Spatial ecological complexity measures in GRASS GIS

Good estimates of ecosystem complexity are essential for a number of ecological tasks: from biodiversity estimation, to forest structure variable retrieval, to feature extraction by edge detection and generation of multifractal surface as neutral models for e.g. feature change assessment. Hence, measuring ecological complexity over space becomes crucial in macroecology and geography. Many geospatial tools have been advocated in spatial ecology to estimate ecosystem complexity and its changes over space and time. Among these tools, free and open source options especially offer opportunities to guarantee the robustness of algorithms and reproducibility. In this paper we will summarize the most straightforward measures of spatial complexity available in the Free and Open Source Software GRASS GIS, relating them to key ecological patterns and processes

The Canopy Health Monitoring (CanHeMon) project

As part of the EU emergency measures against the pine wood nematode (PWN) (Bursaphelenchus xylophilus) laid down under Decision 2012/535/EU, Portugal should perform, outside and during the flight season of the vector, surveys of coniferous trees located in the 20 km wide buffer zone established along the Spanish border, with the aim to detect trees which are dead, in poor health or affected by fire or storm. These trees shall be felled and removed, as required by the Decision, to avoid that they act as attractants for the longhorn beetle (Monochamus species), the vector responsible for the spread of PWN. The CanHeMon project tasked the Joint Research Centre with analysing a portion of the buffer zone, using remote sensing data, to support detection on the ground of declining pine trees. During the project, a 400 km2 area was imaged twice, in autumn 2015 and autumn 2016, at 15 cm resolution from aircraft, and individual declining tree crowns were detected using a MaxEnt-based iterative image analysis algorithm, the performance of which was gauged through visual photointerpretation. The scalability of the automated methods was then tested using an image mosaic of the entire buffer zone at 30 cm resolution. Finally, broad recommendations were formulated on the use of remote sensing for large-area surveys in the context of plant health emergencies.JRC.D.1-Bio-econom

Remote sensing in support of plant health measures

The Canopy Health Monitoring (CanHeMon) project ran at the Joint Research Centre of the European Commission from mid-2015 to mid-2018 and was funded by DG SANTE. Its aim was to develop and implement remote-sensing based monitoring of a section of the Pine Wood Nematode buffer zone to support the measures against this quarantine plant pest there, and particularly the detection of pine trees in poor health. This report describes the main findings from the project, which achieved the detection of ca. 19 000 individual declining coniferous trees through remote sensing, and an outlook on the potential future use of remote sensing in support of plant health measures.JRC.D.1-Bio-econom

A new methodology for virtual water level Gauges

Monitoring water stored in lakes and reservoirs is much needed in various countries for energy generation, food security and mitigating floods, among recurrent global issues. Natural and human-made open water bodies do not all have monitoring systems, this lack of regular information generates uncertainties in modeling, and increases unaccounted time-bound residuals in water balances. A large amount of water bodies storage variations are not monitored around the World. Here we show that this can be changed by the creation and the implementation of the concept of water Level Virtual Gauges (wLVGs) based on slope tracks upstream of water bodies, correlated to publicly available satellite remote sensing information returning water levels bi-monthly on average, sometimes weekly. An operational RMSE is found to be 12-52 cm height, depending on the characteristics of the upstream slopes used to calibrate wLVGs. This methodology is simple enough to be implemented for all medium to large reservoirs, but is alsofound successful for smaller rural reservoirs in tropical/sub-tropical countries. We anticipate that this can open globally distributed pathways to monitor open water bodies across the World, improve public databases on water storages and give management information for non/less-monitored water bodies

Wavelet-based spatio-temporal fusion of observed rainfall with NDVI in Sri Lanka

Paper presented at the 33rd Asian Conference on Remote Sensing, Pattaya, Thailand, 26-30 November 2012Availability of rainfall time-series is limited in many parts of the World, and the continuity of such records is variable. This research endeavors to extend actual daily rainfall observations to ungauged areas, taking into account events of rainfall as well as cumulative total daily rainfall, over a period of 11 years. Results show that rainfall events histograms can be reconstructed, and that total cumulative rainfall is estimated with 85% accuracy, using a surrounding network of rain gauges at 30-50 Km of distance from the point of study. This research can strengthen various types of research and applications such as ungauged basins research, regional climate modeling, food security early warning systems, agricultural insurance systems, etc