Recent Advances in Remote Sensing for Crop Growth Monitoring by Tao ChengRecent Advances in Remote Sensing for Crop Growth Monitoring by Tao Cheng

Recent Advances in Remote Sensing for Crop Growth Monitoring

EditorTao Cheng

Hardcover | August 19, 2016

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This special issue book gathers sixteen papers focusing on the application of remote sensing techniques to crop growth monitoring. The studies feature multi-scale and multi-source remotely sensed data, a combination of empirical and physical approaches, and a range of topics on crop growth parameters estimation and crop mapping. It is recommended to graduate students, professors, scientists and engineers who have broad interests in the agricultural applications of remote sensing.

Title:Recent Advances in Remote Sensing for Crop Growth MonitoringFormat:HardcoverDimensions:406 pages, 9.61 × 6.69 × 1.25 inPublished:August 19, 2016Publisher:MDPI AGLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3038422266

ISBN - 13:9783038422266

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Table of Contents

(1) Quantitative Estimation of Fluorescence Parameters for Crop Leaves with Bayesian Inversion(2) Evaluation of Six Algorithms to Monitor Wheat Leaf Nitrogen Concentration(3) Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan(4) Satellite Remote Sensing-Based In-Season Diagnosis of Rice Nitrogen Status in Northeast China(5) Temporal Dependency of Yield and Quality Estimation through Spectral Vegetation Indices in Pear Orchards(6) Comparison of NDVIs from GOCI and MODIS Data towards Improved Assessment of Crop Temporal Dynamics in the Case of Paddy Rice(7) Exploring the Vertical Distribution of Structural Parameters and Light Radiation in Rice Canopies by the Coupling Model and Remote Sensing(8) The Impact of Sunlight Conditions on the Consistency of Vegetation Indices in Croplands-Effective Usage of Vegetation Indices from Continuous Ground-Based Spectral Measurements(9) Monitoring Spatio-Temporal Distribution of Rice Planting Area in the Yangtze River Delta Region Using MODIS Images(10) Rice Fields Mapping in Fragmented Area Using Multi-Temporal HJ-1A/B CCD Images(11) A Hidden Markov Models Approach for Crop Classification: Linking Crop Phenology to Time Series of Multi-Sensor Remote Sensing Data(12) MODIS-Based Fractional Crop Mapping in the U.S. Midwest with Spatially Constrained Phenological Mixture Analysis(13) Feature Selection of Time Series MODIS Data for Early Crop Classification Using Random Forest: A Case Study in Kansas, USA(14) In-Season Mapping of Crop Type with Optical and X-Band SAR Data: A Classification Tree Approach Using Synoptic Seasonal Features(15) Rapid Assessment of Crop Status: An Application of MODIS and SAR Data to Rice Areas in Leyte, Philippines Affected by Typhoon Haiyan(16) Mapping of Daily Mean Air Temperature in Agricultural Regions Using Daytime and Nighttime Land Surface Temperatures Derived from TERRA and AQUA MODIS Data