Estimation of the NDVI vegetation index to the Canaan forest using temporal spatial images

Paper Details

Research Paper 01/06/2018
Views (358) Download (12)

Estimation of the NDVI vegetation index to the Canaan forest using temporal spatial images

Ahmed Bahjat Khalaf
J. Bio. Env. Sci.12( 6), 204-209, June 2018.
Certificate: JBES 2018 [Generate Certificate]


This study was conducted on the Kanaan Forest within the Diyala Governorate between latitude 44°50’33.30”- 44°54”27.58” and 33º39’51.46”-33º34’25.54” and an area of ​​971.51km2. Using 12 satellite images of Landsat 8 satellite OLI_TIRS (row 37 and path 168) for 2015-2016 and 2017 by 4 images per year for the purpose of calculating NDVI values, the study found that there were significant differences for NDVI values ​​ (P-value for t-test was 0.0015, and the chi-square test is 0,0009 and the probability level is 0.05. For the years of study, the highest value of the index NDVI (0.514) was recorded on 12/3/2016 and the lowest value (0.234) on 18/9/2015. There was a difference at the quarterly and annual levels.


Aiad AK, Jasim K. 2013. Calculate value of (NDVI) and vegetation Indexes for evaluation degradation status of rangelands by using remote sensing techniques. University Tkirt Agricultural Sciences Journal 13(1), 264-274.

Alrawe KM. 2000. Introduction to Statistics. Ministry of Higher Education and Scientific Research. University of Al Mosul. Dar Al Kuttab for Printing and Publishing, University of Mosul. (in Arabic).

Bindhu VM, Narasimhan B. 2014. Temporal disaggregation method to derive time series of Normalized Difference Vegetation Index and Land surface temperature at spatial resolution, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Journal 8, 1397-1401.

Chuai W, Huang J, Wang W. 2013. NDVI temperature and precipitation changes and their relationships with different vegetation types during 1998–2007 in Inner Mongolia, China. Int. J. Climatol 33, 1696–1706.

Ehsan S, Kazem, D. 2013. Analysis of land use-land covers changes using normalized difference vegetation index (NDV) differencing and classification methods, African Journal of Agricultural Research 8(37), 4614-4622.

Eyad A, Rada K. 2016. Monitoring Changes in Vegetation cover in Agriculture Stability Zones of Syria Using Time Series NDVI/MODIS During 2000-2012. Syrian Journal of Agricultural Research 3(2), 188-205.

Ilene M, Wael A. 2016. Calculating the Normalized Difference Vegetation Index (NDVI) for Pinus bruutia ten. Satnds using satellite images in Jableh at Spatial and Temporal Scales. Tishreen University Journal for Research and Scientific Studies – Biological Sciences Series 38(3), 25-40.

Israa JM. 2016. Change detection of remotely sensed image using NDVI subtractive and classification methods, Iraqi Journal of Physics 14(29), 125-137.

Jinru X, Baofeng S. 2017. Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications. Journal of Sensors. Volume 2017, Article ID 1353691, 17 pages.

Jones HG, Vaughan, RA. 2010. Remote Sensing of Vegetation. Principles, Techniques and Applications. Oxford University Press, UK.

Lukasova V, Lang M, Skvarenina J. 2014. Seasonal Changes in NDVI in relation to Phenological Phases, LAI and PAI of Beech Forests, Baltic 20(2), 248-262.

Mohamed R. 2015. Estimation Leave area index of pinus bruti group in Jabala using satellite images, Master Thesis, collage of Agriculture, Tishreen University press.

Ravi P, Neha S, Saumitra M. 2016. Normalized Difference Vegetation Index (NDVI) Based Classification to Assess the Change in Land Use/Land Cover (LULC) in Lower Assam, India, International Journal of Advanced Remote Sensing and GIS 5(10), 1963-1970.

Thomas P, Elias S. 2014. Assessing Land Degradation and Desertification Using Vegetation Index Data: Current Frameworks and Future Directions Remote Sens 6, 9552-9575.

Tingting G, Huimin L, Dawen Y, Yang J, Hanbo Y. 2017. Monitoring the variations of evapotranspiration due to land use/cover change in a semiarid shrubland. Hydrol. Earth Syst. Sci. 21, 863–877.