading a land cover map, creating a sample from the map, interpreting the sample with very high resolution satellite imagery and generating a report with accuracy measures. The aim of this paper is to present the main features of this new tool followed by an example of how it can be used for accuracy assessment of a land cover map. For the purpose of illustration, we have chosen GlobeLand30 for Kenya. Two different samples were interpreted by three individuals: one sample was provided by the GlobeLand30 team as part of their international efforts in validating GlobeLand30 with GEO (Group on Earth Observation) member states while a second sample was generated using LACO-Wiki. Using satellite imagery from Google Maps, Bing and Google Earth, the results show overall accuracies between 53% to 61%, which is lower than the global accuracy assessment of GlobeLand30 but may be reasonable given the complex landscapes found in Kenya. Statistical models were then fit to the data to determine what factors affect the agreement between the three interpreters such as the land cover class, the presence of very high resolution satellite imagery and the age of the image in relation to the baseline year for GlobeLand30 (2010). The results showed that all factors had a significant effect on the agreement

Forest Biomass Observation: Current State and Prospective

With this article, we provide an overview of the methods, instruments and initiatives for forest biomass observation at a global scale. We focus on the freely available information provided by both remote and in-situ observations. The advantages and limitation of various space borne methods, including optical, radar (C, L and P band) and LiDAR, as well as respective instruments available on the orbit (MODIS, Proba-V, Landsat, Sentinel-1, Sentinel-2 , ALOS PALSAR, Envisat ASAR) or expecting (BIOMASS, GEDI, NISAR, SAOCOM-CS) are discussed. We emphasize the role of in-situ methods in the development of a biomass models, providing calibration and validation of remote sensing data. We focus on freely available forest biomass maps, databases and empirical models. We describe the functionality of Biomass.Geo-Wiki.org portal, which provides access to a collection of global and regional biomass maps in full resolution with unified legend and units overplayed with high-resolution imagery. The Forest-Observation-System.net is announced as an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. Prospects of unmanned aerial vehicles in the forest inventory are briefly discussed. The work was partly supported by ESA IFBN project (contract 4000114425/15/NL/FF/gp)

A global dataset of crowdsourced land cover and land use reference data

Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general

Evaluation of Elevated Tritium Levels in Groundwater Downgradient from the 618-11 Burial Ground Phase I Investigations

This report describes the results of the preliminary investigation of elevated tritium in groundwater discovered near the 618-11 burial ground, located in the eastern part of the Hanford Site. Tritium in one well downgradient of the burial ground was detected at levels up to 8,140,000 pCi/L. The 618-11 burial ground received a variety of radioactive waste from the 300 Area between 1962 and 1967. The burial ground covers 3.5 hectare (8.6 acre) and contains trenches, large diameter caissons, and vertical pipe storage units. The burial ground was stabilized with a native sediment covering. The Energy Northwest reactor complex was constructed immediately east of the burial ground

“I’m tired of black boxes!”: A systematic comparison of faculty well-being and need satisfaction before and during the COVID-19 crisis

As of today, surprisingly little is known about the subjective well-being of faculty in general, but especially when teaching online and during a time of pandemic during lockdowns in particular. To narrow this research gap, the present study systematically compared the subjective well-being of faculty teaching face-to-face before to those teaching online during the COVID-19 pandemic, adopting a self-determination theory framework. The data reported here stem from a study conducted before the pandemic (Sample 1, n = 101) and which repeated-measures survey design we replicated to collect corresponding data during the pandemic (Sample 2, n = 71). Results showed that faculty teaching online during the pandemic reported impaired satisfaction of all three basic needs, that is reduced autonomy, competence, and especially relatedness, as well as impaired subjective well-being (clearly reduced enjoyment and reduced teaching satisfaction; increased anger and a tendency towards more shame) compared to faculty teaching face-to-face before the pandemic. Yet pride, anxiety, and boredom were experienced to a similar extent across both samples. The effects of the teaching format on the different aspects of subjective well-being were overall mediated in self-determination-theory-congruent ways by the satisfaction of the basic needs for autonomy, competence, and relatedness. We conclude for a post-pandemic future that online teaching will supplement rather than replace face-to-face teaching in higher education institutions, as their importance for building relationships and satisfying social interactions not only for students but also for faculty seem to have been underestimated so far

LACO-Wiki Mobile: An Open Source Application for In situ DataCollection and Land Cover Validation

LACO-Wiki Mobile is a smartphone application for in situ data collection, which is being developed as a freeand open source software project in the framework of the European Space Agency funded project CrowdVal. Themobile application works in tandem with the online land cover validation tool LACO-Wiki (https://www.laco-wiki.net), where users can generate a statistically robust sample for validation purposes. The land cover legend isread directly from the map uploaded to LACO-Wiki for generating the sample. The user must also indicate the typeof validation to be undertaken. Blind validation is where the user chooses the land cover type from a pre-definedlegend, plausibility validation is where users can see the land cover type from the map while on the ground andcan then choose to accept it as correct or not, while enhanced plausibility allows users to indicate the correct landcover type when it is incorrectly specified in the land cover map. This sample is then transferred to the mobileapplication, which directs users to specific locations on the ground to collect the validation data, i.e. operating in a‘directed’ mode. The user can see the locations of the points on the mobile phone, and as they approach a point, theuser is given the option to validate the land cover. These points can then be used in the accuracy assessment of theland cover map. The application also operates in ‘opportunistic’ mode, i.e. allowing the user to collect land coverat any location of their choice, e.g. while driving along a road. Such data collection can be useful for verifyingvisually interpreted samples or complementing training data for the development of land cover maps. Although theopen source application is still under development, a version will be openly accessible in github by the time of theconference