List of Articles Scalable

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  1 - A scalable physical model based on remote sensing in paddy yield estimation
  Ehsan Asmar Mohammad H. Vahidnia Mojtaba Rezaei Ebrahim Amiri
  Background and Objective: Rice is one of the most strategic plants in Iran. On the other hand, agriculture makes a wide variety of environmental amenities and problems. Thus researches that help the production and sustainable development in this area are significant. Th More

  Background and Objective: Rice is one of the most strategic plants in Iran. On the other hand, agriculture makes a wide variety of environmental amenities and problems. Thus researches that help the production and sustainable development in this area are significant. The main purpose of this research is the design and development of a scalable remote sensing-based paddy yield model.Material and Methodology: In this study, we used several different images available in Google Earth Engine (GEE) to estimate paddy yield at various temporal (growing seasons) and spatial scales (from 30 m resolution to regional scales). Then, a remote sensing-based light use efficiency (LUE) model integrated with inanimate environmental stressors, was implemented. This operational model was assessed against actual field-level yield data in 2016, 2017, and 2019 growing seasons across more than 691 paddy fields in Gilan province.The efficiency of the current model was evaluated through different statistical measures. The results showed a positive correlation and a signed agreement between the estimated and measured values so that in the studied growing seasons, the average correlation coefficient (R) and agreement index (d) was equal to 0.55. The average RMSE equal to 500 kg/ha, the average MAE equal to 440 kg/ha, and the average NRMSE equal to 0.12, all indicate that the accuracy of the model in estimating crop yield in these locations and years is satisfactory. Also, the submitted model showed the appropriate variability of yield values at the farm scale.Discussion and conclusion: In general, this new approach has confirmed that the use of remote sensing in the GEE is appropriate for estimating crop yield at various temporal and spatial scales, as the current model can be utilized in a wide range of applications such as agricultural management and insurance.   Manuscript profile
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  2 - Matching of Remote Sensing Images Using Improved SURF Detector and Direction-Invariant BRISK Descriptor in the Simulator Environment of Affine Transform Functions
  Fatemeh Khalili Farbod Razzazi Abolfazl Hosseini
  Remote sensing images are often captured by a variety of sensors at different times and with various deviation angles. This makes the matching procedure of image pairs be a challenge. To solve this problem, some algorithms have been proposed to improve this matching. On More

  Remote sensing images are often captured by a variety of sensors at different times and with various deviation angles. This makes the matching procedure of image pairs be a challenge. To solve this problem, some algorithms have been proposed to improve this matching. One of the most popular methods is SURF (Speedup robust features) algorithm, which is somewhat resistant to scale changes, rotation of images, brightness variation, and noise. In addition, the algorithm is suitable for the image deviation angles up to 45 degrees. However, the overlap and proximity of the extracted key points in this algorithm are high and it does not provide a suitable spatial distribution for the key points. This study is looking for a method that is resistant to the changes of affine transformation parameters. We use an IMAS (Image matching by affine simulation) simulator environment, which offers a suitable distribution of key points and can be considered as a solution to more angle differences than SURF. A morphology filter is used to find the boundaries and the edges with more clarity in the images. To reveal the key points, the images centers of mass are employed, which address the main direction of feature points and describe the invariable rotation. In addition, RBRISK (Rotation invariant binary robust invariant scalable key point) descriptor is employed in the algorithm which is temporally stable. The results of the experiments show that the proposed method improved the matching rate in satellite images by about 10% with suitable computational complexity. Manuscript profile