Preface: Recent Advances in Remote Sensing for Crop Growth Monitoring

This Special Issue gathers sixteen papers focusing on applying various remote sensing techniques to crop growth monitoring. The studies span observations from multiple scales, a combination of model simulations and experimental measurements, and a range of topics on crop monitoring and mapping. This preface provides a brief overview of the contributed papers.

[1]  Kazuaki Yoshida,et al.  Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan , 2015, Remote. Sens..

[2]  Yoshio Inoue,et al.  The Impact of Sunlight Conditions on the Consistency of Vegetation Indices in Croplands - Effective Usage of Vegetation Indices from Continuous Ground-Based Spectral Measurements , 2015, Remote. Sens..

[3]  Li Wang,et al.  Feature Selection of Time Series MODIS Data for Early Crop Classification Using Random Forest: A Case Study in Kansas, USA , 2015, Remote. Sens..

[4]  Jing Wang,et al.  Rice Fields Mapping in Fragmented Area Using Multi-Temporal HJ-1A/B CCD Images , 2015, Remote. Sens..

[5]  Cuizhen Wang,et al.  MODIS-Based Fractional Crop Mapping in the U.S. Midwest with Spatially Constrained Phenological Mixture Analysis , 2015, Remote. Sens..

[6]  Jia Liu,et al.  Mapping of Daily Mean Air Temperature in Agricultural Regions Using Daytime and Nighttime Land Surface Temperatures Derived from TERRA and AQUA MODIS Data , 2015, Remote. Sens..

[7]  Giorgos Mallinis,et al.  A Hidden Markov Models Approach for Crop Classification: Linking Crop Phenology to Time Series of Multi-Sensor Remote Sensing Data , 2015, Remote. Sens..

[8]  Lorenzo Busetto,et al.  Rapid Assessment of Crop Status: An Application of MODIS and SAR Data to Rice Areas in Leyte, Philippines Affected by Typhoon Haiyan , 2015, Remote. Sens..

[9]  Laurent Tits,et al.  Temporal Dependency of Yield and Quality Estimation through Spectral Vegetation Indices in Pear Orchards , 2015, Remote. Sens..

[10]  Jingjing Shi,et al.  Monitoring Spatio-Temporal Distribution of Rice Planting Area in the Yangtze River Delta Region Using MODIS Images , 2015, Remote. Sens..

[11]  Jong-Min Yeom,et al.  Comparison of NDVIs from GOCI and MODIS Data towards Improved Assessment of Crop Temporal Dynamics in the Case of Paddy Rice , 2015, Remote. Sens..

[12]  Fei Yuan,et al.  Satellite Remote Sensing-Based In-Season Diagnosis of Rice Nitrogen Status in Northeast China , 2015, Remote. Sens..

[13]  Bo Dai,et al.  Quantitative Estimation of Fluorescence Parameters for Crop Leaves with Bayesian Inversion , 2015, Remote. Sens..

[14]  Giacomo Fontanelli,et al.  In-Season Mapping of Crop Type with Optical and X-Band SAR Data: A Classification Tree Approach Using Synoptic Seasonal Features , 2015, Remote. Sens..

[15]  Ling Zhang,et al.  Exploring the Vertical Distribution of Structural Parameters and Light Radiation in Rice Canopies by the Coupling Model and Remote Sensing , 2015, Remote. Sens..

[16]  Yu Huang,et al.  Evaluation of Six Algorithms to Monitor Wheat Leaf Nitrogen Concentration , 2015, Remote. Sens..