Recent Advances in Forest Observation with Visual Interpretation of Very High-Resolution Imagery

The land area covered by freely available very high-resolution (VHR) imagery has grown dramatically over recent years, which has considerable relevance for forest observation and monitoring. For example, it is possible to recognize and extract a number of features related to forest type, forest management, degradation and disturbance using VHR imagery. Moreover, time series of medium-to-high-resolution imagery such as MODIS, Landsat or Sentinel has allowed for monitoring of parameters related to forest cover change. Although automatic classification is used regularly to monitor forests using medium-resolution imagery, VHR imagery and changes in web-based technology have opened up new possibilities for the role of visual interpretation in forest observation. Visual interpretation of VHR is typically employed to provide training and/or validation data for other remote sensing-based techniques or to derive statistics directly on forest cover/forest cover change over large regions. Hence, this paper reviews the state of the art in tools designed for visual interpretation of VHR, including Geo-Wiki, LACO-Wiki and Collect Earth as well as issues related to interpretation of VHR imagery and approaches to quality assurance. We have also listed a number of success stories where visual interpretation plays a crucial role, including a global forest mask harmonized with FAO FRA country statistics; estimation of dryland forest area; quantification of deforestation; national reporting to the UNFCCC; and drivers of forest change

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

User Manual for the JRC Land Cover/Use Change Validation Tool

The JRC TREES-3 project aims at estimating forest cover changes at continental and regional levels for the Tropical belt for the periods 1990-2000 and 2000-(2005)-2010 based on a systematic sample of forest cover change maps. An operational system has been developed for the processing and change assessment of a large data set of multi-temporal medium resolution imagery (sample units of 20 km x 20 km size analysed from with Landsat imagery). The main task is to assess as accurately as possible for each sample unit the forest cover and forest cover change between two dates. The analysis includes a crucial final step of visual verification and final assignment of land cover labels which is carried out by forestry national officers or remote sensing experts from tropical countries. The visual interpretation is conducted interdependently on two-date imagery to verify and to adjust the labels pre-assigned to each segment for the different dates. A dedicated stand-alone application has been developed for this purpose. The application is a graphical user interface, called the JRC Land Cover/Use Change Validation Tool. The aim of this tool is to provide a user-friendly interface, with an optimised set of commands to navigate through and assess a given dataset of satellite imagery and land cover maps, and to correct easily the land-cover labels as appropriate. The present technical document, entitled ¿User Manual for the JRC Land Cover Change Validation Tool¿ describes the steps for the installation of the tool on a personal computer, as well as the detailed features of this dedicated graphical user interface. The authors welcome feedbacks from potential users of the tool, in particular reporting of any potential software issue or providing suggestions for improvements of future versions of the tool.JRC.DDG.H.3-Global environement monitorin

The Role of Citizen Science in Earth Observation

Citizen Science (CS) and crowdsourcing are two potentially valuable sources of data for Earth Observation (EO), which have yet to be fully exploited. Research in this area has increased rapidly during the last two decades, and there are now many examples of CS projects that could provide valuable calibration and validation data for EO, yet are not integrated into operational monitoring systems. A special issue on the role of CS in EO has revealed continued trends in applications, covering a diverse set of fields from disaster response to environmental monitoring (land cover, forests, biodiversity and phenology). These papers touch upon many key challenges of CS including data quality and citizen engagement as well as the added value of CS including lower costs, higher temporal frequency and use of the data for calibration and validation of remotely-sensed imagery. Although still in the early stages of development, CS for EO clearly has a promising role to play in the future

An introduction to the Digital Observatory for Protected Areas (DOPA) and the DOPA Explorer (Beta)

The Digital Observatory for Protected Areas (DOPA) is conceived around a set of interacting Critical Biodiversity Informatics Infrastructures (databases, web modelling services, broadcasting services, ...) hosted at different institutions, including the Joint Research Centre of the European Commission, the World Conservation Monitoring Centre (UNEP-WCMC), the International Union for Conservation of Nature (IUCN), the Global Biodiversity Information Facility (GBIF) and BirdLife International. The current services of DOPA provide to a large variety of end-users, ranging from park managers, funding agencies to researchers, with means to assess, monitor and possibly forecast the state and pressure of protected areas at the local, national and global scales. With an introduction to the DOPA, the readers will find here a user manual of the beta version of DOPA Explorer, a first web based assessment tool where information on 9 000 protected areas covering almost 90% of the global protected surface has been processed automatically to generate a set of indicators on ecosystems, climate, phenology, species, ecosystem services and pressures. DOPA Explorer can so help identify the protected areas with most unique ecosystems and species and assess the pressures they are exposed to because of human development. Ecological data derived from and near real-time earth observations are also made available for the African continent. Inversely, DOPA Explorer indirectly highlights the protected areas for which the information is incomplete.JRC.H.5-Land Resources Managemen

User generated spatial content sources for land use/land cover validation purposes : suitability analysis and integration model

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsTraditional geographic information has been produced by mapping agencies and corporations, using high skilled people as well as expensive precision equipment and procedures, in a very costly approach. The production of land use and land cover databases are just one example of such traditional approach. On the other side, The amount of Geographic Information created and shared by citizens through the Web has been increasing exponentially during the last decade, resulting from the emergence and popularization of technologies such as the Web 2.0, cloud computing, GPS, smart phones, among others. Such comprehensive amount of free geographic data might have valuable information to extract and thus opening great possibilities to improve significantly the production of land use and land cover databases. In this thesis we explored the feasibility of using geographic data from different user generated spatial content initiatives in the process of land use and land cover database production. Data from Panoramio, Flickr and OpenStreetMap were explored in terms of their spatial and temporal distribution, and their distribution over the different land use and land cover classes. We then proposed a conceptual model to integrate data from suitable user generated spatial content initiatives based on identified dissimilarities among a comprehensive list of initiatives. Finally we developed a prototype implementing the proposed integration model, which was then validated by using the prototype to solve four identified use cases. We concluded that data from user generated spatial content initiatives has great value but should be integrated to increase their potential. The possibility of integrating data from such initiatives in an integration model was proved. Using the developed prototype, the relevance of the integration model was also demonstrated for different use cases