22.5.11.6.4 Palm Trees, Oil Palms, Trees as Crops

Chapter Contents (Back)
Orchards. Palm Trees.

Srestasathiern, P.[Panu], Rakwatin, P.[Preesan],
Oil Palm Tree Detection with High Resolution Multi-Spectral Satellite Imagery,
RS(6), No. 10, 2014, pp. 9749-9774.
DOI Link 1411
BibRef

Li, L.[Li], Dong, J.W.[Jin-Wei], Tenku, S.N.[Simon Njeudeng], Xiao, X.M.[Xiang-Ming],
Mapping Oil Palm Plantations in Cameroon Using PALSAR 50-m Orthorectified Mosaic Images,
RS(7), No. 2, 2015, pp. 1206-1224.
DOI Link 1503
BibRef

Teng, K.C.[Khar Chun], Koay, J.Y.[Jun Yi], Tey, S.H.[Seng Heng], Lim, K.S.[Ka Sing], Ewe, H.T.[Hong Tat], Chuah, H.T.[Hean Teik],
A Dense Medium Microwave Backscattering Model for the Remote Sensing of Oil Palm,
GeoRS(53), No. 6, June 2015, pp. 3250-3259.
IEEE DOI 1503
microwave imaging BibRef

Chemura, A.[Abel], van Duren, I.[Iris], van Leeuwen, L.M.[Louise M.],
Determination of the age of oil palm from crown projection area detected from WorldView-2 multispectral remote sensing data: The case of Ejisu-Juaben district, Ghana,
PandRS(100), No. 1, 2015, pp. 118-127.
Elsevier DOI 1502
Age detection BibRef

Nunes, M.H.[Matheus H.], Ewers, R.M.[Robert M.], Turner, E.C.[Edgar C.], Coomes, D.A.[David A.],
Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Toh, C.M., Ewe, H.T., Tey, S.H., Tay, Y.H.,
A Study on Oil Palm Remote Sensing at L-Band With Dense Medium Microwave Backscattering Model,
GeoRS(57), No. 10, October 2019, pp. 8037-8047.
IEEE DOI 1910
backscatter, radar imaging, radiative transfer, remote sensing by radar, synthetic aperture radar, vegetation BibRef

Li, W.[Weijia], Fu, H.[Haohuan], Yu, L.[Le], Cracknell, A.[Arthur],
Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Hidayat, S.[Sarip], MATSUOKA, M.[Masayuki], Baja, S.[Sumbangan], Rampisela, D.A.[Dorothea Agnes],
Object-Based Image Analysis for Sago Palm Classification: The Most Important Features from High-Resolution Satellite Imagery,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Al-Ruzouq, R.[Rami], Shanableh, A.[Abdallah], Gibril, M.B.A.[Mohamed Barakat A.], AL-Mansoori, S.[Saeed],
Image Segmentation Parameter Selection and Ant Colony Optimization for Date Palm Tree Detection and Mapping from Very-High-Spatial-Resolution Aerial Imagery,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Li, W.[Weijia], Dong, R.[Runmin], Fu, H.[Haohuan], Yu, L.[Le],
Large-Scale Oil Palm Tree Detection from High-Resolution Satellite Images Using Two-Stage Convolutional Neural Networks,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Descals, A.[Adriŕ], Szantoi, Z.[Zoltan], Meijaard, E.[Erik], Sutikno, H.[Harsono], Rindanata, G.[Guruh], Wich, S.[Serge],
Oil Palm (Elaeis guineensis) Mapping with Details: Smallholder versus Industrial Plantations and their Extent in Riau, Sumatra,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Li, W.H.[Wen-Hui], Fu, D.J.[Dong-Jie], Su, F.Z.[Fen-Zhen], Xiao, Y.[Yang],
Spatial-Temporal Evolution and Analysis of the Driving Force of Oil Palm Patterns in Malaysia from 2000 to 2018,
IJGI(9), No. 4, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Freudenberg, M.[Maximilian], Nölke, N.[Nils], Agostini, A.[Alejandro], Urban, K.[Kira], Wörgötter, F.[Florentin], Kleinn, C.[Christoph],
Large Scale Palm Tree Detection in High Resolution Satellite Images Using U-Net,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Casapia, X.T.[Ximena Tagle], Falen, L.[Lourdes], Bartholomeus, H.[Harm], Cárdenas, R.[Rodolfo], Flores, G.[Gerardo], Herold, M.[Martin], Coronado, E.N.H.[Eurídice N. Honorio], Baker, T.R.[Timothy R.],
Identifying and Quantifying the Abundance of Economically Important Palms in Tropical Moist Forest Using UAV Imagery,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link 2001
BibRef

Wagner, F.H.[Fabien H.], Dalagnol, R.[Ricardo], Casapia, X.T.[Ximena Tagle], Streher, A.S.[Annia S.], Phillips, O.L.[Oliver L.], Gloor, E.[Emanuel], Aragăo, L.E.O.C.[Luiz E. O. C.],
Regional Mapping and Spatial Distribution Analysis of Canopy Palms in an Amazon Forest Using Deep Learning and VHR Images,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007
BibRef

Zheng, J.P.[Jue-Peng], Fu, H.H.[Hao-Huan], Li, W.J.[Wei-Jia], Wu, W.Z.[Wen-Zhao], Zhao, Y.[Yi], Dong, R.M.[Run-Min], Yu, L.[Le],
Cross-regional oil palm tree counting and detection via a multi-level attention domain adaptation network,
PandRS(167), 2020, pp. 154 - 177.
Elsevier DOI 2008
BibRef
Earlier: A4, A1, A2, A3, A7, Only
Cross-Regional Oil Palm Tree Detection,
AgriVision20(248-257)
IEEE DOI 2008
Oil palm tree detection, Attention mechanism, Domain adaptation, Deep learning, Adversarial neural networks. Vegetation, Oils, Remote sensing, Object detection, Satellites, Feature extraction, Machine learning BibRef

Migolet, P.[Pierre], Goďta, K.[Kalifa],
Evaluation of FORMOSAT-2 and PlanetScope Imagery for Aboveground Oil Palm Biomass Estimation in a Mature Plantation in the Congo Basin,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Avtar, R.[Ram], Suab, S.A.[Stanley Anak], Syukur, M.S.[Mohd Shahrizan], Korom, A.[Alexius], Umarhadi, D.A.[Deha Agus], Yunus, A.P.[Ali P.],
Assessing the Influence of UAV Altitude on Extracted Biophysical Parameters of Young Oil Palm,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Viera-Torres, M.[Mauricio], Sinde-González, I.[Izar], Gil-Docampo, M.[Mariluz], Bravo-Yandún, V.[Vladimir], Toulkeridis, T.[Theofilos],
Generating the Baseline in the Early Detection of Bud Rot and Red Ring Disease in Oil Palms by Geospatial Technologies,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Vermote, E.F.[Eric F.], Skakun, S.[Sergii], Becker-Reshef, I.[Inbal], Saito, K.[Keiko],
Remote Sensing of Coconut Trees in Tonga Using Very High Spatial Resolution WorldView-3 Data,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Culman, M.[María], Delalieux, S.[Stephanie], van Tricht, K.[Kristof],
Individual Palm Tree Detection Using Deep Learning on RGB Imagery to Support Tree Inventory,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
BibRef


Suab, S.A., Syukur, M.S., Avtar, R., Korom, A.,
Unmanned Aerial Vehicle (UAV) Derived Normalised Difference Vegetation Index (NDVI) and Crown Projection Area (CPA) to Detect Health Conditions of Young Oil Palm Trees for Precision Agriculture,
GGT19(611-614).
DOI Link 1912
BibRef

Shaharum, N.S.N., Shafri, H.Z.M., Ghani, W.A.W.A.K., Samsatli, S., Yusuf, B., Al-Habshi, M.M.A., Prince, H.M.,
Image Classification for Mapping Oil Palm Distribution Via Support Vector Machine Using Scikit-learn Module,
GeoDisast18(133-137).
DOI Link 1901
BibRef

Idbraim, S.[Soufiane], Mammass, D.[Driss], Bouzalim, L.[Lahoucine], Oudra, M.[Moulid], Labrador-Garca, M.[Mauricio], Arbelo, M.[Manuel],
Palm Trees Detection from High Spatial Resolution Satellite Imagery Using a New Contextual Classification Method with Constraints,
ICISP16(283-292).
WWW Link. 1606
BibRef

Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Forest Analysis, Depth, LiDAR, Laser Scanner .


Last update:Nov 23, 2020 at 10:27:11