Ecological response of Eucalyptus camaldulensis (river red gum) to extended drought and flooding along the River Murray, South Australia (1997–2011) and implications for environmental flow management

2014 ◽  
Vol 65 (12) ◽  
pp. 1082 ◽  
Author(s):  
Tanya M. Doody ◽  
Simon N. Benger ◽  
Jodie L. Pritchard ◽  
Ian C. Overton
Keyword(s):  
Vegetation Index ◽  
Environmental Flows ◽  
Riparian Forest ◽  
South Australia ◽  
Eucalyptus Camaldulensis ◽  
Millennium Drought ◽  
Normalised Difference Vegetation Index ◽  
Floodplain Inundation ◽  
Flood Pulses ◽  
The Relationship

Riparian forest and woodlands of the lower River Murray floodplain are exhibiting deteriorating health as a result of anthropogenic alterations to flow regimes and south-eastern Australia’s long-term ‘Millennium Drought’ from 1997 to 2009. Extensive flooding in 2010/2011 brought the drought to an end, providing an opportunity to monitor ecological floodplain recovery. The relationship between flooding and lateral recharge and condition of the dominant riparian tree species, Eucalyptus camaldulensis, was determined between 2007 and 2011 using the Landsat (LTM5) Normalised Difference Vegetation Index (NDVI). Linking the river hydrograph with the River Murray Floodplain Inundation Model (RiM-FIM) allowed exploration of the relationship between inundation duration and E. camaldulensis water requirements. Results indicate lateral bank recharge is an important mechanism in the maintenance of vegetation condition along the River Murray channel. Higher in-channel irrigation water delivery during summer months was identified as critical to survival of trees adjacent to the channel during the drought. The research suggests that weir pool manipulation to create in-channel flood pulses will aid E. camaldulensis maintenance. Furthermore, release of environmental flows once every 3 to 5 years to create bank-full flow or preferably overbank flows, will increase hydrological connectivity between river banks, wetlands and riparian zones, providing positive ecological benefits to E. camaldulensis and other floodplain and aquatic ecological assets.

scholarly journals Rapid identification of shallow inundation for mosquito disease mitigation using drone-derived multispectral imagery

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Tasya Vadya Sarira ◽  
Kenneth Clarke ◽  
Philip Weinstein ◽  
Lian Pin Koh ◽  
Megan Lewis
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Multispectral Imaging ◽  
Imaging System ◽  
South Australia ◽  
Rapid Identification ◽  
Breeding Habitat ◽  
Mapping Accuracy ◽  
Normalised Difference Vegetation Index ◽  
Mosquito Breeding

Mosquito breeding habitat identification often relies on slow, labour-intensive and expensive ground surveys. With advances in remote sensing and autonomous flight technologies, we endeavoured to accelerate this detection by assessing the effectiveness of a drone multispectral imaging system to determine areas of shallow inundation in an intertidal saltmarsh in South Australia. Through laboratory experiments, we characterised Near-Infrared (NIR) reflectance responses to water depth and vegetation cover, and established a reflectance threshold for mapping water sufficiently deep for potential mosquito breeding. We then applied this threshold to field-acquired drone imagery and used simultaneous in-situ observations to assess its mapping accuracy. A NIR reflectance threshold of 0.2 combined with a vegetation mask derived from Normalised Difference Vegetation Index (NDVI) resulted in a mapping accuracy of 80.3% with a Cohen’s Kappa of 0.5, with confusion between vegetation and shallow water depths (< 10 cm) appearing to be major causes of error. This high degree of mapping accuracy was achieved with affordable drone equipment, and commercially available sensors and Geographic Information Systems (GIS) software, demonstrating the efficiency of such an approach to identify shallow inundation likely to be suitable for mosquito breeding.

scholarly journals Latrine site selection of raccoon dogs in a hilly area in north-eastern Japan

2021 ◽  
pp. 79-85
Author(s):  
Kazuma Watanabe ◽  
Nami Kumagai ◽  
Masayuki U. Saito
Keyword(s):  
Vegetation Index ◽  
Vegetation Type ◽  
Slope Angle ◽  
Normalised Difference Vegetation Index ◽  
North Eastern ◽  
Position Index ◽  
Latrine Site ◽  
The Relationship ◽  
Eastern Japan ◽  
Raccoon Dogs

We evaluated the environment types of raccoon dog latrine sites in the hilly areas of north-eastern Japan. We conducted a route census in the spring and autumn of 2020 to record the latrine sites and analysed the relationship between the presence or absence of latrine sites and environmental factors, namely, topographic position index (TPI), slope, normalised difference vegetation index (NDVI), and vegetation type for each season. To investigate the space use of raccoon dogs, we also conducted camera trapping from July to November 2020 along the spring survey route. We analysed the relationship between the occurrence frequency of raccoon dogs and TPI, slope angle, NDVI, and vegetation type. The analysis showed that latrine sites tended to be located at sites with a high TPI (topography closer to the ridge) in both seasons. However, the occurrence of latrine sites in broadleaf forests was significantly higher in autumn. The frequency of raccoon dogs, based on camera-trap footage, was significantly higher at sites with gentle slopes; although the environment and space used by raccoon dogs at these sites differed. Raccoon dogs possibly select visually and olfactorily conspicuous sites on the ridge as latrine sites to facilitate odour dispersal. In addition, broadleaf forests in autumn are considered important feeding grounds for raccoon dogs, suggesting that the latrine sites were formed near foraging sites.

scholarly journals Monitoring leaf area index at watershed level through NDVI from Landsat-7/ETM+ data

2004 ◽  
Vol 61 (3) ◽  
pp. 243-252 ◽  
Author(s):  
Alexandre Cândido Xavier ◽  
Carlos Alberto Vettorazzi
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Index ◽  
Hydrological Cycle ◽  
Riparian Forest ◽  
Empirical Relationships ◽  
Area Index ◽  
Landsat 7 ◽  
The Mean ◽  
The Relationship

Leaf area index (LAI) is an important parameter of the vegetation canopy, and is used, for instance, to estimate evapotranspiration, an important component of the hydrological cycle. This work analyzed the relationship between LAI, measured in field, and NDVI from four dates (derived from Landsat-7/ETM+ data), and with such vegetation index, to generate and analyze LAI maps of the study area for the diverse dates. LAI data were collected monthly in the field with LAI-2000 equipment in stands of sugar cane, pasture, corn, eucalypt, and riparian forest. The relationships between LAI and NDVI were adjusted by a potential model; 57% to 72% of the NDVI variance were explained by the LAI. LAI maps generated by empirical relationships between LAI and NDVI showed reasonable precision (standard error of LAI estimate ranged from 0.42 to 0.87 m² m-2). The mean LAI value of each monthly LAI map was shown to be related to the total precipitation in the three previous months.

scholarly journals Assessing the Relationship of LST, NDVI and EVI with Land Cover Changes in the Lagos Lagoon Environment

2020 ◽  
Vol 39 (3) ◽  
pp. 87-109 ◽  
Author(s):  
Alfred S. Alademomi ◽  
Chukwuma J. Okolie ◽  
Olagoke E. Daramola ◽  
Raphael O. Agboola ◽  
Tosin J. Salami
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Urban Expansion ◽  
Normalised Difference Vegetation Index ◽  
Lagos Lagoon ◽  
The Mean ◽  
Lagoon Environment ◽  
The Relationship ◽  
Derived Data

AbstractThe Lagos Lagoon is under increased pressure from growth in human population, growing demands for natural resources, human activities, and socioeconomic factors. The degree of these activities and the impacts are directly proportional to urban expansion and growth. In the light of this situation, the objectives of this study were: (i) to estimate through satellite imagery analysis the extent of changes in the Lagos Lagoon environment for the periods 1984, 2002, 2013 and 2019 using Landsat-derived data on land cover, Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI); and (ii) to evaluate the relationship between the derived data and determine their relative influence on the lagoon environment. The derived data were subjected to descriptive statistics, and relationships were explored using Pearson's correlation and regression analysis. The effect of land cover on LST was measured using the Contribution Index and a trend analysis was carried out. From the results, the mean LSTs for the four years were 22.68°C (1984), 24.34°C (2002), 26.46°C (2013) and 28.40°C (2019). Generally, the mean LSTs is in opposite trend with the mean NDVIs and EVIs as associated with their dominant land cover type. The strongest positive correlations were observed between NDVI and EVI while NDVI had the closest fit with LST in the regression. Built-up areas have the highest contributions to LST while vegetation had a cooling influence. The depletion in vegetative cover has compromised the biodiversity of this environment and efforts are required to reverse this trend.

scholarly journals A Long-Term Spatiotemporal Analysis of Vegetation Greenness over the Himalayan Region Using Google Earth Engine

Climate ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 109
Author(s):  
Nikul Kumari ◽  
Ankur Srivastava ◽  
Umesh Chandra Dumka
Keyword(s):  
Vegetation Index ◽  
Google Earth ◽  
Himalayan Region ◽  
Spatiotemporal Variability ◽  
Series Data ◽  
Vegetation Greenness ◽  
Normalised Difference Vegetation Index ◽  
Google Earth Engine ◽  
Hydroclimatic Factors ◽  
The Relationship

The Himalayas constitute one of the richest and most diverse ecosystems in the Indian sub-continent. Vegetation greenness driven by climate in the Himalayan region is often overlooked as field-based studies are challenging due to high altitude and complex topography. Although the basic information about vegetation cover and its interactions with different hydroclimatic factors is vital, limited attention has been given to understanding the response of vegetation to different climatic factors. The main aim of the present study is to analyse the relationship between the spatiotemporal variability of vegetation greenness and associated climatic and hydrological drivers within the Upper Khoh River (UKR) Basin of the Himalayas at annual and seasonal scales. We analysed two vegetation indices, namely, normalised difference vegetation index (NDVI) and enhanced vegetation index (EVI) time-series data, for the last 20 years (2001–2020) using Google Earth Engine. We found that both the NDVI and EVI showed increasing trends in the vegetation greening during the period under consideration, with the NDVI being consistently higher than the EVI. The mean NDVI and EVI increased from 0.54 and 0.31 (2001), respectively, to 0.65 and 0.36 (2020). Further, the EVI tends to correlate better with the different hydroclimatic factors in comparison to the NDVI. The EVI is strongly correlated with ET with r2 = 0.73 whereas the NDVI showed satisfactory performance with r2 = 0.45. On the other hand, the relationship between the EVI and precipitation yielded r2 = 0.34, whereas there was no relationship was observed between the NDVI and precipitation. These findings show that there exists a strong correlation between the EVI and hydroclimatic factors, which shows that changes in vegetation phenology can be better captured using the EVI than the NDVI.

A field method for statewide ground-truthing of a spatial pasture growth model

2000 ◽  
Vol 40 (8) ◽  
pp. 1069 ◽  
Author(s):  
R. C. Hassett ◽  
H. L. Wood ◽  
J. O. Carter ◽  
T. J. Danaher
Keyword(s):  
Growth Model ◽  
Vegetation Index ◽  
South Australia ◽  
Basal Area ◽  
Field Method ◽  
Projective Cover ◽  
Efficient Manner ◽  
Related Data ◽  
Normalised Difference Vegetation Index ◽  
Ground Truthing

This paper describes an innovative method, commonly referred to as ‘spider mapping’, that allows pasture biomass and related data to be collected over large areas in a timely and efficient manner. Spider mapping was developed initially to collect data to allow calibration and validation of a spatial and temporal pasture growth model operating across Queensland on a 5 km grid basis. Two field officers made over 220 000 estimates and collected about 1300 samples of pasture biomass between January 1994 and August 1995. A number of selected biomass samples were analysed for nitrogen, phosphorus and carbon content. In addition, data were also collected on foliage projective cover and tree basal area for a range of woodland communities and both variables compared with mean long-term Normalised Difference Vegetation Index values derived from a time series of National Oceanographic and Atmospheric Administration satellite imagery. Both variables were strongly related to the satellite data with overstorey foliage projective cover having the strongest non-linear correlation (r2 = 0.91). The method described here is currently being used in related work in the rangelands of New South Wales, South Australia, Western Australia and the Northern Territory.

Dingo baiting did not reduce fetal/calf loss in beef cattle in northern South Australia

2019 ◽  
Vol 59 (2) ◽  
pp. 319 ◽  
Author(s):  
Greg Campbell ◽  
Andrew Coffey ◽  
Heather Miller ◽  
John L. Read ◽  
Anthony Brook ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Vegetation Index ◽  
South Australia ◽  
Explanatory Factors ◽  
Direct Observations ◽  
Normalised Difference Vegetation Index ◽  
Beef Herds ◽  
Arid Rangelands ◽  
Time Of Year ◽  
Livestock Diseases

Beef cattle production is the major agricultural pursuit in the arid rangelands of Australia. Dingo predation is often considered a significant threat to production in rangeland beef herds, but there is a need for improved understanding of the effects of dingo baiting on reproductive wastage. We experimentally compared fetal/calf loss on baited and non-baited treatment areas within three northern South Australian beef herds over a 2–4-year period. At re-musters, lactation was used to determine the outcomes of known pregnancies. Potential explanatory factors for fetal/calf loss (dingo baiting, dingo activity, summer heat, cow age, seasonal conditions, activity of dingo prey and selected livestock diseases) were investigated. From 3145 tracked pregnancies, fetal/calf loss averaged 18.6%, with no overall significant effect of baiting. Fetal/calf loss averaged 27.3% for primiparous (first pregnancy) heifers and 16.8% for multiparous (2nd or later calf) cows. On average, dingo-activity indices were 59.3% lower in baited treatments than in controls, although background site differences in habitat, weather and previous dingo control could have contributed to these lower indices. The overall scale and timing of fetal/calf loss was not correlated with dingo activity, time of year, a satellite-derived measure of landscape greenness (normalised difference vegetation index), or activity of alternative dingo prey. Limited blood testing suggested that successful pregnancy outcomes, especially in primiparous heifers, may have been reduced by the livestock diseases pestivirus and leptospirosis. The percentage occurrence of cattle hair in dingo scats was higher when seasonal conditions were poorer and alternative prey less common, but lack of association between fetal/calf loss and normalised difference vegetation index suggests that carrion feeding, rather than calf predation, was the more likely cause. Nevertheless, during the fair to excellent prevailing seasons, there were direct observations of calf predation. It is likely that ground baiting, as applied, was ineffective in protecting calves, or that site effects, variable cow age and disease confounded our results.

scholarly journals Photogrammetry for assessment of pasture biomass

2019 ◽  
pp. 33-40 ◽  
Author(s):  
Kathryn Wigley ◽  
Jennifer L. Owens ◽  
Matthias Westerschulte ◽  
Paul Riding ◽  
Jaco Fourie ◽  
...  
Keyword(s):  
Linear Relationship ◽  
Plant Height ◽  
Vegetation Index ◽  
Digital Camera ◽  
Proof Of Concept ◽  
Destructive Sampling ◽  
Normalised Difference Vegetation Index ◽  
Surface Models ◽  
The Relationship ◽  
Strong Linear Relationship

New tools are required to provide estimates of pasture biomass as current methods are time consuming and labour intensive. This proof-of-concept study tested the suitability of photogrammetry to estimate pasture height in a grazed dairy pasture. Images were obtained using a digital camera from one site on two separate occasions (May and June 2017). Photogrammetry-derived pasture height was estimated from digital surface models created using the photos. Pasture indices were also measured using two currently available methods: a Rising Plate Meter (RPM), and Normalised Difference Vegetation Index (NDVI). Empirical pasture biomass measurements were taken using destructive sampling after all other measurements were made, and were used to evaluate the accuracy of the estimates from each method. There was a strong linear relationship between photogrammetry-derived plant height and actual biomass (R2=0.92May and 0.78June) and between RPM and actual biomass (R2=0.91May and 0.78June). The relationship between NDVI and actual biomass was relatively weaker (R2=0.65May and 0.66June). Photogrammetry could be an efficient way to measure pasture biomass with an accuracy comparable to that of the RPM but further work is required to confirm these preliminary findings.

HEALTHINESS OF OIL PALM PLANTATION TOWARDS SUSTAINABILITY OF ENVIRONMENT

2020 ◽  
Vol 7 (1) ◽  
pp. 21
Author(s):  
Faradina Marzukhi ◽  
Nur Nadhirah Rusyda Rosnan ◽  
Md Azlin Md Said
Keyword(s):  
Oil Palm ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Vegetation Indices ◽  
Soil Nutrient ◽  
Oil Palm Plantation ◽  
Sustainable Environment ◽  
Moisture Analysis ◽  
The Relationship

The aim of this study is to analyse the relationship between vegetation indices of Normalized Difference Vegetation Index (NDVI) and soil nutrient of oil palm plantation at Felcra Nasaruddin Bota in Perak for future sustainable environment. The satellite image was used and processed in the research. By Using NDVI, the vegetation index was obtained which varies from -1 to +1. Then, the soil sample and soil moisture analysis were carried in order to identify the nutrient values of Nitrogen (N), Phosphorus (P) and Potassium (K). A total of seven soil samples were acquired within the oil palm plantation area. A regression model was then made between physical condition of the oil palms and soil nutrients for determining the strength of the relationship. It is hoped that the risk map of oil palm healthiness can be produced for various applications which are related to agricultural plantation.

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