22.2.7.2 Invasive Plants, Weeds, Exotic Plants

Chapter Contents (Back)
Weeds. Invasive Plants. Exotic Plants. Trees can be weeds in this sense. Close Range Analysis for weeds:
See also Weed Detection, Close Range.

Pearlstine, L.[Leonard], Portier, K.M.[Kenneth M.], Smith, S.E.[Scot E.],
Textural Discrimination of an Invasive Plant, Schinus terebinthifolius, from Low Altitude Aerial Digital Imagery,
PhEngRS(71), No. 3, March 2005, pp. 289-298.
WWW Link. 0509
Texture features derived from first and second order statistics and edge components in high-resolution digital color infrared images were tested for their ability to discriminate Schinus terebinthifolius in multiple linear logistic regressions. BibRef

Olsson, A., van Leeuwen, W., Marsh, S.,
Feasibility of Invasive Grass Detection in a Desertscrub Community Using Hyperspectral Field Measurements and Landsat TM Imagery,
RS(3), No. 10, October 2011, pp. 2283-2304.
DOI Link 1203
BibRef

Jones, D., Pike, S., Thomas, M., Murphy, D.,
Object-Based Image Analysis for Detection of Japanese Knotweed s.l. taxa (Polygonaceae) in Wales (UK),
RS(3), No. 2, February 2011, pp. 319-342.
DOI Link 1203
BibRef

Mirik, M., Ansley, R.,
Utility of Satellite and Aerial Images for Quantification of Canopy Cover and Infilling Rates of the Invasive Woody Species Honey Mesquite (Prosopis Glandulosa) on Rangeland,
RS(4), No. 7, July 2012, pp. 1947-1962.
DOI Link 1208
BibRef

Taylor, S.L.[Sarah L.], Hill, R.A.[Ross A.], Edwards, C.[Colin],
Characterising invasive non-native Rhododendron ponticum spectra signatures with spectroradiometry in the laboratory and field: Potential for remote mapping,
PandRS(81), No. 1, July 2013, pp. 70-81.
Elsevier DOI 1306
Hyperspectral remote sensing; Invasive species; Logistic regression; Species discrimination; Leaf plasticity BibRef

Mirik, M., Ansley, R., Steddom, K., Jones, D., Rush, C., Michels, G., Elliott, N.,
Remote Distinction of A Noxious Weed (Musk Thistle: CarduusNutans) Using Airborne Hyperspectral Imagery and the Support Vector Machine Classifier,
RS(5), No. 2, February 2013, pp. 612-630.
DOI Link 1303
BibRef

Hung, C.[Calvin], Xu, Z.[Zhe], Sukkarieh, S.[Salah],
Feature Learning Based Approach for Weed Classification Using High Resolution Aerial Images from a Digital Camera Mounted on a UAV,
RS(6), No. 12, 2014, pp. 12037-12054.
DOI Link 1412
BibRef

Levick, S.R.[Shaun R.], Setterfield, S.A.[Samantha A.], Rossiter-Rachor, N.A.[Natalie A.], Hutley, L.B.[Lindsay B.], MacMaster, D.[Damien], Hacker, J.M.[Jorg M.],
Monitoring the Distribution and Dynamics of an Invasive Grass in Tropical Savanna Using Airborne LiDAR,
RS(7), No. 5, 2015, pp. 5117-5132.
DOI Link 1506
BibRef

Lehmann, J.R.K.[Jan Rudolf Karl], Große-Stoltenberg, A.[André], Römer, M.[Meike], Oldeland, J.[Jens],
Field Spectroscopy in the VNIR-SWIR Region to Discriminate between Mediterranean Native Plants and Exotic-Invasive Shrubs Based on Leaf Tannin Content,
RS(7), No. 2, 2015, pp. 1225-1241.
DOI Link 1503
BibRef

Wallace, C.S.A.[Cynthia S. A.], Walker, J.J.[Jessica J.], Skirvin, S.M.[Susan M.], Patrick-Birdwell, C.[Caroline], Weltzin, J.F.[Jake F.], Raichle, H.[Helen],
Mapping Presence and Predicting Phenological Status of Invasive Buffelgrass in Southern Arizona Using MODIS, Climate and Citizen Science Observation Data,
RS(8), No. 7, 2016, pp. 524.
DOI Link 1608
BibRef

Peerbhay, K.[Kabir], Mutanga, O.[Onisimo], Lottering, R.[Romano], Bangamwabo, V.[Victor], Ismail, R.[Riyad],
Detecting bugweed (Solanum mauritianum) abundance in plantation forestry using multisource remote sensing,
PandRS(121), No. 1, 2016, pp. 167-176.
Elsevier DOI 1609
Remote sensing BibRef

Liu, X.[Xiang], Liu, H.Y.[Hui-Yu], Gong, H.B.[Hai-Bo], Lin, Z.S.[Zhen-Shan], Lv, S.C.[Shi-Cheng],
Appling the One-Class Classification Method of Maxent to Detect an Invasive Plant Spartina alterniflora with Time-Series Analysis,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Dutra Silva, L.[Lara], Brito de Azevedo, E.[Eduardo], Bento Elias, R.[Rui], Silva, L.[Luís],
Species Distribution Modeling: Comparison of Fixed and Mixed Effects Models Using INLA,
IJGI(6), No. 12, 2017, pp. xx-yy.
DOI Link 1801
Invasive species. BibRef

Alvarez-Taboada, F.[Flor], Paredes, C.[Claudio], Julián-Pelaz, J.[Julia],
Mapping of the Invasive Species Hakea sericea Using Unmanned Aerial Vehicle (UAV) and WorldView-2 Imagery and an Object-Oriented Approach,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Martin, F.M.[François-Marie], Müllerová, J.[Jana], Borgniet, L.[Laurent], Dommanget, F.[Fanny], Breton, V.[Vincent], Evette, A.[André],
Using Single- and Multi-Date UAV and Satellite Imagery to Accurately Monitor Invasive Knotweed Species,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Louargant, M.[Marine], Jones, G.[Gawain], Faroux, R.[Romain], Paoli, J.N.[Jean-Noël], Maillot, T.[Thibault], Gée, C.[Christelle], Villette, S.[Sylvain],
Unsupervised Classification Algorithm for Early Weed Detection in Row-Crops by Combining Spatial and Spectral Information,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Pflanz, M.[Michael], Nordmeyer, H.[Henning], Schirrmann, M.[Michael],
Weed Mapping with UAS Imagery and a Bag of Visual Words Based Image Classifier,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Bah, M.D.[M Dian], Hafiane, A.[Adel], Canals, R.[Raphael],
Deep Learning with Unsupervised Data Labeling for Weed Detection in Line Crops in UAV Images,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Tarantino, C.[Cristina], Casella, F.[Francesca], Adamo, M.[Maria], Lucas, R.[Richard], Beierkuhnlein, C.[Carl], Blonda, P.[Palma],
Ailanthus altissima mapping from multi-temporal very high resolution satellite images,
PandRS(147), 2019, pp. 90-103.
Elsevier DOI 1901
Invasive species, Alien species, mapping, multi-temporal WorldView-2 data, Remote sensing, Novel ecosystems BibRef

Rasti, P.[Pejman], Ahmad, A.[Ali], Samiei, S.[Salma], Belin, E.[Etienne], Rousseau, D.[David],
Supervised Image Classification by Scattering Transform with Application to Weed Detection in Culture Crops of High Density,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Mbaabu, P.R.[Purity Rima], Ng, W.T.[Wai-Tim], Schaffner, U.[Urs], Gichaba, M.[Maina], Olago, D.[Daniel], Choge, S.[Simon], Oriaso, S.[Silas], Eckert, S.[Sandra],
Spatial Evolution of Prosopis Invasion and its Effects on LULC and Livelihoods in Baringo, Kenya,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Zhu, X.D.[Xu-Dong], Meng, L.X.[Ling-Xuan], Zhang, Y.[Yihui], Weng, Q.[Qihao], Morris, J.[James],
Tidal and Meteorological Influences on the Growth of Invasive Spartina alterniflora: Evidence from UAV Remote Sensing,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Abeysinghe, T.[Tharindu], Milas, A.S.[Anita Simic], Arend, K.[Kristin], Hohman, B.[Breann], Reil, P.[Patrick], Gregory, A.[Andrew], Vázquez-Ortega, A.[Angélica],
Mapping Invasive Phragmites australis in the Old Woman Creek Estuary Using UAV Remote Sensing and Machine Learning Classifiers,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Luo, Q.[Qian], Song, J.L.[Jin-Ling], Yang, L.[Lei], Wang, J.[Jindi],
Improved Spring Vegetation Phenology Calculation Method Using a Coupled Model and Anomalous Point Detection,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Farooq, A.[Adnan], Jia, X.P.[Xiu-Ping], Hu, J.K.[Jian-Kun], Zhou, J.[Jun],
Multi-Resolution Weed Classification via Convolutional Neural Network and Superpixel Based Local Binary Pattern Using Remote Sensing Images,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908

See also Superpixel-Based Graphical Model for Remote Sensing Image Mapping. BibRef

Masemola, C., Cho, M.A., Ramoelo, A.,
Assessing the Effect of Seasonality on Leaf and Canopy Spectra for the Discrimination of an Alien Tree Species, Acacia Mearnsii, From Co-Occurring Native Species Using Parametric and Nonparametric Classifiers,
GeoRS(57), No. 8, August 2019, pp. 5853-5867.
IEEE DOI 1908
geophysics computing, pattern classification, time series, vegetation, vegetation mapping, native plant species, random forest (RF) BibRef

Bayat, M.[Mahmoud], Noi, P.T.[Phan Thanh], Zare, R.[Rozita], Bui, D.T.[Dieu Tien],
A Semi-empirical Approach Based on Genetic Programming for the Study of Biophysical Controls on Diameter-Growth of Fagus orientalis in Northern Iran,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Dash, J.P.[Jonathan P.], Watt, M.S.[Michael S.], Paul, T.S.H.[Thomas S. H.], Morgenroth, J.[Justin], Pearse, G.D.[Grant D.],
Early Detection of Invasive Exotic Trees Using UAV and Manned Aircraft Multispectral and LiDAR Data,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Kiala, Z.[Zolo], Mutanga, O.[Onisimo], Odindi, J.[John], Peerbhay, K.[Kabir],
Feature Selection on Sentinel-2 Multispectral Imagery for Mapping a Landscape Infested by Parthenium Weed,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Ghoussein, Y.[Youssra], Nicolas, H.[Hervé], Haury, J.[Jacques], Fadel, A.[Ali], Pichelin, P.[Pascal], Hamdan, H.A.[Hussein Abou], Faour, G.[Ghaleb],
Multitemporal Remote Sensing Based on an FVC Reference Period Using Sentinel-2 for Monitoring Eichhornia crassipes on a Mediterranean River,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
Water hyacinth. BibRef

Villarreal, M.L.[Miguel L.], Soulard, C.E.[Christopher E.], Waller, E.K.[Eric K.],
Landsat Time Series Assessment of Invasive Annual Grasses Following Energy Development,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Landmann, T.[Tobias], Dubovyk, O.[Olena], Ghazaryan, G.[Gohar], Kimani, J.[Jackson], Abdel-Rahman, E.M.[Elfatih M.],
Wide-area invasive species propagation mapping is possible using phenometric trends,
PandRS(159), 2020, pp. 1-12.
Elsevier DOI 1912
MODIS EVI, Phenometrics, Land degradation, Bush encroachment, Logistic regression BibRef

de Castro, A.I.[Ana I.], Peña, J.M.[José M.], Torres-Sánchez, J.[Jorge], Jiménez-Brenes, F.M.[Francisco M.], Valencia-Gredilla, F.[Francisco], Recasens, J.[Jordi], López-Granados, F.[Francisca],
Mapping Cynodon Dactylon Infesting Cover Crops with an Automatic Decision Tree-OBIA Procedure and UAV Imagery for Precision Viticulture,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link 2001
BibRef

Sabat-Tomala, A.[Anita], Raczko, E.[Edwin], Zagajewski, B.[Bogdan],
Comparison of Support Vector Machine and Random Forest Algorithms for Invasive and Expansive Species Classification Using Airborne Hyperspectral Data,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Labonté, J.[Joanie], Drolet, G.[Guillaume], Sylvain, J.D.[Jean-Daniel], Thiffault, N.[Nelson], Hébert, F.[Francois], Girard, F.[Francois],
Phenology-Based Mapping of an Alien Invasive Species Using Time Series of Multispectral Satellite Data: A Case-Study with Glossy Buckthorn in Québec, Canada,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Tian, Y.L.[Yan-Lin], Jia, M.M.[Ming-Ming], Wang, Z.M.[Zong-Ming], Mao, D.H.[De-Hua], Du, B.[Baojia], Wang, C.[Chao],
Monitoring Invasion Process of Spartina alterniflora by Seasonal Sentinel-2 Imagery and an Object-Based Random Forest Classification,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Liu, Y.F.[Yi-Fei], Ma, J.[Jun], Wang, X.X.[Xin-Xin], Zhong, Q.Y.[Qiao-Yan], Zong, J.M.[Jia-Min], Wu, W.B.[Wan-Ben], Wang, Q.[Qing], Zhao, B.[Bin],
Joint Effect of Spartina alterniflora Invasion and Reclamation on the Spatial and Temporal Dynamics of Tidal Flats in Yangtze River Estuary,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Sheffield, K.[Kathryn], Dugdale, T.[Tony],
Supporting Urban Weed Biosecurity Programs with Remote Sensing,
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Sivakumar, A.N.V.[Arun Narenthiran Veeranampalayam], Li, J.[Jiating], Scott, S.[Stephen], Psota, E.[Eric], Jhala, A.J.[Amit J.], Luck, J.D.[Joe D.], Shi, Y.[Yeyin],
Comparison of Object Detection and Patch-Based Classification Deep Learning Models on Mid- to Late-Season Weed Detection in UAV Imagery,
RS(12), No. 13, 2020, pp. xx-yy.
DOI Link 2007
BibRef

Masemola, C.[Cecilia], Cho, M.A.[Moses Azong], Ramoelo, A.[Abel],
Towards a semi-automated mapping of Australia native invasive alien Acacia trees using Sentinel-2 and radiative transfer models in South Africa,
PandRS(166), 2020, pp. 153-168.
Elsevier DOI 2007
Invasive alien plant, Radiative Transfer Model, PROSAIL, Sentinel-2, Leaf Area Index, Canopy Chlorophyll Content BibRef

Worqlul, A.W.[Abeyou W.], Ayana, E.K.[Essayas K.], Dile, Y.T.[Yihun T.], Moges, M.A.[Mamaru A.], Dersseh, M.G.[Minychl G.], Tegegne, G.[Getachew], Kibret, S.[Solomon],
Spatiotemporal Dynamics and Environmental Controlling Factors of the Lake Tana Water Hyacinth in Ethiopia,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Gée, C.[Christelle], Denimal, E.[Emmanuel],
RGB Image-Derived Indicators for Spatial Assessment of the Impact of Broadleaf Weeds on Wheat Biomass,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Cabezas, M.[Mariano], Kentsch, S.[Sarah], Tomhave, L.[Luca], Gross, J.[Jens], Caceres, M.L.L.[Maximo Larry Lopez], Diez, Y.[Yago],
Detection of Invasive Species in Wetlands: Practical DL with Heavily Imbalanced Data,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Dutta, D.[Dipanwita], Chen, G.[Gang], Chen, C.[Chen], Gagné, S.A.[Sara A.], Li, C.[Changlin], Rogers, C.[Christa], Matthews, C.[Christopher],
Detecting Plant Invasion in Urban Parks with Aerial Image Time Series and Residual Neural Network,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Pepe, M.[Monica], Pompilio, L.[Loredana], Gioli, B.[Beniamino], Busetto, L.[Lorenzo], Boschetti, M.[Mirco],
Detection and Classification of Non-Photosynthetic Vegetation from PRISMA Hyperspectral Data in Croplands,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Peteinatos, G.G.[Gerassimos G.], Reichel, P.[Philipp], Karouta, J.[Jeremy], Andújar, D.[Dionisio], Gerhards, R.[Roland],
Weed Identification in Maize, Sunflower, and Potatoes with the Aid of Convolutional Neural Networks,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Liu, X.[Xiang], Liu, H.Y.[Hui-Yu], Datta, P.[Pawanjeet], Frey, J.[Julian], Koch, B.[Barbara],
Mapping an Invasive Plant Spartina alterniflora by Combining an Ensemble One-Class Classification Algorithm with a Phenological NDVI Time-Series Analysis Approach in Middle Coast of Jiangsu, China,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Singh, G.[Geethen], Reynolds, C.[Chevonne], Byrne, M.[Marcus], Rosman, B.[Benjamin],
A Remote Sensing Method to Monitor Water, Aquatic Vegetation, and Invasive Water Hyacinth at National Extents,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Haagsma, M.[Marja], Page, G.F.M.[Gerald F. M.], Johnson, J.S.[Jeremy S.], Still, C.[Christopher], Waring, K.M.[Kristen M.], Sniezko, R.A.[Richard A.], Selker, J.S.[John S.],
Using Hyperspectral Imagery to Detect an Invasive Fungal Pathogen and Symptom Severity in Pinus strobiformis Seedlings of Different Genotypes,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Zou, K.L.[Kun-Lin], Chen, X.[Xin], Zhang, F.[Fan], Zhou, H.[Hang], Zhang, C.L.[Chun-Long],
A Field Weed Density Evaluation Method Based on UAV Imaging and Modified U-Net,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Ronay, I.[Inbal], Ephrath, J.E.[Jhonathan E.], Eizenberg, H.[Hanan], Blumberg, D.G.[Dan G.], Maman, S.[Shimrit],
Hyperspectral Reflectance and Indices for Characterizing the Dynamics of Crop-Weed Competition for Water,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Pfitzner, K.[Kirrilly], Bartolo, R.[Renee], Whiteside, T.[Tim], Loewensteiner, D.[David], Esparon, A.[Andrew],
Hyperspectral Monitoring of Non-Native Tropical Grasses over Phenological Seasons,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Bolch, E.A.[Erik A.], Hestir, E.L.[Erin L.], Khanna, S.[Shruti],
Performance and Feasibility of Drone-Mounted Imaging Spectroscopy for Invasive Aquatic Vegetation Detection,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Benjamin, A.R.[Adam R.], Abd-Elrahman, A.[Amr], Gettys, L.A.[Lyn A.], Hochmair, H.H.[Hartwig H.], Thayer, K.[Kyle],
Monitoring the Efficacy of Crested Floatingheart (Nymphoides cristata) Management with Object-Based Image Analysis of UAS Imagery,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Bransky, N.[Nathaniel], Sankey, T.[Temuulen], Sankey, J. .B.[Joel B.], Johnson, M.[Matthew], Jamison, L.[Levi],
Monitoring Tamarix Changes Using WorldView-2 Satellite Imagery in Grand Canyon National Park, Arizona,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
Tamarisk -- invasive shrub. BibRef

Kaivosoja, J.[Jere], Hautsalo, J.H.[Ju-Ho], Heikkinen, J.[Jaakko], Hiltunen, L.[Lea], Ruuttunen, P.[Pentti], Näsi, R.[Roope], Niemeläinen, O.[Oiva], Lemsalu, M.[Madis], Honkavaara, E.[Eija], Salonen, J.[Jukka],
Reference Measurements in Developing UAV Systems for Detecting Pests, Weeds, and Diseases,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Larson, K.B.[Kyle B.], Tuor, A.R.[Aaron R.],
Deep Learning Classification of Cheatgrass Invasion in the Western United States Using Biophysical and Remote Sensing Data,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Mattivi, P.[Pietro], Pappalardo, S.E.[Salvatore Eugenio], Nikolic, N.[Nebojša], Mandolesi, L.[Luca], Persichetti, A.[Antonio], de Marchi, M.[Massimo], Masin, R.[Roberta],
Can Commercial Low-Cost Drones and Open-Source GIS Technologies Be Suitable for Semi-Automatic Weed Mapping for Smart Farming? A Case Study in NE Italy,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Brooks, C.[Colin], Weinstein, C.[Charlotte], Poley, A.[Andrew], Grimm, A.[Amanda], Marion, N.[Nicholas], Bourgeau-Chavez, L.[Laura], Hansen, D.[Dana], Kowalski, K.[Kurt],
Using Uncrewed Aerial Vehicles for Identifying the Extent of Invasive Phragmites australis in Treatment Areas Enrolled in an Adaptive Management Program,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Hu, C.S.[Cheng-Song], Sapkota, B.B.[Bishwa B.], Thomasson, J.A.[J. Alex], Bagavathiannan, M.V.[Muthukumar V.],
Influence of Image Quality and Light Consistency on the Performance of Convolutional Neural Networks for Weed Mapping,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Huang, T.C.[Tie-Cheng], Ding, X.J.[Xiao-Juan], Zhu, X.[Xuan], Chen, S.J.[Shu-Jiang], Chen, M.Y.[Meng-Yu], Jia, X.[Xiang], Lai, F.B.[Feng-Bing], Zhang, X.L.[Xiao-Li],
Assessment of Poplar Looper (Apocheima cinerarius Erschoff) Infestation on Euphrates (Populus euphratica) Using Time-Series MODIS NDVI Data Based on the Wavelet Transform and Discriminant Analysis,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Quan, L.Z.[Long-Zhe], Li, H.D.[Heng-Da], Li, H.L.[Hai-Long], Jiang, W.[Wei], Lou, Z.X.[Zhao-Xia], Chen, L.Q.[Li-Qing],
Two-Stream Dense Feature Fusion Network Based on RGB-D Data for the Real-Time Prediction of Weed Aboveground Fresh Weight in a Field Environment,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
BibRef


Asad, M.H.[Muhammad Hamza], Bais, A.[Abdul],
Weed Density Estimation Using Semantic Segmentation,
PSIVT19(162-171).
Springer DOI 2003
BibRef

Baidar, T., Shrestha, A.B., Ranjit, R., Adhikari, R., Ghimire, S., Shrestha, N.,
Impact Assessment of Mikania Micrantha On Land Cover And Maxent Modeling to Predict Its Potential Invasion Sites,
Hannover17(305-310).
DOI Link 1805
BibRef

Martínez-Sánchez, J., González-de Santos, L.M., Novo, A., González-Jorge, H.,
UAV and Satellite Imagery Applied to Alien Species Mapping in NW Spain,
UAV-g19(455-459).
DOI Link 1912
BibRef

Mudereri, B.T., Dube, T., Adel-Rahman, E.M., Niassy, S., Kimathi, E., Khan, Z., Landmann, T.,
A Comparative Analysis of Planetscope and Sentinel Sentinel-2 Space-borne Sensors in Mapping Striga Weed Using Guided Regularised Random Forest Classification Ensemble,
IWIDF19(701-708).
DOI Link 1912
BibRef

Förster, M., Schmidt, T., Wolf, R., Kleinschmit, B., Fassnacht, F.E., Cabezas, J., Kattenborn, T.,
Detecting the spread of invasive species in central Chile with a Sentinel-2 time-series,
MultiTemp17(1-4)
IEEE DOI 1712
geophysical image processing, hyperspectral imaging, image segmentation, land cover, least squares approximations, time-series BibRef

Marshall, V., Lewis, M., Ostendorf, B.,
Do Additional Bands (coastal, Nir-2, Red-edge And Yellow) In Worldview-2 Multispectral Imagery Improve Discrimination Of An Invasive Tussock, Buffel Grass (cenchrus Ciliaris)?,
ISPRS12(XXXIX-B8:277-281).
DOI Link 1209
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Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Soybean Crop Analysis, Beans, Production, Detection, Health, Change .


Last update:Jul 11, 2021 at 20:18:24