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Items: 1 to 20 of 102

1.
2.

[Comparison of GIMMS and MODIS normalized vegetation index composite data for Qing-Hai-Tibet Plateau].

Du JQ, Shu JM, Wang YH, Li YC, Zhang LB, Guo Y.

Ying Yong Sheng Tai Xue Bao. 2014 Feb;25(2):533-44. Chinese.

PMID:
24830255
3.

[Pheno-climatic profiles of vegetation based on multitemporal analysis of satellite data].

Taddei R.

Parassitologia. 2004 Jun;46(1-2):63-6. Italian.

PMID:
15305688
5.

Using NOAA AVHRR data to assess flood damage in China.

Wang Q, Watanabe M, Hayashi S, Murakami S.

Environ Monit Assess. 2003 Mar;82(2):119-48.

PMID:
12602625
6.

Analysis of land cover/use changes using Landsat 5 TM data and indices.

Ettehadi Osgouei P, Kaya S.

Environ Monit Assess. 2017 Apr;189(4):136. doi: 10.1007/s10661-017-5818-5. Epub 2017 Mar 1.

PMID:
28251451
7.

Comparison and Evaluation of Annual NDVI Time Series in China Derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 Products.

Guo X, Zhang H, Wu Z, Zhao J, Zhang Z.

Sensors (Basel). 2017 Jun 6;17(6). pii: E1298. doi: 10.3390/s17061298.

8.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

Midekisa A, Holl F, Savory DJ, Andrade-Pacheco R, Gething PW, Bennett A, Sturrock HJW.

PLoS One. 2017 Sep 27;12(9):e0184926. doi: 10.1371/journal.pone.0184926. eCollection 2017.

9.

Long-term Satellite NDVI Data Sets: Evaluating Their Ability to Detect Ecosystem Functional Changes in South America.

Baldi G, Nosetto MD, Aragón R, Aversa F, Paruelo JM, Jobbágy EG.

Sensors (Basel). 2008 Sep 3;8(9):5397-5425.

10.

Evaluating the consistency of the 1982-1999 NDVI trends in the Iberian Peninsula across four time-series derived from the AVHRR sensor: LTDR, GIMMS, FASIR, and PAL-II.

Alcaraz-Segura D, Liras E, Tabik S, Paruelo J, Cabello J.

Sensors (Basel). 2010;10(2):1291-314. doi: 10.3390/s100201291. Epub 2010 Feb 8.

11.

Land cover change of watersheds in Southern Guam from 1973 to 2001.

Wen Y, Khosrowpanah S, Heitz L.

Environ Monit Assess. 2011 Aug;179(1-4):521-9. doi: 10.1007/s10661-010-1760-5. Epub 2010 Nov 12.

PMID:
21072586
12.

Land cover in Upper Egypt assessed using regional and global land cover products derived from MODIS imagery.

Fuller DO, Parenti MS, Gad AM, Beier JC.

Remote Sens Lett. 2012 Jan 1;3(2):171-180.

13.

Spatially and temporally continuous LAI datasets based on the mixed pixel decomposition method.

Zhao J, Wang Y, Zhang H, Zhang Z, Guo X, Yu S, Du W.

Springerplus. 2016 Apr 26;5:516. doi: 10.1186/s40064-016-2166-9. eCollection 2016.

14.

Land cover classification with an expert system approach using Landsat ETM imagery: a case study of Trabzon.

Kahya O, Bayram B, Reis S.

Environ Monit Assess. 2010 Jan;160(1-4):431-8. doi: 10.1007/s10661-008-0707-6.

PMID:
19083107
16.

Monitoring forest dynamics with multi-scale and time series imagery.

Huang C, Zhou Z, Wang D, Dian Y.

Environ Monit Assess. 2016 May;188(5):273. doi: 10.1007/s10661-016-5271-x. Epub 2016 Apr 8.

PMID:
27056478
17.

Analysis of spatial and temporal evolution of vegetation cover in the Spanish Central Pyrenees: role of human management.

Vicente-Serrano SM, Lasanta T, Romo A.

Environ Manage. 2004 Dec;34(6):802-18.

PMID:
15562324
18.

Mapping paddy rice distribution using multi-temporal Landsat imagery in the Sanjiang Plain, northeast China.

Jin C, Xiao X, Dong J, Qin Y, Wang Z.

Front Earth Sci. 2016 Mar;10(1):49-62. Epub 2015 Jul 28.

19.

Mapping the Philippines' mangrove forests using Landsat imagery.

Long JB, Giri C.

Sensors (Basel). 2011;11(3):2972-81. doi: 10.3390/s110302972. Epub 2011 Mar 7.

20.

Assessing the use of global land cover data for guiding large area population distribution modelling.

Linard C, Gilbert M, Tatem AJ.

GeoJournal. 2011 Oct;76(5):525-538. Epub 2010 May 25.

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