Preface: Recent Advances in Remote Sensing for Crop Growth Monitoring

Cheng, Tao; Yang, Zhengwei; Inoue, Yoshio; Zhu, Yan; Cao, Weixing

doi:10.3390/rs8020116

Cited by 17 publications

(19 citation statements)

References 16 publications

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“…In recent decades, advances in technology and algorithms have allowed remote sensing to play an important role in crop monitoring [1,2], which relies on continuous and dense time series. However, the cloud detection and optimization are reported as the main issues in the NASA's harmonized product [11].…”

Section: Introductionmentioning

confidence: 99%

Harmonization of Landsat and Sentinel 2 for Crop Monitoring in Drought Prone Areas: Case Studies of Ninh Thuan (Vietnam) and Bekaa (Lebanon)

Nguyen

Baez-Villanueva

Bui³

et al. 2020

Remote Sensing

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Proper satellite-based crop monitoring applications at the farm-level often require near-daily imagery at medium to high spatial resolution. The combination of data from different ongoing satellite missions Sentinel 2 (ESA) and Landsat 7/8 (NASA) provides this unprecedented opportunity at a global scale; however, this is rarely implemented because these procedures are data demanding and computationally intensive. This study developed a robust stream processing for the harmonization of Landsat 7, Landsat 8 and Sentinel 2 in the Google Earth Engine cloud platform, connecting the benefit of coherent data structure, built-in functions and computational power in the Google Cloud. The harmonized surface reflectance images were generated for two agricultural schemes in Bekaa (Lebanon) and Ninh Thuan (Vietnam) during 2018–2019. We evaluated the performance of several pre-processing steps needed for the harmonization including the image co-registration, Bidirectional Reflectance Distribution Functions correction, topographic correction, and band adjustment. We found that the misregistration between Landsat 8 and Sentinel 2 images varied from 10 m in Ninh Thuan (Vietnam) to 32 m in Bekaa (Lebanon), and posed a great impact on the quality of the final harmonized data set if not treated. Analysis of a pair of overlapped L8-S2 images over the Bekaa region showed that, after the harmonization, all band-to-band spatial correlations were greatly improved. Finally, we demonstrated an application of the dense harmonized data set for crop mapping and monitoring. An harmonic (Fourier) analysis was applied to fit the detected unimodal, bimodal and trimodal shapes in the temporal NDVI patterns during one crop year in Ninh Thuan province. The derived phase and amplitude values of the crop cycles were combined with max-NDVI as an R-G-B false composite image. The final image was able to highlight croplands in bright colors (high phase and amplitude), while the non-crop areas were shown with grey/dark (low phase and amplitude). The harmonized data sets (with 30 m spatial resolution) along with the Google Earth Engine scripts used are provided for public use.

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Section: Introductionmentioning

confidence: 99%

Harmonization of Landsat and Sentinel 2 for Crop Monitoring in Drought Prone Areas: Case Studies of Ninh Thuan (Vietnam) and Bekaa (Lebanon)

Nguyen

Baez-Villanueva

Bui³

et al. 2020

Remote Sensing

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“…However, a number of limitations associated with satellite imagery, the conventional remote sensing resource, has restricted its application and usage in such regions as SSA. These limitations include significant cloud cover, the complex and heterogeneous nature of farming systems, poor and unavailable crop yield databases, as well as the generally coarse spatial and temporal resolutions of most readily available satellite imagery vis-à-vis farm plot sizes [19][20][21][22]. Thus, while satellite remote sensing has been successfully implemented in monitoring crop status and predicting yields in more developed and homogeneous farming systems, its application in SSA has been largely restricted due to these limitations.…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing of Yields: Application of UAV Imagery-Derived NDVI for Estimating Maize Vigor and Yields in Complex Farming Systems in Sub-Saharan Africa

Wahab

Hall

Jirström

2018

Drones

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The application of remote sensing methods to assess crop vigor and yields has had limited applications in Sub-Saharan Africa (SSA) due largely to limitations associated with satellite images. The increasing use of unmanned aerial vehicles in recent times opens up new possibilities for remotely sensing crop status and yields even on complex smallholder farms. This study demonstrates the applicability of a vegetation index derived from UAV imagery to assess maize (Zea mays L.) crop vigor and yields at various stages of crop growth. The study employs a quadcopter flown at 100 m over farm plots and equipped with two consumer-grade cameras, one of which is modified to capture images in the near infrared. We find that UAV-derived GNDVI is a better indicator of crop vigor and a better estimator of yields—r = 0.372 and r = 0.393 for mean and maximum GNDVI respectively at about five weeks after planting compared to in-field methods like SPAD readings at the same stage (r = 0.259). Our study therefore demonstrates that GNDVI derived from UAV imagery is a reliable and timeous predictor of crop vigor and yields and that this is applicable even in complex smallholder farms in SSA.

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“…The growth status is generally assessed by measuring the changes of leaf area, leaf color, leaf inclination angle, plant height, density, and stem diameter [1]. At different growth stages, crop growth rate and condition will be different [2]. Even at the same growth stage, the same crop type can exhibit different growth conditions due to differences in soil property, water supply, incoming radiation, temperature, pest/disease, and land management practices [3].…”

Section: Introductionmentioning

confidence: 99%

“…Although this method can be accurate, it is time-consuming, costly, and limited in area of survey. In recent years, with the fast development of geospatial science and technology, remote sensing technologies were increasingly applied to monitoring crop growth conditions [2,4,5]. Remote sensing technologies have the advantages of imaging large areas repeatedly at a reasonable cost.…”

Section: Introductionmentioning

confidence: 99%

Bibliometric Analysis of Remote Sensing Research Trend in Crop Growth Monitoring: A Case Study in China

et al. 2019

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Remote sensing of crop growth monitoring is an important technique to guide agricultural production. To gain a comprehensive understanding of historical progression and current status, and future trend of remote sensing researches and applications in the field of crop growth monitoring in China, a study was carried out based on the publications from the past 20 years by Chinese scholars. Using the knowledge mapping software CiteSpace, a quantitative and qualitative analysis of research development, current hotspots, and future directions of crop growth monitoring using remote sensing technology in China was conducted. Furthermore, the relationship between high-frequency keywords and the emerging hot topics were visually analyzed. The results revealed that Chinese researchers paid more attention on keywords such as “vegetation index”, “crop growth”, “winter wheat”, “leaf area index (LAI)”, and “model” in the field of crop growth monitoring, and “LAI” and “unmanned aerial vehicle (UAV)”, appeared increasingly in frontier research of this discipline. Overall, bibliometric results from this CiteSpace-aided study provide a quantitative visualization to enrich our understanding on the historical development, current status, and future trend of crop growth monitoring in China.

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Preface: Recent Advances in Remote Sensing for Crop Growth Monitoring

Cited by 17 publications

References 16 publications

Harmonization of Landsat and Sentinel 2 for Crop Monitoring in Drought Prone Areas: Case Studies of Ninh Thuan (Vietnam) and Bekaa (Lebanon)

Harmonization of Landsat and Sentinel 2 for Crop Monitoring in Drought Prone Areas: Case Studies of Ninh Thuan (Vietnam) and Bekaa (Lebanon)

Remote Sensing of Yields: Application of UAV Imagery-Derived NDVI for Estimating Maize Vigor and Yields in Complex Farming Systems in Sub-Saharan Africa

Bibliometric Analysis of Remote Sensing Research Trend in Crop Growth Monitoring: A Case Study in China

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