Hello,

One option would be to analyze time series in the scale of years for an area.

Sir,

I have modify my question, please re-read it and your comments are valueable and highly appriciated.

Have look at our article Dai et al. 2017 in my RG Contributions at a finer resolution of both cover and meteorology, hopefully for some inspiration.

Dear Naveed,

To answer this question, one way is to start by asking the right questions. First of all, you must not assume the climate has changed by default, as has become the norm. You could determine climate change by calculating the anomalies of important climatic indices such as humidity, rainfall, temperature, soil moisture in your specific study area etc, based on lengthy datasets (30-60 years). As an index of vegetation change, you could use the time series of NDVI or related indices provided by NASA via its GIOVANNI data portal.

Now, since vegetation change may have a number of drivers related or unrelated to climate, depending on your study area and review of existing literature, identify all possible causal variables. Therefore, in addition to climatic indices and soil erosion indices, you need data on socio-economic indices (population change, land-use/land cover change, volume of timber trade).

After collecting your data and ensuring their quality, then proceed to the analysis stage. You could consider analytical techniques such as a combination of correlation analysis, PCA analysis, Multiple regression analysis, causality analysis , or even advanced machine learning (data mining) techniques such as ANN.

By interpreting your results, you will ascertain whether climate change is driving vegetation change, and to what extent, or whether it is more of a combination of multiple complex inter-related factors.

Another point to note is that for any assessment of climate change in particular, your data must span at-least 60 years (two climatic data points).

I hope this helps, and good luck with your research.

Regards

The use of geostatistical analyses can help assess all subject variables: air temperature, humidity, pressure, ndvi, other vegetation indices etc. The use of ArcGIS and Idrisi Land Change Model could be of help too.

Dear Anthony,

First of all thanks a lot for detailed reply.

I have already detected the change in the air tepmeratures and precipitation in my research area and I used mentioned vegetation indexes, now I am stuck at this point how to relate this climate change with vegetation cover change?

I used 1960-2017 climatic parameters data sets (Precipitations, Max and Min Temperature) and NDVI (1982-2015).

Looking forward to you.

Thanks once againg.

Regards

Naveed

Naveed,

I see your point.

In that case, conduct statistical and geospatial analyses as mentioned earlier by Eneche Patrick and I (try a variety of methods, beginning with simple correlation; for this, Eviews, SPSS or ENZight will do just fine). However, I still maintain that by focusing only on ppt and temp, you may end-up with just a little part of the answer because you are leaving out a number of other potentially influential factors. Ignoring factors related to land-cover and change, changes in soil characteristics etc could affect the reliability of your results. If you use a broad variety of indices, then you could determine the weight of each with regards to its observed relationship with vegetation change. In this case, you will need more sophisticated methods and tools for big data analysis.

If I may ask, it this a Ph.D. project?

Regards

Hi, Anthony,

Yes, this one objective of PhD project.

Hi Naveed

You can relate primary production to rainfall. See

https://www.researchgate.net/.../225942819_Biomass_and_Production_of_Large_Africa...

Dec 19, 2017 - Biomass and Production of Large African Herbivores in Relation to Rainfall and Primary Production. Article (PDF Available) in Oecologia 22(4):341-354 · December 1976 with 121 Reads. DOI: 10.1007/BF00345312. Cite this publication. M. J. Coe · David H. M. Cumming at University of Cape Town.

Regards

Christiaan

see all the papers related to NDVI indices

Hi,

You may want to check this out.

Yin, G., Hu, Z., Chen, X. et al. J. Arid Land (2016) 8: 375. https://doi.org/10.1007/s40333-016-0043-6

https://www.usgs.gov/faqs/how-do-changes-climate-and-land-use-relate-one-another-1?qt-news_science_products=0#qt-news_science_products

Article Regional vegetation dynamics and its response to climate cha...

https://espace.library.uq.edu.au/data/UQ_380297/s4271282_final_thesis.pdf?Expires=1521558459&Signature=cuolm9Y77g6cSXjiGQ61T29L90zk8Sp6cwn6uq84YF8~rIk55DmYXM6OqtfegGr8EM9b8msxaomcKBJQPFaGZUuJA9BfYW5dw102rIkW4ellqbF8u5UTYBeaKWT5gCHGa~pt0gLIenb-uc3zhYuAAtb16b2CT8BwqXa2sX1E4OUd-Wbu5G~TG5QRTlAizHt64Wn3ELh2zFpUhcS2yiTl09ZbpbLb9ZAuDI2IRVqu6cXyB5u2DPw-hwRlsq-EEgsCQfJtRfHHt1kNPI2-508ggbtxed1X87FnPlDzNfI-6tXV4Xq5vrjPw3M57mSzz-fe7zwvNWRSubciQgDdLiYkOQ__&Key-Pair-Id=APKAJKNBJ4MJBJNC6NLQ

Kindly check this too..

https://www.nature.com/articles/524044a?WT.ec_id=NATURE-20150806&spMailingID=49256879&spUserID=MjA1NjIyNjczNAS2&spJobID=740835078&spReportId=NzQwODM1MDc4S0

Hello, to analyse correlation between climate change and vegetation cover, you can work on precipitation series according to your work and analyse the change of quantity, and to compare it with vegetation you can work using remote sensing data like Landsat to study vegetation cover change and by statistical analysis tests like regression you can have a clear vision.

Best regards

Dear you can use statistical analysis with SSPS software

My regards