Assessment of groundwater extraction in the Tadla irrigated perimeter (Morocco) using the SSEBI remote sensing algorithm

In the Tadla irrigation perimeter, farmers supplement their irrigation supplies with groundwater, leading to water table depletion in the area. An additional concern is the deteriorating water quality in the area. There is no regulation to control withdrawals of groundwater, and no data are available to quantify groundwater use. The paper demonstrates a method based on remote sensing techniques and field observation data to estimate the ground water use for the 2006 hydrological year. Calculations show that for Tadla, average groundwater use amounts to around 55% of the surface irrigation water use. This is substantial, and requires immediate attention. Policy recommendations are needed to control the use of groundwater and to reach an integral management with the canal water. For exact calculations, data on groundwater levels are needed

Drought risk reduction

Due to the shortage of water resources and its inhomogeneous distribution in space and time, large scale droughts occur frequently all over the world. Consequently, drought has become a key factor constraining the economic development and threatening the food security. This report describes the results of the Drought Risk Reduction project, which aimed at creating an integrated system for the monitoring and evaluation of drought at continental scale. A prototype operational system has been developed by combining remote sensing algorithms (SEBS) with a crop growth model (Rotask) in a data assimilation framework (Ensemble Kalman filter). The developed techniques are tested and partly implemented in the current drought forecasting system of Chin

Methodology proposal for estimation of carbon storage in urban green areas

Methodology proposal for estimation of carbon storage in urban green areas; final report. Subtitle: Final report of task Task 262-5-6 "Carbon sequestration in urban green infrastructure" Project manager Marie Cugny-Seguin. Date: 15-10-201

A lightweight hyperspectral mapping system and photogrammetric processing chain for unmanned aerial vehicles

During the last years commercial hyperspectral imaging sensors have been miniaturized and their performance has been demonstrated on Unmanned Aerial Vehicles (UAV). However currently the commercial hyperspectral systems still require minimum payload capacity of approximately 3 kg, forcing usage of rather large UAVs. In this article we present a lightweight hyperspectral mapping system (HYMSY) for rotor-based UAVs, the novel processing chain for the system, and its potential for agricultural mapping and monitoring applications. The HYMSY consists of a custom-made pushbroom spectrometer (400–950 nm, 9 nm FWHM, 25 lines/s, 328 px/line), a photogrammetric camera, and a miniature GPS-Inertial Navigation System. The weight of HYMSY in ready-to-fly configuration is only 2.0 kg and it has been constructed mostly from off-the-shelf components. The processing chain uses a photogrammetric algorithm to produce a Digital Surface Model (DSM) and provides high accuracy orientation of the system over the DSM. The pushbroom data is georectified by projecting it onto the DSM with the support of photogrammetric orientations and the GPS-INS data. Since an up-to-date DSM is produced internally, no external data are required and the processing chain is capable to georectify pushbroom data fully automatically. The system has been adopted for several experimental flights related to agricultural and habitat monitoring applications. For a typical flight, an area of 2–10 ha was mapped, producing a RGB orthomosaic at 1–5 cm resolution, a DSM at 5–10 cm resolution, and a hyperspectral datacube at 10–50 cm resolution

Evaluation of MSG-derived global radiation estimates for application in a regional crop model

Crop monitoring systems that rely on agrometeorologic models require estimates of global radiation. These estimates are difficult to obtain due to the limited number of weather stations that measure this variable. In the present study, we validated the global radiation estimates derived from MeteoSat Second Generation (MSG) and evaluated their use in the European Crop Growth Monitoring System (CGMS). A validation with measurements from four CarboEurope flux towers showed that the MSG estimates are accurate and unbiased (standard deviation between 30 and 51 W/m2). Moreover, a comparison with global radiation estimates from about 300 operational weather stations throughout Europe confirmed that the quality of the MSG product is high and spatially uniform. We also made an intercomparison between the MSG product and the ECMWF (ERA-INTERIM) and CGMS products at 25 km resolution, thus demonstrating that the CGMS and ECMWF products generally underestimate radiation. Nevertheless, the CGMS product showed irregular spatial patterns of local over- and underestimation, while the ECMWF product consistently underestimated. A trend analysis using a seasonal Mann-Kendall test between 2005 and 2009 did not reveal any significant monotonic trends in the MSG radiation estimates, except for 1 location out of 15. Finally, when we applied the WOFOST crop model for maize throughout Europe, the simulated potential total biomass increased due to higher estimates of global radiation made by MSG. In contrast, the water-limited simulated total-biomass generally decreased due to a higher reference evapotranspiration, causing faster depletion of soil moisture and increased water stress

GrasMaïs-Signaal; adviessysteem precisielandbouw melkveehouderij : haalbaarheidsstudie naar het genereren van opbrengst- en voederwaardekengetallen met sensoren en modellen voor gras en snijmaïs

A feasibility study has been worked out for an integrated advisory system for precision agriculture on the production of forage (grass and maize) for dairy farming in the Netherlands. Technology is not restrictive anymore to apply precision agriculture on important cultivation measures. It is now about achieving an effective integration of sensor data, models, metrics and equipment in a comprehensive advice system. It has been advised how a practical advice system for operational decisions can be realized on the dairy farm in the foreseeable future

Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONE’s aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver: 1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators; 2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species; 3. A proposal for a cost-effective biodiversity monitoring system. There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme. The issues that we faced were many: 1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset. 2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything. 3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration. 4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output. EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data. EBONE in its initial development, focused on three main indicators covering: (i) the extent and change of habitats of European interest in the context of a general habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas. For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles: using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples. For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved. Restricted access to European wide species data prevented work on the indicator ‘abundance and distribution of species’. With respect to the indicator ‘fragmentation’, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations

A technique for large scale drought monitoring (China National 94.8 Technique Import Project)

Drought is one of the main natural disasters that man has suffered since the ancient era. In China nation-wide droughts occur year after year, imposing severe threats to the food security and constraining the sustainable development of social economy.The Water Resources Information Centre of the Ministry of Water Resources of China (WRIC/MWR) developed an operational drought monitoring system in 1996, based on a river basin hydrological model. This system produces daily nation-wide maps of soil waterdeficit. However, it is felt that two aspects need to be improved: the spatial resolution is low (only 590 sites for whole China) and the hydrological model used in this system is a single-point model (interpolation between the points cannot reveal the actual situation). Alterra has developed the Surface Energy Balance System (SEBS) to estimate drought characteristic parameters using satellite remote sensing images. In order to import this advanced technique and apply it for the nation-wide drought monitoring, the Ministry of Water Resources of China funded a technique import project. This report shows the design, transplantation and modification of this technique to the Chinese situation, and the analysis of the first results of the new approach