Remote Sensing of Vegetation Recovery in Grasslands after the 1988 Fires in Yellowstone National Park

Traditional methods for measurement of vegetative characteristics can be time-consuming and labor-intensive, especially across large areas. Yet such estimates are necessary to investigate the effects of large scale disturbances on ecosystem components and processes. Because foliage of plants differentially absorbs and reflects energy within the electromagnetic spectrum, one alternative for monitoring vegetation is to use remotely sensed spectral data (Tueller 1989). Spectral indices developed from field radiometric and Landsat data have been used successfully to quantify green leaf area, biomass, and total yields in relatively homogeneous fields for agronomic uses (Shibayama and Akiyama 1989), but have met with variable success in wildland situations (Pearson et aL 1976). Interference from soils (Hardinsky et al. 1984, Huete et al. 1985), weathered litter (Huete and Jackson 1987), and senesced vegetation (Sellers 1985) have diminished the relationship between green vegetation characteristics and various vegetation indices. In 1987, we found that a linear combination of Landsat Multi-spectral Scanner (MSS) band 7 and the ratio of MSS bands 6 to 4 explained 63% of the variation in green herbaceous phytomass (GHP) in sagebrush-grasslands on ungulate summer range in the northeastern portion of Yellowstone National Park (Merrill et al. 1993). The extensive fires that occurred in the Park in the summer of 1988 provided an opportunity to determine whether remote sensing could be used to estimate green phytomass in burned areas and to monitor grassland vegetation recovery in the Park after the fires. Remote sensing has previously been used to follow succession of seral stages in pine forests (Jakubauskas et al. 1990) after burning and to monitor plant cover in tundra (Hall et al. 1980) after wildfires. The objectives of our study were to: (1) develop a model for predicting GHP in sagebrushÂ grassland communities using Landsat TM spectral information and field data on GHP for 2 years, (2) validate the model by comparing predictions made from the model to actual field data collected in a third year, and if successful (3) compare initial vegetation recovery in burned areas relative to unburned sagebrush-grassland.

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Remote Sensing of Vegetation Recovery in Grasslands after the 1988 Yellowstone Fires in Yellowstone National Park

The UW National Parks Service Research Station Annual Reports ◽

10.13001/uwnpsrc.1990.2921 ◽

1990 ◽

Vol 14 ◽

pp. 151-153

Author(s):

Evelyn Merrill ◽

Cathy Wilson ◽

Ronald Marrs

Keyword(s):

Remote Sensing ◽

Spectral Data ◽

Satellite Imagery ◽

Yellowstone National Park ◽

National Park ◽

Large Scale ◽

Vegetation Recovery ◽

Electromagnetic Spectrum ◽

Traditional Methods ◽

Vegetative Biomass

Traditional methods for measurement of vegetative biomass can be time-consuming and laborÂintensive, especially across large areas. Yet such estimates are necessary to investigate the effects of large scale disturbances on ecosystem components and processes. One alternative to traditional methods for monitoring rangeland vegetation is to use satellite imagery. Because foliage of plants differentially absorbs and reflects energy within the electromagnetic spectrum, remote sensing of spectral data can be used to quantify the amount of green vegetative biomass present in an area (Tucker and Sellers 1986).

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LOFAR observations of the XMM-LSS field

Astronomy and Astrophysics ◽

10.1051/0004-6361/201833906 ◽

2019 ◽

Vol 622 ◽

pp. A4 ◽

Cited By ~ 8

Author(s):

C. L. Hale ◽

W. Williams ◽

M. J. Jarvis ◽

M. J. Hardcastle ◽

L. K. Morabito ◽

...

Keyword(s):

Large Scale ◽

Angular Resolution ◽

Low Frequency ◽

Primary Beam ◽

Electromagnetic Spectrum ◽

Radio Sources ◽

Spectral Indices ◽

The North ◽

True Source ◽

Scale Calibration

We present observations of the XMM Large-Scale Structure (XMM-LSS) field observed with the LOw Frequency ARray (LOFAR) at 120–168 MHz. Centred at a J2000 declination of −4.5°, this is a challenging field to observe with LOFAR because of its low elevation with respect to the array. The low elevation of this field reduces the effective collecting area of the telescope, thereby reducing sensitivity. This low elevation also causes the primary beam to be elongated in the north-south direction, which can introduce side lobes in the synthesised beam in this direction. However the XMM-LSS field is a key field to study because of the wealth of ancillary information, encompassing most of the electromagnetic spectrum. The field was observed for a total of 12 h from three four-hour LOFAR tracks using the Dutch array. The final image presented encompasses ∼27 deg2, which is the region of the observations with a >50% primary beam response. Once combined, the observations reach a central rms of 280μJy beam−1at 144 MHz and have an angular resolution of 7.5 × 8.5″. We present our catalogue of detected sources and investigate how our observations compare to previous radio observations. This includes investigating the flux scale calibration of these observations compared to previous measurements, the implied spectral indices of the sources, the observed source counts and corrections to obtain the true source counts, and finally the clustering of the observed radio sources.

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Evaluation of the Influence of Disturbances on Forest Vegetation Using the Time Series of Landsat Data: A Comparison Study of the Low Tatras and Sumava National Parks

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8020071 ◽

2019 ◽

Vol 8 (2) ◽

pp. 71 ◽

Cited By ~ 1

Author(s):

Premysl Stych ◽

Josef Lastovicka ◽

Radovan Hladky ◽

Daniel Paluba

Keyword(s):

Time Series ◽

National Park ◽

Vegetation Indices ◽

Forest Vegetation ◽

Vegetation Changes ◽

Landsat Data ◽

Climate Data ◽

Data Record ◽

Climate Data Record ◽

Level 2

This study focused on the evaluation of forest vegetation changes from 1992 to 2015 in the Low Tatras National Park (NAPANT) in Slovakia and the Sumava National Park in Czechia using a time series (TS) of Landsat images. The study area was damaged by wind and bark beetle calamities, which strongly influenced the health state of the forest vegetation at the end of the 20th and beginning of the 21st century. The analysis of the time series was based on the ten selected vegetation indices in different types of localities selected according to the type of forest disturbances. The Landsat data CDR (Climate Data Record/Level 2) was normalized using the PIF (Pseudo-Invariant Features) method and the results of the Time Series were validated by in-situ data. The results confirmed the high relevance of the vegetation indices based on the SWIR bands (e.g., NDMI) for the purpose of evaluating the individual stages of the disturbance (especially the bark beetle calamity). Usage of the normalized Landsat data Climate Data Record (CDR/Level 2) in the research of long-term forest vegetation changes has a high relevance and perspective due to the free availability of the corrected data.

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Evaluating the relationship between SIF and GPP under climate extremes

10.5194/egusphere-egu21-8939 ◽

2021 ◽

Author(s):

Sebastian Wieneke ◽

Ana Bastos ◽

Manuela Balzarolo ◽

José Miguel Barrios ◽

Ivan Janssens

Keyword(s):

Large Scale ◽

Gross Primary Production ◽

Vegetation Indices ◽

Climate Extremes ◽

Vegetation Stress ◽

Linear Relationships ◽

Forest Sites ◽

Good Proxy ◽

The Relationship

Sun Induced Chlorophyll Fluorescence (SIF) is considered as a good proxy for photosynthesis given its closer link to the photosynthetic light reactions compared to remote sensing vegetation indices typically used for ecosystem productivity modelling (eg. NDVI). Satellite-based SIF shows significant linear relationships with gross primary production (GPP) from in-situ measurements across sites, biomes and seasons. While SIF can be considered a good proxy for large scale spatial and seasonal variability in GPP, much of the SIF-GPP co-variance can be explained by their common dependence on the absorbed photosynthetically active radiation. Whether SIF can be an equally good proxy for interannual variability in GPP especially during periods of vegetation stress (drought/heat) is, so far, not clear.In this study, we evaluate the relationship between satellite-based SIF and in-situ GPP measurements during vegetation stress periods (drought/heat), compared to non-stress periods. GPP is obtained from eddy-covariance measurements from a set of forest sites pre-filtered to ensure homonegeous footprints. SIF is obtained from GOME-2 covering the period 2007-2018. Because of scale mismatch between each site&#8217;s footprint (in the order of hundred meters) and the spatial resolution of GOME-2 (ca. 50km), we additionally use SIF from the downscale product from Duveiller et al. 2020 (ca. 5km) and the more recent dataset from TROPOMI (ca. 7 x 3.5 km), covering only the last year of the study period.We develop a classification of stress periods that is based on both the occurrence of drought/heat extreme events and the presence of photosynthetic downregulation. We then evaluate the relationship between SIF and GPP and their yields, for different plant functional types and at site-level. We evaluate how these relationships vary depending on environmental conditions and in particular for &#8220;stress&#8221; versus &#8220;non-stress&#8221; days.Duveiller, G., Filipponi, F., Walther, S., K&#246;hler, P., Frankenberg, C., Guanter, L., and Cescatti, A.: A spatially downscaled sun-induced fluorescence global product for enhanced monitoring of vegetation productivity, Earth Syst. Sci. Data, 12, 1101&#8211;1116, https://doi.org/10.5194/essd-12-1101-2020, 2020.

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Application of geo-informatics engineering to estimate above-ground carbon sequestration

Engineering review ◽

10.30765/er.38.3.7 ◽

2018 ◽

Vol 38 (3) ◽

pp. 303-308

Author(s):

Teerawong Laosuwan ◽

Yannawut Uttaruk ◽

Tanutdech Rotjanakusol ◽

Kusuma Arsasana

Keyword(s):

Carbon Sequestration ◽

Vegetation Index ◽

Vegetation Indices ◽

Coefficient Of Determination ◽

Landsat 8 ◽

Regression Equations ◽

Landsat 8 Oli ◽

Green Vegetation ◽

Simple Ratio ◽

The Relationship

This research aims to estimate above-ground carbon sequestration of orchards by using the data collected from Landsat 8 OLI. Regression equations are applied to study the relationship between the amount of above-ground carbon sequestration and vegetation indices from Landsat 8 OLI, in which the data was collected in 2015 in 3 methods: 1) Difference Vegetation Index (DVI), 2) Green Vegetation Index (GVI), and 3) Simple Ratio (SR). The results are as follows: 1) By DVI method, it results in the equation y = 0.3184e0.0482x and the coefficient of determination R² = 0.8457. The amount of the above-ground sequestration calcula-tion's result is 213.176 tons per rai. 2) Using the GVI method, it results in the equation y = 0.2619e0.0489x and the coefficient of determination R²=0.8763. The amount of the above-ground sequestration calculation's result is 220.510 tons per rai. 3) Using the SR method, it results in the equation y = 0.8900e0.0469x and the coefficient of determination R² = 0.7748. The amount of the above-ground sequestration calculation's result is 234.229 tons per rai.

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Planning for Human-Wildlife Coexistence: Conceptual Framework, Workshop Process, and a Model for Transdisciplinary Collaboration

Frontiers in Conservation Science ◽

10.3389/fcosc.2021.752953 ◽

2021 ◽

Vol 2 ◽

Author(s):

Silvio Marchini ◽

Katia M. P. M. B. Ferraz ◽

Vania Foster ◽

Thiago Reginato ◽

Aline Kotz ◽

...

Keyword(s):

Decision Making ◽

Conceptual Framework ◽

National Park ◽

Large Scale ◽

Decision Makers ◽

Theory Of Change ◽

Positive Interactions ◽

Evidence Based ◽

The Relationship ◽

Agreed Definition

Coexistence, as a concept and as a management goal and practice, has attracted increasing attention from researchers, managers and decision-makers dedicated to understanding and improving human-wildlife interactions. Although it still lacks a universally agreed definition, coexistence has increasingly been associated with a broad spectrum of human-wildlife interactions, including positive interactions, transcending a conservation focus on endangered wildlife, and involving explicitly considerations of power, equity and justice. In a growingly complex and interconnected human-dominated world, the key to turning human-wildlife interactions into large-scale coexistence is thorough planning. We present an approach for evidence-based, structured, and participatory decision-making in planning for human-wildlife coexistence. More specifically, we propose (i) a conceptual framework for describing the situation and setting the goals, (ii) a process for examining the causes of the situation and creating a theory of change, and (iii) a model for transdisciplinary research and collaboration integrating researchers, decision-makers and residents along with the interests of wildlife. To illustrate the approach, we report on the workshop considering the Jaguars of Iguaçu, a conservation project whose strategy includes the improvement of the relationship between ranchers and jaguars outside Iguaçu National Park, Brazil.

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Relationship between total plasma homocysteine and the risk of aneurysms – a meta-analysis

VASA ◽

10.1024/0301-1526/a000891 ◽

2020 ◽

pp. 1-6

Author(s):

Hanji Zhang ◽

Dexin Yin ◽

Yue Zhao ◽

Yezhou Li ◽

Dejiang Yao ◽

...

Keyword(s):

Large Scale ◽

Meta Analysis ◽

Single Species ◽

Total Plasma ◽

Control Groups ◽

Randomized Controlled ◽

Randomized Controlled Studies ◽

The Difference ◽

The Relationship ◽

Healthy Participants

Summary: Our meta-analysis focused on the relationship between homocysteine (Hcy) level and the incidence of aneurysms and looked at the relationship between smoking, hypertension and aneurysms. A systematic literature search of Pubmed, Web of Science, and Embase databases (up to March 31, 2020) resulted in the identification of 19 studies, including 2,629 aneurysm patients and 6,497 healthy participants. Combined analysis of the included studies showed that number of smoking, hypertension and hyperhomocysteinemia (HHcy) in aneurysm patients was higher than that in the control groups, and the total plasma Hcy level in aneurysm patients was also higher. These findings suggest that smoking, hypertension and HHcy may be risk factors for the development and progression of aneurysms. Although the heterogeneity of meta-analysis was significant, it was found that the heterogeneity might come from the difference between race and disease species through subgroup analysis. Large-scale randomized controlled studies of single species and single disease species are needed in the future to supplement the accuracy of the results.

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HEALTHINESS OF OIL PALM PLANTATION TOWARDS SUSTAINABILITY OF ENVIRONMENT

Malaysian Journal of Sustainable Environment ◽

10.24191/myse.v7i1.8905 ◽

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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Classification of vegetation in Cucphuong National Park with the aim of large-scale mapping, Vietnam

Geobotanical mapping ◽

10.31111/geobotmap/1994-1995.64 ◽

1996 ◽

pp. 64-67 ◽

Cited By ~ 1

Author(s):

Nguen Nghia Thin ◽

Nguen Ba Thu ◽

Tran Van Thuy

Keyword(s):

National Park ◽

Large Scale ◽

Satellite Images ◽

Field Work ◽

Aerial Photographs ◽

Vegetation Map ◽

Dense Forest ◽

Broad Leaved Forest ◽

Leaved Forest

The tropical seasonal rainy evergreen broad-leaved forest vegetation of the Cucphoung National Park has been classified and the distribution of plant communities has been shown on the map using the relations of vegetation to geology, geomorphology and pedology. The method of vegetation mapping includes: 1) the identifying of vegetation types in the remote-sensed materials (aerial photographs and satellite images); 2) field work to compile the interpretation keys and to characterize all the communities of a study area; 3) compilation of the final vegetation map using the combined information. In the classification presented a number of different level vegetation units have been identified: formation classes (3), formation sub-classes (3), formation groups (3), formations (4), subformations (10) and communities (19). Communities have been taken as mapping units. So in the vegetation map of the National Park 19 vegetation categories has been shown altogether, among them 13 are natural primary communities, and 6 are the secondary, anthropogenic ones. The secondary succession goes through 3 main stages: grassland herbaceous xerophytic vegetation, xerophytic scrub, dense forest.

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