Refine
Document Type
- Article (1)
- Master's Thesis (1)
Language
- English (2)
Has Fulltext
- yes (2)
Keywords
- Ernte (2) (remove)
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.
The increase in greenhouse gas emissions, mainly due to the burning of fossil fuels and land use change, has led to changes in the global climate. Agriculture is one of the economic sectors most vulnerable to the impacts generated by climate change. For this reason, the challenge facing humanity today is to develop innovative solutions to address the complexity of agricultural sustainability.
On the other hand, sugarcane is one of the crops that emits the most pollutants into the atmosphere, mainly due to the burning of sugarcane before and after harvesting. Most of these atmospheric pollutants are precursors of climate change and have an impact on the health and quality of life of communities. Moreover, this agricultural practice causes the gradual deterioration of the soil, directly affecting sugarcane production. Consequently, several sugarcane-producing countries have established regulations or dispositions to eliminate this agricultural practice, and one option to eliminate it is the mechanization of harvesting. However, its implementation implies social, environmental, and economic impacts that must be analyzed systemically to avoid potential failures during the technological transition process. It is for this reason that this research, through the MICMAC method, focused on identifying the variables associated with the reduction of sugarcane burning in Campos dos Goytacazes and Tamasopo, to subsequently analyze their direct and indirect interrelationship, and, thus, determine the opportunities and limitations of each locality for the reduction of sugarcane burning.
Through this analysis, it became evident that although the technological transition is an imminent step for the sustainability of sugarcane cultivation, certain factors such as legislation, technological innovation, and the perception of the stakeholders regarding the consequences of sugarcane burning, is what defines in the study sites the speed and subsequent success of this process of change towards green harvesting.