Crop classification in Magic Valley for 2003 for Analysis of Crop
Coefficient and Impact of Irrigation Method Type
Dr. Ignacio Lorite Torres1 and Dr. Richard G. Allen2
Introduction
This report summarizes work during 2003 and 2004 to classify crops of Magic
Valley by general crop type and the associated analysis of the population of crop
coefficients of the valley, by crop type, using crop coefficients derived by the METRIC
satellite remote sensing software of the University of Idaho. The report supercedes
previous reports (Crop classification for Magic Valley in 2003), as modifications to some
procedures have been made in this report. All information contained in the previous
reports is included in this report.
Materials
Prior to classification of crops in the Magic Valley, the primary cultivated areas in
the valley were defined by outlining the primary irrigated areas (see Map 1). These areas
were the focus of all the analysis described in this report. Individual outlined areas
(Figure 1) included the “Northside” (top left of figure), Twin Falls Canal Company
(bottom left), “Minidoka” region (upper left), and Burley area (lower right). These areas
were delineated for purposes of comparing relative water use by crop (i.e., the crop
coefficient) among the subregions and well as comparing relative water use by major
irrigation system type (center pivot is the predominant system type on the north side of
the Snake River and furrow irrigation, wheel-line or hand-move sprinkler are
predominant on the south-side, especially in the TFCC tract).
Four progressive tests and delineations were applied during the crop classification
with heavy reliance on ground truthed data on crop type. In total, crops were identified
during ground-truthing during 2003 for 318 fields (80 alfalfa, 33 bean, 16 corn, 26
potatoes, 60 sugar beet and 103 wheat). The results of the four progressive tests to define
crop class are accumulative. Only those crops (fields) that had some question on
identification during a previous tests are subjected to a following test. Only one pixel in
each field was considered. All the locations considered for this analysis are shown in
Appendix 1. The normalized difference vegetation index (NDVI) was calculated for 7
Landsat images (see Table 1), with trends in NDVI serving as the primary basis for
distinguishing crop types. Unfortunately, no cloud-free Landsat 5 dates were available in
2003 beyond August 31. Therefore, months of September and October, where crops are
Post-doctoral research, University of Idaho Kimberly Research and Extension Center, August 2003 –
August 2004, currently Researcher, Instituto de Investigación y Formación Agroalimentaria y Pesquera,
CIFA Alameda del Obispo, Córdoba, Spain.
2
Professor of Water Resources Engineering, University of Idaho Kimberly Research and Extension Center.
1
1
in senescence mode (browning and dying) could not be used to distinguish between crop
types. This made the analysis more challenging.
Map 1. Cultivated areas in Magic Valley evaluated during this study (Landsat image
8/31/2003).
Test 0. NDVI analysis
This test was used to filter and remove some fields from the ground truth set that
had strange NDVI signatures. Thus, restrictive rules as shown in Table 1 were identified
to remove some fields. If any” field did not comply with these rules, the field was
removed from further use in the ground-truth set. The NDVI is computed as a relatively
simple difference ratio between two of the six short-wave bands of Landsat. These two
bands (the red and the shortest near-infrared band) provide relatively good indication of
vegetation, since healthy, green vegetation characteristically absorbs large amounts of red
light but tends to reflect large amounts of near infrared. Therefore, the more the
vegetation, the larger the difference between these two bands. Mathematically:
  3
NDVI  4
 4  3
2
where ρ4 is the reflectance in band 4 (reflectance ranges from 0 for no reflectance (black
in this band range) to 1 (complete reflectance (i.e, mirror)) in the band), and ρ 3is the
reflectance in band 3 (the red band). The difference between ρ4 and ρ3 in the numerator
is divided by the sum of the two reflectances to “normalize.” In our application, we used
reflectances “at the top of the atmosphere” (i.e., not corrected for the effects of
atmospheric attenuation or scattering).
Table 1. Preliminary tests to remove some ground-truthed fields that did not follow
expected behavior crop, and the dates of 2003 Landsat images used in the analyses (last
two columns).
Crop
Alfalfa
NDVI
> 0.2
> 0.3
Beans
> 0.4
< 0.3
> 0.5
Corn
< 0.2
Potato
< 0.3
> 0.5
Sugar beet > 0.6
< 0.3
Wheat
< 0.6
> 0.5
> 0.4
Image
2 and 3
1 or 2
6
2, 3 and 4
< 60 days
2 and 3
2 and 3
6
6 and 7
2
6 and 7
4
3
Date range
May
April – Mid May
Late July
May - June
May
May
Late July
Late July - August
Mid May
Late July - August
Late June
Late May
Landsat
Image
Date
1
2
3
4
5
6
7
9-Apr
19-May
27-May
28-Jun
14-Jul
30-Jul
31-Aug
Finally, the restriction for beans that the period during which NDVI is higher than
0.5 must have a duration shorter than 60 days was kept, although this restriction may be
excessively restrictive. See later in this report for more details.
The resulting plots of NDVI for ground truthed fields are shown in Fig. 1 to 6
sorted by crop and filtered using Table 1. Fields removed due to inconsistent behavior
(potentially due to errors in ground data) included 8 plots for alfalfa, 13 for beans, 4 for
corn, 7 for potatoes, 17 for sugar beets and 23 for wheat. These are not ioncluded in the
figures 1-6 (see Appendix 2). The original ground data and the plots removed using the
rules cited in Table 1 are shown in Appendices 1 and 2.
3
4Ju
n
11
-J
un
18
-J
un
25
-J
un
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
Alfalfa
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Fig. 1. NDVI evolution for filtered, ground-truthed alfalfa.
Bean
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
4
4Ju
n
11
-J
un
18
-J
un
25
-J
un
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
4Ju
n
11
-J
un
18
-J
un
25
-J
un
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
Fig. 2. NDVI evolution for filtered, ground-truthed beans.
Corn
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Fig. 3. NDVI evolution for filtered, ground-truthed corn.
Potato
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
5
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
Fig. 4. NDVI evolution for filtered, ground-truthed potatoes.
Sugar beet
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Fig. 5. NDVI evolution for filtered, ground-truthed sugar beets.
Wheat
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
6
Fig. 6. NDVI evolution for filtered, ground-truthed wheat (both spring and winter types).
Test 1. Unsupervised classification to create 50 categories
An “unsupervised” classification of all delineated agricultural areas of Magic
Valley (Figure 1) was made based on NDVI over the seven Landsat images available for
2003 to associate each field in the valley with a unique class of NDVI trends. ERDAS
Imagine software was used for this process. In this unsupervised classification process
only 50 categories were created and the unsupervised classification was applied only to
areas within the agricultural region of Magic Valley.
Table 2 shows the results using the unsupervised classification of ERDAS
Imagine and the association of some of the “agricultural” classes (of the 50 original) with
crops identified during ground-truthing.
Table 2. Categories determined using unsupervised classification on NDVI trends over
seven Landsat images
Categories
Alfalfa
8*, 11*, 18*, 29, 31*, 33, 34*, 35, 37*, 38*, 40*, 42*, 43, 45, 46, 47, 48, 49, 50
Bean
12, 13, 14, 16, 19*
Corn
14, 22, 24
Potato
16*, 22, 23, 25*, 26, 28*
Sugar Beet 22, 24, 25, 26
Wheat
6*, 20*, 32, 33, 34, 35, 36, 37
Some categories were eliminated if the category occurred only once for a crop
(we required at least 2 times). However, in other cases these categories were considered
as correct (See Test 4 for details).
Test 2. Separation of alfalfa from wheat
Only the ground-truthed fields filtered during test 0 and shown in the figures 1-6
were used for analyses in Tests 2 and 3. The NDVI evolution throughout the season was
primarily analyzed according to oscillating increases and decreases in the index.
Traditional crops such as wheat or sugar beet have relatively continuous increases in
NDVI and then a decreasing convex trend in NDVI during senescence. This is very
different from NDVI signatures for alfalfa. Alfalfa, due to the frequent cuttings, exhibits
7
several increases and decreases in NDVI during the season (Fig. 1) which are not present
for other crops.
This test procedure was uniquely applied to two categories (33 and 35) to separate
wheat and alfalfa. Beans, corn or other crops were not considered during this test. A
crop was considered to be alfalfa if the NDVI fell significantly during some period and
then later recovered. This behavior is not expected for annual crops that are not harvested
for forage. A 0.15 variation in NDVI was used to indicate a significant reduction or
increase in NDVI. An additional test was considered, where NDVI7 (NDVI on 8/31)
must be higher than 0.3 to separate alfalfa from wheat. If any of the two tests were
positive, the crop was considered as alfalfa.
Initially, a 0.05 reversed fluctuation in NDVI was considered to denote alfalfa,
but finally it was considered to be too small, even though this value obtained better
separation between alfalfa and wheat in categories 33 and 35. When considering a value
change equal of 0.15 for separation, the accuracy for alfalfa was reduced to around 68%
with similar, corresponding error for wheat.
Alfalfa
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
4/
9/
20
0
4/
16 4
/2
00
4/
4
23
/2
00
4/
30 4
/2
00
4
5/
7/
20
0
5/
14 4
/2
00
5/
21 4
/2
00
5/
4
28
/2
00
4
6/
4/
20
0
6/
11 4
/2
00
6/
4
18
/2
00
6/
25 4
/2
00
4
7/
2/
20
04
7/
9/
20
0
7/
16 4
/2
00
7/
4
23
/2
00
7/
30 4
/2
00
4
8/
6/
20
0
8/
13 4
/2
00
8/
20 4
/2
00
8/
4
27
/2
00
4
0
Figure 7. NDVI evolution observed for alfalfa
The accuracy of the alfalfa-wheat separation method is shown in Table 3. This
table represents all filtered ground data for alfalfa and wheat. Beans or corn do not appear
in this table, as the test was only used for categories 33 and 35; Table 2.
The percentage of filtered fields that this test considered as alfalfa is shown in
Table 3. Considering uniquely the NDVI variation (0.15), small accuracy in separation
between alfalfa and wheat was found (67.5%). However this accuracy was increased by
analyzing NDVI on 8/31 (NDVI7). Finally, in 88.8% of the cases, fields of alfalfa were
correctly identified as alfalfa and in the 1.9% of the cases the plots that were really wheat
8
were marked as alfalfa. The other 9.3 % of the dates (100-88.8-1.9) could not be
classified using this test.
Table 3. Percentage of filtered fields that the alfalfa-wheat separation method (Test 2)
considered to be alfalfa. The first column used only NDVI variation, the second column
used only NDVI7 and the third column considered both.
Alfalfa
Wheat
C=0.15
67.5
0.0
NDVI7>0.3
86.3
1.9
OR
88.8
1.9
The analysis and results are located in c:/mv/crop classification/alfalfa_clas.xls
Test 3. Band combinations to separate some categories containing potatoes, sugar
beets, corn and beans
Some crops, especially potatoes, sugar beets, corn and beans are problematic to
separate via unsupervised identification using only NDVI (which is computed using only
bands 3 and 4 of Landsat). Thus, specific band combinations have been used to separate
these crops. Table 4 shows the Landsat band combinations used to differentiate crop
types. Only the image for August 30 was considered because on this date all the crops
were at full cover except wheat, making the crop differentiation easier and more
consistent. This procedure was uniquely applied to crops in categories created by the
previous unsupervised test that contained multiple crop types (see categories colored in
Table 2).
9
Table 4. Band combinations to differentiate the crops in categories colored in Table 2
except categories 33 and 35. Categories suggested to the test are in parentheses.
1.
If
Band 1  Band 5
 0.20
Band 1  Band 7
then Potato otherwise Sugar beet (22; 26)
2.
If
Band 2  Band 5
 3.5
Band 2  Band 7
then
Corn otherwise Sugar beet (22; 24)
3.
If
Band 4  Band 5
 0.5
Band 4  Band 7
then
Beans otherwise Corn (14)
4.
If
Band 1  Band 5
 0.35
Band 1  Band 7
then
Potato otherwise Corn (22)
The percentages of accuracy in correctly classifying a given crop are shown in
Table 5 when the rules presented in Table 4 are applied. For example, in the first test,
using the first band combination, 94.74 % of potato fields were correctly classified as
potatoes and 97.67 % of sugar beets was correctly classified as sugar beet. The errors for
this case were 5.26 % of potatoes were classified as sugar beet and 2.33 % of sugar beets
were classified as potatoes. In the same way the percentage of accuracy using the other
band combination tests provided similar results (Table 5).
Others band combinations also were considered. However, the results obtained
(percentage of accuracy for each crop) were worse than those shown in Table 5.
Table 5. Percentage of accuracy (the crop obtained from the ground data coincides with
the results using the rules of Table 4) in the separation of crops using band method.
Test
Corn
Sugar B.
Beans
Potato
1
2
3
4
100.0
95.35
83.33
83.33
97.67
80.0
94.74
73.68
10
Test 4. Crop assignment by considering one unique coincidence (see Test 1)
In Test 1, several category – ground-truthed combinations were discluded when
only one occurrence was found (categories 8, 11, 34, 37, 38, 40, 42 for alfalfa, 19 for
bean, 16, 25 and 28 for potato and 6 and 20 for wheat). These were discluded because
only one observation in that class was considered to be insufficient to judge the accuracy
and consistency of that class for identifying the specific crop type.
In this test, some categories having only one occurrence have been reconsidered
for use. If the analysis of NDVI during the season and the values contained in Table 7
indicated that these categories were effective in describing attributes of the original crop,
this category was retained as a valid representation. Thus, categories 11, 38 and 40 were
retained as alfalfa, 19 as beans, 28 as potato and 6 as wheat (Table 6). Other categories
including 18, 31 and 42 could have been accurate in distinguishing alfalfa from other
crop types, although this was questionable. The same question occurred with category 20
for wheat (Table 6).
Table 6. “A” categories added in test 4, “B” categories could have been included but
were not.
A
Alfalfa
11, 18, 42
Bean
19
Corn
Potato
28
Sugar beet
Wheat
Double cropping *
38, 40
B
31
20, 6
* The double cropping has been determined uniquely using the NDVI evolution but it has
not been validated in the field. The categories 38 and 40 were initially marked as alfalfa
during field ground-truthing (see Table 2).
Results
For all retained ground-truthed fields, an average NDVI by crop was determined
(Table 7). The NDVI was based on 4 pixels in each field to obtain a better average value.
The same values contained in the Table 7 are shown in the Figure 8. Unfortunately, no
cloud-free Landsat images were available past 31 August of 2003.
Table 7. Average NDVI of filtered ground-truthed fields by date (of the Landsat image)
Alfalfa
Beans
9-Apr
0.394
0.098
19-May
0.764
0.146
27-May
0.804
0.106
28-Jun
0.664
0.178
14-Jul
0.611
0.397
30-Jul
0.595
0.710
31-Aug
0.676
0.429
11
Maize
Potatoes
Sugar Beet
Wheat
Double Cropping
0.103
0.115
0.102
0.221
0.280
0.139
0.144
0.135
0.687
0.694
0.110
0.123
0.122
0.750
0.777
0.275
0.685
0.550
0.762
0.257
0.549
0.823
0.701
0.503
0.245
0.756
0.803
0.744
0.220
0.713
0.762
0.515
0.781
0.146
0.799
For each of the 50 unique crop type categories determined using ERDAS during
“test 1”, the mean value of NDVI averaged over all pixels (fields) assigned to that
category and date was determined and is presented in Table 8. These values can be
compared to the mean ground-truthed values shown in Table 7 and Figure 8.
Categories in Table 8 where no crop is identified are those where it was not
possible to assign a crop to that category (i.e. 7, 17, 18, 20, 21, 26, 27, 30, 31, 39, 41, 42
and 44). However, during later test iterations, some of these were finally assigned a crop
identification.
0.9
0.8
Alfalfa
Beans
Maize
0.7
Potatoes
Sugar Beet
0.6
Wheat
*
NDVI
Double cropping
0.5
0.4
0.3
0.2
0.1
0.0
14-Mar
3-Apr
23-Apr
13-May
2-Jun
22-Jun
12-Jul
1-Aug
21-Aug
10-Sep
Figure 8 Mean NDVI evolution for the main crops in Magic Valley area based on
ground-truthed fields.
12
The decreasing value in NDVI for potatoes for the last (31 August) image date
was caused by the fields in category 23 (See Table 8). The other categories used to
identify potatoes (22, 23 and 28) had values of NDVI around 0.7. It is possible that
different varieties of potatoes caused these differences in NDVI and lowered the average
value. The category 23 might represent potatoes of the Norkota variety, for example, that
senesce and are harvested early for French fry production, whereas categories 22, 23 and
28 represent longer season varieties such as baking potatoes.
Table 8 Average NDVI for each category and date. Additionally, the crop assignment
was made using tests 0, 1, 2, 3 and 4 for each category.
Category
9-Apr
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
0.035
0.128
0.245
0.230
0.401
0.282
0.291
0.139
0.231
0.131
0.290
0.136
0.125
0.139
0.318
0.130
0.310
0.187
0.123
0.135
0.139
0.121
0.125
0.123
0.111
0.114
0.308
0.140
0.256
0.226
0.126
0.106
0.127
19-May 27-May 28-Jun
0.101
0.204
0.322
0.416
0.541
0.646
0.471
0.355
0.309
0.190
0.457
0.172
0.167
0.161
0.428
0.740
0.533
0.284
0.159
0.249
0.192
0.155
0.154
0.155
0.145
0.149
0.258
0.215
0.421
0.502
0.213
0.399
0.494
0.036
0.178
0.245
0.349
0.394
0.652
0.380
0.449
0.270
0.157
0.370
0.138
0.131
0.125
0.373
0.138
0.513
0.273
0.126
0.269
0.167
0.132
0.133
0.133
0.130
0.136
0.251
0.251
0.467
0.570
0.275
0.584
0.605
0.056
0.187
0.182
0.216
0.234
0.344
0.340
0.438
0.278
0.242
0.265
0.166
0.206
0.177
0.361
0.227
0.492
0.401
0.311
0.579
0.439
0.332
0.685
0.391
0.556
0.707
0.564
0.703
0.540
0.613
0.742
0.786
0.684
14-Jul
30-Jul
31-Aug
Crop
Fields*
0.054
0.172
0.166
0.192
0.214
0.262
0.292
0.322
0.285
0.291
0.279
0.229
0.352
0.316
0.404
0.409
0.414
0.467
0.616
0.493
0.652
0.553
0.799
0.723
0.728
0.797
0.750
0.509
0.528
0.682
0.737
0.711
0.466
0.540
0.172
0.690
0.187
0.219
0.221
0.280
0.245
0.294
0.329
0.338
0.416
0.641
0.659
0.462
0.673
0.376
0.433
0.709
0.313
0.651
0.690
0.739
0.755
0.751
0.783
0.730
0.555
0.604
0.521
0.401
0.287
0.252
0.043
0.164
0.159
0.164
0.196
0.189
0.277
0.197
0.296
0.365
0.561
0.659
0.246
0.706
0.387
0.521
0.401
0.559
0.218
0.222
0.526
0.741
0.284
0.743
0.759
0.736
0.733
0.663
0.650
0.501
0.194
0.166
0.181
Water
Desert
Desert
Desert
Desert
Wheat
0
0
0
0
0
1
Cities/Trees
Cities/Trees
Cities/Trees
Alfalfa ***
Beans
Beans
Beans/Corn
Cities/Trees
Beans
0
0
0
1
4
3
4/4
0
8
Beans
1
Corn/Pot/Sugar B 4/2/7
Potatoes
3
Sugar Beet
8
Potatoes/Sugar B 1/20
Potatoes
Alfalfa ***
1
2
Wheat
Alfalfa/Wheat
8
2/10
13
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
0.135
0.152
0.573
0.429
0.441
0.499
0.368
0.634
0.455
0.340
0.552
0.366
0.398
0.404
0.466
0.278
0.495
0.676
0.737
0.791
0.768
0.721
0.636
0.591
0.404
0.641
0.733
0.766
0.744
0.779
0.778
0.746
0.751
0.799
0.762
0.780
0.790
0.766
0.713
0.405
0.546
0.224
0.619
0.775
0.340
0.778
0.814
0.811
0.763
0.788
0.795
0.795
0.728
0.680
0.735
0.346
0.403
0.419
0.318
0.610
0.416
0.533
0.376
0.631
0.668
0.720
0.744
0.787
0.645
0.378
0.344
0.552
0.341
0.701
0.417
0.566
0.564
0.760
0.673
0.681
0.803
0.796
0.735
0.390
0.380
0.249
0.220
0.215
0.378
0.423
0.406
0.535
0.694
0.559
0.366
0.697
0.746
0.440
0.379
0.686
0.722
0.769
0.166
0.177
0.165
0.316
0.526
0.496
0.598
0.702
0.625
0.757
0.734
0.710
0.402
0.793
0.706
0.669
0.751
Wheat
Alfalfa/Wheat
Wheat
Wheat
Alfalfa **
16
4/22
17
5
1
Alfalfa **
1
Alfalfa
6
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
4
11
8
5
7
14
* Number of ground truthed fields assigned to the category
** Finally categories 38 and 40 were labeled as “double cropped” although category 40
could be “pasture”
*** Could be “pasture”
The results obtained for each set of progressive tests have been reported in Table
9. The global results using the four sets of tests had 94% (0.943) accuracy using filtered
ground truthed data. Crop by crop, the maximum accuracy was found for wheat (97.5%)
and the worst for potatoes (89.5% due to abandonment of some single populated
categories).
Table 9. Accuracy in the classification of original, filtered ground truthed fields using the
progressive crop classification (1 equal to maximum accuracy).
Alfalfa
Bean
Corn
Potatoes
Sugar B
Wheat
Global
Test 1 (ERD)
0.814
0.750
0.000
0.158
0.465
0.575
Test 2 (Alf)
0.871
0.750
0.000
0.158
0.465
0.975
0.578
0.725
Test 3 (Band) Test 4 (Categ) OK/Total
0.871
0.914
64/70
0.850
0.900
18/20
0.917
0.917
11/12
0.842
0.895
17/19
0.977
0.977
42/43
0.975
0.975
78/80
0.922
0.943
230/244
These results could be improved if the conditions in Test 0 were more restrictive,
removing some specific signatures assigned to potatoes or alfalfa. However, this would
increase the number of fields in the valley that can not be assigned to a specific class.
14
Other ways to improve accuracy would be to consider other categories listed under test 4
(Table 6). The location, crop, and category assigned by ERDAS is shown in Appendix 3
for each ground-truthed data point, along with the accuracy for each test. Additionally,
fields with problems with crop identification are included in Appendix 4.
15
Maps showing 2003 crop classification in Magic Valley
Using the previously developed test sets, a crop classification for the entire Magic
Valley irrigated area was determined. The results are shown in Maps 2, 3 and 4.
It is possible that the spring wheat category includes peas, which were not
available as part of the ground-truth set. The similarity of growing season dates and
lengths with wheat would probably cause peas to be falsely classified as wheat (Allen,
personal communication).
a.
b.
Map 2. Crop classification for Magic Valley in 2003. Light green indicates alfalfa, red
indicates beans, dark green indicates maize, cyan indicates potatoes, blue indicates sugar
beet, yellow indicates wheat and white indicates double cropping. Unclassified or
unidentified fields are in black.
16
Map 3. Close up of 2003 crop classification in Twin Falls - Kimberly area. Light green
indicates alfalfa, red indicates beans, dark green indicates maize, cyan indicates potatoes,
blue indicates sugar beet, yellow indicates wheat and white indicates double cropping.
Unclassified or unidentified fields are in black.
17
a.
b.
Map 4. Close up of crop classification in areas a and b (see Map 1). Light green indicates
alfalfa (or in some situations, pasture), red indicates beans, dark green indicates maize,
cyan indicates potatoes, blue indicates sugar beet, yellow indicates wheat and white
indicates double cropping. Unclassified or unidentified fields are in black.
18
Separation of winter wheat from spring wheat
The ground-truth data set in 2003 provided information essentially only for wheat
in general, without distinction for winter vs. spring crops. In this section, the two wheat
varieties are separated. Initially, only NDVI was considered to separate winter and spring
wheat. However, we have observed that spring wheat tends to have a “lighter” green
color during the first month or two of growth as compared to winter wheat, with is
typically darker green. Therefore we additionally evaluated using differences in albedo
for separation.
Finally, the two different tests (NDVI and albedo in the first image available
during 2003; 04/09) were applied to separate winter wheat from spring wheat since this
category was only identified as wheat during ground truth process. Wheat was separated
into spring wheat when NDVI in the first image (April 9) was lower than 0.3. Results are
shown in Figure 9.
19
0.9
Spring
wheat
0.8
0.7
NDVI
0.6
0.5
0.4
0.3
0.2
0.1
9A
16 p r
-A
23 pr
-A
30 pr
-A
7- pr
M
14 a y
-M
21 ay
-M
28 ay
-M
ay
4Ju
11 n
-J
18 u n
-J
u
25 n
-J
un
2Ju
9- l
Ju
16 l
-J
u
23 l
-J
30 u l
-J
u
6- l
Au
13 g
-A
20 ug
-A
27 ug
-A
ug
0
0.9
Winter
wheat
0.8
0.7
NDVI
0.6
0.5
0.4
0.3
0.2
0.1
9A
16 p r
-A
23 pr
-A
30 pr
-A
7- pr
M
14 a y
-M
21 ay
-M
28 ay
-M
ay
4Ju
11 n
-J
18 u n
-J
u
25 n
-J
un
2Ju
9- l
Ju
16 l
-J
u
23 l
-J
30 u l
-J
u
6- l
Au
13 g
-A
20 ug
-A
27 ug
-A
ug
0
Figure 9. Differentiation in ground-truth wheat into winter and spring wheat based on
NDVI in the first image (April 9; NDVI > 0.3 = winter wheat)
The values of NDVI vs albedo are compared in Figure 10. On 04/09, fields with
lower values of NDVI had the higher values of albedo, which probably represented
spring wheat during early development. However, the soil effects when the crop is not at
full cover must be considered where light colored soil (high albedo) may confuse results.
Using a unique albedo could separate both types of crop with similar results as
using NDVI. In the 04/09 image, the value of albedo to provide similar separation as
NDVI is around 0.23 (Fig. 10). However, results are similar to that using NDVI, thus
using both would be redundant and spurious.
20
0.9
04/09
0.8
0.7
NDVI
0.6
Spring wheat
0.5
Winter wheat
0.4
0.3
0.2
0.1
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Albedo
0.9
05/19
0.8
0.7
Spring wheat
Winter wheat
NDVI
0.6
0.5
0.4
0.3
0.2
0.1
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Albedo
21
0.9
05/27
0.8
0.7
Spring wheat
Winter wheat
NDVI
0.6
0.5
0.4
0.3
0.2
0.1
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Albedo
0.9
06/28
0.8
0.7
NDVI
0.6
Spring wheat
Winter wheat
0.5
0.4
0.3
0.2
0.1
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Albedo
22
0.9
07/14
0.8
0.7
Spring wheat
Winter wheat
NDVI
0.6
0.5
0.4
0.3
0.2
0.1
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Albedo
0.9
07/30
0.8
0.7
Spring wheat
NDVI
0.6
Winter wheat
0.5
0.4
0.3
0.2
0.1
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Albedo
23
0.9
08/31
0.8
0.7
Spring wheat
NDVI
0.6
Winter wheat
0.5
0.4
0.3
0.2
0.1
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Albedo
Figure 10. Relationship between NDVI and albedo for predicted delineation of spring and
winter wheat (no ground-truth was available). The fields labeled as winter wheat were
distinguished from within the general wheat classification (ground-truthed fields only) as
those fields having NDVI>0.3 on April 9
24
Alfalfa vs. Pasture
Our classification analysis did not contain ground-truth samples for grass pasture.
Due to the length of greenness of pasture and the tendency of periodically grazed pasture
to oscillate in the value for NDVI similar to alfalfa, pasture was probably misclassified as
alfalfa in a number of cases. Following closer analysis of alfalfa classifications,
categories 11, 29 and 40 were changed from alfalfa to pasture labels. Because validation
is not possible, this relabeling has not been included in the final results.
The categories previously classified as alfalfa, but switched to pature have
reduced values of NDVI during the whole irrigation season (See Table 8). We considered
including a new restriction to consider a field as alfalfa if NDVI is higher than 0.7 at least
twice in the season (not included in this report), but did not have ground-truthing data to
support this. Categories 43, 45, 46, 47, 48, 49 and 50 are good examples of alfalfa.
The map differentiating between alfalfa and pasture is shown in Map 5.
Map 5. Close up of crop classification in area b (Buhl area (see Maps 1 and 4)) including
pasture (in magenta) and alfalfa (in light green). The other colors have been explained
previously.
25
Analysis of Crop Coefficient (i.e., ETrF) by Crop Type
The METRIC ET process can calculate the amount of ET from any 30 m x 30 m
pixel in both mm/day and also as a fraction of reference ET (ETr). ETr is defined as the
amount of ET expected from full cover alfalfa (0.5 m tall) and is used as a sort of climatic
index for evaporation. The ratio of ET from a specific pixel to the reference ET (ET r is
computed from weather data) is termed the “fraction of reference ET” or ETrF. ETrF is
essentially the same as the well-know crop coefficient (Kc).
Following the classification of fields in Magic Valley for crop type (see maps
previously introduced), the ETrF of each crop type was sampled from each field having
that classification. The result was a large “population” of ETrF values for each crop type.
Three different methods were explored to determine the average ETrF by crop type. In
the first approach, all the pixels for each crop were considered, including those along the
edges of fields. In the second approach, around 22,000 pixels in total were selected, with
four pixels taken from each classified field, and from well within each field to avoid the
effect of contamination from outside a field. The number of pixels and fields selected are
shown in Table 10. In both methods the crop classification map (Map 2) obtained with
the procedure described previously in this report, was used. In the third approach, only
those fields that were ground- truthed were used, based on four pixels sampled from each
field. This third approach, while represented a much smaller sample of fields, does
represent essentially perfect knowledge of crop type.
Table 10. Number of pixels and fields (four pixels from each field) selected, by crop, for
all classified fields having areas larger than about 10 acres.
Crop
Pixels
Fields
Alfalfa
Beans
Maize
Potatoes
Sugar Beet
Wheat
Double Crop
6320
1720
720
1684
3288
8196
296
1580
430
180
421
822
2049
74
Total
22224
5556
The average values of NDVI for each method are shown in the Figure 11.
26
1.00
a.
0.90
0.80
0.70
ETrF
0.60
0.50
0.40
0.30
Alfalfa
Beans
Maize
Potatoes
Sugar beet
Wheat
Double cropping
0.20
0.10
0.00
1.00
b. 18-Apr
29-Mar
0.90
8-May
28-May
17-Jun
7-Jul
27-Jul
16-Aug
5-Sep
0.80
0.70
ETrF
0.60
0.50
0.40
0.30
Alfalfa
Beans
Maize
Potatoes
Sugar beet
Wheat
Double cropping
0.20
0.10
0.00
29-Mar
18-Apr
8-May
28-May
17-Jun
7-Jul
27-Jul
16-Aug
27
5-Sep
1.00
c.
0.90
0.80
0.70
ETrF
0.60
0.50
0.40
0.30
Alfalfa
Beans
Maize
Potatoes
Sugar beet
Wheat
Double cropping
0.20
0.10
0.00
29-Mar
18-Apr
8-May
28-May
17-Jun
7-Jul
27-Jul
16-Aug
5-Sep
Figure 11. Average ETrF vs. time of 2003 by crop type using one of three sampling
methods: a) sampling all pixels for the crop, b) sampling four pixels interior to each field
and c) sampling four pixels interior to ground truthed fields, only.
Figure 12 compares the results of the three different sampling methods by crop.
With the exception of the double cropped category (due to the very limited number of
fields analyzed) the resulting average ETrF values are very similar among the three
sampling methods in regard to trends during the season. However, when crops were near
full cover (of the soil) and especially for alfalfa, averaged values for ETrF by the first
method (sampling all pixels) were lower than for the other methods due to contamination
of pixels by areas outside fields. The contamination of pixels is especially severe for the
temperature band of Landsat 5 (used for all of 2003 images), since the pixel size of this
band is 120 m by 120 m. Therefore, any 30 m pixels sampled that lie within 120 m (400
ft) of the edge of a field are prone to contamination by temperatures of outside areas.
Because areas outside irrigated fields in Idaho are usually drier than the field, they have
higher temperatures. The higher temperatures cause METRIC to predict lower ET rates
and thus lower ETrF (i.e., Kc). The low bias by sample method “a” is apparent for all
crops during periods of maximum ground cover (Figure 12).
28
Alfalfa
1.0
0.9
0.8
0.7
ETrF
0.6
0.5
0.4
0.3
0.2
Method 1 (All the pixels)
Method 2 (Four pixels)
Method 3 (Validated fields)
0.1
0.0
14-Mar 3-Apr 23-Apr 13-May 2-Jun 22-Jun 12-Jul
1-Aug 21-Aug 10-Sep
Beans
1.0
0.9
0.8
0.7
Method 1 (All the pixels)
Method 2 (Four pixels)
Method 3 (Validated fields)
ETrF
0.6
0.5
0.4
0.3
0.2
0.1
0.0
14-Mar 3-Apr
23-Apr 13-May 2-Jun
22-Jun 12-Jul
1-Aug 21-Aug 10-Sep
29
Maize
1.0
0.9
0.8
0.7
0.6
Method 1 (All the pixels)
Method 2 (Four pixels)
Method 3 (Validated fields)
ETrF
In Figures 12 to
0.5
0.4
0.3
0.2
0.1
0.0
14-Mar 3-Apr
23-Apr 13-May 2-Jun
22-Jun 12-Jul
1-Aug 21-Aug 10-Sep
Potatoes
1.0
0.9
0.8
0.7
ETrF
0.6
0.5
0.4
0.3
Method 1 (All the pixels)
0.2
Method 2 (Four pixels)
Method 3 (Validated fields)
0.1
0.0
14-Mar 3-Apr
23-Apr 13-May 2-Jun
22-Jun 12-Jul
1-Aug 21-Aug 10-Sep
30
Sugar beets
1.0
0.9
Method 1 (All the pixels)
0.8
Method 2 (Four pixels)
0.7
Method 3 (Validated fields)
ETrF
0.6
0.5
0.4
0.3
0.2
0.1
0.0
14-Mar 3-Apr
23-Apr 13-May 2-Jun
22-Jun 12-Jul
1-Aug 21-Aug 10-Sep
Wheat
1.0
0.9
0.8
0.7
ETrF
0.6
0.5
0.4
0.3
Method 1 (All the pixels)
0.2
Method 2 (Four pixels)
0.1
0.0
14-Mar 3-Apr
Method 3 (Validated fields)
23-Apr 13-May 2-Jun
22-Jun 12-Jul
1-Aug 21-Aug 10-Sep
31
Double cropping
1.0
0.9
0.8
0.7
ETrF
0.6
0.5
0.4
0.3
Method 1 (All the pixels)
0.2
Method 2 (Four pixels)
0.1
Method 3 (Validated fields)
0.0
14-Mar 3-Apr
23-Apr 13-May 2-Jun 22-Jun 12-Jul
1-Aug 21-Aug 10-Sep
Figure 12. ETrF comparison for each crop depending on the method described previously
Variation within populations of ETrF
The populations of ETrF for each major crop of the area are shown in Figures 13
to 19. In these figures, average values for 4 pixels from each field are shown for each
image date. The vertical line above each dates serves as the zero point for ETrF, which
plots away from the vertical line, toward the right.
32
Alfalfa
1.2
1
ETrF
0.8
0.6
0.4
0.2
0
0
1
2
3
4
5
6
7
8
9
10
Figure 13. Distribution of ETrF for alfalfa by field for the 7 image dates analyzed.
Beans
1.2
1
ETrF
0.8
0.6
0.4
0.2
0
0
1
2
3
4
5
6
7
8
9
10
Figure 14. Distribution of ETrF for beans by field for the 7 image dates analyzed.
33
Maize
1.2
1
ETrF
0.8
0.6
0.4
0.2
0
0
1
2
3
4
5
6
7
8
9
10
Figure 15. Distribution of ETrF for corn (maize) by field for the 7 image dates analyzed.
Potatoes
1.2
1
ETrF
0.8
0.6
0.4
0.2
0
0
1
2
3
4
5
6
7
8
9
10
Figure 16. Distribution of ETrF for potatoes by field for the 7 image dates analyzed.
34
Sugar beet
1.2
1
ETrF
0.8
0.6
0.4
0.2
0
0
1
2
3
4
5
6
7
8
9
10
Figure 17. Distribution of ETrF for sugar beets by field for the 7 image dates analyzed.
Wheat
1.2
1
ETrF
0.8
0.6
0.4
0.2
0
0
1
2
3
4
5
6
7
8
9
10
Figure 18. Distribution of ETrF for wheat (winter and spring) by field for the 7 image
dates analyzed.
35
Double cropping
1.2
1
ETrF
0.8
0.6
0.4
0.2
0
0
1
2
3
4
5
6
7
8
9
10
Figure 19. Distribution of ETrF for fields assumed to be double-cropped, for the 7 image
dates analyzed.
36
Impact of Irrigation method on ET
Theoretically, fields irrigated by center pivot systems should have somewhat
higher ET and thus ETrF than fields irrigated by surface irrigation. The higher ET stems
from generally higher wetting frequency and subsequent increased evaporation from wet
soil. In addition, water application uniformity and water management for center pivot
irrigated crops may be higher than for surface irrigated crops. This would encourage
better crop growth due to less water stress so that ET could be greater.
Five subregions within Magic Valley were defined for purposes of evaluating the
impact of irrigation system type on ETrF. The subregions are shown in Map 6. Each subregion has a predominant method for irrigation. The subregions are shown in Map 6 and
are termed Northside Canal Company (NSCC) (with mostly center pivots), Twin Falls
Canal Company (TFCC) (with mostly furrow (surface) irrigation and some sprinkler
irrigation), Oakley Fan (mostly center pivots), Minidoka (with a majority surface
irrigated) and NE desert (with center pivots).
5.
1.
2.
4.
3.
Map 6. Selected subregions of Magic Valley for evaluation of impact of general irrigation
method on ET. Zone 1 is NSCC (center pivots), zone 2 is TFCC (mostly surface
irrigation), zone 3 is Oakley Fan (center pivots), zone 4 is Minidoka (mostly surface) and
zone 5 is NE desert (center pivots)
Average ETrF was calculated for each crop type and image date for each of the
five subregions within Magic Valley. Table 11 summarizes mean ETrF for all crops and
image dates. Figure 20 gives a graphic comparison of mean ETrF by crop type.
37
Table 11. Average ETrF values by date and crop during 2003 for five subregions of
Magic Valley.
Crop
Alfalfa
Zone Location
1NSCC
2TFCC
3Oakley Fan
4Minidoka
5NE desert
Irrigation Method
Pivot
Surface
Pivot
Surface
Pivot
9-Apr
0.760
0.754
0.744
0.728
0.608
19-May 27-May 28-Jun 14-Jul
0.635
0.824 0.853 0.708
0.645
0.819 0.758 0.702
0.605
0.897 0.875 0.680
0.587
0.882 0.824 0.634
0.501
0.840 0.921 0.541
30-Jul 31-Aug
0.822 0.840
0.727 0.876
0.713 0.878
0.809 0.876
0.820 0.824
Crop
Zone Location
Sugar Beet
1NSCC
2TFCC
3Oakley Fan
4Minidoka
5NE desert
Irrigation Method
Pivot
Surface
Pivot
Surface
Pivot
9-Apr
0.477
0.405
0.473
0.535
0.432
19-May 27-May 28-Jun 14-Jul
0.139
0.193 0.848 0.984
0.078
0.098 0.773 0.869
0.019
0.117 0.751 0.869
0.057
0.125 0.808 0.871
-0.023 0.105 0.844 0.900
30-Jul 31-Aug
0.978 0.965
0.885 0.931
0.927 0.926
0.936 0.905
0.938 0.918
Crop
Beans
Zone Location
1NSCC
2TFCC
3Oakley Fan
4Minidoka
5NE desert
Irrigation Method
Pivot
Surface
Pivot
Surface
Pivot
9-Apr
0.533
0.423
0.520
0.514
0.429
19-May 27-May 28-Jun 14-Jul
0.160
0.207 0.547 0.753
0.160
0.119 0.217 0.499
0.049 -0.016 0.336 0.719
0.086
0.223 0.412 0.608
-0.007 0.043 0.596 0.846
30-Jul 31-Aug
0.901 0.298
0.819 0.573
0.942 0.417
0.934 0.519
0.901 0.470
Crop
Potatoes
Zone Location
1NSCC
2TFCC
3Oakley Fan
4Minidoka
5NE desert
Irrigation Method
Pivot
Surface
Pivot
Surface
Pivot
9-Apr
0.510
0.407
0.539
0.535
0.425
19-May 27-May 28-Jun 14-Jul
0.192
0.244 0.943 0.849
0.186
0.196 0.891 0.707
0.058
0.272 0.930 0.855
0.089
0.259 0.946 0.845
0.000
0.163 0.936 0.892
30-Jul 31-Aug
0.900 0.532
0.782 0.818
0.871 0.636
0.899 0.701
0.891 0.506
Crop
Wheat
Zone Location
1NSCC
2TFCC
3Oakley Fan
4Minidoka
5NE desert
Irrigation Method
Pivot
Surface
Pivot
Surface
Pivot
9-Apr
0.669
0.580
0.606
0.623
0.460
19-May 27-May 28-Jun 14-Jul
0.702
0.920 0.992 0.725
0.657
0.866 0.882 0.564
0.635
0.927 0.895 0.524
0.651
0.924 1.019 0.775
0.426
0.900 1.031 0.837
30-Jul 31-Aug
0.459 0.298
0.388 0.349
0.331 0.288
0.563 0.447
0.540 0.252
Crop
Maize
Zone Location
1NSCC
2TFCC
3Oakley Fan
4Minidoka
5NE desert
Irrigation Method
Pivot
Surface
Pivot
Surface
Pivot
9-Apr
0.502
0.449
0.536
0.561
0.339
19-May 27-May 28-Jun 14-Jul
0.189
0.211 0.514 0.934
0.120
0.164 0.319 0.666
0.032
0.009 0.579 0.856
0.039
0.121 0.471 0.819
-0.069 0.592 0.366 0.980
30-Jul 31-Aug
1.014 0.971
0.934 0.924
0.997 0.946
0.956 0.926
1.075 1.027
38
For many crops, the mean ETrF curve was lower for the two predominately
surface irrigated subregions (TFCC and Burley-Minidoka), which is expected. However,
this trend is not consistent for each crop. On average, however, there does appear to be
higher water use by crops in the more predomately sprinkler irrigated areas. In the case
of sugar beets, the NSCC (pivots) zone had ETrF that was about 10% greater than for the
TFCC (mostly surface). The difference was relatively consistent through the season.
Alfalfa in Magic Valley during 2003
1.0
0.9
0.8
0.7
ETrF
0.6
0.5
NSCC (pivots)
TFCC (surface)
Oakley Fan (pivots)
Minidoka-Burley (surface)
NE desert (pivots)
0.4
0.3
0.2
0.1
0.0
April-03
May-03
June-03
July-03
August-03 September-03
39
Sugar Beets in Magic Valley during 2003
1.0
0.9
0.8
0.7
ETrF
0.6
0.5
NSCC (pivots)
TFCC (surface)
Oakley Fan (pivots)
Minidoka-Burley (surface)
NE desert (pivots)
0.4
0.3
0.2
0.1
0.0
April-03
May-03
June-03
July-03
August-03 September-03
Beans in Magic Valley during 2003
1.0
0.9
0.8
0.7
ETrF
0.6
NSCC (pivots)
TFCC (surface)
Oakley Fan (pivots)
Minidoka-Burley (surface)
NE desert (pivots)
0.5
0.4
0.3
0.2
0.1
0.0
April-03
May-03
June-03
July-03
August-03 September-03
40
Potatoes in Magic Valley during 2003
1.0
0.9
0.8
0.7
ETrF
0.6
0.5
0.4
NSCC (pivots)
TFCC (surface)
Oakley Fan (pivots)
Minidoka-Burley (surface)
NE desert (pivots)
0.3
0.2
0.1
0.0
April-03
May-03
June-03
July-03
August-03 September-03
Wheat in Magic Valley during 2003
1.2
NSCC (pivots)
TFCC (surface)
Oakley Fan (pivots)
Minidoka-Burley (surface)
NE desert (pivots)
1.0
ETrF
0.8
0.6
0.4
0.2
0.0
April-03
May-03
June-03
July-03
August-03 September-03
41
Corn in Magic Valley during 2003
1.2
NSCC (pivots)
TFCC (surface)
Oakley Fan (pivots)
Minidoka-Burley (surface)
1.0
ETrF
0.8
0.6
0.4
0.2
0.0
April-03
May-03
June-03
July-03
August-03 September-03
Figure 20. Comparison of mean ETrF by crop among five subregions of Magic Valley.
The mean ETrF for the first image date, April 9, was high for the entire region,
averaging about 0.5, because rainfall during the period prior to April 9 caused residual
evaporation on the 9th. The ETrF for the hot pixel for the April 9 image (used to
calibrate METRIC) was set equal to 0.3 based on a daily soil water balance and
prediction of evaporation due to the previous rainfall events. ETrF for the hot pixel was
assumed to equal zero for the rest of the images in 2003.
Spatial Distribution of ETrF in the Valley
The average ETrF for each crop and zone is shown in Figure 21, where the
average ETrF was computed by dividing the sum of ET for the growing season by the
sum of reference ETr for the same period. The TFCC (zone 2) and NE Desert (zone 5)
had the lowest values of ETrF, in general for the growing season for all crops except
alfalfa. In the case of TFCC area, the lower ETrF could stem from the irrigation method
practiced (surface). However in the NE Desert (zone 5), where center pivots are primarily
used, the values of ETrF are low, which is unexpected. Some of this may stem from
42
calmer weather in that area and variation in soil that effected surface temperature along
with the higher elevation.
0.8
0.7
Alfalfa
0.6
Sugar B
ETrF
0.5
Beans
0.4
Potatoes
0.3
Wheat
0.2
Maize
0.1
0.0
1
2
3
4
5
Zone
Figure 21. ETrF by zone (see Map 6) and crop in 04/09 (first image of the analysis).
43
Spatial distribution of ETrF by Crop
ETrF varied with location in Southeast of Magic Valley for image date ____. as
shown for sugar beet and potato crops in Map 7. For both crops, values of ETrF were
higher in the southeast area (values around 0.8) vs. the values found in the north (around
0.5). Soil and/or weather conditions could be the reason for this.
a.-
b.
-
Map 7. Spatial distribution of ETrF for sugar beets (a) and potatoes (b) in Southeast
Magic Valley.
44
ETrF vs. Albedo and vs. Surface Temperature
Relationships between ETrF and. albedo and Ts were evaluated by sampling four
pixels from each substantial field in the region for the April 9 image date. Differences in
the correlations were found depending on the crop type (crops having ground cover in
April such as wheat, alfalfa and double cropped). The analyses by crop are shown in
Appendix 6.
1.2
y = -3.2499x + 1.3482
R2 = 0.774
1
ETrF
0.8
0.6
0.4
0.2
0
-0.2
0
0.1
0.2
0.3
0.4
0.5
Albedo
1.2
y = -0.0455x + 14.25
R2 = 0.6392
1
ETrF
0.8
0.6
0.4
0.2
0
285
290
295
300
305
310
315
Ts
Figure 22. Comparison of ETrF vs. albedo and ETrF vs. Ts for all the plots selected in
Magic Valley (all the crops has been included).
45
Appendix 1. Original ground data on crop types
In this annex, all original ground data on crop type is shown. The data on crop
type were collected during three outings by Allen-Tasumi, Allen-Tasumi and TasumiAlfalfa
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
4Ju
n
11
-J
un
18
-J
un
25
-J
un
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
0
Bean
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
0
46
Lorite-Dille. NDVI for the seven satellites dates is shown in the figures of this appendix
for each field location that was typed.
47
0.5
0.6
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
0.3
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
0.4
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
0.5
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
Corn
0.9
0.8
0.7
0.6
Sugar beet
0.40.9
0.30.8
0.20.7
0.10.6
00.5
Potato
0.90.2
0.80.1
0.7 0
0.5
Wheat
0.4
1
0.3
0.9
0.20.8
0.10.7
0.6
0
0.4
0.3
0.2
0.1
0
48
49
Appendix 2. Removed ground data by crop type
In this appendix, the NDVI evolution in time was used to remove ground-truthed
fields that had anomalous trends in NDVI. This was done during Test 0. Additionally, the
origin of the ground data is shown. Thin lines indicate ground data collected by Tasumi,
Dille and Lorite in September 2003, and thick lines indicate ground data collected by
Allen and Tasumi in August 2003. Some fields were removed from the set because it
appears that may have been misidentification or misrecorded.
Alfalfa
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
0
50
0.9
Winter wheat with
late beans?
0.8
4Ju
n
11
-J
un
18
-J
un
25
-J
un
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
0.8
4Ju
n
11
-J
un
18
-J
un
25
-J
un
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
Bean
0.9
Potatoes?
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Corn
Winter wheat?
Late corn
(chopped)?
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
51
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
0.1
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
4Ju
n
11
-J
un
18
-J
un
25
-J
un
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
Potato
0.9
0.8
0.7
0.6
0.5
0.4
0.3
Alfalfa?
0.2
0.1
0
Sugar beet
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
Alfalfa?
0
52
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
Wheat
1
0.9
Alfalfa?
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
53
Appendix 3. Location of each field
The location, crop (using ground-truth), the category assigned by ERDAS and the
accuracy for each test is shown in this appendix for each ground-truthed field. The fields
that were misclassified following the four classification tests are marked in orange. Fields
initially considered to be alfalfa but finally classified as double cropped category are in
yellow (see Table 2 and 6).
Crop
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
X
2475017
2492807
2478535
2476554
2517631
2491566
2490943
2517837
2492457
2479696
2491561
2476552
2472913
2486022
2494424
2481317
2517848
2482282
2492965
2513862
2513511
2517653
2517835
2477414
2512592
2517624
2517637
2486539
2486905
2489693
2489714
2492442
2488287
2487716
2516003
2490607
2490267
2517604
Y
Category Test 1 (ERD) Test 2 (Alf) Test 3 (Band)
1252015
8
0
0
0
1252529
11
0
0
0
1259344
18
0
0
0
1260318
29
1
1
1
1270254
29
1
1
1
1246515
31
0
0
0
1246161
33
0
1
1
1269086
33
0
1
1
1245404
34
0
0
0
1250999
35
0
0
0
1246125
35
0
1
1
1259906
35
0
1
1
1262449
35
0
0
0
1247928
37
0
0
0
1246451
38
0
0
0
1259336
40
0
0
0
1273029
42
0
0
0
1258501
43
1
1
1
1250678
43
1
1
1
1263288
43
1
1
1
1262995
43
1
1
1
1269697
43
1
1
1
1269575
43
1
1
1
1251344
45
1
1
1
1263756
45
1
1
1
1268555
45
1
1
1
1268709
45
1
1
1
1246196
46
1
1
1
1246215
46
1
1
1
1246518
46
1
1
1
1246179
46
1
1
1
1252529
46
1
1
1
1252628
46
1
1
1
1252890
46
1
1
1
1263060
46
1
1
1
1263824
46
1
1
1
1263852
46
1
1
1
1270753
46
1
1
1
Test 4
(Categ)
0
1
1
1
1
0
1
1
0
0
1
1
0
0
*
*
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
54
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Alfalfa
Beans
Beans
Beans
Beans
Beans
Beans
Beans
Beans
Beans
Beans
Beans
Beans
Beans
Beans
Beans
Beans
2487374
2481818
2480998
2480291
2475595
2475391
2517594
2514088
2485768
2490388
2488333
2479241
2476327
2475167
2473369
2483440
2489381
2489128
2488601
2517611
2478211
2480427
2488756
2491338
2476367
2474735
2474280
2473141
2516766
2516380
2514804
2497675
2492978
2492341
2477435
2485295
2502691
2497220
2507408
2507067
2500127
2476391
2474799
2495682
2517774
2476751
2492487
2476579
2508936
2500592
1252891
1259334
1259337
1259339
1260803
1260959
1266020
1263294
1249909
1252878
1252951
1259440
1260923
1251138
1262426
1251064
1263853
1263823
1263732
1278413
1251078
1250954
1246149
1252654
1259506
1262339
1262546
1262577
1263216
1263246
1263244
1264275
1264125
1263788
1259364
1252681
1263857
1263792
1264158
1263916
1263852
1259813
1261061
1264156
1275805
1251423
1252066
1261118
1263881
1263876
47
47
47
47
47
47
47
47
48
48
48
48
48
49
49
49
49
49
49
49
50
50
50
50
50
50
50
50
50
50
50
50
50
50
12
12
12
12
13
13
13
14
14
14
14
16
16
16
16
16
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
1
1
1
1
1
1
1
55
Beans
Beans
Beans
Beans
Corn
Corn
Corn
Corn
Corn
Corn
Corn
Corn
Corn
Corn
Corn
Corn
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Potatoes
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
2517828
2517822
2517857
2506703
2486127
2489336
2477234
2476358
2481317
2482277
2488391
2488391
2474801
2481341
2475502
2511923
2517805
2517786
2517788
2505789
2517564
2517572
2494510
2485358
2476750
2485815
2492849
2483728
2482939
2510085
2517644
2517598
2517833
2517879
2483431
2486014
2483716
2484160
2517608
2517605
2517548
2517827
2492412
2495498
2496081
2492435
2492136
2492500
2485768
2517833
1272274
1271887
1271717
1264104
1246216
1252594
1259384
1260337
1250933
1251045
1246450
1246503
1261423
1251377
1251119
1263695
1275465
1288869
1288173
1263848
1285853
1281540
1243494
1252910
1251008
1250219
1248427
1256122
1251037
1264137
1288574
1288520
1270344
1269938
1256000
1246623
1251007
1250987
1286901
1277532
1275311
1272782
1246144
1246476
1245286
1245919
1252869
1248396
1246641
1279939
16
16
16
19
14
14
14
14
22
22
22
22
24
24
24
24
16
22
22
23
23
23
25
26
26
26
26
26
26
26
26
26
26
26
28
22
22
22
22
22
22
22
24
24
24
24
24
24
24
24
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
1
0
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
56
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Sugar B
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
2495509
2495668
2495539
2495541
2486117
2489771
2483145
2484584
2496069
2490136
2511081
2506907
2504776
2504491
2498995
2487711
2517612
2517598
2517833
2517623
2476870
2492162
2492915
2492494
2487350
2478032
2511350
2505060
2479897
2504148
2514405
2506160
2517626
2517592
2517833
2517814
2517568
2517808
2494467
2492889
2492417
2501185
2517759
2517810
2517794
2517823
2517793
2517592
2484969
2485384
1246142
1245278
1244869
1244558
1252909
1252964
1251343
1251339
1245686
1252903
1264119
1264127
1264125
1264123
1264093
1263748
1286354
1283201
1279261
1272566
1259366
1246505
1245897
1251276
1252630
1259369
1264114
1264156
1259073
1263876
1263058
1264125
1289098
1283547
1281198
1277780
1275897
1271107
1244384
1248920
1250957
1263752
1289322
1287957
1287513
1286786
1286724
1283704
1250999
1251029
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
26
26
26
26
26
26
26
26
6
20
32
32
32
32
32
32
32
32
33
33
33
33
33
33
33
33
33
33
34
34
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
57
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
2492484
2492942
2517625
2511513
2503960
2502108
2499811
2517592
2517585
2517807
2517810
2517589
2517815
2517830
2474768
2479057
2482049
2494446
2492874
2490980
2490364
2487008
2476394
2476099
2515687
2509257
2507909
2503055
2502195
2501800
2499384
2498078
2497363
2496890
2495213
2492604
2478209
2478475
2479697
2485748
2486066
2485719
2487650
2491690
2484478
2484112
2483478
2483215
2481894
2480786
1249685
1249937
1265266
1263854
1264186
1263845
1264118
1279633
1278882
1278126
1277224
1276699
1276653
1271568
1252386
1250904
1251349
1246178
1251695
1252655
1252679
1252877
1260616
1260802
1263250
1263895
1264456
1264118
1264153
1264102
1264044
1264079
1264121
1264184
1263841
1264100
1251325
1251325
1251382
1251182
1249856
1247716
1246139
1252883
1254640
1254547
1256647
1257141
1259110
1259090
34
34
34
34
34
34
34
34
34
34
34
34
34
34
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
35
36
36
36
36
36
36
36
36
36
36
36
36
36
36
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
58
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
Wheat
2471701
2509620
2502484
2486039
2483022
2517642
2515139
2500431
1261943
1264161
1264153
1247672
1256898
1264330
1263228
1264118
36
36
36
37
37
37
37
37
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
59
Appendix 4. Plots not classified after tests 1, 2 and 3.
NDVI evolution in the original fields (from ground data) that have not been
possible to determine correctly for type of cultivated crop after Tests 1, 2 and 3 are
summarized here. For each field the number indicates the category assigned by ERDAS.
Following Test 4, some of these fields were assigned the correct crop type. See Test 4
and Table 6 for more details. For alfalfa, categories 38 and 40 were finally considered to
be double cropped (see Table 2 and 6).
Categories 11, 18 and 42 were considered to be alfalfa in Test 4. Categories 38
and 40 may have been peas or wheat that was then seeded to alfalfa.
Alfalfa
1
34
0.9
40
31
0.8
35
0.7
42
0.6
38
0.5
8
0.4
37
0.3
0.2
11
18
0.1
35
4Ju
n
11
-J
un
18
-J
un
25
-J
un
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
0
60
0.7
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
0.3
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
Bean
0.9
0.8
14
0.7
14
0.6
0.5
0.4
19
0.2
0.1
0
Corn
0.9
0.8
14
0.6
0.5
0.4
0.3
0.2
0.1
0
61
0.5
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
Potato
0.9
0.8
25
0.7
0.6
28
0.5
0.4
16
0.3
0.2
0.1
0
Sugar beet
0.8
0.7
0.6
22
0.4
0.3
0.2
0.1
0
62
Wheat
1
0.9
0.8
20
0.7
6
0.6
0.5
0.4
0.3
0.2
0.1
2Ju
l
9Ju
l
16
-J
ul
23
-J
ul
30
-J
ul
6Au
g
13
-A
ug
20
-A
ug
27
-A
ug
4Ju
n
11
-J
un
18
-J
un
25
-J
un
9Ap
r
16
-A
pr
23
-A
pr
30
-A
pr
7M
ay
14
-M
ay
21
-M
ay
28
-M
ay
0
In the case of wheat, both categories (6 and 20) probably were not wheat (Allen,
personal communication).
63
Appendix 5. Comparison of ETrF depending on irrigation method and crop
ETrF evolution by crop for 5 different areas described in Map 6 are shown in the
following graphs.
Alfalfa
Alfalfa
1.0
1.0
0.9
0.9
0.8
0.8
0.7
0.7
0.6
ETrF
NSCC (Pivot)
0.5
TFCC (Surface)
0.4
0.5
Oakley Fan
0.4
0.3
0.3
0.2
0.2
0.1
0.1
NE desert
Beans
29-Aug
15-Aug
1-Aug
10-Sep
18-Jul
21-Aug
4-Jul
1-Aug
20-Jun
12-Jul
6-Jun
22-Jun
23-May
2-Jun
9-May
13-May
25-Apr
23-Apr
11-Apr
0.0
3-Apr
28-Mar
0.0
14-Mar
Minidoka
14-Mar
ETrF
0.6
Beans
1.0
1.0
0.9
0.8
0.8
0.7
NSCC (Pivot)
0.5
ETrF
ETrF
0.6
TFCC (Surface)
0.6
0.4
0.4
Oakley Fan
Minidoka
0.3
NE desert
0.2
0.2
0.1
29-Aug
4-Jul
29-Aug
Potatoes
15-Aug
-0.2
15-Aug
10-Sep
1-Aug
21-Aug
18-Jul
1-Aug
20-Jun
12-Jul
6-Jun
22-Jun
23-May
2-Jun
9-May
13-May
25-Apr
23-Apr
11-Apr
3-Apr
28-Mar
0.0
14-Mar
0.0
14-Mar
Potatoes
1.0
1.0
0.9
0.8
0.8
0.7
NSCC (Pivot)
0.5
ETrF
0.4
0.4
Oakley Fan
Minidoka
0.3
NE desert
0.2
0.2
0.1
21-Aug
10-Sep
-0.2
4-Jul
1-Aug
1-Aug
18-Jul
12-Jul
20-Jun
22-Jun
6-Jun
2-Jun
23-May
13-May
9-May
23-Apr
25-Apr
3-Apr
11-Apr
0.0
28-Mar
0.0
14-Mar
14-Mar
ETrF
0.6
TFCC (Surface)
0.6
64
Wheat
Wheat
1.2
1.0
1.0
0.8
0.8
ETrF
ETrF
1.2
0.6
0.4
0.6
0.4
NSCC (Pivot)
Oakley Fan
TFCC (Surface)
0.2
0.2
0.0
14-Mar
0.0
Minidoka
1-Aug
15-Aug
1-Aug
15-Aug
29-Aug
18-Jul
1.2
1.2
1.0
1.0
Oakley Fan
Minidoka
NSCC (Pivot)
0.8
NE desert
TFCC (Surface)
0.6
0.6
ETrF
0.4
0.4
0.2
0.2
21-Aug
10-Sep
-0.2
65
29-Aug
1-Aug
20-Jun
12-Jul
6-Jun
22-Jun
23-May
2-Jun
9-May
13-May
25-Apr
23-Apr
11-Apr
3-Apr
28-Mar
0.0
0.0
14-Mar
14-Mar
ETrF
18-Jul
Maize
Maize
0.8
4-Jul
10-Sep
4-Jul
21-Aug
20-Jun
1-Aug
6-Jun
12-Jul
23-May
22-Jun
9-May
2-Jun
25-Apr
13-May
11-Apr
23-Apr
28-Mar
3-Apr
14-Mar
NE desert
Appendix 6. Relationship between ETrF and albedo and Ts by crop
For the image 04/09 analyses between ETrF, albedo and Ts have been made. The
behavior between crops was different depending on the cover by the crop or not in this
date.
Sugar beet:
A significant correlation was found between ETrF and albedo, however, no
correlation was found between ETrF and Ts.
1
0.9
y = -2.145x + 1.0103
R2 = 0.7459
ETrF
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
0.1
0.2
0.3
0.4
0.5
Albedo
1
ETrF
0.9
0.8
y = -0.0176x + 5.784
R2 = 0.094
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
290
295
300
305
310
315
Ts
Similar results were found for beans, potatoes and maize.
66
Wheat:
A significant correlation was found between ETrF and albedo and ETrF and Ts.
In the analyzed date, some fields (those with winter wheat) have full cover.
1.2
y = -3.4128x + 1.3936
R2 = 0.7752
1
ETrF
0.8
0.6
0.4
0.2
0
-0.2
0
0.1
0.2
0.3
0.4
0.5
Albedo
1.2
y = -0.0462x + 14.428
R2 = 0.6868
1
ETrF
0.8
0.6
0.4
0.2
0
285
290
295
300
305
310
315
Ts
Similar results were found for alfalfa.
67