In vervolg op onze plannen voor een promotie (PhD) onderzoek naar maaivelddaling stuur ik u bijgaand een gedetailleerd projectplan.

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1 Our reference Contact person Date 10 Maart 2015 RH Prof.dr.ir. R.F. Hanssen Projectbeschrijving Maaivelddaling Subject Delft University of Technology Department of Geoscience and Remote Sensing Faculty of Civil Engineering and Geosciences Aan: Dhr. S Riemersma Hoogheemraadschap van Delfland Postbus DB Delft Geachte heer Riemersma, In vervolg op onze plannen voor een promotie (PhD) onderzoek naar maaivelddaling stuur ik u bijgaand een gedetailleerd projectplan. In uw van 20 maart j.l. liet u mij weten dat uw collega Peter Hollanders dit onderzoeksvoorstel heeft besproken in de innovatiegroep van Delfland en de portefeuillehouder heeft geïnformeerd, en dat Delfland in principe euro per jaar (voor een reguliere PhDperiode van vier jaar) wil bijdragen aan dit onderzoek. Daarna heb ik het op mij genomen om een medefinancier te zoeken om dit onderzoek mogelijk te maken. Zoals ik u eerder per mail heb laten weten is dit gelukt, en is Rijkswaterstaat bereid om een bijdrage van euro per jaar te leveren. Met bijgaand Plan van Aanpak (projectplan), zou dan D&H de aanvraag kunnen goedkeuren om het project te kunnen starten. U gaf daarbij aan dat het belangrijk is het project voor 1 juni 2015 te starten. Ik hoop dat bijgaand projectplan de goedkeuring kan krijgen van D&H, en dat Hoogheemraadschap Delfland, Rijkswaterstaat, en TU Delft een volgende stap kunnen zetten in het inzetten van innovatieve methodes om de beheersproblematiek van maaivelddaling aan te pakken. Met vriendelijke groet, Prof.dr.ir. Ramon F. Hanssen Antoni van Leeuwenhoek hoogleraar Afdelingsvoorzitter Department of Geoscience and Remote Sensing PS. Ten overvloede memoreer ik nog dat we onlangs een voorstel hebben gedaan bij de Technologiestichting STW (de zogenaamde Water-call ) om te proberen dit onderzoek breder in te bedden. In dat voorstel zou bijvoorbeeld ook onderzoek kunnen worden gedaan naar de efficiënte monitoring van waterkeringen. Indien dit STW voorstel zou worden gehonoreerd, zou het onderliggende project hier integraal in kunnen worden ingebed, waardoor Delfland ook zou kunnen profiteren van dit bredere onderzoek door officieel deel te nemen in de gebruikersgroep. Page/of 1/17

2 Page/of 2/17 Project plan / Plan van Aanpak Subsidence of peat soils observed by satellite remote sensing Prof.dr.ir. R.F. Hanssen Delft University of Technology Stevinweg 1, 2628 CN, Delft r.f.hanssen@tudelft.nl, Secretary: Ms. Rebeca Domingo. Tel/Fax: , secr-grs-citg@tudelft.nl Objective: Develop a methodology to provide reliable empirical estimates of current shallow subsidence processes, using satellite remote sensing, particularly pasture in peat-rich areas Composition of the research group: Name Institute Specialization Involvement Vacancy TU Delft Civil Eng/ Earth Sci Promovendus/PhD Prof.dr.ir. R.F. Hanssen TU Delft Geodesy/RS Promotor /project lead Dr.ir. Freek van Leijen TU Delft Geodesy/RS co-supervisor Composition of the steering group: Name Institute Specialization Involvement S. Riemersma HH Delfland Water management sponsor P. Hollanders HH Delfland Water management sponsor P. van Waarden Rijkswaterstaat Geodesy, NAP sponsor J. van Steenbruggen Rijkswaterstaat Civil Engineering sponsor Duration of the project: 4 years Proposed starting date: before 1 June 2015 Scientific summary Surface elevation in low-lying coastal regions is not constant. Combined with rising sea levels, this affects the lives of more than a billion people on earth. Elevation change can be a consequence of geophysical processes as well as anthropogenic activities. To predict elevation change using physical predictive models, accurate geodetic observations are indispensable. Geodetic networks consisting of well-defined benchmarks have been established in many areas, and terrestrial and spaceborne techniques such as InSAR deliver relevant information. However, the wide-scale and precise motion of pasture on (drained) peat soils cannot be measured with geodetic techniques yet, due to the absence of identifiable points for repeated measurements. Yet, peat soils are particularly susceptible to subsidence when cultivated. As a result, elevation changes are unknown, and long-term sustainability in relation to flooding risks, as well as water table management, is sub-optimal.

3 Page/of 3/17 In this project we will develop, test, and deploy a method for the direct estimation of elevation changes of pasture on drained peat-soils in the Netherlands, starting in the management area of Hoogheemraadschap Delfland, particularly using spaceborne InSAR. We will build upon recent advances in the estimation of surface motion over low-coherence areas, using the combination of all available SAR data and a new spatio-temporal estimation method. The project will produce surface elevation change maps over the areas of interest, which will be combined within the larger effort to establish a Dynamic-DEM, in relation to flood management. Moreover, the elevation change maps will improve drainage and water table management, enabling more sustainable agriculture, and limiting excessive greenhouse gas fluxes. Dutch management abstract De hoogte van land in laaggelegen kustgebieden, zoals Nederland, is niet constant. In combinatie met zeespiegelstijging beïnvloedt dit het leven van meer dan een miljard mensen op aarde. Hoogteveranderingen worden veroorzaakt door natuurlijke effecten, maar ook door menselijk handelen, zoals bijvoorbeeld de bemaling van polders. Om ook de hoogteligging in de toekomst middels modellen te kunnen voorspellen zijn nauwkeurige metingen van hoogteverandering cruciaal. Hiervoor worden geodetische netwerken aangelegd, bestaand uit goed identificeerbare merkpunten (zoals waterpasbouten). Daarnaast leveren zowel terrestrische als vliegtuig- en satelliettechnieken relevante informatie. Echter, op dit moment is het onmogelijk om de hoogteverandering van weide- en akkerbouwgebieden te meten met geodetische technieken, simpelweg doordat het in dit soort gebieden niet mogelijk is om representatieve merkpunten aan te brengen: op een graspol kun je niet met millimeter-precisie meten. Als gevolg hiervan kennen we de werkelijke hoogteverandering dus nauwelijks, waardoor miljarden-beslissingen over infrastructuur en waterveiligheid een empirisch fundament missen, maar waardoor ook overstromingsmodellen suboptimaal zijn, en waterschappen hun beleid slecht kunnen onderbouwen. In dit onderzoek ontwikkelen en testen we een methode om hoogteverandering in het veenweidegebied, met name het beheersgebied van Hoogheemraadschap Delfland met hoge precisie te meten, middels satelliet radartechnologie. Een recente voorstudie toonde aan dat dit mogelijk is door alle beschikbare satellietdata te combineren in een nieuw ruimte-tijdmodel. Hiermee kunnen bodembewegingskaarten gemaakt worden, die uiteindelijk zullen worden gecombineerd in een dynamisch hoogtemodel. Dit leidt tot betere overstromingsmodellen, het duurzaam beheren van het karakteristieke Nederlandse veenweidegebied in relatie tot landbouw en ecologie, en tot de beperking van uitstoot van broeikasgassen. Historical background of the project Much of the western part of the Netherlands is covered with pasture on drained peat soils (Langeveld et al, 1997), see Figure 1. Peat is composed of organic materials which oxidize and emit greenhouse gases when exposed to the air (Bartlett and Harriss, 1993; Van Huissteden et al., 2006). Peat oxidation contributes for 1-3% of the annual greenhouse gas (GHG) emissions of the Netherlands (Van den Bos, 2003): Peat soils with a subsidence rate of 10 mm/y equate to an emission of about 22 tons of CO2 per hectare/y (Van den Akker et al., 2008).

4 Page/of 4/17 Oxidation of peat soils results in volume reduction and subsequent subsidence. As a result, the thickness of the vadose zone decreases, as the land surface gets closer to the phreatic zone or groundwater level. Figure 1 (A) Typical example of pasture on drained peat soils. (B) Spatial variability of cumulative subsidence over a period of 37 years. (Van den Akker, 2005) Consequently, to keep the land sufficiently dry to be used as pasture, the soil needs to be drained, resulting in an increased vadose zone thickness, in more oxidation, and therefore more subsidence. In addition to oxidation, the peat soils are consolidating when drained, as the weight of the increased thickness of the vadose zone increases the effective stress of the saturated peat. Peat consolidation generally occurs on time scales of decades, whereas peat oxidation continues until the peat soils have disappeared completely (Van Asselen et al., 2009). Many parts of these regions are currently situated below sea level and are expected to subside significantly in the coming decades. Subsidence rates in drained peat soils in the western Netherlands are believed to range from 0.2 to 5.1 cm/y, with common values between 0.5 to 1.5 cm/y (Baas, 2001). However, most quantitative subsidence rates reported in literature are either modeling results, or results from few mechanical point measurements using a local in situ device (Van den Akker, 2005). Moreover, subsidence rates are not constant in time and space (Schothorst, 1977; Stouthamer et al. 2008). Periodic geodetic estimates, with high precision and proper quality description, available with contiguous spatial sampling over all areas of interest are not available. First indications of seasonal deformation caused by the change of the groundwater level between the seasons (low in summer and high in winter) from remote sensing were observed by Van Leijen and Hanssen, (2008) and Cuenca and Hanssen, Measuring wide-scale subsidence rates in pasture on drained peat soils is difficult, if not impossible, with conventional geodetic methods as soft soils make it impossible to install fixed benchmarks for repeated terrestrial surveying. The local roughness of the pasture is in the order of a decimeter, and changes continuously due to grazing cattle. Returning to the same location for a repeated precise height measurement is nearly impossible, but even if it was feasible, the local effects of grass and cattle may be even higher than the signal of interest. This makes precise terrestrial geodetic point measurements over large areas impossible.

5 Page/of 5/17 Airborne laser altimetry (lidar) is able to determine the elevation of the pasture areas. The quality of the lidar-derived elevation estimates (the AHN-2 digital elevation model) is expected to be better than 5 cm in terms of the systematic offset (bias) and better than 5 cm in terms of stochastic error (dispersion). When two lidar surveys acquired with a certain time difference are differenced to estimate subsidence, these quality metric imply that, with a 5% level of significance, a difference of 14 cm will be detected with a 50% likelihood. Additionally, this calculation ignores (i) the repeatability of the measurements (measuring the same locations in the pasture), (ii) the two systematic offsets, (iii) the footprint width of the lidar, relative to the roughness of the terrain. In other words, it is not possible to estimate subsidence from repeated lidar surveys, unless the deformation signal is in the order of a decimeter (hence, long time intervals), or unless it is allowed to perform spatial averaging over large areas under the assumption that the averaged area is flat. InSAR and InSAR time series approaches such as Persistent Scatterer Interferometry (PSI) or Small Baseline Subsets (SBAS) are able to detect millimeter level elevation changes as relative double-differences in space and time (Hanssen, 2001). However, conventional InSAR cannot maintain coherence due to the very fast temporal decorrelation in the area (te Brake et al., 2012). The absence of coherent point scatterers prohibits the use of PSI, and even when buildings are found in the area, it is likely that their deformation will not be representative of the subsidence in the center of pasture fields (Cuenca and Hanssen, 2008). Goals and objectives Given the problem description above we want to develop a methodology to provide reliable empirical estimates of current shallow subsidence processes, using satellite remote sensing, particularly pasture in peat-rich areas. Recent preparatory studies by Morishita and Hanssen (2014,2015) have demonstrated that observing such processes is feasible by combining data from several satellite missions and by applying an innovative data processing methodology. Moreover, these first results show that subsidence rates may be a factor 2-3 greater than previously expected, and are very spatially variable, stressing the importance of better empirical observations. To reach this goal, we need (i) to develop better radar processing methods, exploit new satellite missions, and combine information over time series data now archived. Additionally, since the estimated shallow subsidence observed cannot be validated, we will (ii) study the driving mechanisms behind the shallow subsidence, and (iii) perform additional in situ measurements using a SET (Surface Elevation Table), a portable mechanical leveling device for measuring the relative elevation change of wetland sediments. Specific scientific significance and innovative aspects The main innovative aspect of this project is the fact that we will measure something which has been unmeasurable until now: the subsidence of pasture land. The main significance of the project is that, if successful, for the first time subsidence of pasture in areas below sea level will be established from empirical data, instead of physical models or sparse point measurements. Since expectations on (and knowledge of) land motion are driving investments of billions of euros1 for decades to come in the Netherlands, it is crucial that policy decisions can be based on empirical information. 1 the Delta program will cost billion euro/year until 2050, and billion euro/year from

6 Page/of 6/17 In terms of innovation, the contributing factors are (i) the algorithmic approach, (ii) the (spaceborne) multi-sensor approach, and (iii) the link with in situ data and modelling. The algorithmic approach will be based on three pillars. First, the underlying idea is to use all available SAR data over the area of interest, optimizing for coherence per land unit, rather than for radar image resolution cells. The second pillar is that we start with parametric models to describe the land motion, including long term velocities as well as seasonal variability. The third pillar is to trade spatial resolution for noise reduction, acknowledging the difficult coherence conditions for InSAR over pasture. Until recently, it was uncertain whether this approach would be successful, but recent results in a demonstration project (Morishita and Hanssen, 2014, 2015) over a small test area show the feasibility of the approach. The second innovative aspect is the spaceborne multi-sensor approach. We use X-, C-, and L-band data in a weighted approach, and exploit the optimal characteristics of each sensor in terms of repeat interval, resolution, and wavelength-dependent decorrelation rates. Most importantly, we expect a fundamental improvement by using the Sentinel-1a and -1b time series which will become available starting early The third innovative aspect is the fact that we will not only produce results from satellite data processing, but we will perform in-situ validation using terrestrial measurements, linking the expertise of partner institutes such as Utrecht and Wageningen University and Deltares, and update existing subsidence models. In terms of significance and relevance, this research relates to (i) land subsidence in relation to flood risk, (ii) sustainability of agriculture in the Dutch pasture lands, (iii) assessment and control of greenhouse gas emission rates, (iv) water management, (v) ecological long term planning. The relation of land subsidence with flood risk (i) is evident. It should be stressed here that changes in predicted subsidence rates in the order of millimetres per year have dramatic consequences for the water storage capacity (WCS) of the area. To compute the WCS, the (extra) subsidence should be multiplied with an area that can be many tens of square kilometres, which leads to very large volumetric amounts. Thus, flood prediction models need to be adjusted if subsidence values are not as expected. The sustainability of agriculture (ii) in the Dutch pasture ( veenweidegebied ) relies completely on artificial drainage of the peat soils. To prevent excessive subsidence, water authorities try to minimize the vadose zone. As a consequence, some pasture areas are too wet for access by tractors or cattle, and these will be lost for agricultural exploitation. This is a major problem for farmers in this area, and is already leading to farmers changing their activities. As stated above, annual greenhouse gas (GHG) emissions of the Netherlands (iii) are for 1-3% due to peat oxidation (Van den Bos, 2003), and directly related to the volume of the vadose zone. Since subsidence rates are an indicator of the vadose zone (a lower phreatic level implies more subsidence), they can be used as a proxy for the GHG emissions of the area. In terms of water management, (iv) the Netherlands has 24 autonomous regional water authorities ( waterschappen ) charged with managing water barriers, waterways, water levels, water quality and sewage treatment in their respective regions. They base their decisions to change ground water levels ( peilbesluiten ) also on subsidence predictions. However, in our preparatory research, we concluded that these predictions are never based on direct empirical data of subsidence, but only on modeling results using soil types (from drillings) as input. Consequently, these authorities are currently not able to assess the quality of these predictions, even though they have a major impact for agriculture, recreation, ecology, and civil society in general. Finally, the significance of subsidence for ecological long term planning (v) is large. Already now, the water authorities need to make decisions on socalled break-points ( knikpunten ). These are moments in time, when land use has to change from, e.g. pasture and cattle, to more wet ecologic situations, such as marshes and wetlands. Clearly, this has major impact on the typical Dutch landscape and biodiversity.

7 Page/of 7/17 Research methodology and technical feasibility The research methodology is based on first ideas tested in a preparatory study (Morishita and Hanssen, 2014), applied over a small area south of Delft, the Netherlands, see Figure 2A. We show the results of standard persistent scatter results in Figure 2B (an Envisat C-band time series), demonstrating that it is not possible to estimate deformation over the pasture with conventional methods. Only some coherent reflections stemming from farm buildings are visible. The research methodology of this project relies on (1) the spatial averaging of statistically homogeneous pixels using non-overlapping estimation windows, (2) a parametric deformation model and a generalized least-squares method, and (3) a combination of all available satellite SAR data stemming from different sensors see Figure 3(Left). In our preparatory study, we combine data from ALOS, TerraSAR-X, Radarsat-2, and Envisat and obtain subsidence rates for the test areas in the order of several centimeters per year, and a seasonal signal with an amplitude of almost 1 cm, cf. Figure 3. Figure 2 (A) Location of the test site, a pasture area south of Delft. (B) Typical Persistent Scatterer result over this area, showing only coherent points coinciding with buildings, and not at the pasture itself (Morishita and Hanssen, 2014) Yet, although these results are encouraging and suggest feasibility of the method, the numerical results still trigger fundamental questions. First, the estimated rates appear to be quite large if compared with model results. The preliminary version of the algorithm needs to be updated and improved, and quality assessment needs to be improved. Secondly, spatial resolutions of 230 meter were obtained disregarding the shape of the pasture fields. We expect that including such information in the processing approach will improve the results significantly. Figure 3 (Left) Overview of all SAR data as a function of time and orbital separation. The picture is intended to show how many SAR datasets have

8 Page/of 8/17 been used in the analysis. Lines connect acquisitions with coherent information. (Middle) Estimated subsidence rates in mm/y for the area of Figure 2. This is the main encouragement that observation of subsidence over pasture may be feasible, if the optimal data processing method is used. (Right) Amplitude of the seasonal motion in mm (Morishita and Hanssen, 2014). Regarding the physical processes, we will investigate the compaction and oxidation of organic shallow layers, focusing on the identification of driving mechanisms, the description of contemporary spatial and temporal variability, and the improvement of descriptive and predictive models. The observed geodetic subsidence signal is used to tune the experimental part of the physical study. The fieldwork based part of the study focuses on the construction and deployment of Surface Elevation Tables. The input from the geodetic observations will be used to identify optimal and representative locations of these devices. The results will be used to validate the geodetic data on a point-by-point level, enabling us to scale the methodology over wider regions, i.e., the entire western and northern part of the Netherlands. Cooperation other parties Apart from the main sponsors of the project, Hoogheemraadschap Delfland and Rijkswaterstaat, we seek close collaboration with other research groups at TU Delft (mainly in the soil sciences and water management), Utrecht University, Wageningen University and Deltares Research Institute. Links with (inter)national research programmes The project has a link with the Top Sector Agri and Food, since subsiding peat soils significantly impact the Dutch productivity in agriculture and food. It also relates to Top Sector Water: theme: Leefbare delta, and the prospective international coastal hazards supersite in relation to the Group on Earth Observations ( Expected results and potential users of the results of the project The project will yield, for the first time, geodetic estimates of subsidence due to shallow causes such as compaction, peat oxidation, and consolidation. These estimates will have a huge impact on water management strategies, since they enable water management boards, such as Hoogheemraadschap Delfland, to improve their long term predictions on the manageability of the subsidence problem and to assess the consequences of their groundwater policy on increased flood risk. They will impact agriculture, farmers and therefore the Dutch economy, as it may show that land which is currently appropriate (or thought to be appropriate) for agriculture may not be appropriate anymore within a few decades or less. (This is already a major concern for provinces in the western part of the Netherlands. They will impact the Dutch budget of CO2 and methane emissions, as the oxidation of organic material is a great contributor to these budgets. As of 2021, land use induced greenhouse gas emissions will become part of the European Union CO 2 reduction strategy. Counter-intuitively, they will help narrowing the estimates of subsidence due to mining activities, and therefore improve the attribution of damage, nowadays in the order of many millions of Euros per year, to specific parties. This is a consequence of the fact that disentangling the different origins of the subsidence is nowadays very difficult. The economic impact of the availability of reliable subsidence estimates will therefore be very significant. In fact, we address the manageability of

9 Page/of 9/17 a society largely living below natural water levels. In terms of SME interest, the possibility to measure deformation in green areas will widen the market opportunities for value-adding companies. Technically, the study will lead to new and improved ways to analyze very big data sets, based on advanced data processing algorithms. Finally, the results will be documented in peer-reviewed journal publications The likelihood that this study will lead to breakthroughs can be considered high, since (i) this type of information is nowadays simply unavailable, and (ii) we already have indications that shallow subsidence is locally greater than previously expected. References Cuenca, M. and R. Hanssen, Subsidence due to peat decomposition in the Netherlands, kinematic observations from radar interferometry. In Proc. Fringe 2007 Workshop, Langeveld, C., R. Segers, B. Dirks, A. Van den Pol-van Dasselaar, G. Velthof, and A. Hensen, Emissions of CO2, CH4 and N2O from pasture on drained peat soils in the Netherlands, European Journal of Agronomy, vol. 7, no. 1-3, pp , Bartlett, K. and R. Harriss, Review and assessment of methane emissions from wetlands, Chemosphere, vol. 26, no. 1, pp , Hanssen, R.F. Radar interferometry: data interpretation and error analysis, Springer 2001 Morishita, Y. and R.F. Hanssen, "Temporal Decorrelation in L-, C-, and X-band Satellite Radar Interferometry for Pasture on Drained Peat Soils," IEEE Transactions on Geoscience and Remote Sensing, vol.53, no.2, pp.1096,1104, Feb. 2015, doi: /TGRS Morishita, Y. and R.F. Hanssen, Deformation parameter estimation in low coherence areas using a multisatellite InSAR approach, accepted by IEEE Transactions on Geoscience and Remote Sensing, 2014 Stouthamer, E. H.J.A. Berendsen, J. Peeters & M.T.I.J. Bouman, Toelichting Bodemkaart Veengebieden provincie Utrecht, schaal 1:25.000, Universiteit Utrecht, Te Brake, B., R.F. Hanssen, M. J. van der Ploeg, G. H. de Rooij, Satellite-Based Radar Interferometry to Estimate Large- Scale Soil Water Depletion from Clay Shrinkage: Possibilities and Limitations, Vadose Zone J., doi: /vzj , 2012 Van den Akker, J. (2005). Maaivelddaling en verdwijnende veengronden. In: W. Rienks & A. Gerritsen (2005), Veenweide 25x belicht. Alterra. Van den Bos, R.M., Restoration of former wetlands in the Netherlands; effect on the balance between CO2 sink and CH4 source. Netherlands Journal of Geosciences 82: Van Huissteden, J., R. van den Bos, and I. Alvarez, Modelling the effect of water-table management on CO2 and CH4 fluxes from peat soils, Netherlands Journal of Geosciences, vol. 85, no. 1, p. 3, Van Leijen, F. and R. Hanssen, Ground water management and its consequences in Delft, the Netherlands as observed by persistent scatterer interferometry, in Proc. Fringe 2007 Workshop, 2008.

10 Page/of 10/17 Work packages and milestones Time Schedule. The project will be performed by a PhD student together with the project team. Two main phases in the project can be distinguished. In the first phase we will setup a first version of the complete processing chain and perform case studies for representative area. This will enable us to identify bottlenecks in the processing flow in an early stage. This is followed by an iterative process of theory and methodology development, and testing. Moreover, in an early stage of the project the Surface Elevation Tables (SET) will be deployed. In the second stage, the methods will be applied for wider regions, and data analysis, interpretation and validation will be performed. The project is concluded via the PhD theses. If possible, open source software tools will be used. The entire project will take 4 years. Phase 1 consists of work packages WP1-4: WP1: Literature review The candidate will perform a literature review to the state-of-the-art in radar interferometric processing, surface deformation retrieval, and physical processes in soft-soils. This includes the following topics: What is the societal relevance of the research? What is the particular relevance for Hoogheemraadschap Delfland? Review of the research already performed on the subject of subsidence over pastures Which organizations, knowledge institutes and universities are involved in this research How will the proposed remote sensing technology differ from conventional techniques? WP2: Data processing training Based on a small dataset, the candidate will become familiar with the interferometric data processing. WP3: Surface Elevation Table (SET) deployment WP3.1: Management of technical design and construction of SETs WP3.2: Planning of locations of SETs WP3.3: Deployment of SETs WP3.4: SET measurements WP4: Methodology development and case studies WP4.1: Segmentation of homogenous areas (brotherhoods) WP4.2: Design and development of parametric deformation model WP4.3: Design and development of integrated deformation estimation from multi-sensor datasets WP4.4: Case-studies for representative areas Phase 2 consists of the work packages 5-6: WP5: Application to wide area WP5.1: Setup of an automated processing environment WP5.2: Data processing and quality assessment WP5.3: Post-processing to retrieve deformation values and creation of database WP6: Data analysis, interpretation and validation WP6.1: Analysis and interpretation of results WP6.2: Validation based on SET measurements

11 Page/of 11/17 During complete duration of project: WP7: Writing of publications and thesis The candidate will be responsible for the literature review and the majority of the algorithm development and implementation. Milestones We specified three milestones during the project, indicated with respect to the Kick-off (KO): Milestone 1: state-of-the-art review and deployed SETs, KO+6 months Milestone 2: implemented processing chain and case study results, KO+24 months Milestone 3: finalized analysis, interpretation, and validation for wide area, KO+42 months Milestone 4: finalized thesis, KO+48 months These milestones, and the planning of the work packages, are indicated in the Ganttchart in Figure 4. The working hours per project participant are indicted in Table 1. Figure 4 Gantt-chart of the project.

12 Page/of 12/17 Table 1 Schedule of assigned working hours per project participant and Work Package. Ramon Hanssen Freek van Leijen PhD candidate WP total WP1 Literature review WP2 Data processing training WP3.1 Design and construction SETs WP3.2 Planning locations SETs WP3.3 Deployment of SETs WP3.4 Measurement of SETs WP4.1 Segmentation of homogenous areas WP4.2 Parametric deformation model WP4.3 Integrated deformation estimation WP4.4 Case studies WP5.1 Automated processing WP5.2 Data processing WP5.3 Creation database WP6.1 Analysis and interpretation WP6.2 Validation WP7 Writing thesis Total Publication plan. Results of the project will be reported via: Half-yearly project reports to the sponsor Half-yearly project meetings with sponsors and advisors Publications in peer-reviewed journals Publications and presentations at relevant conference PhD thesis (dissertation) Moreover, as the results of the project are potentially interested for other waterschappen, we plan to organize two workshops for a wider audience during the period of the project.

13 Page/of 13/17 Cost breakdown (in k ) Description of the costs Year 1 Year 2 Year 3 Year 4 Total: PhD salary Bench fee 5 5 Travel Material Total: k 220 Description of the funds Year 1 Year 2 Year 3 Year 4 Total: HH Delfland Rijkswaterstaat Total: k 220 Motivation of the requested funds: Material: non-free SAR images (e.g. TerraSAR-X), publication expenses (page charges). It is assumed that HH Delfland will make in situ data available, or invest in SET-instrumentation Travel: eventual short-stays with future collaborators, dissemination of results with fellow researchers and workshops around PhD defense. Personnel: full salary of one Ph.D. student (4 years) Nature of the own contribution and the contribution of other parties. The own contribution of the TU Delft represents the faculty overhead during those four years and the cost of the hours for supervising the PhD student, furthermore there is also the university overhead which is calculated as a P.M. post. The contribution from other parties (Delfland/RWS) represent the salary of the participants, corresponding to the hours invested in this project. Description of the research group The Department of Geoscience and Remote Sensing is embedded in the faculty of Civil Engineering and Geosciences. The department was formed early 2012, after a university reorganization that fused all groups working on geodesy, remote sensing and the earth and atmospheric sciences. More in particular, all radar research groups, originally from the disciplines of electrical engineering, aerospace engineering, and earth sciences, merged at that time in the department of Geoscience and Remote Sensing. This created a challenging, inspiring and innovative cluster of scientists and engineers with valuable and highly complementary skills and experiences. For example, both radar instrument development, (SAR and interferometric) algorithm design, computational optimization, geodesy and application development are now embedded in one single department. Relevant to this project, our department also holds specialists in geodetic data analysis and atmospheric and climate sciences. Hence, the project will benefit from the multi-disciplinary expertise of the department.

14 Page/of 14/17 Curriculum vitae NAME ORGANISATION CURRENT POSITION Ramon Hanssen Delft University of Technology Full professor. Head department of Geoscience and Remote Sensing, Fac. Civil Eng. and Geosciences ACADEMIC QUALIFICATION 1993 MSc.(Ir.) Geodetic Engineering, Delft University of Technology 2001 Ph.D. (Dr.ir.) (cum laude), Delft University of Technology Assist.-Assoc. professor, Fac. Aerospace Engineering, TU Delft 2008 Full professor, Antoni van Leeuwenhoek chair, TU Delft Guest professor at Wuhan University, China Professional experience Head department of Geoscience and Remote Sensing, Fac. Civil Eng. and Geosciences Head department of Remote Sensing, faculty of Aerospace Engineering Chair section Mathematical Geodesy and Positioning, GPS/GNSS radar interferometry General director of Hansje Brinker, a TU Delft spin-off initiative Visiting scholar at Scripps Inst.of Oceanography, University of Miami, University of Iceland Fulbright Fellow at Stanford University, CA Guest researcher at Stuttgart University and DLR (German Aerospace Center) PhD researcher TU Delft Research fellow at ITC (Int. Inst. for Aerospace Survey and Earth Sciences) Distinctions/memberships President of National Committee of IUGG, International Union of Geodesy and Geophysics 2009 Chair of subcie on Land Subsidence and Sea Level Change, Neth. Geodetic Comm. Royal Academy of Sciences (KNAW) 2008 Antoni van Leeuwenhoek chair 2003 Bomford prize of the International Association of Geodesy (IAG) 2003 Innovational Research Award, (Vernieuwingsimpuls) of Neth. Org. for Sci. Res. (NWO) Editor of Journal of Geodesy Member of Institute of Electrical and Electronics Engineers, Inc. (IEEE), member of American Geophysical Union (AGU), of the Sentinel-1 Scientific Advisory Group, European Space Agency (ESA) Publications, see Achievements, see Relevant publications: 1. Morishita, Y.; Hanssen, R.F., "Temporal Decorrelation in L-, C-, and X-band Satellite Radar I nterferometry for Pasture on Drained Peat Soils," Geoscience and Remote Sensing, IEEE Transactions on, vol.53, no.2, pp.1096,1104, Feb doi: /TGRS B. te Brake, R.F. Hanssen, M.J. van der Ploeg, and G.H. de Rooij, Satellite-Based Radar Interferometry to Estimate Large-Scale Soil Water Depletion from Clay Shrinkage: Possibilities and Limitations, Vadose Zone Journal, (11), doi: /vzj , M. Berger, J Moreno, J.A. Johannessen, P.F. Levelt and R.F. Hanssen, ESA's Sentinel missions in support to Earth system science, Remote Sensing of Environment, 120(0), 84-90, Mahapatra, P.S.; Samiei-Esfahany, S.; van der Marel, H.; Hanssen, R.F., "On the Use of Transponders as Coherent Radar Targets for SAR Interferometry," Geoscience and Remote Sensing, IEEE Transactions on, vol.pp, no.99, pp.1,1, 0 doi: /TGRS

15 Page/of 15/17 5. M. Caro Cuenca, A. Hooper and R.F. Hanssen, A New Method for Temporal Phase Unwrapping of Persistent Scatterers InSAR Time Series, IEEE Trans. Geosci. and Remote Sensing, 99, 1-10, doi: /tgrs , Hanssen, R.F., T.M.Weckwerth, H.A. Zebker, and R. Klees. High-resolution water vapor mapping from interferometric radar measurements. Science, 283: , Kampes, B.M., and R.F. Hanssen, Ambiguity Resolution for Permanent Scatterer Interferometry IEEE Transactions on Geoscience and Remote Sensing, 42(11): , Hanssen, R. F. (2001). Radar interferometry: data interpretation and error analysis (Vol. 2). Springer. 9. Hanssen, R. F. (2005). Satellite radar interferometry for deformation monitoring: a priori assessment of feasibility and accuracy. International Journal of Applied Earth Observation and Geoinformation, 6(3), NAME ORGANISATION CURRENT POSITION Freek van Leijen Delft University of Technology Researcher ACADEMIC QUALIFICATION 2002 MSc. (Ir.) Geodetic Engineering, Delft University of Technology He has over 10 years of experience in satellite radar interferometry and deformation analysis. Freek obtained his master degree in Geodetic Engineering at Delft University of Technology in In 2003, he rejoined Delft University of Technology as a PhD-student, working on satellite radar interferometric research. He developed software algorithms for Persistent Scatterer interferometry. In 2007 he co-founded Hansje Brinker, a spin-off initiative of Delft University of Technology, focusing on the monitoring of infrastructure using radar interferometry. Since 2013 Freek is back at Delft University of Technology as a researcher, with a prime interest in geodesy, radar interferometry, and deformation analysis. Relevant publications: Ramon Hanssen and Freek van Leijen. Modeling and spatial interpolation of tropospheric signal delay for space-geodetic observations based on GPS time series analysis. In EGS XXV General Assembly, Nice, France, April 2002, Geophys. Res Abstracts, 2, Freek van Leijen and Ramon Hanssen. Interferometric radar meteorology: resolving the acquisition ambiguity. In CEOS SAR Workshop, Ulm Germany, May 2004, page 6, R F Hanssen and F van Leijen. Water vapor monitoring using Envisat spectrometer and radar measurements. European Meteorological Society, 4th Annual Meeting, Nice, France, September 2004, R F Hanssen, F van Leijen, and S Businger. Satellite radar interferometry for water vapor distribution monitoring: towards a meteorological product. European Meteorological Society, 4th Annual Meeting, Nice, France, September 2004, R F Hanssen and F J van Leijen. Monitoring water defense structures using radar interferometry. In IEEE Radar Conference, Rome, Italy, May 2008, page 4, Petar Marinkovic, Gini Ketelaar, Freek van Leijen, and Ramon Hanssen. InSAR quality control: Analysis of five years of corner reflector time series. In Fifth International Workshop on ERS/Envisat SAR Interferometry, `FRINGE07', Frascati, Italy, 26 Nov-30 Nov 2007, page 8 pp., Freek J van Leijen and Ramon F Hanssen. Persistent scatterer density improvement using adaptive deformation models. In International Geoscience and Remote Sensing Symposium, Barcelona, Spain, July 2007, page 4 pp, 2007.

16 Page/of 16/17 Freek J van Leijen and Ramon F Hanssen. Persistent scatterer interferometry using adaptive deformation models. In ESA ENVISAT Symposium, Montreux, Switzerland, April 2007, page pp, 2007.

17 Page/of 17/17 Bijlage 2 Cases Delfland: 1. Meten effect van onderwaterdrainage op de maaivelddaling In het gebied van Delfland zijn recent een aantal kleine percelen voorzien van onderwaterdrainage. De verwachting is dat deze vorm van drainering minder maaivelddaling veroorzaakt dan in ongedraineerde percelen. Aandachtspunten: - Het gaat hier om graslanden van circa 50 x 50 meter Mogelijkheden onderzoek: - Door een vergelijking te maken van oude maaivelddalingsgegevens en maaivelddalingsgegevens van naburige percelen kan een betere onderbouwing worden gemaakt. - Betere resultaten kunnen behaald worden door resultaten worden te matchen met bodemeenheden (veen, klei, kreekruggen) en door bebouwing, infrastructuur, water uit te sluiten (filtering). 2. Monitoring maaivelddaling van lage delen Inzicht in de daling van lage plekken in landbouwpolders is nuttige informatie voor peilbesluiten en aanpak van wateroverlast. Aandachtspunten: - Het gaat hier om (kleine) grillige gebieden en vormen Mogelijkheden onderzoek: - Betere resultaten kunnen behaald worden door resultaten te matchen met bodemeenheden (veen, klei, kreekruggen) en door bebouwing, infrastructuur, water uit te sluiten (filtering). 3. Maaivelddaling per peilgebied Bij het opstellen van peilbesluiten wordt de maaivelddaling per peilgebied bepaald van de afgelopen periode (10 jaar). Hiermee wil Delfland afwegen of de drooglegging gelijk moet blijven door het waterpeil aan te passen aan die bodemdaling. Aandachtspunten: - De bodemdaling moet per peilgebied worden bepaald voor een lage periode (circa 10 jaar).