22.1.5.22 NDVI, Normalized Difference Vegetation Index, Changes

Berra, E.F., Gaulton, R., Barr, S.,
Commercial Off-the-Shelf Digital Cameras on Unmanned Aerial Vehicles for Multitemporal Monitoring of Vegetation Reflectance and NDVI,
GeoRS(55), No. 9, September 2017, pp. 4878-4886.
IEEE DOI 1709
autonomous aerial vehicles, vegetation mapping, COTS cameras, Landsat series, UAV-retrieved reflectance, digital numbers, fine spatial resolution, ground NDVI, ground measurements, ground reflectance, illumination conditions, infrared-modified commercial off-the-shelf camera, low-cost approaches, normalized difference vegetation index, quantitative remote sensing products, surface reflectance, unmanned aerial vehicle, user-controlled revisit periods, vegetation monitoring, within-flight illumination, Calibration, Cameras, Radiometry, Remote sensing, Satellites, Unmanned aerial vehicles, Vegetation mapping, Calibration, forest, multispectral, phenology, unmanned, aerial, system BibRef

Liao, C.H.[Chun-Hua], Wang, J.[Jinfei], Pritchard, I.[Ian], Liu, J.G.[Jian-Gui], Shang, J.[Jiali],
A Spatio-Temporal Data Fusion Model for Generating NDVI Time Series in Heterogeneous Regions,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Cai, Z.Z.[Zhan-Zhang], Jönsson, P.[Per], Jin, H.X.[Hong-Xiao], Eklundh, L.[Lars],
Performance of Smoothing Methods for Reconstructing NDVI Time-Series and Estimating Vegetation Phenology from MODIS Data,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Yin, G.F.[Gao-Fei], Li, A.N.[Ai-Nong], Verger, A.[Aleixandre],
Spatiotemporally Representative and Cost-Efficient Sampling Design for Validation Activities in Wanglang Experimental Site,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Houborg, R.[Rasmus], McCabe, M.F.[Matthew F.],
Daily Retrieval of NDVI and LAI at 3 m Resolution via the Fusion of CubeSat, Landsat, and MODIS Data,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Onyia, N.N.[Nkeiruka Nneti], Balzter, H.[Heiko], Berrio, J.C.[Juan-Carlos],
Normalized Difference Vegetation Vigour Index: A New Remote Sensing Approach to Biodiversity Monitoring in Oil Polluted Regions,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Bonthoux, S.[Sébastien], Lefèvre, S.[Solenne], Herrault, P.A.[Pierre-Alexis], Sheeren, D.[David],
Spatial and Temporal Dependency of NDVI Satellite Imagery in Predicting Bird Diversity over France,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Yang, J.X.[Jia-Xin], Chen, Y.[Yumin], Chen, M.[Meijie], Yang, F.[Fan], Yao, M.[Ming],
A Segmented Processing Approach of Eigenvector Spatial Filtering Regression for Normalized Difference Vegetation Index in Central China,
IJGI(7), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Peter, J.S.[Joseph St.], Hogland, J.[John], Hebblewhite, M.[Mark], Hurley, M.A.[Mark A.], Hupp, N.[Nicole], Proffitt, K.[Kelly],
Linking Phenological Indices from Digital Cameras in Idaho and Montana to MODIS NDVI,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Han, Y.[Yinan], Peng, J.[Jian], Meersmans, J.[Jeroen], Liu, Y.X.[Yan-Xu], Zhao, Z.Q.[Zhi-Qiang], Mao, Q.[Qi],
Integrating Spatial Continuous Wavelet Transform and Normalized Difference Vegetation Index to Map the Agro-Pastoral Transitional Zone in Northern China,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Novillo, C.J.[Carlos J.], Arrogante-Funes, P.[Patricia], Romero-Calcerrada, R.[Raúl],
Recent NDVI Trends in Mainland Spain: Land-Cover and Phytoclimatic-Type Implications,
IJGI(8), No. 1, 2019, pp. xx-yy.
DOI Link 1901
BibRef

Guan, S.[Senlin], Fukami, K.[Koichiro], Matsunaka, H.[Hitoshi], Okami, M.[Midori], Tanaka, R.[Ryo], Nakano, H.[Hiroshi], Sakai, T.[Tetsufumi], Nakano, K.[Keiko], Ohdan, H.[Hideki], Takahashi, K.[Kimiyasu],
Assessing Correlation of High-Resolution NDVI with Fertilizer Application Level and Yield of Rice and Wheat Crops Using Small UAVs,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Lang, M.[Marc], Alleaume, S.[Samuel], Luque, S.[Sandra], Baghdadi, N.[Nicolas], Féret, J.B.[Jean-Baptiste],
Complementarity between Textural and Radiometric Indices From Airborne and Spaceborne Multi VHSR Data: Disentangling the Complexity of Heterogeneous Landscape Matrix,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
Manage biodiversity. NDVI BibRef

Talebiesfandarani, S.[Somayeh], Zhao, T.[Tianjie], Shi, J.C.[Jian-Cheng], Ferrazzoli, P.[Paolo], Wigneron, J.P.[Jean-Pierre], Zamani, M.[Mehdi], Pani, P.[Peejush],
Microwave Vegetation Index from Multi-Angular Observations and Its Application in Vegetation Properties Retrieval: Theoretical Modelling,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Dimitrov, P.[Petar], Dong, Q.[Qinghan], Eerens, H.[Herman], Gikov, A.[Alexander], Filchev, L.[Lachezar], Roumenina, E.[Eugenia], Jelev, G.[Georgi],
Sub-Pixel Crop Type Classification Using PROBA-V 100 m NDVI Time Series and Reference Data from Sentinel-2 Classifications,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Maselli, F., Chiesi, M., Pieri, M.,
A New Method to Enhance the Spatial Features of Multitemporal NDVI Image Series,
GeoRS(57), No. 7, July 2019, pp. 4967-4979.
IEEE DOI 1907
Vegetation mapping, Spatial resolution, MODIS, Indexes, Spatiotemporal phenomena, Sensors, Remote sensing, Sequential Maximum Angle Convex Cone (SMACC) BibRef

Filgueiras, R.[Roberto], Mantovani, E.C.[Everardo Chartuni], Althoff, D.[Daniel], Fernandes Filho, E.I.[Elpídio Inácio], França da Cunha, F.[Fernando],
Crop NDVI Monitoring Based on Sentinel 1,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Balzarolo, M.[Manuela], Peñuelas, J.[Josep], Veroustraete, F.[Frank],
Influence of Landscape Heterogeneity and Spatial Resolution in Multi-Temporal In Situ and MODIS NDVI Data Proxies for Seasonal GPP Dynamics,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Gholamnia, M.[Mehdi], Khandan, R.[Reza], Bonafoni, S.[Stefania], Sadeghi, A.[Ali],
Spatiotemporal Analysis of MODIS NDVI in the Semi-Arid Region of Kurdistan (Iran),
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

McGwire, K.C.[Kenneth C.],
Optimized Stratification for Mapping Riparian Vegetation in Arid and Semiarid Environments,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
Using NDVI. BibRef

Colditz, R.R., Villanueva, V.L.A., Tecuapetla-Gómez, I., Gómez Mendoza, L.,
Temporal relationships between daily precipitation and NDVI time series in Mexico,
MultiTemp17(1-4)
IEEE DOI 1712
atmospheric precipitation, rain, time series, vegetation, correlation coefficients, Precipitation BibRef

Lopes, M., Fauvel, M., Ouin, A., Girard, S.,
Potential of Sentinel-2 and SPOT5 (Take5) time series for the estimation of grasslands biodiversity indices,
MultiTemp17(1-4)
IEEE DOI 1712
regression analysis, time series, vegetation, vegetation mapping, NDVI time series, SPOT5 Take5, SPOT5 time series, high resolution time series BibRef

León-Tavares, J., Swinnen, E., Smets, B., Roujean, J.L.,
Angular normalisation of PROBA-V 300m NDVI,
MultiTemp17(1-5)
IEEE DOI 1712
vegetation, Copernicus global land service, MSG-SEVIRI NDVI angular normalised time series, Vegetation mapping BibRef

Colditz, R.R., Ressl, R.A., Bonilla-Moheno, M.,
Trends in 15-year MODIS NDVI time series for Mexico,
MultiTemp15(1-4)
IEEE DOI 1511
land cover BibRef

Pirotti, F., Parraga, M.A., Sturaro, E., Dubbini, M., Masiero, A., Ramanzin, M.,
NDVI from Landsat 8 Vegetation Indices to Study Movement Dynamics of Capra Ibex in Mountain Areas,
Thematic14(147-153).
DOI Link 1404
BibRef

Ali, A., de Bie, C.A.J.M., Scarrott, R.G., Ha, N.T.T., Skidmore, A.K.,
Comparative Performance Analysis Of A Hyper-temporal NDVI Analysis Approach and a Landscape-Ecological Mapping Approach,
AnnalsPRS(I-7), No. 2012, pp. 105-110.
HTML Version. 1209
BibRef

Ding, S., Rulinda, C.M., Stein, A., Bijker, W.,
NDVI time series and Markov chains to model the change of fuzzy vegetative drought classes,
MultiTemp11(201-204).
IEEE DOI 1109
BibRef

Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Land Cover Change Analysis, Longer Term, Seasonal, Annual Variations, Climate Change, Analysis .

Last update:Sep 9, 2019 at 16:26:55