scholarly journals Exploring the Potential of High Resolution WorldView-3 Imagery for Estimating Yield of Mango

2018 ◽  
Vol 10 (12) ◽  
pp. 1866 ◽  
Author(s):  
Muhammad Rahman ◽  
Andrew Robson ◽  
Mila Bristow
Keyword(s):  
High Resolution ◽  
Vegetation Indices ◽  
Sampling Technique ◽  
Fruit Yield ◽  
Ann Model ◽  
Tree Crown ◽  
Crown Area ◽  
Fruit Number ◽  
Growing Seasons ◽  
Yield Parameters

Pre-harvest yield estimation of mango fruit is important for the optimization of inputs and other resources on the farm. Current industry practice of visual counting the fruit on a small number of trees for yield forecasting can be highly inaccurate due to the spatial variability, especially if the trees selected do not represent the entire crop. Therefore, this study evaluated the potential of high resolution WorldView-3 (WV3) satellite imagery to estimate yield of mango by integrating both geometric (tree crown area) and optical (spectral vegetation indices) data using artificial neural network (ANN) model. WV3 images were acquired in 2016–2017 and 2017–2018 growing seasons at the early fruit stage from three orchards in Acacia Hills region, Northern Territory, Australia. Stratified sampling technique (SST) was applied to select 18 trees from each orchard and subsequently ground truthed for yield (kg·tree−1) and fruit number per tree. For each sampled tree, spectral reflectance data and tree crown area (TCA) was extracted from WV3 imagery. The TCA was identified as the most important predictor of both fruit yield (kg·tree−1) and fruit number, followed by NDVI red-edge band when all trees from three orchards in two growing seasons were combined. The results of all sampled trees from three orchards in two growing seasons using ANN model produced a strong correlation (R2 = 0.70 and 0.68 for total fruit yield (kg·tree−1) and fruit number respectively), which suggest that the model can be obtained to predict yield on a regional level. On orchard level also the ANN model produced a high correlation when both growing seasons were combined. However, the model developed in one season could not be applied in another season due to the influence of seasonal variation and canopy condition. Using the relationship derived from the measured yield parameters against combined VIs and TCA data, the total fruit yield (t·ha−1) and fruit number were estimated for each orchard, produced 7% under estimation to less than 1% over estimation. The accuracy of the findings showed the potential of WV3 imagery to better predict the yield parameters than the current practice across the mango industry as well as to quantify lost yield as a result of delayed harvest.

Estimating Tree Crown Area and Aboveground Biomass in Miombo Woodlands From High-Resolution RGB-Only Imagery

2018 ◽  
Vol 11 (3) ◽  
pp. 868-875 ◽  
Author(s):  
Herbet Tichaona Mareya ◽  
Paradzayi Tagwireyi ◽  
Henry Ndaimani ◽  
Tawanda Winmore Gara ◽  
David Gwenzi
Keyword(s):  
High Resolution ◽  
Aboveground Biomass ◽  
Miombo Woodlands ◽  
Tree Crown ◽  
Crown Area

scholarly journals Exploring the Potential of High Resolution Satellite Imagery for Yield Prediction of Avocado and Mango Crops

Proceedings ◽  
2020 ◽  
Vol 36 (1) ◽  
pp. 154
Author(s):  
Moshiur Rahman ◽  
Andrew Robson ◽  
Surantha Salgadoe ◽  
Kerry Walsh ◽  
Mila Bristow
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Vegetation Index ◽  
Mangifera Indica ◽  
Linear Regression Analysis ◽  
Vegetation Indices ◽  
Persea Americana ◽  
Yield Estimation ◽  
Yield Parameters ◽  
Normalised Difference Vegetation Index

Accurate pre-harvest yield estimation of high value fruit tree crops provides a range of benefits to industry and growers. Currently, yield estimation in Avocado (Persea americana) and Mango (Mangifera indica) orchards is undertaken by a visual count of a limited number of trees. However, this method is labour intensive and can be highly inaccurate if the sampled trees are not representative of the spatial variability occurring across the orchard. This study evaluated the accuracies of high resolution WorldView (WV) 2 and 3 satellite imagery and targeted field sampling for the pre-harvest prediction of yield. A stratified sampling technique was applied in each block to measure relevant yield parameters from eighteen sample trees representing high, medium and low vigour zones (6 from each) based on classified normalised difference vegetation index (NDVI) maps. For avocado crops, principal component analysis (PCA) and non-linear regression analysis were applied to 18 derived vegetation indices (VIs) to determine the index with the strongest relationship to the measured yield parameters. For mango, an integrated approach of geometric (tree crown area) and optical (spectral vegetation indices) data using artificial neural network (ANN) model produced more accurate predictions. The results demonstrate that accurate maps of yield variability and total orchard yield can be achieved from WV imagery and targeted sampling; whilst accurate maps of fruit size and the incidence of phytophthora can also be achieved in avocado. These outcomes offer improved forecasting than currently adopted practices and therefore offer great benefit to both the avocado and mango industries.

Evaluating satellite remote sensing as a method for measuring yield variability in Avocado and Macadamia tree crops

2017 ◽  
Vol 8 (2) ◽  
pp. 498-504 ◽  
Author(s):  
A. Robson ◽  
M. M. Rahman ◽  
J. Muir ◽  
A. Saint ◽  
C. Simpson ◽  
...  
Keyword(s):  
Satellite Remote Sensing ◽  
Vegetation Indices ◽  
Fruit Weight ◽  
Measured Parameter ◽  
Harvest Scheduling ◽  
Fruit Number ◽  
Yield Parameters ◽  
Commercial Yield ◽  
Selling Decisions ◽  
Very High

This paper evaluates the potential of very high resolution multispectral (Worldview-3) satellite imagery for mapping yield parameters in avocado and macadamia orchards. An evaluation of 18 structural and pigment based vegetation indices (VIs) derived from Worldview-3 imagery identified a positive relationship to nut/ fruit weight (kg/tree) R2>0.69 for macadamia and R2>0.68 for avocado; and nut/ fruit number (per tree) R2>0.6 for macadamia and R2>0.61 for avocado. Using the algorithms derived between the optimal VI and the measured parameter, yield and nut/ fruit number maps were derived for each block. In the absence of a commercial yield monitor, the resulting yield maps offer significant benefit to growers for improving orchard management, harvest scheduling, and forward selling decisions.

scholarly journals Forest Aboveground Biomass Estimation and Mapping through High-Resolution Optical Satellite Imagery—A Literature Review

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 914
Author(s):  
Adeel Ahmad ◽  
Hammad Gilani ◽  
Sajid Rashid Ahmad
Keyword(s):  
High Resolution ◽  
Literature Review ◽  
Satellite Imagery ◽  
Aboveground Biomass ◽  
Vegetation Indices ◽  
Biomass Estimation ◽  
Independent Variables ◽  
Non Linear ◽  
Multiple Variables ◽  
Forest Aboveground Biomass

This paper provides a comprehensive literature review on forest aboveground biomass (AGB) estimation and mapping through high-resolution optical satellite imagery (≤5 m spatial resolution). Based on the literature review, 44 peer-reviewed journal articles were published in 15 years (2004–2019). Twenty-one studies were conducted across six continents in Asia, eight in North America and Africa, five in South America, and four in Europe. This review article gives a glance at the published methodologies for AGB prediction modeling and validation. The literature review suggested that, along with the integration of other sensors, QuickBird, WorldView-2, and IKONOS satellite images were most widely used for AGB estimations, with higher estimation accuracies. All studies were grouped into six satellite-derived independent variables, including tree crown, image textures, tree shadow fraction, canopy height, vegetation indices, and multiple variables. Using these satellite-derived independent variables, most of the studies used linear regression (41%), while 30% used linear (multiple regression and 18% used non-linear (machine learning) regression, while very few (11%) studies used non-linear (multiple and exponential) regression for estimating AGB. In the context of global forest AGB estimations and monitoring, the advantages, strengths, and limitations were discussed to achieve better accuracy and transparency towards the performance-based payment mechanism of the REDD+ program. Apart from technical limitations, we realized that very few studies talked about real-time monitoring of AGB or quantifying AGB change, a dimension that needs exploration.

scholarly journals Potentialities and Limitations of Research on VHRS Data: Alexander the Great’s Military Camp at Gaugamela on the Navkur Plain in Kurdish Iraq as a Test Case

2021 ◽  
Vol 13 (5) ◽  
pp. 904
Author(s):  
Tomasz Pirowski ◽  
Michał Marciak ◽  
Marcin Sobiech
Keyword(s):  
Image Processing ◽  
High Resolution ◽  
Vegetation Indices ◽  
Test Case ◽  
Linear Features ◽  
Negative Results ◽  
Research Perspectives ◽  
Military Camp ◽  
Different Color ◽  
Very High

This paper presents a selected aspect of research conducted within the Gaugamela Project, which seeks to finally identify the location of one of the most important ancient battles: the Battle of Gaugamela (331 BCE). The aim of this study was to discover material remains of the Macedonian military camp on the Navkur Plain in Kurdish Iraq. For this purpose, three very high resolution satellite (VHRS) datasets from Pleiades and WorldView-2 were acquired and subjected to multi-variant image processing (development of different color composites, integration of multispectral and panchromatic images, use of principle component analysis transformation, use of vegetation indices). Documentation of photointerpretation was carried out through the vectorization of features/areas. Due to the character of the sought-after artifacts (remnants of a large enclosure), features were categorized into two types: linear features and areal features. As a result, 19 linear features and 2 areal features were found in the study area of the Mahad hills. However, only a few features fulfilled the expected geometric criteria (layout and size) and were subjected to field groundtruthing, which ended in negative results. It is concluded that no traces have been found that could be interpreted as remnants of an earthen enclosure capable of accommodating around 47,000 soldiers. Further research perspectives are also suggested.

scholarly journals Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development

2012 ◽  
Vol 84 (2) ◽  
pp. 263-274 ◽  
Author(s):  
Fábio M. Breunig ◽  
Lênio S. Galvão ◽  
Antônio R. Formaggio ◽  
José C.N. Epiphanio
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Constant Factor ◽  
The Other ◽  
Large Field ◽  
Phenological Stages ◽  
Water Index ◽  
Growing Seasons ◽  
Moderate Resolution Imaging Spectroradiometer

Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS). In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI1640 and NDWI2120) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.

scholarly journals Diallel cross among fresh market tomato inbreeding lines

2012 ◽  
Vol 30 (2) ◽  
pp. 246-251 ◽  
Author(s):  
Lívia M de Souza ◽  
Maria Elisa AGZ Paterniani ◽  
Paulo César T de Melo ◽  
Arlete MT de Melo
Keyword(s):  
Combining Ability ◽  
Yield Components ◽  
Block Design ◽  
Diallel Cross ◽  
Fruit Yield ◽  
Soluble Solids ◽  
Width Ratio ◽  
Parental Line ◽  
Fresh Market ◽  
Fruit Number

The general combining ability (GCA), specific combining ability (SCA), and heterosis were studied in a complete diallel cross among fresh market tomato breeding lines with reciprocal excluded. Fifteen genotypes (five parents and ten hybrids) were tested using a randomized complete block design, with three replications, and the experiments were conducted in Itatiba, São Paulo state, Brazil, in 2005/06. The yield components evaluated were fruit yield per plant (FP), fruit number per plant (FN), average fruit weight (FW); cluster number per plant (CN); fruit number per cluster (FC), fruit wall thickness (FT) and number of locules per fruit (NL). Fruit quality components evaluated were total soluble solids (SS); total titratable acidity (TA); SS/TA ratio, fruit length (FL); fruit width (WI); length to width ratio (FL/WI). The data for each trait was first subjected to analysis of variance. Griffing's method 2, model 1 was employed to estimate the general (GCA) and specific (SCA) combining abilities. Parental and hybrid data for each trait were used to estimate of mid-parent heterosis. For plant fruit yield, IAC-2 was the best parental line with the highest GCA followed by IAC-4 and IAC-1 lines. The hybrids IAC-1 x IAC-2, IAC-1 x IAC-4 and IAC-2 x IAC-4 showed the highest effects of SCA. High heterotic responses were found for fruit yield and plant fruit number with values up to 49.72% and 47.19%, respectively. The best hybrids for fruit yield and plant fruit number were IAC-1 x IAC-2, IAC-1 x IAC-4 and IAC-2 x IAC-5, for fruit yield and plant fruit number, the main yield components.

scholarly journals Fruit yield of european cranberry (Oxycoccus palustris Pers.) in different plant communities of peatlands (northern Wielkopolska, Poland)

2012 ◽  
Vol 62 (1) ◽  
pp. 97-105 ◽  
Author(s):  
Artur Adamczak ◽  
Maciej Gąbka ◽  
Waldemar Buchwald
Keyword(s):  
Plant Community ◽  
Plant Communities ◽  
Leaf Size ◽  
Fruit Weight ◽  
Fruit Yield ◽  
Habitat Conditions ◽  
Fruit Number ◽  
Oxycoccus Palustris

The aim of this study was to determine fruit yield of <i>Oxycoccus palustris</i> under the climatic and habitat conditions of northern Wielkopolska (the Greater Poland region), depending on the type of occupied plant community. Total fruit number and fruit weight as well as average cranberry leaf size were determined on 33 plots with an area of 1 m<sup>2</sup>, located on 7 peatlands. On the study areas, European cranberry produced crops from 9.2 up to 242.0 g &#56256;&#56457;&#56256;&#56323; m<sup>-2</sup>, which gives 92-2420 kg &#56256;&#56457;&#56256;&#56323;ha<sup>-1</sup>. It has been demonstrated that on the peatlands of northern Wielkopolska <i>O. palustris</i> reaches its generative and vegetative optimum in the communities of the class <i>Scheuchzerio- Caricetea fuscae</i>, in particular in the community <i>Sphagno recurvi-Eriophoretum angustifolii</i>.

scholarly journals Fruit production and quality of mini-watermelon with different number of stems, in troughs cultivation system and substrate reuse

2021 ◽  
Vol 42 (2) ◽  
pp. 471-486
Author(s):  
Josiéle Garcia Dutra ◽  
◽  
Roberta Marins Nogueira Peil ◽  
Tatiana da Silva Duarte ◽  
Cesar Valmor Rombaldi ◽  
...  
Keyword(s):  
Fruit Quality ◽  
Positive Impact ◽  
Fruit Weight ◽  
Fruit Yield ◽  
Soluble Solids ◽  
Plant Management ◽  
Cultivation System ◽  
Fruit Number ◽  
Yield And Quality ◽  
The One

Substrate-filled pots are growing systems commonly used for vegetable farming. However, few are the studies available relating them to mini-watermelon cultivation. Our study presents a growing system using substrate-filled troughs and leachate recirculation as a low-cost and less environmentally harmful soilless cultivation system for mini-watermelons. For a growing system to be viable and provide high fruit yield and quality, several aspects must be studied, including substrate physical properties and reuse potential in successive crops, besides plant management-related aspects. Therefore, our goal was to evaluate the effects of a trough system and substrate reuse on changes in the properties of raw rice husk and on fruit yield and quality for mini-watermelons at different stem training. To this purpose, two trials were conducted using nutrient solution recirculation systems. In the first, we evaluated the effects of pot and trough systems. In the second, first- and second-use substrates were compared in the trough system. In both trials, one and two-stem training systems were analyzed. The results of the first trial show that the trough system had a greater positive impact on substrate water holding capacity (WHC), which increased from 7.9 to 15.6%, while the pots increased substrate WHC only to 11.2%. However, both systems neither affected fruit yield (8 kg/m² on average) nor fruit quality. The two-stem training promoted higher fruit yields (4.2 kg/plant) and contents of total soluble solids - TSS (11.4 °Brix) but did not affect average fruit weight. Moreover, the one-stem training provided higher fruit number (7.3 fruits/m²) and fruit yield (9.7 kg/m²). In the second trial, the reused substrate showed a higher WHC (12.4%) than the one used for the first time (9.9%). The reused substrate also provided better results in terms of fruit yield and quality (5.9 fruits/m², 5.3 kg/m², and 10.5o Brix). In the second trial, two-stem training also increased average fruit weight, and hence yields per plant. Nevertheless, the stem number did not affect fruit number per plant, fruit yield per square meter, and fruit quality.

scholarly journals Pine wilt disease detection in high-resolution UAV images using object-oriented classification

2021 ◽  
Author(s):  
Zhao Sun ◽  
Yifu Wang ◽  
Lei Pan ◽  
Yunhong Xie ◽  
Bo Zhang ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Digital Camera ◽  
Object Oriented ◽  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Segmentation Algorithm ◽  
Tree Crown ◽  
Multi Scale ◽  
Pine Wilt

AbstractPine wilt disease (PWD) is currently one of the main causes of large-scale forest destruction. To control the spread of PWD, it is essential to detect affected pine trees quickly. This study investigated the feasibility of using the object-oriented multi-scale segmentation algorithm to identify trees discolored by PWD. We used an unmanned aerial vehicle (UAV) platform equipped with an RGB digital camera to obtain high spatial resolution images, and multi-scale segmentation was applied to delineate the tree crown, coupling the use of object-oriented classification to classify trees discolored by PWD. Then, the optimal segmentation scale was implemented using the estimation of scale parameter (ESP2) plug-in. The feature space of the segmentation results was optimized, and appropriate features were selected for classification. The results showed that the optimal scale, shape, and compactness values of the tree crown segmentation algorithm were 56, 0.5, and 0.8, respectively. The producer’s accuracy (PA), user’s accuracy (UA), and F1 score were 0.722, 0.605, and 0.658, respectively. There were no significant classification errors in the final classification results, and the low accuracy was attributed to the low number of objects count caused by incorrect segmentation. The multi-scale segmentation and object-oriented classification method could accurately identify trees discolored by PWD with a straightforward and rapid processing. This study provides a technical method for monitoring the occurrence of PWD and identifying the discolored trees of disease using UAV-based high-resolution images.

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