Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

This work was financially supported by the German Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE), (2851ERA01J). FT and RPR were supported by FACCE MACSUR (3200009600) through the Finnish Ministry of Agriculture and Forestry (MMM). EC, HE and EL were supported by The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (220-2007-1218) and by the strategic funding ‘Soil-Water-Landscape’ from the faculty of Natural Resources and Agricultural Sciences (Swedish University of Agricultural Sciences) and thank professor P-E Jansson (Royal Institute of Technology, Stockholm) for support. JC, HR and DW thank the INRA ACCAF metaprogramm for funding and Eric Casellas from UR MIAT INRA for support. CB was funded by the Helmholtz project “REKLIM—Regional Climate Change”. CK was funded by the HGF Alliance “Remote Sensing and Earth System Dynamics” (EDA). FH was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) under the Grant FOR1695. FE and SS acknowledge support by the German Science Foundation (project EW 119/5-1). HH, GZ, SS, TG and FE thank Andreas Enders and Gunther Krauss (INRES, University of Bonn) for support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Advanced interpretation of subsidence in Murcia (SE Spain) using A-DInSAR data – modelling and validation

Subsidence is a natural hazard that affects wide areas in the world causing important economic costs annually. This phenomenon has occurred in the metropolitan area of Murcia City (SE Spain) as a result of groundwater overexploitation. In this work aquifer system subsidence is investigated using an advanced differential SAR interferometry remote sensing technique (A-DInSAR) called Stable Point Network (SPN). The SPN derived displacement results, mainly the velocity displacement maps and the time series of the displacement, reveal that in the period 2004–2008 the rate of subsidence in Murcia metropolitan area doubled with respect to the previous period from 1995 to 2005. The acceleration of the deformation phenomenon is explained by the drought period started in 2006. The comparison of the temporal evolution of the displacements measured with the extensometers and the SPN technique shows an average absolute error of 3.9±3.8 mm. Finally, results from a finite element model developed to simulate the recorded time history subsidence from known water table height changes compares well with the SPN displacement time series estimations. This result demonstrates the potential of A-DInSAR techniques to validate subsidence prediction models as an alternative to using instrumental ground based techniques for validation.

Radar interferometry techniques for the study of ground subsidence phenomena: a review of practical issues through cases in Spain

Subsidence related to multiple natural and human-induced processes affects an increasing number of areas worldwide. Although this phenomenon may involve surface deformation with 3D displacement components, negative vertical movement, either progressive or episodic, tends to dominate. Over the last decades, differential SAR interferometry (DInSAR) has become a very useful remote sensing tool for accurately measuring the spatial and temporal evolution of surface displacements over broad areas. This work discusses the main advantages and limitations of addressing active subsidence phenomena by means of DInSAR techniques from an end-user point of view. Special attention is paid to the spatial and temporal resolution, the precision of the measurements, and the usefulness of the data. The presented analysis is focused on DInSAR results exploitation of various ground subsidence phenomena (groundwater withdrawal, soil compaction, mining subsidence, evaporite dissolution subsidence, and volcanic deformation) with different displacement patterns in a selection of subsidence areas in Spain. Finally, a cost comparative study is performed for the different techniques applied.

Estimation of Key Dates and Stages in Rice Crops Using Dual-Polarization SAR Time Series and a Particle Filtering Approach

Information of crop phenology is essential for evaluating crop productivity. In a previous work, we determined phenological stages with remote sensing data using a dynamic system framework and an extended Kalman filter (EKF) approach. In this paper, we demonstrate that the particle filter is a more reliable method to infer any phenological stage compared to the EKF. The improvements achieved with this approach are discussed. In addition, this methodology enables the estimation of key cultivation dates, thus providing a practical product for many applications. The dates of some important stages, as the sowing date and the day when the crop reaches the panicle initiation stage, have been chosen to show the potential of this technique.

Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry

Beijing is one of the most water-stressed cities in the world. Due to over-exploitation of groundwater, the Beijing region has been suffering from land subsidence since 1935. In this study, the Small Baseline InSAR technique has been employed to process Envisat ASAR images acquired between 2003 and 2010 and TerraSAR-X stripmap images collected from 2010 to 2011 to investigate land subsidence in the Beijing region. The maximum subsidence is seen in the eastern part of Beijing with a rate greater than 100 mm/year. Comparisons between InSAR and GPS derived subsidence rates show an RMS difference of 2.94 mm/year with a mean of 2.41 ± 1.84 mm/year. In addition, a high correlation was observed between InSAR subsidence rate maps derived from two different datasets (i.e., Envisat and TerraSAR-X). These demonstrate once again that InSAR is a powerful tool for monitoring land subsidence. InSAR derived subsidence rate maps have allowed for a comprehensive spatio-temporal analysis to identify the main triggering factors of land subsidence. Some interesting relationships in terms of land subsidence were found with groundwater level, active faults, accumulated soft soil thickness and different aquifer types. Furthermore, a relationship with the distances to pumping wells was also recognized in this work.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.

Boston, Massachusetts Region LIDAR First Return Elevation Data, 2002

LIDAR (LIght Detection And Ranging) first return elevation data of the Boston, Massachusetts region from MassGIS at 1-meter resolution. This LIDAR data was captured in Spring 2002. LIDAR first return data (which shows the highest ground features, e.g. tree canopy, buildings etc.) can be used to produce a digital terrain model of the Earth's surface. This dataset consists of 74 First Return DEM tiles. The tiles are 4km by 4km areas corresponding with the MassGIS orthoimage index. This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). The area of coverage corresponds to the following MassGIS orthophoto quads covering the Boston region (MassGIS orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 233906, 233910, 237890, 237894, 237898, 237902, 237906, 237910, 241890, 241894, 241898, 241902, 245898, 245902). The geographic extent of this dataset is the same as that of the MassGIS dataset: Boston, Massachusetts Region 1:5,000 Color Ortho Imagery (1/2-meter Resolution), 2001 and was used to produce the MassGIS dataset: Boston, Massachusetts, 2-Dimensional Building Footprints with Roof Height Data (from LIDAR data), 2002 [see cross references].

New Hampshire, 1796 Raster Image

This layer is a digitized geo-referenced raster image of a 1796 map of New Hampshire drawn by D.F. Sotzmann. These Sotzmann maps (10 maps of New England and Mid-Atlantic states) typically portray both natural and manmade features. They are highly detailed with symbols for churches, roads, court houses, distilleries, iron works, mills, academies, county lines, town lines, and more. Relief is usually indicated by hachures and country boundaries have also been drawn. Place names are shown in both German and English and each map usually includes an index to land grants. Prime meridians used for this series are Greenwich and Washington, D.C.

Vermont, 1796 Raster Image

This layer is a digitized geo-referenced raster image of a 1796 map of Vermont drawn by D.F. Sotzmann. These Sotzmann maps (10 maps of New England and Mid-Atlantic states) typically portray both natural and manmade features. They are highly detailed with symbols for churches, roads, court houses, distilleries, iron works, mills, academies, county lines, town lines, and more. Relief is usually indicated by hachures and country boundaries have also been drawn. Place names are shown in both German and English and each map usually includes an index to land grants. Prime meridians used for this series are Greenwich and Washington, D.C.

Massachusetts, 1797 Raster Image

This layer is a digitized geo-referenced raster image of a 1797 map of Massachusetts drawn by D.F. Sotzmann. These Sotzmann maps (10 maps of New England and Mid-Atlantic states) typically portray both natural and manmade features. They are highly detailed with symbols for churches, roads, court houses, distilleries, iron works, mills, academies, county lines, town lines, and more. Relief is usually indicated by hachures and country boundaries have also been drawn. Place names are shown in both German and English and each map usually includes an index to land grants. Prime meridians used for this series are Greenwich and Washington, D.C.

Rhode Island, 1797 Raster Image

This layer is a digitized geo-referenced raster image of a 1797 map of Rhode Island drawn by D.F. Sotzmann. These Sotzmann maps (10 maps of New England and Mid-Atlantic states) typically portray both natural and manmade features. They are highly detailed with symbols for churches, roads, court houses, distilleries, iron works, mills, academies, county lines, town lines, and more. Relief is usually indicated by hachures and country boundaries have also been drawn. Place names are shown in both German and English and each map usually includes an index to land grants. Prime meridians used for this series are Greenwich and Washington, D.C.

Connecticut, 1796 Raster Image

This layer is a digitized geo-referenced raster image of a 1796 map of Connecticut drawn by D.F. Sotzmann. These Sotzmann maps (10 maps of New England and Mid-Atlantic states) typically portray both natural and manmade features. They are highly detailed with symbols for churches, roads, court houses, distilleries, iron works, mills, academies, county lines, town lines, and more. Relief is usually indicated by hachures and country boundaries have also been drawn. Place names are shown in both German and English and each map usually includes an index to land grants. Prime meridians used for this series are Greenwich and Washington, D.C.

New York, 1799 Raster Image

This layer is a digitized geo-referenced raster image of a 1799 map of New York drawn by D.F. Sotzmann. These Sotzmann maps (10 maps of New England and Mid-Atlantic states) typically portray both natural and manmade features. They are highly detailed with symbols for churches, roads, court houses, distilleries, iron works, mills, academies, county lines, town lines, and more. Relief is usually indicated by hachures and country boundaries have also been drawn. Place names are shown in both German and English and each map usually includes an index to land grants. Prime meridians used for this series are Greenwich and Washington, D.C.

Pennsylvania, 1797 Raster Image

This layer is a digitized geo-referenced raster image of a 1797 map of Pennsylvania drawn by D.F. Sotzmann. These Sotzmann maps (10 maps of New England and Mid-Atlantic states) typically portray both natural and manmade features. They are highly detailed with symbols for churches, roads, court houses, distilleries, iron works, mills, academies, county lines, town lines, and more. Relief is usually indicated by hachures and country boundaries have also been drawn. Place names are shown in both German and English and each map usually includes an index to land grants. Prime meridians used for this series are Greenwich and Washington, D.C.

Maryland and Delaware, 1797 Raster Image

This layer is a digitized geo-referenced raster image of a 1797 map of Maryland and Delaware drawn by D.F. Sotzmann. These Sotzmann maps (10 maps of New England and Mid-Atlantic states) typically portray both natural and manmade features. They are highly detailed with symbols for churches, roads, court houses, distilleries, iron works, mills, academies, county lines, town lines, and more. Relief is usually indicated by hachures and country boundaries have also been drawn. Place names are shown in both German and English and each map usually includes an index to land grants. Prime meridians used for this series are Greenwich and Washington, D.C.