scholarly journals UAV and ground-based imagery analysis detects canopy structure changes after canopy management applications

OENO One ◽  
2020 ◽  
Vol 54 (4) ◽  
pp. 1093-1103
Author(s):  
Jingyun Ouyang ◽  
Roberta De Bei ◽  
Sigfredo Fuentes ◽  
Cassandra Collins
Keyword(s):  
Vegetation Index ◽  
Management Practices ◽  
Canopy Structure ◽  
Area Index ◽  
Structure Changes ◽  
Grape Quality ◽  
Canopy Volume ◽  
Canopy Area ◽  
Plant Area Index ◽  
Canopy Management

Aim: To analyse unmanned aerial vehicle (UAV)-based imagery to assess canopy structural changes after the application of different canopy management practices in the vineyard.Methods and results: Four different canopy management practices: i–ii) leaf removal within the bunch zone (eastern side/both eastern and western sides), iii) bunch thinning and iv) shoot trimming were applied to grapevines at veraison, in a commercial Cabernet-Sauvignon vineyard in McLaren Vale, South Australia. UAV-based imagery captures were taken: i) before the canopy treatments, ii) after the treatments and iii) at harvest to assess the treatment outcomes. Canopy volume, projected canopy area and normalized difference vegetation index (NDVI) were derived from the analysis of RGB and multispectral imagery collected using the UAV. Plant area index (PAI) was calculated using the smartphone app VitiCanopy as a ground-based measurement for comparison with UAV-derived measurements. Results showed that all three types of UAV-based measurements detected changes in the canopy structure after the application of canopy management practices, except for the bunch thinning treatment. As expected, ground-based PAI was the only technique to effectively detect internal canopy structure changes caused by bunch thinning. Canopy volume and PAI were found to better detect variations in canopy structure compared to NDVI and projected canopy area. The latter were negatively affected by the interference of the trimmed shoots left on the ground.Conclusions: UAV-based tools can provide accurate assessments to some canopy management outcomes at the vineyard scale. Among different UAV-based measurements, canopy volume was more sensitive to changes in canopy structure, compared to NDVI and projected canopy area, and demonstrated a greater potential to assess the outcomes of a range of canopy management practices.  Significance and impact of the study: Canopy management practices are widely applied to regulate canopy growth, improve grape quality and reduce disease pressure in the bunch zone. Being able to detect major changes in canopy structure, with some limitations when the practice affects the internal structure (i.e., bunch thinning), UAV-based imagery analysis can be used to measure the outcome of common canopy management practices and it can improve the efficiency of vineyard management.  

scholarly journals Improving Field-Scale Wheat LAI Retrieval Based on UAV Remote-Sensing Observations and Optimized VI-LUTs

2019 ◽  
Vol 11 (20) ◽  
pp. 2456 ◽  
Author(s):  
Wanxue Zhu ◽  
Zhigang Sun ◽  
Yaohuan Huang ◽  
Jianbin Lai ◽  
Jing Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Management Practices ◽  
Near Infrared ◽  
Lookup Table ◽  
Field Scale ◽  
Area Index ◽  
Biophysical Parameter ◽  
Retrieval Accuracy

Leaf area index (LAI) is a key biophysical parameter for monitoring crop growth status, predicting crop yield, and quantifying crop variability in agronomic applications. Mapping the LAI at the field scale using multispectral cameras onboard unmanned aerial vehicles (UAVs) is a promising precision-agriculture application with specific requirements: The LAI retrieval method should be (1) robust so that crop LAI can be estimated with similar accuracy and (2) easy to use so that it can be applied to the adjustment of field management practices. In this study, three UAV remote-sensing missions (UAVs with Micasense RedEdge-M and Cubert S185 cameras) were carried out over six experimental plots from 2018 to 2019 to investigate the performance of reflectance-based lookup tables (LUTs) and vegetation index (VI)-based LUTs generated from the PROSAIL model for wheat LAI retrieval. The effects of the central wavelengths and bandwidths for the VI calculations on the LAI retrieval were further examined. We found that the VI-LUT strategy was more robust and accurate than the reflectance-LUT strategy. The differences in the LAI retrieval accuracy among the four VI-LUTs were small, although the improved modified chlorophyll absorption ratio index-lookup table (MCARI2-LUT) and normalized difference vegetation index-lookup table (NDVI-LUT) performed slightly better. We also found that both of the central wavelengths and bandwidths of the VIs had effects on the LAI retrieval. The VI-LUTs with optimized central wavelengths (red = 612 nm, near-infrared (NIR) = 756 nm) and narrow bandwidths (~4 nm) improved the wheat LAI retrieval accuracy (R2 ≥ 0.75). The results of this study provide an alternative method for retrieving crop LAI, which is robust and easy use for precision-agriculture applications and may be helpful for designing UAV multispectral cameras for agricultural monitoring.

Modelling understory light availability in a heterogeneous landscape using drone-derived structural parameters and a 3D radiative transfer model

2020 ◽  
Author(s):  
Dominic Fawcett ◽  
Jonathan Bennie ◽  
Karen Anderson
Keyword(s):  
Radiative Transfer ◽  
Vegetation Index ◽  
Structural Parameters ◽  
Point Clouds ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Area Index ◽  
Vegetation Height ◽  
Plant Area Index ◽  
The Impact

<p>The light environment within vegetated landscapes is a key driver of microclimate, creating varied habitats over small spatial extents and controls the distribution of understory plant species. Modelling spatial variations of light at these scales requires finely resolved (< 1 m) information on topography and canopy properties. We demonstrate an approach to modelling spatial distributions and temporal progression of understory photosynthetically active radiation (PAR) utilising a three dimensional radiative transfer model (discrete anisotropic radiative transfer model: DART) where the scene is parameterised by drone-based data.</p><p>The study site, located in west Cornwall, UK, includes a small mixed woodland as well as isolated free-standing trees. Data were acquired from March to August 2019. Vegetation height and distribution were derived from point clouds generated from drone image data using structure-from-motion (SfM) photogrammetry. These data were supplemented by multi-temporal multispectral imagery (Parrot Sequoia camera) which were used to generate an empirical model by relating a vegetation index to plant area index derived from hemispherical photography taken over the same time period. Simulations of the 3D radiative budget were performed for the PAR wavelength interval (400 – 700 nm) using DART.</p><p>Besides maps of instantaneous above and below canopy irradiance, we provide models of daily light integrals (DLI) which are assessed against field validation measurements with PAR quantum sensors. We find relatively good agreement for simulated PAR in the woodland. The impact of simplifying assumptions regarding leaf angular distributions and optical properties are discussed. Finally, further opportunities which fine-grained drone data can provide in a radiative transfer context are highlighted.</p>

Himalayan yew: stand structure, canopy damage, regeneration and conservation strategy

1998 ◽  
Vol 25 (4) ◽  
pp. 334-341 ◽  
Author(s):  
H.C. RIKHARI ◽  
L.M.S. PALNI ◽  
S. SHARMA ◽  
S.K. NANDI
Keyword(s):  
Stand Structure ◽  
Canopy Structure ◽  
Conservation Strategy ◽  
Cancer Drug ◽  
Taxus Baccata ◽  
Area Index ◽  
Canopy Volume ◽  
Anti Cancer ◽  
Canopy Removal ◽  
Canopy Damage

Taxus baccata L. subsp. wallichiana (Zucc.) Pilger has come into prominence in recent times due to its uncontrolled harvesting from the Himalayan wilds for the extraction of the anti-cancer drug Taxol. It is a very slow growing tree with poor regeneration, and the extent of canopy damage is likely to have serious consequences on biomass yield, plant survival and natural regeneration by affecting 'seed' output. The present study in the Jageshwar area of the Central Himalaya aimed to determine the stand and canopy structure, microsite characteristics, extent of canopy removal, and regeneration in human-disturbed and undisturbed sites. The number of trees, saplings and seedlings varied amongst plots. Leaf area index and canopy volume increased with increasing circumference at breast height. Of the total canopy volume, 57.4% was found to have been removed from the study area (9.54 ha; representing about 8% of the total T. baccata habitat). Regeneration of the species was found to be better in moist and shady microsites at undisturbed locations than in disturbed sites. Efforts made thus far for its conservation, and future strategies are discussed.

scholarly journals NEW VEGETATION INDICES FOR FULL AND COMPACT POLARIMETRIC SAR DATA: IN PREPARATION FOR THE RADARSAT CONSTELLATION MISSION (RCM)

2020 ◽  
Vol IV-3/W2-2020 ◽  
pp. 41-46
Author(s):  
D. Ratha ◽  
D. Mandal ◽  
S. Dey ◽  
A. Bhattacharya ◽  
A. Frery ◽  
...  
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Time Series Data ◽  
Geodesic Distance ◽  
Vegetation Indices ◽  
Series Data ◽  
Biophysical Parameters ◽  
Area Index ◽  
Plant Area Index ◽  
Sar Data

Abstract. In this paper, we present two radar vegetation indices for full-pol and compact-pol SAR data, respectively. Both are derived using the notion of a geodesic distance between observation and well-known scattering models available in the literature. While the full-pol version depends on a generalized volume scattering model, the compact-pol version uses the ideal depolariser to model the randomness in the vegetation. We have utilized the RADARSAT Constellation Mission (RCM) time-series data from the SAMPVEX16-MB campaign in the Manitoba region of Canada for comparing and assessing the indices in terms of the change in the biophysical parameters as well. The compact-pol data for comparison is simulated from the full-pol RCM time series. Both the indices show better performance at correlating with biophysical parameters such as Plant Area Index (PAI) and Volumetric Water Content (VWC) for wheat and soybean crops, in comparison to the state-of-art Radar Vegetation Index (RVI) of Kim and van Zyl. These indices are timely for the upcoming release of the data from the RCM, which will provide data in both full and compact-pol modes, aimed at better crop monitoring from space.

scholarly journals The Impact of Non-Photosynthetic Vegetation on LAI Estimation by NDVI in Mixed Grassland

2020 ◽  
Vol 12 (12) ◽  
pp. 1979
Author(s):  
Dandan Xu ◽  
Deshuai An ◽  
Xulin Guo
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Series Data ◽  
Vegetation Indices ◽  
Series Data ◽  
Area Index ◽  
Plant Area Index ◽  
The Impact

Leaf area index (LAI) is widely used for algorithms and modelling in the field of ecology and land surface processes. At a global scale, normalized difference vegetation index (NDVI) products generated by different remote sensing satellites, have provided more than 40 years of time series data for LAI estimation. NDVI saturation issues are reported in agriculture and forest ecosystems at high LAI values, creating a challenge when using NDVI to estimate LAI. However, NDVI saturation is not reported on LAI estimation in grasslands. Previous research implies that non-photosynthetic vegetation (NPV) reduces the accuracy of LAI estimation from NDVI and other vegetation indices. A question arises: is the absence of NDVI saturation in grasslands a result of low LAI value, or is it caused by NPV? This study aims to explore whether there is an NDVI saturation issue in mixed grassland, and how NPV may influence LAI estimation by NDVI. In addition, in-situ measured plant area index (PAI) by sensors that detect light interception through the vegetation canopy (e.g., Li-cor LAI-2000), the most widely used field LAI collection method, might create bias in LAI estimation or validation using NDVI. Thus, this study also aims to quantify the contribution of green vegetation (GV) and NPV on in-situ measured PAI. The results indicate that NDVI saturation (using the portion of NDVI only contributed by GV) exists in grassland at high LAI (LAI threshold is much lower than that reported for other ecosystems in the literature), and that the presence of NPV can override the saturation effects of NDVI used to estimate green LAI. The results also show that GV and NPV in mixed grassland explain, respectively, the 60.33% and 39.67% variation of in-situ measured PAI by LAI-2000.

Comparing nondestructive measures of forage structure and phytomass

2000 ◽  
Vol 80 (3) ◽  
pp. 565-573 ◽  
Author(s):  
B. E. Olson ◽  
R. T. Wallander ◽  
J. M. Beaver
Keyword(s):  
Radiative Transfer ◽  
Leaf Area ◽  
Canopy Structure ◽  
Plant Canopy ◽  
Native Range ◽  
Area Index ◽  
Crested Wheatgrass ◽  
Canopy Volume ◽  
Peak Standing Crop ◽  
Intercepted Radiation

Nondestructive radiative transfer and canopy volume methods were compared with the destructive hand-clipping method to determine forage structure and phytomass. On a native range site, fifteen 1-m2 circular plots were located at each of five microsites. On a crested wheatgrass site, thirty 1-m2 plots were located in grazed and in ungrazed areas. At peak standing crop, all plots were measured with a LI-COR Plant Canopy Analyzer to determine leaf area index (LAI), diffuse non-intercepted radiation (DNIR), and mean tilt angle (MTA) of leaves. Then, plants within plots were measured with a ruler to determine volume. Finally, all phytomass within plots was harvested. At the native range site, plant volume was related with LAI and DNIR on four of five microsites. Phytomass was related with LAI and DNIR on two microsites. At the crested wheatgrass site, volume and phytomass were related with LAI, DNIR, and MTA on grazed plots. Only phytomass was related with LAI and DNIR on ungrazed plots. The Plant Canopy Analyzer measures canopy structure and phytomass; it is fast, and its data are transferred directly to a computer. Measuring plant volume is inexpensive and requires minimal training. Determining phytomass by clipping is accurate and requires minimal training, but it is time-consuming and destructive. Key words: Leaf area, canopy, volume, phytomass, radiative transfer

scholarly journals Stemflow and its controlling factors in the subshrub Artemisia ordosica during two contrasting growth stages in the Mu Us sandy land of northern China

2015 ◽  
Vol 47 (2) ◽  
pp. 409-418 ◽  
Author(s):  
Liu Li ◽  
Xiao-Yan Li ◽  
Si-Yi Zhang ◽  
Zhi-Yun Jiang ◽  
Xiao-Ran Zheng ◽  
...  
Keyword(s):  
Growth Stage ◽  
Canopy Structure ◽  
Northern China ◽  
Growth Stages ◽  
Sandy Land ◽  
Artemisia Ordosica ◽  
Growth Season ◽  
Area Index ◽  
Mu Us Sandy Land ◽  
Canopy Area

The yield of stemflow from vegetation is mostly affected by rainfall and canopy structure, but few past studies have paid attention to the dynamics of canopy structure during the growth season. Artemisia ordosica is a typical subshrub, very different from trees and shrubs. Assessing the influence of canopy structure and rainfall on stemflow yield in A. ordosica during the growth season will fill a knowledge gap in our understanding of stemflow yield from subshrub species. This study therefore examined the effects of those two factors on stemflow at two growth stages of A. ordosica, using 20 experimental individuals in the Mu Us sandy land of northern China. It demonstrated that the mean stemflow percentage of gross rainfall (SF%) for this subshrub was 8.56%, and the average funneling ratio was 75.80. The critical control factors of stemflow volumes were rainfall amount and canopy area, which varied greatly during the growth season. The SF% was significantly lower during the reproductive growth stage than during the vegetative growth stage, because of the rapid increase in leaf area index at the former stage. This evaluation of the effects of vegetation growth dynamics on stemflow yield will improve the accuracy of future hydrological models.

The relationship between effective plant area index and Landsat spectral response across elevation, solar insolation, and spatial scales in a northern Idaho forest

2004 ◽  
Vol 34 (2) ◽  
pp. 465-480 ◽  
Author(s):  
Amy L Pocewicz ◽  
Paul Gessler ◽  
Andrew P Robinson
Keyword(s):  
Spatial Scale ◽  
Complex Terrain ◽  
Vegetation Index ◽  
Remotely Sensed ◽  
Solar Insolation ◽  
Area Index ◽  
Plant Area Index ◽  
Plant Area ◽  
Northern Idaho ◽  
The Relationship

Leaf area index (LAI) is an important forest characteristic related to photosynthesis and carbon sequestration, and gains in efficiency for LAI measurements are possible using remotely sensed imagery. However, the potential effects of complex topography on this measurement system are not well understood. Our objective was to understand how complex terrain and measurement aggregation influence the relationship between LAI and remotely sensed vegetation indices across a mountainous conifer forest. We identified NDVIc, a middle-infrared (MIR) correction to NDVI (Normalized Difference Vegetation Index), as the vegetation index providing the best prediction of effective plant area index (PAIe), used to approximate LAI. We tested formal hypotheses to identify how elevation and solar insolation gradients and spatial scale of measurement aggregation affected the PAIe–NDVIc relationship and found that it changed across elevation at one spatial scale. Comparisons of NDVIc with NDVI revealed that vegetation index choice is important in complex terrain, and we concluded that the MIR correction improves the PAIe–NDVI relationship by explaining variation related to solar insolation. Our results suggest that NDVIc calculated from Landsat ETM+ provides a practical estimate of PAIe across our northern Idaho study area and potentially other conifer forests in complex terrain.

scholarly journals Measuring Woody Encroachment along a Forest–Savanna Boundary in Central Africa

2009 ◽  
Vol 13 (8) ◽  
pp. 1-29 ◽  
Author(s):  
E. T. A. Mitchard ◽  
S. S. Saatchi ◽  
F. F. Gerard ◽  
S. L. Lewis ◽  
P. Meir
Keyword(s):  
Vegetation Change ◽  
Vegetation Index ◽  
Alternative Hypothesis ◽  
Canopy Cover ◽  
Fire Frequency ◽  
Weight Of Evidence ◽  
Competitive Balance ◽  
Area Index ◽  
Boundary Area ◽  
Canopy Area

Abstract Changes in net area of tropical forest are the sum of several processes: deforestation, regeneration of previously deforested areas, and the changing spatial location of the forest–savanna boundary. The authors conducted a long-term (1986–2006) quantification of vegetation change in a 5400 km2 forest–savanna boundary area in central Cameroon. A cross-calibrated normalized difference vegetation index (NDVI) change detection method was used to compare three high-resolution images from 1986, 2000, and 2006. The canopy dimensions and locations of over 1000 trees in the study area were measured, and a very strong relationship between canopy area index (CAI) and NDVI was found. Across 5400 km2 12.6% of the area showed significant positive change in canopy cover from 1986 to 2000 (0.9% yr−1) and 7.8% from 2000 to 2006 (1.29% yr−1), whereas <0.4% of the image showed a significant decrease in either period. The largest changes were in the lower canopy cover classes: the area with <0.2 m2 m−2 CAI decreased by 43% in 20 years. One cause may be a recent reduction in fire frequency, as documented by Along Track Scanning Radiometer-2/Advanced ATSR (ATSR-2/AATSR) data on fire frequency over the study area from 1996 to 2006. The authors suggest this is due to a reduction in human pressure caused by urbanization, as rainfall did not alter significantly over the study period. An alternative hypothesis is that increasing atmospheric CO2 concentrations are altering the competitive balance between grasses and trees. These data add to a growing weight of evidence that forest encroachment into savanna is an important process, occurring in forest–savanna boundary regions across tropical Africa.

scholarly journals The value of different vegetative indices (NDVI, GAI) for the assessment of yield potential of pea (Pisum sativum L.) at different growth stages and under varying management practices

2018 ◽  
Vol 71 (1) ◽  
Author(s):  
Agnieszka Klimek-Kopyra ◽  
Tadeusz Zając ◽  
Andrzej Oleksy ◽  
Bogdan Kulig ◽  
Anna Ślizowska
Keyword(s):  
Vegetation Index ◽  
Management Practices ◽  
Normalized Difference Vegetation Index ◽  
Negative Impact ◽  
Yield Potential ◽  
Growth Stages ◽  
Maturity Stage ◽  
Area Index ◽  
Foliar Fertilizer ◽  
Vegetative Indices

This research evaluated the NDVI (normalized difference vegetation index) and GAI (green area index) in order to indicate the productivity and developmental effects of <em>Rhizobium inoculants</em> and microelement foliar fertilizer on pea crops. Two inoculants, Nitragina (a commercial inoculant) and IUNG (a noncommercial inoculant gel) and a foliar fertilizer (Photrel) were studied over a 4-year period, 2009–2012. The cultivars chosen for the studies were characterized by different foliage types, namely a semileafless pea ‘Tarchalska’ and one with regular foliage, ‘Klif’. Foliar fertilizer significantly increased the length of the generative shoots and the number of fruiting nodes in comparison to the control, which in turn had a negative impact on the harvest index. Pea seed yield was highly dependent on the interaction between the years of growth and the microbial inoculant, and was greater for ‘Tarchalska’ (4.33 t ha<sup>−1</sup>). Presowing inoculation of seeds and foliar fertilization resulted in a significantly higher value of GAI at the flowering (3.91 and 3.81, respectively) and maturity stages (4.82 and 4.77, respectively), whereas the value of NDVI was higher for these treatments only at the maturity stage (0.67 and 0.79, respectively). A significantly greater yield (5.0–5.4 t ha<sup>−1</sup>) was obtained after inoculation with IUNG during the dry years.

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