Integrating Vegetation Indices Models and Phenological Classification with Composite SAR and Optical Data for Cereal Yield Estimation in Finland (Part I)

Abstract

During 1996-2006 the Ministry of Agriculture and Forestry in Finland, MTT Agrifood Research Finland and the Finnish Geodetic Institute carried out a joint remote sensing satellite research project. It evaluated the applicability of composite multispectral SAR and optical satellite data for cereal yield estimations in the annual crop inventory program. Three Vegetation Indices models (VGI, Infrared polynomial, NDVI and Composite multispectral SAR and NDVI) were validated to estimate cereal yield levels using solely optical and SAR satellite data (Composite Minimum Dataset). The average R 2 for cereal yield (y b ) was 0.627. The averaged composite SAR modeled grain yield level was 3,750 kg/ha (RMSE = 10.3%, 387 kg/ha) for high latitude spring cereals (4,018 kg/ha for spring wheat, 4,037 kg/ha for barley and 3,151 kg/ha for oats).

Cereal Yield Modeling in Finland Using Optical and Radar Remote Sensing

“…The System Analysis overview is reviewed in a recent publication by Laurila et al [37] and in [38][39][40][41]. Respectively, the Integrated LAI-bridge coupling mechanism applied in this publication is depicted in Figure 1 [19,21] between phenologically pre-classified optical data (GEMI model III, Table 1) and dynamic crop model (Model V, CropWatN, [29,31] -ap, bp, cp, dp classes correspond on average to Zadoks crop phenological growth scale with cereals:…”

“…Composite SAR/ASAR and NDVI [37] 6) yb = NDVI (ap, bp, cp ) + σ 0 HH5GHz, (ap, bp, cp, dp) + σ 0 VV5GHz , (ap, bp, cp, dp) + σ 0 HV5GHz, (ap, bp, cp, dp) + σ 0 VH5GHz, (ap, bp, cp, dp) NDVI ( ap,bp,cp ), σ 0 5GHz ( ap,bp,cp, dp)…”

“…Composite multispectral SAR/ASAR and NDVI model for spring cereals (swh, oats, barley) using NDVI reflectance and microwave backscattering (σ 0 , f = 5.4 GHz) data (Table 12, [37]). Used only in validation of the optical VGI models 6) 1) Equations applied after REG/Stepwise for linear models (Equation 1, Table 10, Appendix B [51,52]) and RSREG for polynomial non-linear models (Equation 2, Table 10, Appendix B) 2) Independent variables classified with SatPhenClass-algorithm.…”

“…In a recent publication by Laurila et al [37], spring cereal yield modeling results were presented for Finnish high latitude growing conditions using multispectral composite SAR backscattering and NDVI data (Composite Minimum Dataset). Cereal maximum yield capacity is limited by environmental (e.g., drought periods) and vegetation stresses (e.g., nutrient deficiencies, pathogen epidemics) during growing season.…”

A comparative ideotype, yield component and cultivation value analysis for spring wheat adaptation in Finland

“…Dataset III provided the baseline yield (y b kg ha -1 ) estimates for HiL and MidE spring wheat cultivars using the Finnish agricultural remote sensing large area results in 1996−2006 (Laurila et al 2010a(Laurila et al , 2010b. Experimental sites were located in southern Finland and in Etelä-Pohjanmaa Agricultural Advisory Centre in growing zones I−IV.…”