water
int64 0
1
| sur_refl_b01_1
int64 8
9.22k
| sur_refl_b02_1
int64 1
8.84k
| sur_refl_b03_1
int64 -100
8.91k
| sur_refl_b04_1
int64 6
9.16k
| sur_refl_b05_1
int64 -92
6.38k
| sur_refl_b06_1
int64 51
6.61k
| sur_refl_b07_1
int64 0
6.13k
| ndvi
int64 -9,493
8.59k
| ndwi1
int64 -9,862
8.82k
| ndwi2
int64 -9,692
10k
|
|---|---|---|---|---|---|---|---|---|---|---|
0 | 2,031 | 3,113 | 776 | 1,200 | 3,626 | 3,480 | 2,957 | 2,103 | -556 | 257 |
1 | 410 | 494 | 183 | 319 | 295 | 329 | 307 | 929 | 2,004 | 2,334 |
0 | 1,609 | 2,615 | 797 | 1,000 | 2,143 | 1,708 | 1,107 | 2,381 | 2,098 | 4,051 |
0 | 2,593 | 3,315 | 1,250 | 1,944 | 3,923 | 4,194 | 3,909 | 1,222 | -1,170 | -822 |
0 | 2,485 | 3,365 | 905 | 1,527 | 4,520 | 4,646 | 4,137 | 1,504 | -1,599 | -1,029 |
1 | 112 | 52 | 117 | 165 | 196 | 183 | 47 | -3,658 | -5,574 | 505 |
1 | 469 | 362 | 650 | 647 | 388 | 409 | 268 | -1,287 | -609 | 1,492 |
1 | 189 | 220 | 189 | 250 | 190 | 240 | 137 | 757 | -434 | 2,324 |
1 | 51 | 23 | 19 | 75 | 157 | 321 | 144 | -3,783 | -8,662 | -7,245 |
0 | 1,388 | 2,005 | 548 | 852 | 2,433 | 2,413 | 2,210 | 1,818 | -923 | -486 |
0 | 4,767 | 5,084 | 3,996 | 4,221 | 3,102 | 1,502 | 945 | 321 | 5,438 | 6,865 |
1 | 464 | 341 | 525 | 496 | 176 | 256 | 61 | -1,527 | 1,423 | 6,965 |
0 | 750 | 2,293 | 453 | 720 | 2,549 | 2,321 | 1,538 | 5,070 | -60 | 1,970 |
0 | 2,408 | 3,329 | 829 | 1,463 | 4,896 | 5,380 | 4,772 | 1,605 | -2,355 | -1,781 |
1 | 125 | 81 | 232 | 291 | 492 | 362 | 200 | -2,135 | -6,343 | -4,234 |
0 | 2,280 | 3,207 | 768 | 1,231 | 4,017 | 4,188 | 3,874 | 1,689 | -1,326 | -941 |
1 | 175 | 123 | 182 | 211 | 190 | 268 | 352 | -1,744 | -3,708 | -4,821 |
1 | 981 | 890 | 832 | 1,036 | 1,145 | 1,230 | 928 | -486 | -1,603 | -209 |
1 | 149 | 75 | 723 | 1,058 | 1,557 | 1,824 | 1,524 | -3,303 | -9,210 | -9,061 |
1 | 647 | 618 | 820 | 1,030 | 1,551 | 1,532 | 1,134 | -229 | -4,251 | -2,945 |
1 | 475 | 208 | 460 | 722 | 1,448 | 597 | 461 | -3,909 | -4,832 | -3,781 |
1 | 186 | 193 | 268 | 342 | 532 | 504 | 430 | 184 | -4,461 | -3,804 |
0 | 2,040 | 2,957 | 672 | 1,080 | 3,513 | 3,705 | 3,188 | 1,835 | -1,122 | -375 |
0 | 2,899 | 3,933 | 849 | 1,401 | 4,038 | 4,594 | 3,897 | 1,513 | -775 | 45 |
1 | 236 | 152 | 479 | 653 | 848 | 943 | 625 | -2,164 | -7,223 | -6,087 |
0 | 1,216 | 1,982 | 415 | 619 | 1,642 | 1,406 | 939 | 2,395 | 1,700 | 3,570 |
1 | 331 | 291 | 239 | 303 | 539 | 504 | 305 | -643 | -2,679 | -234 |
0 | 1,827 | 2,337 | 691 | 1,046 | 2,499 | 2,597 | 2,262 | 1,224 | -526 | 163 |
1 | 171 | 132 | 167 | 264 | 310 | 363 | 102 | -1,287 | -4,666 | 1,282 |
1 | 375 | 346 | 482 | 673 | 967 | 1,187 | 971 | -402 | -5,485 | -4,745 |
0 | 1,573 | 2,311 | 837 | 1,281 | 3,121 | 3,173 | 2,484 | 1,900 | -1,571 | -360 |
1 | 276 | 122 | 259 | 472 | 178 | 145 | 251 | -3,869 | -861 | -3,458 |
0 | 592 | 1,591 | 322 | 483 | 1,564 | 1,192 | 719 | 4,576 | 1,433 | 3,774 |
0 | 2,622 | 3,633 | 663 | 1,171 | 3,066 | 2,820 | 2,384 | 1,616 | 1,259 | 2,075 |
1 | 365 | 359 | 424 | 610 | 995 | 1,003 | 827 | -82 | -4,728 | -3,946 |
1 | 937 | 925 | 1,190 | 1,624 | 3,708 | 3,882 | 3,418 | -64 | -6,151 | -5,740 |
0 | 1,580 | 2,552 | 890 | 1,297 | 2,843 | 2,921 | 2,524 | 2,352 | -674 | 55 |
1 | 975 | 1,161 | 664 | 786 | 1,200 | 1,287 | 962 | 870 | -514 | 937 |
1 | 118 | 64 | 150 | 197 | 262 | 236 | 175 | -2,967 | -5,733 | -4,644 |
1 | 518 | 547 | 335 | 476 | 832 | 718 | 673 | 272 | -1,351 | -1,032 |
0 | 1,328 | 2,307 | 428 | 703 | 2,327 | 2,152 | 1,549 | 2,693 | 347 | 1,965 |
0 | 2,059 | 2,854 | 753 | 1,314 | 3,736 | 4,007 | 3,525 | 1,618 | -1,680 | -1,051 |
0 | 1,752 | 2,298 | 742 | 1,353 | 3,197 | 3,379 | 2,756 | 1,348 | -1,904 | -906 |
1 | 60 | 18 | 185 | 217 | 554 | 703 | 596 | -5,384 | -9,500 | -9,413 |
0 | 3,433 | 4,633 | 1,051 | 1,839 | 5,357 | 5,069 | 4,269 | 1,487 | -449 | 408 |
1 | 209 | 154 | 496 | 612 | 1,126 | 641 | 538 | -1,515 | -6,125 | -5,549 |
0 | 726 | 1,695 | 439 | 680 | 1,830 | 1,615 | 1,185 | 4,002 | 241 | 1,770 |
0 | 772 | 1,483 | 452 | 762 | 2,571 | 2,417 | 1,904 | 3,152 | -2,394 | -1,242 |
1 | 442 | 296 | 461 | 468 | 449 | 289 | 117 | -1,978 | 119 | 4,334 |
0 | 2,186 | 2,753 | 1,052 | 1,630 | 3,207 | 3,494 | 3,115 | 1,148 | -1,186 | -616 |
1 | 603 | 774 | 361 | 556 | 1,042 | 1,293 | 1,202 | 1,241 | -2,510 | -2,165 |
1 | 295 | 186 | 350 | 458 | 390 | 242 | 243 | -2,266 | -1,308 | -1,328 |
1 | 279 | 140 | 85 | 286 | 558 | 658 | 400 | -3,317 | -6,491 | -4,814 |
1 | 208 | 126 | 296 | 413 | 462 | 504 | 438 | -2,455 | -6,000 | -5,531 |
1 | 135 | 77 | 476 | 632 | 1,294 | 1,655 | 1,510 | -2,735 | -9,110 | -9,029 |
0 | 899 | 1,833 | 441 | 718 | 2,056 | 1,917 | 1,396 | 3,418 | -224 | 1,353 |
0 | 3,390 | 4,730 | 1,072 | 1,858 | 6,382 | 6,610 | 6,128 | 1,650 | -1,657 | -1,287 |
0 | 1,728 | 2,358 | 967 | 1,375 | 2,785 | 2,879 | 2,151 | 1,541 | -994 | 459 |
1 | 123 | 74 | 581 | 835 | 2,039 | 2,437 | 2,420 | -2,487 | -9,410 | -9,406 |
0 | 2,940 | 3,529 | 1,479 | 2,360 | 4,233 | 4,925 | 4,312 | 910 | -1,651 | -998 |
0 | 862 | 1,000 | 385 | 664 | 933 | 1,038 | 720 | 741 | -186 | 1,627 |
0 | 2,716 | 3,409 | 1,432 | 2,241 | 4,343 | 4,886 | 4,442 | 1,131 | -1,780 | -1,315 |
0 | 714 | 2,096 | 507 | 742 | 2,777 | 2,592 | 1,717 | 4,918 | -1,058 | 993 |
1 | 178 | 163 | 382 | 537 | 1,728 | 1,465 | 1,145 | -439 | -7,997 | -7,507 |
0 | 1,127 | 1,119 | 1,139 | 1,080 | 925 | 515 | 317 | -35 | 3,696 | 5,584 |
1 | 395 | 242 | -100 | 45 | -17 | 106 | 107 | -2,401 | 3,908 | 3,868 |
1 | 193 | 85 | 200 | 286 | 312 | 228 | 210 | -3,884 | -4,568 | -4,237 |
0 | 778 | 1,878 | 399 | 723 | 2,364 | 2,185 | 1,596 | 4,141 | -755 | 811 |
0 | 1,244 | 2,356 | 608 | 998 | 2,887 | 2,762 | 2,033 | 3,088 | -793 | 735 |
0 | 986 | 1,900 | 575 | 878 | 2,515 | 2,645 | 2,029 | 3,167 | -1,639 | -328 |
1 | 411 | 412 | 567 | 769 | 1,352 | 1,544 | 1,376 | 12 | -5,787 | -5,391 |
0 | 598 | 1,457 | 367 | 563 | 1,602 | 1,413 | 997 | 4,180 | 153 | 1,874 |
0 | 1,925 | 2,334 | 930 | 1,564 | 3,309 | 3,765 | 3,284 | 960 | -2,346 | -1,690 |
0 | 1,241 | 2,024 | 581 | 957 | 2,624 | 2,706 | 2,194 | 2,398 | -1,441 | -403 |
1 | 86 | 13 | 101 | 122 | 68 | 128 | 83 | -7,373 | -8,156 | -7,291 |
0 | 2,548 | 3,429 | 882 | 1,362 | 4,039 | 4,559 | 3,988 | 1,473 | -1,414 | -753 |
0 | 2,099 | 3,118 | 552 | 1,313 | 3,676 | 3,994 | 3,080 | 1,953 | -1,231 | 61 |
1 | 125 | 73 | 439 | 655 | 1,538 | 1,546 | 1,476 | -2,626 | -9,098 | -9,057 |
1 | 243 | 206 | 405 | 618 | 1,934 | 2,122 | 1,953 | -824 | -8,230 | -8,091 |
1 | 35 | 1 | 53 | 79 | 110 | 144 | 64 | -9,444 | -9,862 | -9,692 |
1 | 96 | 54 | 124 | 150 | 93 | 73 | 28 | -2,800 | -1,496 | 3,170 |
1 | 185 | 121 | 263 | 348 | 360 | 278 | 256 | -2,091 | -3,934 | -3,580 |
1 | 612 | 514 | 619 | 784 | 725 | 726 | 521 | -870 | -1,709 | -67 |
1 | 288 | 236 | 256 | 336 | 282 | 509 | 366 | -992 | -3,664 | -2,159 |
0 | 2,072 | 2,725 | 862 | 1,386 | 3,292 | 3,561 | 3,139 | 1,361 | -1,329 | -706 |
0 | 1,371 | 2,278 | 789 | 1,162 | 2,818 | 2,773 | 1,993 | 2,485 | -980 | 667 |
0 | 2,584 | 3,397 | 967 | 1,554 | 3,977 | 3,419 | 2,690 | 1,359 | -32 | 1,161 |
0 | 2,241 | 2,771 | 1,171 | 1,794 | 3,661 | 4,216 | 3,616 | 1,057 | -2,068 | -1,322 |
0 | 1,682 | 2,164 | 746 | 1,253 | 2,826 | 2,962 | 2,051 | 1,253 | -1,556 | 268 |
1 | 1,817 | 1,891 | 1,375 | 1,714 | 2,464 | 2,637 | 2,469 | 199 | -1,647 | -1,325 |
1 | 2,286 | 2,783 | 1,249 | 1,405 | 2,937 | 3,094 | 2,691 | 980 | -529 | 168 |
0 | 2,468 | 3,284 | 1,019 | 1,772 | 4,013 | 4,318 | 3,970 | 1,418 | -1,360 | -945 |
0 | 1,241 | 1,710 | 837 | 1,187 | 1,819 | 1,436 | 1,067 | 1,589 | 870 | 2,315 |
0 | 2,315 | 3,369 | 1,905 | 2,136 | 1,596 | 676 | 338 | 1,854 | 6,657 | 8,176 |
0 | 2,273 | 3,022 | 1,059 | 1,454 | 3,071 | 3,136 | 2,786 | 1,414 | -185 | 406 |
1 | 952 | 254 | 520 | 958 | 209 | 378 | 159 | -5,787 | -1,962 | 2,300 |
0 | 1,734 | 2,401 | 847 | 1,318 | 3,175 | 3,283 | 2,758 | 1,613 | -1,551 | -691 |
1 | 483 | 438 | 585 | 838 | 2,247 | 2,287 | 2,010 | -488 | -6,785 | -6,421 |
0 | 762 | 1,661 | 542 | 855 | 2,624 | 2,535 | 1,923 | 3,710 | -2,082 | -731 |
0 | 812 | 1,715 | 403 | 723 | 1,994 | 1,890 | 1,382 | 3,573 | -485 | 1,075 |
End of preview. Expand
in Dataset Viewer.
MODIS Water Lake Powell Toy Dataset
Dataset Summary
Tabular dataset comprised of MODIS surface reflectance bands along with calculated indices and a label (water/not-water)
Dataset Structure
Data Fields
water: Label, water or not-water (binary)sur_refl_b01_1: MODIS surface reflection band 1 (-100, 16000)sur_refl_b02_1: MODIS surface reflection band 2 (-100, 16000)sur_refl_b03_1: MODIS surface reflection band 3 (-100, 16000)sur_refl_b04_1: MODIS surface reflection band 4 (-100, 16000)sur_refl_b05_1: MODIS surface reflection band 5 (-100, 16000)sur_refl_b06_1: MODIS surface reflection band 6 (-100, 16000)sur_refl_b07_1: MODIS surface reflection band 7 (-100, 16000)ndvi: Normalized differential vegetation index (-20000, 20000)ndwi1: Normalized differential water index 1 (-20000, 20000)ndwi2: Normalized differential water index 2 (-20000, 20000)
Data Splits
Train and test split. Test is 200 rows, train is 800.
Dataset Creation
Source Data
MODIS MOD44W MODIS MOD09GA MODIS MOD09GQ
Annotation process
Labels were created by using the MOD44W C6 product to designate pixels in MODIS surface reflectance products as land or water.
- Downloads last month
- 50