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Assessing the effect of band selection on accuracy of pansharpened imagery: application to young woody vegetation mapping

Emmanuel Fundisi, Solomon G. Tesfamichael
2018 South African Journal of Geomatics  
This can be aided by using high spatial resolution remotely-sensed data.  ...  The study shows that band selection did not affect the classification accuracy of woody vegetation significantly.  ...  In contrast, Landsat imagery is a typical example of remotely-sensed data that have been widely used for moderate resolution land cover assessment, including woody vegetation mapping and monitoring (Lwin  ... 
doi:10.4314/sajg.v7i2.2 fatcat:uerykm4dizfefnx6u2n4ds7hyi

GEOSPATIAL APPROACH FOR LANDSLIDE ACTIVITY ASSESSMENT AND MAPPING BASED ON VEGETATION ANOMALIES

M. R. Mohd Salleh, N. I. Ishak, K. A. Razak, M. Z. Abd Rahman, M. A. Asmadi, Z. Ismail, M. F. Abdul Khanan
2018 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
This study introduces a method that utilizes vegetation anomalies extracted using remote sensing data as a bio-indicator for landslide activity analysis and mapping.  ...  </strong> Remote sensing has been widely used for landslide inventory mapping and monitoring.  ...  ACKNOWLEDGEMENTS We would like to express our gratitude to Minerals and Geoscience Department for the remote sensing data and experts in the landslides mapping and inventory process.  ... 
doi:10.5194/isprs-archives-xlii-4-w9-201-2018 fatcat:bw3ix76d3vce3dv2iveq3yi6dy

Development of an integrated multiplatform approach for assessing brush management conservation efforts in semiarid rangelands

Chandra D. Holifield Collins, Mark A. Kautz, Ronald Tiller, Sapana Lohani, Guillermo Ponce-Campos, John Hottenstein, Loretta J. Metz
2015 Journal of Applied Remote Sensing  
An equation for TM-derived woody cover was developed. TM scenes of woody cover (TM WC ) were produced and validated using NAIP and ground-based data.  ...  Results showed that the developed relation produced viable (RMSE ¼ 8.5%, MAE ¼ 6.4%) maps of woody cover that could be used to successfully track the occurrence of brush removal, as well as monitor the  ...  of Arizona, for their cooperation and assistance.  ... 
doi:10.1117/1.jrs.9.096057 fatcat:vpwp75h3ofaqdewa6fijkavwxy

Detection of two intermixed invasive woody species using color infrared aerial imagery and the support vector machine classifier

Mustafa Mirik, Sriroop Chaudhuri, Brady Surber, Srinivasulu Ale, R. James Ansley
2013 Journal of Applied Remote Sensing  
These results indicated that assessment of the current infestation extent and severity of these two woody species in a spatial context is possible using aerial remote sensing imagery.  ...  This study was aimed at: (1) exploring the utility of aerial imagery for detecting and mapping intermixed redberry juniper and honey mesquite while both are in full foliage using the support vector machine  ...  Images used in this study were made available by the USDA-NRCS NAIP program. We thank Mimi Roy for technical discussion and Andy Bell for assisting with data collection.  ... 
doi:10.1117/1.jrs.7.073588 fatcat:j7ckr3hwkrgvrgsc4bifatykze

An Object-oriented Approach to Urban Forest Mapping in Phoenix

Jason S. Walker, John M. Briggs
2007 Photogrammetric Engineering and Remote Sensing  
We present a classification procedure in order to delineate woody vegetation in an arid urban ecosystem using highresolution, true-color aerial photography.  ...  PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING M a y 2 0 0 7 577  ...  The classification was parameterized to maximize the user's accuracy of WOODY in order to use the remotely sensed image to map woody vegetation with a high confidence of proper classification.  ... 
doi:10.14358/pers.73.5.577 fatcat:nwsywc6lyjabvflffgn2mzuhti

Mapping the Abundance of Multipurpose Agroforestry Faidherbia albida Trees in Senegal

Tingting Lu, Martin Brandt, Xiaoye Tong, Pierre Hiernaux, Louise Leroux, Babacar Ndao, Rasmus Fensholt
2022 Remote Sensing  
To better discriminate the Faidherbia albida signal from the background, monthly images from vegetation indices were used to form relevant variables for the model.  ...  We compared our result with a potential Faidherbia albida occurrence map derived by empirical modelling of the species ecology, which deviates notably from the actual species occurrence mapped by this  ...  Acknowledgments: We thank Roeland Kindt who provided the ecologically Faidherbia albida occurrence map. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs14030662 fatcat:oi6yooek4fdjhnoifpun7zlm3y

Studies of land-cover, land-use, and biophysical properties of vegetation in the Large Scale Biosphere Atmosphere experiment in Amazônia

D Roberts
2003 Remote Sensing of Environment  
Remote sensing has played a fundamental role in LBA in research planning, land-cover mapping and in long-term monitoring of changes in land-cover and land-use at multiple scales.  ...  Several themes dominate, including land-cover mapping with an emphasis on wetlands and second-growth forest, evaluation of pasture sustainability and forest degradation and the impact of land-cover change  ...  The US National Aeronautics and Space Administration (NASA) and the Fundac ßão de Amparo à Pesquisa do Estado de São Paulo (FAPESP) provided generous support for ecological research in LBA.  ... 
doi:10.1016/j.rse.2003.08.012 fatcat:2igo32kjdbgf7filef6lcj5oe4

Habitat Classification Predictions on an Undeveloped Barrier Island Using a GIS-Based Landscape Modeling Approach

Emily R. Russ, Bianca R. Charbonneau, Safra Altman, Molly K. Reif, Todd M. Swannack
2022 Remote Sensing  
This represents an example of how the model results can be used to assign economic value of ecosystem services in a coastal system to justify different management and conservation initiatives.  ...  A majority of woody cells were misclassified as herbaceous likely because of the similarity in the predictive parameter distributions.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs14061377 fatcat:6na42jouojhehir3nolmmc5gte

Integrating National Ecological Observatory Network (NEON) Airborne Remote Sensing and In-Situ Data for Optimal Tree Species Classification

Victoria M. Scholl, Megan E. Cattau, Maxwell B. Joseph, Jennifer K. Balch
2020 Remote Sensing  
An important aspect of predicting species using remote sensing data is creating high-quality training sets for optimal classification purposes.  ...  We combine in-situ and airborne remote sensing NEON data to evaluate the impact of automated training set preparation and a novel data preprocessing workflow on classifying the four dominant subalpine  ...  This material is based in part upon work supported by the National Science Foundation through the NEON Program.  ... 
doi:10.3390/rs12091414 fatcat:ibxjtvl5ajfgzkspu6pk5e7oxq

Evaluating Biomass of Juniper Trees (Juniperus pinchotii) from Imagery-Derived Canopy Area Using the Support Vector Machine Classifier

Mustafa Mirik, Sriroop Chaudhuri, Brady Surber, Srinivasulu Ale, Robert James Ansley
2013 Advances in Remote Sensing  
Our objectives were to: 1) identify and delineate individual redberry juniper (Juniperus pinchotii) plants from surrounding live vegetation using the support vector machine method for classifying two-dimensional  ...  Much of the remote sensing research previously completed has focused on determining carbon stocks in forested ecosystems with little attention directed to estimate AGB amount in rangelands.  ...  Images used in this study were made available by the USDA-NRCS. We also thank Mimi Roy for technical discussion and Andy Bell for assisting with data collection.  ... 
doi:10.4236/ars.2013.22021 fatcat:35dh5p3ouraffi56knycoc4kru

Using Satellite Remote Sensing and Machine Learning Techniques Towards Precipitation Prediction and Vegetation Classification

D. Stampoulis, Future H2O, Office of Knowledge Enterprise Development, Arizona State University, Tempe, AZ 85281, USA, H. G. Damavandi, D. Boscovic, J. Sabo, Future H2O, Office of Knowledge Enterprise Development, Arizona State University, Tempe, AZ 85281, USA, Center for Assured and Scalable Data Engineering, Arizona State University, Tempe, AZ 85281, USA, Future H2O, Office of Knowledge Enterprise Development, Arizona State University, Tempe, AZ 85281, USA
2020 Journal of Environmental Informatics  
The characteristics of the predicted precipitation were in turn used to classify vegetation regimes in East Africa.  ...  Our predictive models were able to forecast the three vegetation regimes, i.e., Forest/Woody Savanna, Savanna/Grasslands and Shrubland, with precision rate of at least 81% for all of the aforementioned  ...  The authors would like to acknowledge and appreciate Dr. Francis J. Turk from the Jet Propulsion Laboratory (JPL) and Dr. Li Li from the Naval Research Laboratory (NRL) for providing the WindSat data.  ... 
doi:10.3808/jei.202000427 fatcat:3zwlwu6gyndlzhmohucjrmsyhi

Using Very-High-Resolution Multispectral Classification to Estimate Savanna Fractional Vegetation Components

Andrea E. Gaughan, Nicholas E. Kolarik, Forrest R. Stevens, Narcisa G. Pricope, Lin Cassidy, Jonathan Salerno, Karen M. Bailey, Michael Drake, Kyle Woodward, Joel Hartter
2022 Remote Sensing  
When priorities are placed on ecological integrity, remotely sensed estimates of fractional vegetation components (FVCs) are useful for measuring landscape-level habitat structure and function.  ...  Using Parrot Sequoia imagery, flown on a DJI Mavic Pro micro-quadcopter, we compare pixel- and segment-based random forest classifiers alongside a vegetation height-threshold model for characterizing the  ...  We also thank the anonymous reviewers for their insight and feedback for improving the final version of this manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs14030551 fatcat:h2xrwnm7tbcwtdrzypqeqn2cry

Geospatial modeling of land cover change in the Chocó-Darien global ecoregion of South America; One of most biodiverse and rainy areas in the world

J. Camilo Fagua, R. Douglas Ramsey, Julia A. Jones
2019 PLoS ONE  
Furthermore, the availability of high-resolution remotely sensed data is low for developing countries before 2015.  ...  The analysis of land-use and land-cover (LULC) change within the CGE using remotely sensed imagery is challenging because this area is considered to be one of the rainiest places on the planet (hence high  ...  Acknowledgments We acknowledged COLCIENCIAS-Colombia (529-2011) and Fulbright-US to support this research, Ecology Center and Remote Sensing/GIS lab of Utah State University-US to provide additional financial  ... 
doi:10.1371/journal.pone.0211324 pmid:30707720 pmcid:PMC6358088 fatcat:2l4y57vienbajglaruu2q2s4i4

Mapping habitat and biological diversity in the Maasai Mara ecosystem

B. O. Oindo, A. K. Skidmore, P. de Salvo
2003 International Journal of Remote Sensing  
Remotely sensed data hold tremendous potential for mapping species habitats and indicators of biological diversity, such as species richness.  ...  The accuracy of the resulting habitat map was assessed and indices of habitat diversity computed.  ...  Mwendwa, Director of Department Resource Surveys and Remote Sensing (DRSRS), for providing the animal species data.  ... 
doi:10.1080/01431160210144552 fatcat:gkqsshkv5zdm3hek3clymfb5km

Extraction of Kenyan Grassland Information Using PROBA-V Based on RFE-RF Algorithm

Panpan Wei, Weiwei Zhu, Yifan Zhao, Peng Fang, Xiwang Zhang, Nana Yan, Hao Zhao
2021 Remote Sensing  
Therefore, this paper uses Kenya as the study area to investigate the effective and fast approach for grassland mapping with 100-m resolution using the open resources in the Google Earth Engine cloud platform  ...  The main conclusions are as follows. (1) In the feature combination optimization part of this paper, the machine learning algorithm is used to compare the scores and standard deviations of several common  ...  Acknowledgments: We thank the data providers for this study: the PROBA-V data and the SRT-MGL1_003 data were provided by ESA and NASA JPL.CGLS-LC100 data was provided Copernicus.  ... 
doi:10.3390/rs13234762 fatcat:2kne4676djhkhhpusnvz2kann4
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