47 | Indonesian Journal of Science & Technology, 3 Issue April 2018 Indonesian Journal of Science & Volume Technology 3 .
47-52Hal 47-52 Indonesian Journal of Science & Technology Journal homepage: http://ejournal.
edu/index.
php/ijost/ Normalized Difference Vegetation Index (NDVI) In The Integration Conservation Education Forest At Wan Abdul Rachman Using Modis Data Ali Rahmat1.
Mustofa Abi Hamid2.
Muhammad Khoiru Zaki3.
Abdul Mutolib4 Unite Graduate School of Agriculture Science.
Gifu University, 1-1 Yanagido.
Gifu 501-1193.
Japan Department of Electrical Engineering Vocational Education.
Sultan Ageng Tirtayasa University.
Indonesia Department of Agronomy.
Sebelas Maret University.
Central Java Indonesia Faculty of Agriculture Science.
University of Lampung.
Lampung.
Indonesia Correspondence: E-mail: alyrahmat@yahoo.
ABSTRACT
Forest plays an important role to support a global environment.
Currently, forest degradation occurs in developing Therefore, the excellent strategies to against the forest degradation must be found.
One of the best solutions is understanding the information of vegetation condition.
Here, the objective of this paper was to apply a method as the assessment of vegetation monitoring using satellite data in the integration of conservation education forest at great forest Wan Abdul Rachman in Lampung Province.
Indonesia.
this study, normalized difference vegetation index (NDVI) was used, completed with satellite data .
amely MODIS).
This technique helps in monitoring vegetation status.
Data NDVI from MODIS satellite data showed that forest area decrease very small from 2000-2017.
The data was obtained for June.
July, and the end of September.
ARTICLE INFO
Article History:
Submitted/ Received 11 Dec 2017
First Revised 05 Jan 2018
Accepted 05 Feb 2018
First available online 09 Mar 2018
Publication Date 01 Apr 2018
____________________
Keyword:
Forest Monitoring.
Lampung Province.
MODIS Data.
NDVI.
Wan Abdul Rachman forest.
A 2018 Tim Pengembang Jurnal UPI
INTRODUCTION
Forest ecosystems are an essential in economic and environmental point of view, which is widely spread in most regions of the Unfortunately, both in developed and developing countries, many forests are presently threatened by the expansion of agricultural, urban, and industrial land or by degradation phenomena caused indirectly by human activities (Waring & Running, 1.
Forest and trees have a function as a carbon Tree or plants absorb more CO2 than they release, and the trapped CO2 is stored as a carbon in the biomass .
foliage, branches, trunks, and root.
and soils (Prasetyo, 2016.
Permatasari et al.
, 2.
The carbon storage in the forest is about 50% Ali Rahmat.
Hamid.
Zaki.
Mutolib.
Normalized Difference Vegetation IndexA | 48 of its biomass (Tuly et al.
, 2005.
Chang, 2013.
Rahmat and Mutolib, 2.
Forest monitoring is crucial to support forestry management, but the limitation on funding and technology makes high frequency in monitoring.
Indeed, this increases the difficulties.
normalized difference vegetation index (NDVI.
as an indicator of vegetation growth and coverag.
has been widely employed to describe the spatio-temporal characteristics of land use and land cover, including percent vegetation coverage (Kaufmann et al.
, 2.
Vegetation indices are mainly derived from reflectance data from discrete red (R) and near-infrared (NIR) bands.
They are operated by contrasting intense chlorophyll pigment absorption in the red against the high reflectance of leaf mesophyll in the near This case is well-known as normalized NDVI=[NIR_R]/[NIR R] (Bannari et al.
, 1.
and is the most widely used index, especially when analyzing data taken from satellite platforms.
In practice.
NDVI is and indicator for plant photosynthetic activity and has been found to be highly related to the green leaf area index (LAI) and the fraction of photosynthetically active radiation absorbed by vegetation (FAPAR) (Bannari et al.
, 1995.
Baret & Guyot, 1991.
Veroustraete.
Sabbe, & Eerens.
Nandiyanto et al.
, 2.
There are various methodologies for studying seasonal changes in vegetation through satellite images, one method of which is to apply vegetation indices relating to the quantity of greenness (Chuvieco, 1.
One of them is NDVI from MODIS setelite This paper was to get and use NDVI data from MODIS satelite.
The paper also applied NDVI in the assessment of vegetation monitoring using MODIS satellite data in the integration conservation education forest at great forest Wan Abdul Rachman.
Lampung Province.
METHODS
The study was conducted in IFCE WAR Great Forest Park, which is about 1.
143 ha.
is located in Bandar Lampung.
Indonesia .
etween 105A09Ao22.
17"- 105A11Ao39.
13" E and 5A24Ao 09.
78"-5A26Ao11.
41" S) (Unit Pelaksana Teknis Daerah Taman Hutan Raya Wan Abdul Rachman 2.
The study used MODIS data MOD13Q1 product with large area 6.
25 x 6.
km and interval of day is 16 days.
The product can provide NDVI.
Observation period was from 18 February 2000 to 06 March 2017 .
ee Figure .
RESULTS AND DISCUSSION
The NDVI is a measurement of the balance between energy received and energy emitted by objects on Earth.
When applied NDVI to plant communities, this index establishes a value for how green the area.
In short, that showed the quantity of vegetation present in a given area and its state of health or vigour of growth.
The NDVI is a dimensionless index, so its values is a dimensionless index and values range from Ae1 to 1.
In a practical sense, the values that are below 0.
1 correspond to bodies of water and bare ground, while higher values are indicators of high photosynthetic activity linked to scrub land, temperate forest, rain forest and agricultural activity (Meneses-tavor, 2.
The results shows.
NDVI in the integration conservation education forest at great forest Wan Abdul Rachman decrease very small after 16 years with R2 only 0.
0205 (Figure .
Figure 3 shows annual NDVI from 2000 to 2016 .
8 each yea.
The maximum NDVI every year was around 0.
90, but the minimum of is fluctuative.
Figure 4 shows the highest NDVI in 257 DOY.
This NDVI is stable in 161 until 209 DOY.
DOI: http://dx.
org/10.
17509/ijost.
p- ISSN 2528-1410 e- ISSN 2527-8045 49 | Indonesian Journal of Science & Technology.
Volume 3 Issue 1.
April 2018 Hal 47-52 Figure 1.
Observation area Figure 2.
NDVI data from 2000-20017 in Forest Wan Abdul Rachman based on MODIS data Based on data NDVI from MODIS satelite data, vegetation condition in the integration of conservation education forest at great forest Wan Abdul Rachman is quite good with the NDVI value .
The measurement site is far from home residents and inside of forest.
This condition also explains no land cover or vegetation change in this site.
With growing population pressures, some problems are found, such as in Dhamasraya forest in West Sumatra.
Many forest were grabed by community who living sorrounding the forest (Mutolib, et al.
, 2.
NDVI is influenced by the change of season.
The season gives great impact on phenology of the tree.
Highest NDVI found in 257 DOY is around the end of september.
This correlates with rainfall condition just after dry season.
Also, good NDVI in 161 and 209 DOY was found although this time is lack of rainfall.
However, this is because enough water for the tree and make tree green .
ater trapped inside the soi.
Bad NDVI was found around in January.
October, and November.
Although lot of rainfall occurs, clouds disturb sensor of MODIS to have inappropriate condition to take good data from DOI: http://dx.
org/10.
17509/ijost.
p- ISSN 2528-1410 e- ISSN 2527-8045 Ali Rahmat.
Hamid.
Zaki.
Mutolib.
Normalized Difference Vegetation IndexA | 50 Figure 3.
Yearly average.
Max.
Min of NDVI in Forest Wan Abdul Rachman Figure 4.
Day of year NDVI data in Forest Wan Abdul Rachman
CONCLUSION
Appendix Analysis forest has been investigated.
Data NDVI from MODIS satellite data can be used to monitoring vegetation condition in the integration of conservation education forest at great forest Wan Abdul Rachman.
NDVI
in Wan Abdul Rachman forest decreases slightly from 2000 to 2017.
NDVI in Abdul Rachman forest is around 0.
80 annually.
Good NDVI data was found in June.
July, and the end of September.
How to get MODIS data .
ollowing: Rahmat, 2.
Open: https://daac.
gov/MODIS/ by your computer, choose AuCreate SubsetAy .
ee right botto.
Specify the coordinates for the center of area of interest: Insert the coordinate data .
ongitude and latitud.
can use DOI: http://dx.
org/10.
17509/ijost.
p- ISSN 2528-1410 e- ISSN 2527-8045 51 | Indonesian Journal of Science & Technology.
Volume 3 Issue 1.
April 2018 Hal 47-52 direct GPS data or estimating using Google Earth.
Click AucontinueAy.
Select product and sub size then continue: select MOD13Q1 and replace Au3Ay to Au0Ay .
f you want size in the minimum siz.
in bottom table.
Click AucontinueAy.
Select date and provide email then place order: select starting date and ending date and fill your email address in bottom.
Click AuReview orderAy.
Order summary : Click Aucreate subsetAy After around 1 hour, some information comes to the email.
Click on the following URL to obtain your Data visualization and download: choose Audownload dataAy Download tics_LST_DAY_1km.
ascAy and tics_LST_Night_1km.
ascAy.
AustatisAustatis- Copy and paste to excel or notepad and manually extract.
ACKNOWLEDGEMENTS
The authors thank to Sultan Ageng Tirtayasa University.
Indonesian.
Sebelas Maret University.
Central Java Indonesia.
University of Lampung.
Lampung.
Indonesia, and Gifu University.
Japan.
AUTHORSAo NOTE The author.
that there is no conflict of interest regarding the publication of this article.
Authors confirmed that the data and the paper are free of plagiarism.
REFERENCES