Normalised Difference Vegetation Index (NDVI): Vegetation From Space

Exercise 1.
1.         Describe the NDVI images

In simple words, NDVI stands for normalized different vegetation index. How NDVI works is that through Near-Infrared Radiation reflectance aka NIR reflectance. Different value of NIR reflectance indicates different vegetation on the earth surface. For example, high NIR reflectance normally indicates area with high vegetation and vice versa.

From the formula, (NIR- visible red)/ (NIR + visible red). If the value shown close to 1, normally that area were high in vegetation. This happens to be the other way round when the value is close to -1. What else can we know from the range -1 to 1 is that the status of the crop. For example, the health of the crops.

From the exercise, dark green shows healthy crop, with light green show unhealthy crops while white color shows residential area. By comparing the 2 images, SPOT NDVI January 2000 and SPOT NDVI August 2000, significant changes is portion of darker green color increases which indicates more healthier crops can be found in later.

2.         Where do you find the most abundant vegetation

Peru

3.         Where do you find the least abundant of vegetation?

            Argentina

4.         Compare the precipitation maps for two seasons and try to explain the changes in vegetation from January to August.

            Vegetation of an area in basically depend on sufficiency of water or precipitation to undergo normal processes like photosynthesis and so on. From what we know, precipitation is normally affected by wind direction. During December to February wind flown from North-East towards the central of Latin America, winds carries cloud and caused more precipitation over there. As for June to August, wind flows from South- East to the north part of the Latin America, so it just has more precipitation on north part. Therefore the patterns is in central part of the Latin America, from Dec to Feb has more precipitation but dry season from June to Aug. In north part of Latin America, June to August has more precipitation but less from Dec to Feb.

5.         Find some area where there is much variation in the NDVI. By comparing the NDVI with the precipitation map can you explain the variation?

            Brazil , Bolivia and Argentina as I mention before NDVI value reflects the healths of a plant. These area suffers from droughts at June to August and sufficient precipitation at Dec and Feb. Therefore, plant is healthier from December to February which has high NIR reflectance and NDVI is near 1. While plant is unhealthier from June to August which has high red reflectance and NDVI is near -1.

6.         Find some desert area. Can u explain why precipitation is so low in these area?

            For example, northern part of Chile. In these area, wind blows wildly and carries all the cloud away. That’s why low precipitation in these area.

7.         There are some area with high NDVI values in both seasons, Why?

            For example,Urugual and Chile. Because these area are not affected with wind flow.

Exercise 2

1.      1.                   Observe and describe the variation in the NDVI value in the year 2000

From the observation, when NDVI of an area increases, colour changed from light green into dark green. While NDVI decreases, colour changed from dark green into light green.

2.     2.                    In what months is the NDVI at its maximum in Amazon basin? Why?

November, this is because dark green area covered the most in Amazon

3.      3.                 Observe the Dec image for the northeastern part of Brazil along the Atlantic coast and inland. Can you explain the vegetation image?

During Dec, image shows higher in light green colour which mean is suffer from dry seasons due to wind blow from north-east to south.

4.     4.                     Can you explain the variation in vegetation along the Pacific coast?

In my opinion, this mainly due to monsoon season which abruptly interfere with amount of precipitation.

5.     5.                      Compare the information on  climate as described in the maps in a normal school atlas with the NDVI image. How are yearly changes of the location of the Inter-Tropical Convergence Zone (ITCZ) reflected in the NDVI images?

ITCZ area converge trade wind and raising air that encircle the equator of the earth. The rising air produces high cloudiness, frequent thunder storm and heavy rainfall. The ITCZ shift north and south with the Sun seasonally. It is responsible for the wet and dry seasons in the tropics. The tendency for convective storms in the tropics is short in duration, usually on a small scale but can produce intense rainfall. Greatest rainfall typically occurs when the midday Sun is overhead. On the equator this occurs twice a year in March and September, and consequently there are two wet and two dry seasons. Further away from the equator, the two rainy seasons merge into one, and the climate becomes more monsoonal, with one wet season and one dry season. In the Northern Hemisphere, the wet season occurs from May to July, in the Southern Hemisphere from November to February. 

Linearment Mapping in Remote Sensing

Figure 1: Outcome of Linearment Mapping

Figure 2: DEM file

Question in regarding this topics:

Q1: what is grayscale image?

Greyscale image is image that consist of only 2 colour, black and white. But with different value, hue and chroma. Example of greyscale image in remote sensing is those panchromatic image with one band. Greyscale image must first generated in lineament mapping as it is best to be viewed and compare in grayscale.

Q2: What is false colour composite image

False composite colour image used in interpretation of the map which involve spectral reflectance signature. False colour composite image normally involve in using multi spectral image that are nearly infrared, red and or green spectral band. Different attribute of  colour represent different reflectance value.

Q3:which is the best colour composite for lineament mapping.

The convert of RGB to either intensity or hue or saturation. This is because it helps in preserving the original colour through high pass filtering.

Q4: What is the difference between .ers and .alg

.ers format	.alg format
Data file	Data set
Example: contour.ers,road .ers	Example: 1990.alg
Cannot be open with ermapper staright forward. Only can be used as data layer.	Finish work were saved in .alg form and open to continue editing using ermapper
When we finish editing the .alg were saved as .ers	Unfinish work were saved in .alg in order to continue. Multiple .ers can be used to create .alg

Q5: compare the two  imagery  and describe the landuse change that had occurred between 1990 and 2002.

It is obviously that colour between the map is different. For example, if green color represent the vegetation. It can be noticed that vegetation in 1990  is lighter than 2002. This can be due to regrowth or plantation of new vegetation at the site. The river in 2002 also show obvious lighter colour, we assume that the landuse of the site improved over the year.

Q6: Describe the difference noticed in terms  of spatial resolution..

In term of spatial resolution, by turning on the intensity, we see clearer image with darker colour.

Q7: which one is the best to digitize road? Polyline, polygon or rectangle?

Polyline. Polyline appear are used to digitize line whereas polygon and rectangle used to digitize shaped objects.

Q8: Describe the procedure of changing the colour and thickness of the polyline/

After the we digitize the polyline, line table appear, from there we change their properties.

Q9: what is DEM?

Digital elevation model. It is 3D representation and common input data for any terrain mapping and analysis. It is common in slope and aspect analysis. Contour line created represent the angle of declination of the slope.

Q10: What is the lowest and highest elevation in the study area?

The range is between 800m and 1800m.

Scoreboard for Remote Sensing Quiz

Aerial Photographs and Landslide Delineation using erMapper and ArcGIS

Labwork for ESC 4511 Environmental Remote Sensing:

Question need to be answered before we start using erMapper:

1.    What is rectifying process?

Simple words that explain all is the process of converting/reassign coordinates to pixels from few images into a one common plane. In details, rectification process is a transformation process that used to project 2 or more images onto a image plane/ planimetric image. It’s also part of data projection that bring geometric characteristics of data into conformance with a know coordinate system. Rectification process correct any distortion by transforming the image into standard coordinate system.

2.       What is GCP (Ground control point) in rectifying process

GCP are points that greatly influence the accuracy of spatial interpolation of a data. GCP normally are points on a paper or digital map that has known coordinates and is used to transform another dataset. GCP serve the purpose of:

·         Digitizing data from from paper maps

·         Georeferencing both raster and vector data

·         Spatial adjustment operation

In short, GCP stands for location that are identified on the raster dataset and in real-world coordinates

3.  What is map projection

Map projection is the process of expressing the 3D surface/ curved surface of the earth into a 2D flat surface of a map. Map projection commonly and are important in creating maps. However, it is not an easy job to project an 3D image onto a 2D surface as distortion happens when doing so. Therefore, a good globe can provide accurate representation of the earth and aid in map projection.

4.      4.    What is geodetic datum

Tools used to define the size and size of the earth and the origin and orientation of the coordinate systems used to map the earth

5.       5.   Can two maps of the different map projection can be overlap onto each other? Provide reasons

Definitely yes. As overlaying data layers from separate sources and coordinate systems can be found in ArcGIS which enable us to intergrate datasets within maps that were in common between map projections

6.      6.    Number of GCP we had utilized in georenferencing the aerial photos? Tables of our GCP

We used 6, for the 125.alg

7.       7.   What are the criteria of a good GCP

If we are using quadratic  polynomial order in geocoding. It requires minimum 6 GCP. But for a good result, we recommend 12 GCP. As for the RMSE (root mean square area) must not be exceeding 1 for any of the points

8.      8.    Provide 3 example of good features for GCP

·         Road intersection

·         Landmark like bridges or railway or buildings

·         Natural earth features like lagoons, bays or estuaries

9.     

              9.  What is the min value of RMSE for each point that we manage to achieve

            10.   Why do you think it is difficult to achieve the RMSE of less than 1 in this aerial exercise

Because this exercise requires absolute patients to plot the exactly points that have similar coordinate with the correct one in the true location

1   11.  Why it is important to achieve RMSE of less than 1

In short, RMSE estimate the goodness of the derived transformation. In this process, it measures the fit between the true location and the transformed location of the output control point. The smaller the RMSE, the more precise the point.

Aerial Photographs and Landslide Delineation

Study Area. shp:

 Landslide.shp:

Area of the polygon:

Latest update mosaic.tiff file

3/3/2014 ESC 4511 REMOTE SENSING Lab week 2

This is what i had learnt and done today. No idea of what it is? Basically what we learnt today mostly focused on remote sensing algorithms. From my understanding, algorithms actually is a system that utilize formulas to convert unreadable digital data to readable data through computers. This serve the purpose for the users to read and analyse the data.

Through today lab, we were able to use Ermapper, insert unreadable data through land satellite. Format of the file were ERS file. Then the file undergo varies steps for example contrast setting, changing band colour, add in layers and etc before turning it into 3D view as above. Afterwards we were given task to look for houses, but we could'nt find it. We were very disappointed.

Why is that the algorithms in remote sensing is important in remote sensing. As i mention before, algorithms serve the purpose of converting unreadable format to readable format. This step is important in term of later work regarding map studies or GIS studies. For example, GIS mapping requires raster data that is readable. Other examples were, map making which important in country planning and so on. 

In a nutshell we won't be here if it wasn't because of algorithms of remote sensing. The end.

What is my expectation toward ESC4511 REMOTE SENSING ???

Expectation toward Remote Sensing:

I am a 3rd year environmental studies students from Universiti Putra Malaysia. It has been three year I had studies things about environment. This year I took a course called ESC4511 REMOTE SENSING. We were requested to write blogs and hand in our reports and couseworks through blog. Last year, when I took the course Geographic Information System, i learnt something about remote sensing, but it just the scratch of the surface. I know nothing more about remote sensing. So, here I am taking ESC4511 REMOTE SENSING.

What can i expect from remote sensing? First, i wish to know more about remote sensing. What can remote sensing benefit to me? to people around me? or to the environment? Remote sensing maybe bored to what I had studied about previously, but i am more interested in how come a satellite image sometimes with blurred image can tell so much information?

Second, i wish that i will become more skillful in handling props and software used in remote sensing. From the first lab time, we had been introduce to ERmapper. But we dint even know how to use the software. Therefore, through this course, i hope that i am determined enough to learnt things about remote sensing software.

Third, another of my expectation toward this course is that it may somehow benefits to my future career. I am deeply in love of what I am studying right now. For my future career, i insists of picking jobs related to what I had studied.

Finally, i hope that my dear lecturer can enlighten me with the wonders of the remote sensing. Thank you!