CropGIS - A web application for the spatial and temporal visualization of past, present and future crop biomass development

Abstract Spatial information on crop status and development is required by agricultural managers for a site specific and adapted management. Here, a prototype of a web application is presented for the visualization of biomass production of maize (Zea mays). The web application displays past biomass development and future predictions for user-defined regions of interest along with summary statistics. Biomass is modelled using the crop growth model (CGM) APSIM (Agricultural Production Systems Simulator) using meteorological data from 2001 to 2014. Information on current crop status and subfield heterogeneity is assimilated into APSIM through high-resolution optical satellite imagery. The use of recent satellite data and regional, historical meteorological data increases the reliability of the biomass information provided. Through its unique combination of high-resolution satellite imagery together with mechanistic crop growth modelling, this web application can overcome the often sparse temporal or sparse spatial resolution of biomass information, which is based on remote sensing images or on crop growth modelling alone. The prototype presented, with its high resolution biomass maps, can be the basis for variable rate application as farmers can react site-specifically to plant development.

[1]  Kuolin Hsu,et al.  Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter , 2005 .

[2]  Herman Eerens,et al.  Empirical regression models using NDVI, rainfall and temperature data for the early prediction of wheat grain yields in Morocco , 2008, Int. J. Appl. Earth Obs. Geoinformation.

[3]  Thomas W. Hertel,et al.  Global Food Security in 2050: The Role of Agricultural Productivity and Climate Change , 2014 .

[4]  Nathan Parker,et al.  Design of a GIS-Based Web Application for Simulating Biofuel Feedstock Yields , 2014, ISPRS Int. J. Geo Inf..

[5]  Tyler Mitchell,et al.  Web mapping illustrated - using open source GIS toolkits , 2005 .

[6]  David Flanagan,et al.  JavaScript: The Definitive Guide , 1996 .

[7]  Olaf David,et al.  Development of the Land-use and Agricultural Management Practice web-Service (LAMPS) for generating crop rotations in space and time , 2016 .

[8]  Jeffrey W. White,et al.  Estimating crop biophysical properties from remote sensing data by inverting linked radiative transfer and ecophysiological models , 2012 .

[9]  James Hansen,et al.  Realizing the potential benefits of climate prediction to agriculture: issues, approaches, challenges , 2002 .

[10]  Patrick Matgen,et al.  Enhanced biomass prediction by assimilating satellite data into a crop growth model , 2014, Environ. Model. Softw..

[11]  D. Holzworth,et al.  Re-inventing model-based decision support with Australian dryland farmers. 4. Yield Prophet® helps farmers monitor and manage crops in a variable climate. , 2009 .

[12]  James W. Jones,et al.  Short survey Scaling-up crop models for climate variability applications $ , 2000 .

[13]  M. S. Moran,et al.  New imaging sensor technologies suitable for agricultural management. , 2000 .

[14]  L. Dente,et al.  Assimilation of leaf area index derived from ASAR and MERIS data into CERES - wheat model to map wheat yield , 2008 .

[15]  P. Cantelaube,et al.  Seasonal weather forecasts for crop yield modelling in Europe , 2005 .

[16]  Chris Murphy,et al.  APSIM - Evolution towards a new generation of agricultural systems simulation , 2014, Environ. Model. Softw..

[17]  M. Claverie,et al.  Maize and sunflower biomass estimation in southwest France using high spatial and temporal resolution remote sensing data , 2012 .

[18]  R. C. Muchow,et al.  Testing the CERES-Maize simulation model in a semi-arid tropical environment , 1989 .

[19]  Thomas J. Jackson,et al.  Crop condition and yield simulations using Landsat and MODIS , 2004 .

[20]  G. Fischer,et al.  Effects of climate change on global food production under SRES emissions and socio-economic scenarios , 2004 .

[21]  D. Tilman,et al.  Global food demand and the sustainable intensification of agriculture , 2011, Proceedings of the National Academy of Sciences.

[22]  Zhengwei Yang,et al.  CropScape: A Web service based application for exploring and disseminating US conterminous geospatial cropland data products for decision support , 2012 .

[23]  Brian Youngblood,et al.  GeoServer Beginner’s Guide , 2013 .

[24]  Andrew P. Morse,et al.  DEVELOPMENT OF A EUROPEAN MULTIMODEL ENSEMBLE SYSTEM FOR SEASONAL-TO-INTERANNUAL PREDICTION (DEMETER) , 2004 .

[25]  Stefan Steiniger,et al.  Free and Open Source GIS Software for Building a Spatial Data Infrastructure , 2009, OGRS.

[26]  Francisco J. Doblas-Reyes,et al.  Medium-Range, Monthly, and Seasonal Prediction for Europe and the Use of Forecast Information , 2006 .

[27]  C. R. de Souza Filho,et al.  ASTER and Landsat ETM+ images applied to sugarcane yield forecast , 2006 .

[28]  W. Verhoef,et al.  PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .

[29]  Hongliang Fang,et al.  Corn‐yield estimation through assimilation of remotely sensed data into the CSM‐CERES‐Maize model , 2008 .

[30]  Qingguo Zhou,et al.  Assimilating remote sensing information into a coupled hydrology-crop growth model to estimate regional maize yield in arid regions , 2014 .

[31]  Shirley Gregor,et al.  Intelligent support systems in agriculture: how can we do better? , 2000 .

[32]  A. Bondeau,et al.  Combining agricultural crop models and satellite observations: from field to regional scales , 1998 .

[33]  C. Justice,et al.  A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data , 2010 .

[34]  James W. Jones,et al.  Potential benefits of climate forecasting to agriculture , 2000 .

[35]  T. Lynch,et al.  Success and failure of decision support systems: Learning as we go , 2000 .

[36]  Patrizia Busato,et al.  A web-based tool for biomass production systems , 2014 .

[37]  Roy Fielding,et al.  Architectural Styles and the Design of Network-based Software Architectures"; Doctoral dissertation , 2000 .

[38]  Carlos J. Fernandez,et al.  Development of a Web‐Based Decision Support System For Crop Managers:Structural Considerations and Implementation Case , 2007 .