Synergy between optical and microwave remote sensing to derive soil and vegetation parameters from MAC Europe 1991 Experiment

The ability of remote sensing for monitoring vegetation density and soil moisture for agricultural applications is extensively studied. In optical bands, vegetation indices (NDVI, WDVI) in visible and near infrared reflectances are related to biophysical quantities as the leaf area index, the biomass. In active microwave bands, the quantitative assessment of crop parameters and soil moisture over agricultural areas by radar multiconfiguration algorithms remains prospective. Furthermore the main results are mostly validated on small test sites, but have still to be demonstrated in an operational way at a regional scale. In this study, a large data set of radar backscattering has been achieved at a regional scale on a French pilot watershed, the Orgeval, along two growing seasons in 1988 and 1989 (mainly wheat and corn). The radar backscattering was provided by the airborne scatterometer ERASME, designed at CRPE, (C and X bands and HH and VV polarizations). Empirical relationships to estimate water crop and soil moisture over wheat in CHH band under actual field conditions and at a watershed scale are investigated. Therefore, the algorithms developed in CHH band are applied for mapping the surface conditions over wheat fields using the AIRSAR and TMS images collected during the MAC EUROPE 1991 experiment. The synergy between optical and microwave bands is analyzed

Threats of illegal, unregulated, and unreported fishing to biodiversity and food security in the Republic of the Congo

This is the final version. Available on open access from Wiley via the DOI in this recordIllegal, unregulated, and unreported (IUU) fishing poses a major threat to effective management of marine resources, impacting biodiversity and communities dependent on these coastal resources. Spatio-temporal patterns of industrial fisheries in developing countries are often poorly understood, with global efforts describing spatial patterns of fishing vessel activity currently based on automatic identification system (AIS) data. However, AIS is often not a legal requirement on fishing vessels, likely resulting in underestimates of the scale and distribution of legal and illegal fishing activity, which could have significant ramifications for targeted enforcement efforts and the management of fisheries resources. To help address this knowledge gap, we analysed three years of vessel monitoring system (VMS) data in partnership with the national fisheries department in the Republic of the Congo to describe the behaviour of national and distant water industrial fleets operating in these waters. We reveal the spatial footprint of the industrial fisheries fleet encompasses over one quarter of the Exclusive Economic Zone (EEZ), with an average of 73% of fishing activity taking place on the continental shelf (waters shallower than 200 m). In addition, our findings highlight that VMS is not acting as a deterrent or being effectively used as a pro-active management tool, with as much as 33% (13% on average) of fishing effort occurring within prohibited areas set aside to protect biodiversity, including artisanal fisheries resources; with the distant water fleet (DWF) responsible for as much as 84% of this illegal activity. Given the growth in industrial and distant water fleets across the region, as well as low levels of management and enforcement, these findings highlight that there is an urgent need for the global community to help strengthen regional and national capacity to analyse national scale datasets if efforts to combat IUU fishing are to be effective.Darwin InitiativeWaterloo FoundationWAITT Foundatio

Collateral damage? Small-scale fisheries in the global fight against IUU fishing

© 2020 The Authors. Fish and Fisheries published by John Wiley & Sons Ltd Concern over illegal, unreported and unregulated (IUU) fishing has led to a number of policy, trade and surveillance measures. While much attention has been given to the impact of IUU regulation on industrial fleets, recognition of the distinct impacts on small-scale fisheries is conspicuously lacking from the policy and research debate. In this paper, we outline three ways in which the application of IUU discourse and regulation undermines small-scale fisheries. First, the mainstream construction of “illegal,” “unreported” and “unregulated” fishing, and also the categorical use of “IUU” in an all-inclusive sense, disregards the diversity, legitimacy and sustainability of small-scale fisheries practices and their governing systems. Second, we explore how the recent trade-related measures to counter IUU fishing mask and reinforce existing inequalities between different sectors and countries, creating an unfair burden on small-scale fisheries and countries who depend on them. Third, as IUU fishing is increasingly approached as “organized crime,” there is a risk of inappropriately targeting small-scale fisheries, at times violently. Reflecting on these three trends, we propose three strategies by which a more sensitive and ultimately more equitable incorporation of small-scale fisheries can be supported in the global fight against IUU fishing

Global Atlas of AIS-based fishing activity — Challenges and opportunities

The Automatic Identification System (AIS) provides detailed tracks of tens of thousands of industrial fishing vessels, and these detailed tracking data have the potential to provide estimates of fishing activity and effort in near real time. Realizing this potential, though, is not straightforward and depends on the vessel size, gear type, and the species targeted. This Atlas, using a global database of AIS data from 2017, assesses this potential and shows that AIS can start to be considered a valid technology for estimating fishery indicators. This Atlas reveals both promising findings and key limitations of inferring fishing effort from AIS data. AIS use is steadily increasing and its utility in tracking fishing vessel activity is growing. In 2017, AIS was broadcast by approximately 60 000 fishing vessels of which just over 22 000 could be matched to publicly available vessel registries. This number is steadily increasing, and between 2014 and 2017, the number of vessels broadcasting increased by 10 to 30 percent each year. Moreover, AIS can be used to track the majority of the world’s large fishing vessels (above 24 m), especially those from upper and middle-income countries and territories, distant water fleets and vessels operating on the high seas. AIS tracking performs less well on smaller vessels: only a small fraction of vessels under 24 m, which account for the vast majority of fishing vessels globally, use AIS. The current algorithms perform well at classifying the most common gear types among larger vessels: longlines, trawls and pelagic purse seines. The classification algorithms do less well at differentiating gear types that are more common in smaller coastal vessels, such as set gillnets, trollers and pots and traps. Also, the current AIS algorithms can assign only one gear type, limiting the ability to classify the type of fishing when vessels change gears on a voyage or between voyages. Poor AIS reception limits the ability to monitor fleets in some regions. In particular, satellite AIS reception is weakest in Southeast Asia, followed by East Asia, the northern Indian Ocean, the Gulf of Mexico and Europe, although terrestrial receivers along coastlines can, in some of these regions, compensate for poor satellite reception. The reception quality also depends on the specific type of AIS device in use (Class A or B). Comparing AIS-based fishing vessel activity with catch reconstructions and literature reveals varying use of AIS by region and gear and possible biases in the relative importance of different gears. Catch reconstructions mostly show that areas with high catch have high activity by vessels with AIS, although some areas with high catch have little AIS activity, such as in Southeast Asia (Area 71), as a result of few vessels having AIS. Catch reconstructions agree on ix x the most important gears worldwide (trawlers, followed by purse seiners), although AIS data show a higher importance of longliners because a higher fraction of these broadcast AIS. The recent increasing importance of squid jiggers in the high seas was not captured in the slightly lagged catch reconstruction work. In optimal conditions where AIS use and reception are good, and where vessel registries with gear type exist AIS algorithm can perform well for gears such as longline or trawl and provide good estimates of fishing effort. This work has contributed to improving the quality of FAO fleet statistics, revealed some errors in classifications of gear types in the European Union (EU) registry, and pinpointed limitations of catch reconstructions. With regard to the AIS data, in addition to showing limitations of AIS, this project has helped improve methods for analysing AIS data and align AIS-based metrics with fishery statistical standards, and this work can provide a basis for further improvement of these methods and algorithms

Estimation of evapotranspiration using SVAT models and IR brightness temperature

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Taking into account vegetation effects to estimate soil moisture from C-band radar measurements

International audienceEstimation of surface soil moisture is one of the major potential applications of radar remote sensing. The European Remote Sensing Satellites (ERS1 and 2) are equipped with a synthetic aperture radar working at C-band (5 Ghz) using a rather low incidence angle (23°). For this fequency and angle, the effect of soil roughness and vegetation attenuation are not negligible. It is shown that, for wheat canopy, it is possible to apply an empirical relation for correcting for the effect of vegetation. The proposed algorithm is derived from a data set acquired over several years using an airborne radar. It uses a simple cloud model to describe the vegetation attenuation. This algorithm does not need very precise information on vegetation density and yields a final precision for the moisture content on the order of 0.05 cm3/cm3

Estimation of heat and mass fluxes from IR brightness temperature

International audienceSoil-vegetation-atmosphere transfer models have been developed to simulate mass and energy exchanges between vegetation canopies, the soil, and the atmosphere. They may be used in conjunction with remote sensing data through inversion procedures. In this study, the inversions of two soil-vegetation-atmosphere transfer models are compared on the same data set. Hourly evolutions of stomatal conductance and evapotranspiration are retrieved from the midday measurement of thermal infrared brightness temperature. Seasonal evolution of evapotranspiration and midday stomatal conductance are monitored with a good accuracy with both models. However, the simpler model underestimates evapotranspiration because it does not include a realistic description of hourly evolution of stomatal conductance, and then underestimates morning and afternoon evapotranspiration. The other model gives a better description of hourly evolutions of stomatal conductance and evapotranspiration. This model gives also better estimates of hourly canopy photosynthesis. However, it requires more parameters and computer time than the simpler model, two unfavorable factors for inversion

Estimation of evapotranspiration using SVAT models and IR brightness temperature

National audienc

Seasonal estimation of evaporation and stomatal conductance over a soybean field using surface IR temperatures

International audienc