23.2.8.8.3 Trees in Pasture, Grassland, Rangeland, Savanna, Shrubs

Chapter Contents (Back)
Grassland Classification. Rangeland. Shrubs. Pasture. Savanna.

Chen, Q.[Qi], Baldocchi, D.[Dennis], Gong, P.[Peng], Kelly, M.[Maggi],
Isolating Individual Trees in a Savanna Woodland Using Small Footprint Lidar Data,
PhEngRS(72), No. 8, August 2006, pp. 923-392.
WWW Link. 0610
A new method for detecting treetops from lidar data and applying marked-controlled watershed segmentation to the isolation of individual trees.
See also Estimating Basal Area and Stem Volume for Individual Trees from Lidar Data. BibRef

Cho, M.A., Debba, P., Mathieu, R., Naidoo, L., van Aardt, J., Asner, G.P.,
Improving Discrimination of Savanna Tree Species Through a Multiple-Endmember Spectral Angle Mapper Approach: Canopy-Level Analysis,
GeoRS(48), No. 11, November 2010, pp. 4133-4142.
IEEE DOI 1011
BibRef

Naidoo, L., Cho, M.A., Mathieu, R., Asner, G.P.,
Classification of savanna tree species, in the Greater Kruger National Park region, by integrating hyperspectral and LiDAR data in a Random Forest data mining environment,
PandRS(69), No. 1, April 2012, pp. 167-179.
Elsevier DOI 1202
Savanna tree species; Spectral variability; Tree height; Random Forest; Predictor datasets BibRef

Colgan, M., Baldeck, C.A.[Claire A.], Féret, J., Asner, G.P.[Gregory P.],
Mapping Savanna Tree Species at Ecosystem Scales Using Support Vector Machine Classification and BRDF Correction on Airborne Hyperspectral and LiDAR Data,
RS(4), No. 11, November 2012, pp. 3462-3480.
DOI Link 1211
BibRef

Xian, G.[George], Homer, C.[Collin], Meyer, D.[Debbie], Granneman, B.[Brian],
An approach for characterizing the distribution of shrubland ecosystem components as continuous fields as part of NLCD,
PandRS(86), No. 1, 2013, pp. 136-149.
Elsevier DOI 1312
Shurbland BibRef

Suess, S.[Stefan], van der Linden, S.[Sebastian], Okujeni, A.[Akpona], Leitão, P.J.[Pedro J.], Schwieder, M.[Marcel], Hostert, P.[Patrick],
Using Class Probabilities to Map Gradual Transitions in Shrub Vegetation from Simulated EnMAP Data,
RS(7), No. 8, 2015, pp. 10668.
DOI Link 1509
BibRef

Vanselow, K.A.[Kim André], Samimi, C.[Cyrus],
Predictive Mapping of Dwarf Shrub Vegetation in an Arid High Mountain Ecosystem Using Remote Sensing and Random Forests,
RS(6), No. 7, 2014, pp. 6709-6726.
DOI Link 1408
BibRef

Wang, J., Cao, X., Chen, J., Jia, X.,
Assessment of Multiple Scattering in the Reflectance of Semiarid Shrublands,
GeoRS(53), No. 9, September 2015, pp. 4910-4921.
IEEE DOI 1506
Earth BibRef

Jiménez, M.[Marcos], Díaz-Delgado, R.[Ricardo],
Towards a Standard Plant Species Spectral Library Protocol for Vegetation Mapping: A Case Study in the Shrubland of Doñana National Park,
IJGI(4), No. 4, 2015, pp. 2472.
DOI Link 1601
BibRef

Naidoo, L.[Laven], Mathieu, R.[Renaud], Main, R.[Russell], Kleynhans, W.[Waldo], Wessels, K.[Konrad], Asner, G.[Gregory], Leblon, B.[Brigitte],
Savannah woody structure modelling and mapping using multi-frequency (X-, C- and L-band) Synthetic Aperture Radar data,
PandRS(105), No. 1, 2015, pp. 234-250.
Elsevier DOI 1506
Woody structure BibRef

Stambaugh, M.C.[Michael C.], Hammer, L.D.[Lyndia D.], Godfrey, R.[Ralph],
Performance of Burn-Severity Metrics and Classification in Oak Woodlands and Grasslands,
RS(7), No. 8, 2015, pp. 10501.
DOI Link 1509
BibRef

Schmidt, M.[Michael], Carter, J.[John], Stone, G.[Grant], O'Reagain, P.[Peter],
Integration of Optical and X-Band Radar Data for Pasture Biomass Estimation in an Open Savannah Woodland,
RS(8), No. 12, 2016, pp. 989.
DOI Link 1612
BibRef

Wylie, B.[Bruce], Howard, D.[Daniel], Dahal, D.[Devendra], Gilmanov, T.[Tagir], Ji, L.[Lei], Zhang, L.[Li], Smith, K.[Kelcy],
Grassland and Cropland Net Ecosystem Production of the U.S. Great Plains: Regression Tree Model Development and Comparative Analysis,
RS(8), No. 11, 2016, pp. 944.
DOI Link 1612
BibRef

Main, R.[Russell], Mathieu, R.[Renaud], Kleynhans, W.[Waldo], Wessels, K.[Konrad], Naidoo, L.[Laven], Asner, G.P.[Gregory P.],
Hyper-Temporal C-Band SAR for Baseline Woody Structural Assessments in Deciduous Savannas,
RS(8), No. 8, 2016, pp. 661.
DOI Link 1609
BibRef

Krofcheck, D.J.[Dan J.], Litvak, M.E.[Marcy E.], Lippitt, C.D.[Christopher D.], Neuenschwander, A.[Amy],
Woody Biomass Estimation in a Southwestern U.S. Juniper Savanna Using LiDAR-Derived Clumped Tree Segmentation and Existing Allometries,
RS(8), No. 6, 2016, pp. 453.
DOI Link 1608
BibRef

Marston, C.G.[Christopher G.], Aplin, P.[Paul], Wilkinson, D.M.[David M.], Field, R.[Richard], O'Regan, H.J.[Hannah J.],
Scrubbing Up: Multi-Scale Investigation of Woody Encroachment in a Southern African Savannah,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Cho, M.A.[Moses A.], Ramoelo, A.[Abel], Dziba, L.[Luthando],
Response of Land Surface Phenology to Variation in Tree Cover during Green-Up and Senescence Periods in the Semi-Arid Savanna of Southern Africa,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Madonsela, S.[Sabelo], Cho, M.A.[Moses Azong], Ramoelo, A.[Abel], Mutanga, O.[Onisimo],
Remote sensing of species diversity using Landsat 8 spectral variables,
PandRS(133), No. Supplement C, 2017, pp. 116-127.
Elsevier DOI 1711
PCA, NDVI, Landsat-8, Savannah, Tree species diversity BibRef

Qi, Y.[Yi], Ustin, S.L.[Susan L.], Glenn, N.F.[Nancy F.],
Imaging Spectroscopic Analysis of Biochemical Traits for Shrub Species in Great Basin, USA,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Goldbergs, G.[Grigorijs], Maier, S.W.[Stefan W.], Levick, S.R.[Shaun R.], Edwards, A.[Andrew],
Efficiency of Individual Tree Detection Approaches Based on Light-Weight and Low-Cost UAS Imagery in Australian Savannas,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Higginbottom, T.P.[Thomas P.], Symeonakis, E.[Elias], Meyer, H.[Hanna], van der Linden, S.[Sebastian],
Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data,
PandRS(139), 2018, pp. 88-102.
Elsevier DOI 1804
Landsat-metrics, Optical-radar fusion, Woody cover mapping, Savannahs, Large-area mapping BibRef

Symeonakis, E.[Elias], Higginbottom, T.P.[Thomas P.], Petroulaki, K.[Kyriaki], Rabe, A.[Andreas],
Optimisation of Savannah Land Cover Characterisation with Optical and SAR Data,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef
Earlier: A1, A3, A2, Only:
Landsat-based Woody Vegetation Cover Monitoring In Southern African Savannahs,
ISPRS16(B7: 563-567).
DOI Link 1610
BibRef

Hartfield, K.A.[Kyle A.], van Leeuwen, W.J.D.[Willem J. D.],
Woody Cover Estimates in Oklahoma and Texas Using a Multi-Sensor Calibration and Validation Approach,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Anchang, J.Y.[Julius Y.], Prihodko, L.[Lara], Kaptué, A.T.[Armel T.], Ross, C.W.[Christopher W.], Ji, W.J.[Wen-Jie], Kumar, S.S.[Sanath S.], Lind, B.[Brianna], Sarr, M.A.[Mamadou A.], Diouf, A.A.[Abdoul A.], Hanan, N.P.[Niall P.],
Trends in Woody and Herbaceous Vegetation in the Savannas of West Africa,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Dong, Y.[Yu], Yan, H.M.[Hui-Min], Wang, N.[Na], Huang, M.[Mei], Hu, Y.F.[Yun-Feng],
Automatic Identification of Shrub-Encroached Grassland in the Mongolian Plateau Based on UAS Remote Sensing,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Wessels, K.[Konrad], Mathieu, R.[Renaud], Knox, N.[Nichola], Main, R.[Russell], Naidoo, L.[Laven], Steenkamp, K.[Karen],
Mapping and Monitoring Fractional Woody Vegetation Cover in the Arid Savannas of Namibia Using LiDAR Training Data, Machine Learning, and ALOS PALSAR Data,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Hill, M.J.[Michael J.], Millington, A.[Andrew], Lemons, R.[Rebecca], New, C.[Cherie],
Functional Phenology of a Texas Post Oak Savanna from a CHRIS PROBA Time Series,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Hill, M.J.[Michael J.], Guerschman, J.P.[Juan P.],
The MODIS Global Vegetation Fractional Cover Product 2001-2018: Characteristics of Vegetation Fractional Cover in Grasslands and Savanna Woodlands,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Nagelkirk, R.L.[Ryan L.], Dahlin, K.M.[Kyla M.],
Woody Cover Fractions in African Savannas From Landsat and High-Resolution Imagery,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Gómez-Giráldez, P.J.[Pedro J.], Pérez-Palazón, M.J.[María J.], Polo, M.J.[María J.], González-Dugo, M.P.[María P.],
Monitoring Grass Phenology and Hydrological Dynamics of an Oak-Grass Savanna Ecosystem Using Sentinel-2 and Terrestrial Photography,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Bispo, P.D.[Polyanna Da_Conceição], Rodríguez-Veiga, P.[Pedro], Zimbres, B.[Barbara], do Couto de Miranda, S.[Sabrina], Cezare, C.H.G.[Cassio Henrique Giusti], Fleming, S.[Sam], Baldacchino, F.[Francesca], Louis, V.[Valentin], Rains, D.[Dominik], Garcia, M.[Mariano], del Bon Espírito-Santo, F.[Fernando], Roitman, I.[Iris], Pacheco-Pascagaza, A.M.[Ana María], Gou, Y.Q.[Ya-Qing], Roberts, J.[John], Barrett, K.[Kirsten], Ferreira, L.G.[Laerte Guimaraes], Shimbo, J.Z.[Julia Zanin], Alencar, A.[Ane], Bustamante, M.[Mercedes], Woodhouse, I.H.[Iain Hector], Sano, E.E.[Edson Eyji], Ometto, J.P.[Jean Pierre], Tansey, K.[Kevin], Balzter, H.[Heiko],
Woody Aboveground Biomass Mapping of the Brazilian Savanna with a Multi-Sensor and Machine Learning Approach,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Luck, L.[Linda], Hutley, L.B.[Lindsay B.], Calders, K.[Kim], Levick, S.R.[Shaun R.],
Exploring the Variability of Tropical Savanna Tree Structural Allometry with Terrestrial Laser Scanning,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Oddi, L.[Ludovica], Cremonese, E.[Edoardo], Ascari, L.[Lorenzo], Filippa, G.[Gianluca], Galvagno, M.[Marta], Serafino, D.[Davide], Morra di Cella, U.[Umberto],
Using UAV Imagery to Detect and Map Woody Species Encroachment in a Subalpine Grassland: Advantages and Limits,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Rudge, M.L.M.[Mitchel L. M.], Levick, S.R.[Shaun R.], Bartolo, R.E.[Renee E.], Erskine, P.D.[Peter D.],
Modelling the Diameter Distribution of Savanna Trees with Drone-Based LiDAR,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Cui, X.H.[Xi-Hong], Zhang, Z.[Zheng], Guo, L.[Li], Liu, X.B.[Xin-Bo], Quan, Z.X.[Zhen-Xian], Cao, X.[Xin], Chen, X.H.[Xue-Hong],
The Root-Soil Water Relationship Is Spatially Anisotropic in Shrub-Encroached Grassland in North China: Evidence from GPR Investigation,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Soubry, I.[Irini], Doan, T.[Thuy], Chu, T.[Thuan], Guo, X.[Xulin],
A Systematic Review on the Integration of Remote Sensing and GIS to Forest and Grassland Ecosystem Health Attributes, Indicators, and Measures,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Apellaniz, M.[Melisa], Burnside, N.G.[Niall G.], Brolly, M.[Matthew],
Temperate Grassland Afforestation Dynamics in the Aguapey Valuable Grassland Area between 1999 and 2020: Identifying the Need for Protection,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Rittenhouse, C.D.[Chadwick D.], Berlin, E.H.[Elana H.], Mikle, N.[Nathaniel], Qiu, S.[Shi], Riordan, D.[Dustin], Zhu, Z.[Zhe],
An Object-Based Approach to Map Young Forest and Shrubland Vegetation Based on Multi-Source Remote Sensing Data,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Kloucek, T.[Tomáš], Klápšte, P.[Petr], Marešová, J.[Jana], Komárek, J.[Jan],
UAV-Borne Imagery Can Supplement Airborne Lidar in the Precise Description of Dynamically Changing Shrubland Woody Vegetation,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Gan, L.Q.[Li-Qin], Cao, X.[Xin], Chen, X.[Xuehong], He, Q.[Qian], Cui, X.[Xihong], Zhao, C.C.[Chen-Chen],
Mapping Shrub Coverage in Xilin Gol Grassland with Multi-Temporal Sentinel-2 Imagery,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Iñamagua-Uyaguari, J.P.[Juan Pablo], Green, D.R.[David R.], Fitton, N.[Nuala], Sangoluisa, P.[Pamela], Torres, J.[Jonathan], Smith, P.[Pete],
Use of Unoccupied Aerial Systems to Characterize Woody Vegetation across Silvopastoral Systems in Ecuador,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Zangerl, U.[Ulrich], Haselberger, S.[Stefan], Kraushaar, S.[Sabine],
Classifying Sparse Vegetation in a Proglacial Valley Using UAV Imagery and Random Forest Algorithm,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Simoniello, T.[Tiziana], Coluzzi, R.[Rosa], Guariglia, A.[Annibale], Imbrenda, V.[Vito], Lanfredi, M.[Maria], Samela, C.[Caterina],
Automatic Filtering and Classification of Low-Density Airborne Laser Scanner Clouds in Shrubland Environments,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Kycko, M.[Marlena], Zagajewski, B.[Bogdan], Kluczek, M.[Marcin], Tardà, A.[Anna], Pineda, L.[Lydia], Palà, V.[Vicenç], Corbera, J.[Jordi],
Sentinel-2 and AISA Airborne Hyperspectral Images for Mediterranean Shrubland Mapping in Catalonia,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Bartholomeus, H.[Harm], Calders, K.[Kim], Whiteside, T.[Tim], Terryn, L.[Louise], Moorthy, S.M.K.[Sruthi M. Krishna], Levick, S.R.[Shaun R.], Bartolo, R.[Renée], Verbeeck, H.[Hans],
Evaluating Data Inter-Operability of Multiple UAV-LiDAR Systems for Measuring the 3D Structure of Savanna Woodland,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Hutsler, T.[Thomas], Pricope, N.G.[Narcisa G.], Gao, P.[Peng], Rother, M.T.[Monica T.],
Detecting Woody Plants in Southern Arizona Using Data from the National Ecological Observatory Network (NEON),
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Zeng, Y.F.[Yu-Fan], Yu, Q.[Qiang], Wang, X.[Xiaoci], Ma, J.[Jun], Xu, C.L.[Cheng-Long], Qiu, S.[Shi], Liu, W.[Wei], Wang, F.[Fei],
Research on the Relationship between the Structure of Forest and Grass Ecological Spaces and Ecological Service Capacity: A Case Study of the Wuding River Basin,
RS(15), No. 9, 2023, pp. xx-yy.
DOI Link 2305
BibRef

Strnad, D.[Damjan], Horvat, Š.[Štefan], Mongus, D.[Domen], Ivajnšic, D.[Danijel], Kohek, Š.[Štefan],
Detection and Monitoring of Woody Vegetation Landscape Features Using Periodic Aerial Photography,
RS(15), No. 11, 2023, pp. 2766.
DOI Link 2306
Hedges, tree patches, and riparian vegetation. BibRef

Shen, X.Q.[Xiao-Qing], Clayton, M.K.[Megan K.], Starek, M.J.[Michael J.], Chang, A.[Anjin], Jessup, R.W.[Russell W.], Foster, J.L.[Jamie L.],
Identification of Brush Species and Herbicide Effect Assessment in Southern Texas Using an Unoccupied Aerial System (UAS),
RS(15), No. 13, 2023, pp. 3211.
DOI Link 2307
BibRef

Collins, C.H.[Chandra Holifield], Skirvin, S.[Susan], Kautz, M.[Mark], Winston, Z.[Zachary], Curley, D.[Dustin], Corrales, A.[Andrew], Bishop, A.[Andrew], Bishop, N.[Nadine], Norton, C.[Cynthia], Ponce-Campos, G.[Guillermo], Armendariz, G.[Gerardo], Metz, L.[Loretta], Heilman, P.[Philip], van Leeuwen, W.[Willem],
Rangeland Brush Estimation Tool (RaBET): An Operational Remote Sensing-Based Application for Quantifying Woody Cover on Western Rangelands,
RS(15), No. 21, 2023, pp. 5102.
DOI Link 2311
BibRef

Rose, M.B.[Miranda Brooke], Mills, M.[Mystyn], Franklin, J.[Janet], Larios, L.[Loralee],
Mapping Fractional Vegetation Cover Using Unoccupied Aerial Vehicle Imagery to Guide Conservation of a Rare Riparian Shrub Ecosystem in Southern California,
RS(15), No. 21, 2023, pp. 5113.
DOI Link 2311
BibRef

Xu, Z.Y.[Zheng-Yong], Sun, B.[Bin], Zhang, W.F.[Wang-Fei], Gao, Z.H.[Zhi-Hai], Yue, W.[Wei], Wang, H.[Han], Wu, Z.[Zhitao], Teng, S.[Sihan],
Is Spectral Unmixing Model or Nonlinear Statistical Model More Suitable for Shrub Coverage Estimation in Shrub-Encroached Grasslands Based on Earth Observation Data? A Case Study in Xilingol Grassland, China,
RS(15), No. 23, 2023, pp. 5488.
DOI Link 2312
BibRef

Zhong, B.[Bo], Yang, L.[Li], Luo, X.B.[Xiao-Bo], Wu, J.J.[Jun-Jun], Hu, L.F.[Long-Fei],
Extracting Shrubland in Deserts from Medium-Resolution Remote-Sensing Data at Large Scale,
RS(16), No. 2, 2024, pp. 374.
DOI Link 2402
BibRef


Mbaabu, P.R., Schaffner, U., Eckert, S.,
Invasion of Savannas By Prosopis Trees In Eastern Africa: Exploring Their Impacts on Lulc Dynamics, Livelihoods and Implications on Soil Organic Carbon Stocks,
ISPRS21(B3-2021: 335-340).
DOI Link 2201
BibRef

Symeonakis, E., Korkofigkas, A., Vamvoukakis, G., Stamou, G., Arnau-Rosalén, E.,
Deep Learning Monitoring of Woody Vegetation Density In A South African Savannah Region,
ISPRS20(B3:1645-1649).
DOI Link 2012
BibRef

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Dryland Analysis and Change, Arid Regions .


Last update:Jun 17, 2024 at 21:38:11