Experimental Study on 3D Measurement Accuracy Detection of Low Altitude UAV for Repeated Observation of an Invariant Surface

Low-altitude unmanned aerial vehicle (UAV) photogrammetry combined with structure-from-motion (SFM) algorithms is the latest technological approach to imaging 3D stereo constructions. At present, derivative products have been widely used in landslide monitoring, landscape evolution, glacier movement, volume measurement, and landscape change detection. However, there is still a lack of research into the accuracy of 3D data positioning based on the structure-from-motion of unmanned aerial vehicle (UAV-SFM) technology, itself, which can affect the measurable effectiveness of the results in further applications of this technological approach. In this paper, validation work was carried out for the DJI Phantom 4 RTK UAV, for earth observation data related to 3D positioning accuracy. First, a test plot with a relatively stable surface was selected for repeated flight imaging observations. Specifically, three repeated flights were performed on the test plot to obtain three sorties of images; the structure from motion and multi-view stereo (SFM-MVS) key technology was used to process and construct a 3D scene model, and based on this model the digital surface model (DSM) and digital orthophoto map (DOM) data of the same plot with repeated observations were obtained. In order to check the level of 3D measurement accuracy of the UAV technology itself, a window selection-based method was used to sample the point cloud set data from the three-sortie repeat observation 3D model. The DSM and DOM data obtained from three repeated flights over the surface invariant test plots were used to calculate the repeat observation 3D point errors, taking into account the general methodology of redundant observation error analysis for topographic surveys. At the same time, to further analyze the limits of the UAV measurement technique, possible under equivalent observation conditions with the same processing environment, a difference model (DOD) was constructed for the DSM data from three sorties, to deepen the overall characterization of the differences between the DSMs obtained from repeated observations. The results of the experimental study concluded that both the analysis of the 3D point set measurements based on window sampling and the accuracy evaluation using the difference model were generally able to achieve a centimeter level of planimetric accuracy and vertical accuracy. In addition, the accuracy of the surface-stabilized hardened ground was better, overall, than the accuracy of the non-hardened ground. The results of this paper not only probe the measurement limits of this type of UAV, but also provide a quantitative reference for the accurate control and setting of an acquisition scheme of the UAV-based SfM-MVS method for geomorphological data acquisition and 3D reconstruction.

Early Estimation of Olive Production from Light Drone Orthophoto, through Canopy Radius

Background: The present work aims at obtaining an approximate early production estimate of olive orchards used for extra virgin olive oil production by combining image analysis techniques with light drone images acquisition and photogrammetric reconstruction. Methods: In May 2019, an orthophoto was reconstructed through a flight over an olive grove to predict oil production from segmentation of plant canopy surfaces. The orchard was divided into four plots (three considered as training plots and one considered as a test plot). For each olive tree of the considered plot, the leaf surface was assessed by segmenting the orthophoto and counting the pixels belonging to the canopy. At harvesting, the olive production per plant was measured. The canopy radius of the plant (R) was automatically obtained from the pixel classification and the measured production was plotted as a function of R. Results: After applying a k-means-classification to the four plots, two distinct subsets emerged in association with the year of loading (high-production) and unloading. For each plot of the training set the logarithm of the production curves against R were fitted with a linear function considering only four samples (two samples belonging to the loading region and two samples belonging to the unloading one) and the total production estimate was obtained by integrating the exponent of the fitting-curve over R. The three fitting curves obtained were used to estimate the total production of the test plot. The resulting estimate of the total production deviates from the real one by less than 12% in training and less than 18% in tests. Conclusions: The early estimation of the total production based on R extracted by the orthophotos can allow the design of an anti-fraud protocol on the declared production.

Fixed-time corrective dose fertilizer nitrogen management in wheat using atLeaf meter and leaf colour chart

Fertilizer nitrogen (N) management in any region following standard general recommendations discount the fact that crop response to N varies between sites and seasons. To devise field-specific N management in wheat at jointing stage (Feekes 6 growth stage) using atLeaf meter and leaf colour chart (LCC), eight field experiments were conducted in three wheat seasons during 2017–2020 in the West Delta of Egypt. In the first two seasons, four experiments consisted of treatments with a range of fertilizer N application levels from 0 to 320 kg N ha−1. Monitoring atLeaf and LCC measurements at Feekes 6 growth stage in plots with different yield potentials allowed formulation of different criteria to apply field-specific and crop need-based fertilizer N doses. In the four experiments conducted in the third season in 2019/20, different field-specific N management strategies formulated in 2017/18 and 2018/19 wheat seasons were evaluated. In the atLeaf-based fertilizer N management experiment, prescriptive application of 40 kg N ha−1 at 10 days after seeding (DAS) and 60 kg N ha−1 at 30 DAS followed by application of an adjustable dose at Feekes 6 stage computed by multiplying the difference of atLeaf measurements of the test plot and the N-sufficient plot with 42.25 (as derived from the functional model developed in this study), resulted in grain yield similar or higher to that obtained by following the standard treatment. The LCC-based strategy to apply field-specific fertilizer N at Feekes 6 stage consisted of applying 150, 100 or 0 kg N ha−1 based on LCC shade equal to or less than 4, between 4 and 5 or equal to or more than 5, respectively. Both atLeaf- and LCC-based fertilizer N management strategies not only recorded the highest grain yield levels but also resulted in higher use efficiency with 57–60 kg N ha−1 in average less fertilizer use than the standard treatment.

Spatial and temporal variance of soil and meteorological properties affecting sensor performance—Phase 2

An approach to increasing sensor performance and detection reliability for buried objects is to better understand which physical processes are dominant under certain environmental conditions. The present effort (Phase 2) builds on our previously published prior effort (Phase 1), which examined methods of determining the probability of detection and false alarm rates using thermal infrared for buried-object detection. The study utilized a 3.05 × 3.05 m test plot in Hanover, New Hampshire. Unlike Phase 1, the current effort involved removing the soil from the test plot area, homogenizing the material, then reapplying it into eight discrete layers along with buried sensors and objects representing targets of inter-est. Each layer was compacted to a uniform density consistent with the background undisturbed density. Homogenization greatly reduced the microscale soil temperature variability, simplifying data analysis. The Phase 2 study spanned May–November 2018. Simultaneous measurements of soil temperature and moisture (as well as air temperature and humidity, cloud cover, and incoming solar radiation) were obtained daily and recorded at 15-minute intervals and coupled with thermal infrared and electro-optical image collection at 5-minute intervals.

EVALUASI PERTUMBUHAN TANAMAN UJI KETURUNAN MERANTI MERAH (Shorea leprosula) UMUR 12 TAHUN DI AREAL IUPHHK-HA PT. ERNA DJULIAWATI KALIMANTAN TENGAH

Red meranti (Shorea leprosula) is one of the superior plants in the application of intensive silviculture (SILIN). As a superior plant, PT. Erna Djuliawati has conducted a progeny test for S. leprosula in the IUPHHK-HA area in Central Kalimantan. The aim of this research was to determine the superior seedlot and genetic growth variation of the S. leprosula in the progeny test plot. The object studied was the 30 seedlots of S. leprosula plants in progeny test plot consists divided into 8 blocks, where each seedlot was 4 plants. The data collected consisted of diameter (cm), tree height (m) and percentage of tree life. The results showed that in the progeny test trial plot there were 5 seedlots with superior growth. The results of the analysis of variance on diameter, height and percentage showed a significant difference between the tested seedlots to the properties measured. High heritability values followed by wide genetic diversity indicate that the appearance of these characters is more determined by genetic factors. The value of moderate diameter genetic progress (8.6%) indicates that the diameter character is supported by genetic factors, so that it can facilitate the progress of selection.Keywords : Progeny test, Shorea leprosula, superior dan genetic variation. AbstrakMeranti merah (Shorea leprosula) merupakan salah satu jenis tanaman unggulan dalam penerapan Silvikultur Intensif (SILIN). Sebagai tanaman unggulan, PT. Erna Djuliawati telah melakukan uji keturuan S. leprosula dalam areal IUPHHK-HA di Kalimantan Tengah. Tujuan penelitian ingin menentukan seedlot yang unggul dan variasi pertumbuhan genetik tanaman uji keturunan S. leprosula dalam plot uji keturunan. Objek yang diteliti adalah tanaman meranti merah dalam plot uji keturunan sebanyak 30 seedlot yang terbagi dalam 8 blok, dimana setiap seedlot sebanyak 4 tanaman. Data yang dikumpulkan terdiri dari diameter (cm), tinggi pohon (m) dan pesentase hidup pohon. Hasil penelitian menunjukkan bahwa dalam plot uji coba keturunan terdapat 5 seedlot yang unggul pertumbuhannya. Hasil analisis keragaman (varians) terhadap diameter, tinggi dan persentase menunjukkan adanya perbedaan yang nyata di antara seedlot yang diuji terhadap sifat yang diukur. Nilai heritabilitas yang tinggi diikuti dengan keragaman genetik yang luas menunjukkan penampilan karakter tersebut lebih ditentukan oleh faktor genetik. Nilai kemajuan genetik diameter sedang (8,6 %) mengindikasikan karakter diameter tersebut didukung oleh faktor genetik, sehingga dapat memfasilitasi kemajuan seleksi.Kata kunci : Uji Keturunan, S. leprosula, unggul, dan variasi genetik.

Measurement of water equivalent, average density and height of layered snow cover using UWB electromagnetic pulses.

In this work, the processes of interaction of ultra-wideband (UWB) pulses with the duration of 0.47 ns with layered dry snow cover are theoretically investigated. The layered structure of the snow cover was modeled on the basis of experimental data on the height and density profile of the snow cover, which were measured in field on the test plot of an agricultural field in the area of the village. Minino, Krasnoyarsk Territory from November 12, 2020 to March 21, 2021. It is shown that the snow water equivalent (SWE) can be estimated from the time delay of the pulse reflected from the snow-soil interface with the coefficient of determination (R2) R2 = 0.98 and the root-mean-square error (RMSE) RMSE = 5.6 mm in the case of thickness from 4-6 to 39cm and an average density from 0.21 to 0.37 g/cm3 of snow cover. It is shown that the average density of snow cover linearly depends on the amplitude ratio of impulses reflected from the boundaries, snow-soil and air-snow (R2 = 0.55, RMSE = 0.04 g/cm3). The established dependencies make it possible to estimate the height of the snow cover with R2 = 0.95, RMSE = 2.9 cm. The accuracy of the proposed method for measuring SWE, average density and height of snow cover should be further investigated depending on variations in temperature, moisture, density, and texture of frozen soil, as well as under different moisturized conditions of snow. The obtained results are particular relevance in connection with the possibility of implementing this remote sensing method from the UAV, which opens up the prospects for creating a technology for UWB radar mapping of the main characteristics of the snow cover for use in precision farming systems.

ANALISIS PENGARUH CR DAN ROE TERHADAP PER PADA PT. INDOFOOD SUKSES MAKMUR TBK TAHUN 2011-2018

PER is an important ratio in analyzing stocks, research was conducted at PT. Indofood Sukses Makmur Tbk by using two ratios as analysis tools, namely CR and ROE. The author chooses to conduct research at PT. Indofood Sukses Makmur Tbk because it is the largest consumer food company compared to its peers in Indonesia. This research was conducted to see the effect of CR and ROE simultaneously, partially and dominantly on PER using quantitative descriptive methods. The results showed that the data used were normal using the normal probability test plot. If using multiple linear regression test, the CR has a unidirectional relationship, while the ROE is not in the same direction as the PER. The results of hypothesis testing using the F test and t test. The F test states that the CR and ROE have a simultaneous effect and the t test partially affects the PER. To see how much influence the independent variable has on the dependent variable, a determination coefficient test is carried out with the result that the independent variable is quite influential on the dependent variable by 79.5%, and finally the dominant test with the results of ROE which has the most influence on the PER

Promotion of Growth, Chlorophyll Content and Yield of Rice by a New Drug at Ultra High Dilution

Application of synthetic fertilizers reduces natural fertility of soil and contaminates ground water. Some photosynthesis inhibitors at ultra-high dilution (UHD) increase photosynthesis, growth and yield of crops. A weedicide Paraquat at UHD enhanced growth and yield of potatoes in fields. This weedicide was serially diluted with distilled water and manually succussed in 30 steps following the method of preparation of homeopathic dilutions called potencies. In this way the 30th potency of Paraquat called Paraquat 30cH was prepared and preserved in 90 % ethanol. Paraquat 30cH was diluted with water 1:1000 (v/v) and sprayed on rice plants in a field measuring 0.3125 acre. The control plot of the same area was situated 300 meters away from the test plot. Three treatments were given at an interval of 7 days. Treated plot showed increased growth, chlorophyll content and yield of rice significantly as compared to control. The UHD of the weedicide produced exactly the opposite effect of the crude material on plants. The increased growth and yield of rice by Paraquat 30cH may be due to enhancement of photosynthesis of treated plants. The UHD of Paraquat increased yield of rice by 19.35% over the control.

ЭНТРОПИЯ АБИОТИЧЕСКИХ ГЕОСФЕР И МОДЕЛЬ ДЛЯ ОЦЕНКИ И ПРОГНОЗА ИХ СОСТОЯНИЯ

It has been shown in the present work that the methods used to sum up the coefficients of concentrations (hazards) of different pollutants in the abiotic geospheres are not additive and therefore cannot be universal. Universal is the entropic model developed for the biological structures. However, the classic definition of entropy is not appropriate for the abiotic structures because it comprises both stochastic and deterministic components. In the present work, a novel formula for calculating entropy of abiotic structures based on the environmental risk is proposed and an entropic model for assessing the environmental stability of such structures has been constructed for forecasting their development. The model has been tested by comparing the results of assessing the conditions of a test plot according to the entropic and the classic methodology. The classing one being non-additive yields somewhat overrated rank estimates. The entropic methodology makes it possible to forecast the ecological conditions of the test plot.

Intelligent evaluation of trade efficiency of agricultural products between China and ASEAN: An stochastic frontier approach with noise reduction

As the world’s largest free trade area among developing countries, the China-ASEAN Free Trade Area has gone through 15 years, and the China-ASEAN (Association of Southeast Asian Nations) Free Trade Area cooperation framework with tariff reduction as the core has diminished incentive effects on regional trade, the “21st Century Maritime Silk Road” strategy provide new opportunities for the upgrading and development of the China-ASEAN Free Trade Area. Based on the stochastic frontier gravity model, the random disturbance term was introduced to overcome the inevitable noise problem of macro statistical data, the trade efficiency of agricultural products between China and ASEAN were estimated in this study. The result shows that the potential for trade promotion between China and ASEAN countries is fully tapped. Based on this, it is proposed to strengthen infrastructure construction and smooth maritime trade channels with the help of the “One Road” platform. Strengthen communication and dialogue to weaken the impact of non-tariff barriers on trade, and use the Shanghai Free Trade Zone test plot to enhance the international competitiveness of Chinese agricultural product trade.