├── LICENSE ├── README.md ├── assets ├── GaofenBatch.gif ├── app_icon.ico └── app_icon.png ├── data ├── AtmosphericCorrectionParameter.yaml ├── GMTED2km.tif └── RadiometricCorrectionParameter.json ├── index.html ├── main.js ├── main.py ├── package-lock.json └── package.json /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | logo 2 | 3 | # Gaofen Batch 4 | 5 | 基于GDAL和Electron的国产卫星影像预处理工具 6 | 7 | ### 特性: 8 | - 😉 GDAL驱动，省时高效，结果可靠。 9 | - 😋 解压即可运行，可视化界面，小白友好。 10 | 11 | ### 支持的卫星传感器与功能 12 | 13 | | 卫星传感器 | RPC正射校正 | 大气校正 | 融合 | 14 | |------------|--------------|----------|------| 15 | | CB04A_WPM | ✅ | ❌ | ✅ | 16 | | GF1_PMS | ✅ | ✅ | ✅ | 17 | | GF1_WFV | ✅ | ✅ | / | 18 | | GF1B/C/D-PMS | ✅ | ✅ | ✅ | 19 | | GF2_PMS | ✅ | ✅ | ✅ | 20 | | GF4_PMI | ✅ | ❌ | ✅ | 21 | | GF5_AHSI | ✅ | ❌ | / | 22 | | GF5B_AHSI | ✅ | ❌ | / | 23 | | GF5B_VIMI | ✅ | ❌ | / | 24 | | GF6_PMS | ✅ | ✅ | ✅ | 25 | | GF6_WFV | ✅ | ✅ | / | 26 | | GF7_BWD | ✅ | ✅ | ✅ | 27 | | GF7_DLC | ✅ | ✅ | ✅ | 28 | | HJ2A_CCD | ✅ | ❌ | / | 29 | | HJ2B_CCD | ✅ | ❌ | / | 30 | | ZY1E_VNIC | ✅ | ❌ | / | 31 | | ZY1F_AHSI | ✅ | ❌ | / | 32 | | ZY303_TMS | ✅ | ✅ | ✅ | 33 | 34 | > **注**: "✅" 表示支持，"❌" 表示不支持（缺少太阳辐照度数据）, "/" 表示不需要。大气校正 = 辐射定标 + 大气表观反射率计算 + 地表反射率计算，使用暗像元法。 35 | 36 | ## 如何使用 37 | 38 | 1. 从项目的[Release](https://github.com/GenghisYoung233/Gaofen-Batch/releases)下载程序，解压到本地，路径避免中文和空格。 39 | 2. 双击GaofenBatch.exe，添加待处理数据（原始.tar.gz压缩包）。 40 | 3. 点击“运行”按钮，选择输出文件夹，程序开始逐个解压并处理数据。 41 | 42 | ## 演示Gif（×10倍速） 43 | 44 | demo 45 | 46 | ## 从源码编译 47 | 48 | 1. 克隆本仓库： 49 | ```bash 50 | git clone https://github.com/GenghisYoung233/Gaofen-Batch.git 51 | ``` 52 | 2. 安装并打包Electron： 53 | ```bash 54 | npm install 55 | npm run pack 56 | ``` 57 | 3. 编译Python： 58 | ```bash 59 | pyinstaller main.py 60 | ``` 61 | 编译后的文件夹改名为'bin'。 62 | 4. 下载[Orfeo Toolbox](https://www.orfeo-toolbox.org/download/)，并将它与data文件夹一起放入'bin'中。 63 | -------------------------------------------------------------------------------- /assets/GaofenBatch.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GenghisYoung233/Gaofen-Batch/d9bec730168b0c3dd4aa6a7d15e6f40641cc0dd3/assets/GaofenBatch.gif -------------------------------------------------------------------------------- /assets/app_icon.ico: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GenghisYoung233/Gaofen-Batch/d9bec730168b0c3dd4aa6a7d15e6f40641cc0dd3/assets/app_icon.ico -------------------------------------------------------------------------------- /assets/app_icon.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GenghisYoung233/Gaofen-Batch/d9bec730168b0c3dd4aa6a7d15e6f40641cc0dd3/assets/app_icon.png -------------------------------------------------------------------------------- /data/AtmosphericCorrectionParameter.yaml: -------------------------------------------------------------------------------- 1 | GF1: 2 | PMS1: 3 | MSS: 4 | ESUN: 5 | - 1945.29 6 | - 1854.1 7 | - 1542.9 8 | - 1080.77 9 | gain: 10 | '2014': 11 | - 0.2247 12 | - 0.1892 13 | - 0.1889 14 | - 0.1939 15 | '2015': 16 | - 0.211 17 | - 0.1802 18 | - 0.1806 19 | - 0.187 20 | '2016': 21 | - 0.232 22 | - 0.187 23 | - 0.1795 24 | - 0.196 25 | '2017': 26 | - 0.1424 27 | - 0.1177 28 | - 0.1194 29 | - 0.1135 30 | '2018': 31 | - 0.153 32 | - 0.1356 33 | - 0.1366 34 | - 0.1272 35 | '2019': 36 | - 0.149 37 | - 0.1328 38 | - 0.1311 39 | - 0.1217 40 | '2022': 41 | - 0.1458 42 | - 0.1213 43 | - 0.1230 44 | - 0.1185 45 | offset: 46 | '2014': 47 | - 0 48 | - 0 49 | - 0 50 | - 0 51 | '2015': 52 | - 0 53 | - 0 54 | - 0 55 | - 0 56 | '2016': 57 | - 0 58 | - 0 59 | - 0 60 | - 0 61 | '2017': 62 | - 0 63 | - 0 64 | - 0 65 | - 0 66 | '2018': 67 | - 0 68 | - 0 69 | - 0 70 | - 0 71 | '2019': 72 | - 0 73 | - 0 74 | - 0 75 | - 0 76 | '2022': 77 | - 0 78 | - 0 79 | - 0 80 | - 0 81 | PAN: 82 | ESUN: 83 | - 1371.79 84 | gain: 85 | '2014': 86 | - 0.1963 87 | '2015': 88 | - 0.1956 89 | '2016': 90 | - 0.1982 91 | '2017': 92 | - 0.1228 93 | '2018': 94 | - 0.1428 95 | '2019': 96 | - 0.1381 97 | '2022': 98 | - 0.1306 99 | offset: 100 | '2014': 101 | - 0 102 | '2015': 103 | - 0 104 | '2016': 105 | - 0 106 | '2017': 107 | - 0 108 | '2018': 109 | - 0 110 | '2019': 111 | - 0 112 | '2022': 113 | - 0 114 | PMS2: 115 | MSS: 116 | ESUN: 117 | - 1945.63 118 | - 1853.83 119 | - 1543.9 120 | - 1081.89 121 | gain: 122 | '2014': 123 | - 0.2419 124 | - 0.2047 125 | - 0.2009 126 | - 0.2058 127 | '2015': 128 | - 0.2242 129 | - 0.1887 130 | - 0.1882 131 | - 0.1963 132 | '2016': 133 | - 0.224 134 | - 0.1851 135 | - 0.1793 136 | - 0.1863 137 | '2017': 138 | - 0.146 139 | - 0.1248 140 | - 0.1274 141 | - 0.1255 142 | '2018': 143 | - 0.1523 144 | - 0.1382 145 | - 0.1403 146 | - 0.1334 147 | '2019': 148 | - 0.149 149 | - 0.1328 150 | - 0.1311 151 | - 0.1217 152 | '2022': 153 | - 0.1426 154 | - 0.1241 155 | - 0.1286 156 | - 0.1247 157 | offset: 158 | '2014': 159 | - 0 160 | - 0 161 | - 0 162 | - 0 163 | '2015': 164 | - 0 165 | - 0 166 | - 0 167 | - 0 168 | '2016': 169 | - 0 170 | - 0 171 | - 0 172 | - 0 173 | '2017': 174 | - 0 175 | - 0 176 | - 0 177 | - 0 178 | '2018': 179 | - 0 180 | - 0 181 | - 0 182 | - 0 183 | '2019': 184 | - 0 185 | - 0 186 | - 0 187 | - 0 188 | '2022': 189 | - 0 190 | PAN: 191 | ESUN: 192 | - 1376.37 193 | gain: 194 | '2014': 195 | - 0.2147 196 | '2015': 197 | - 0.2018 198 | '2016': 199 | - 0.1979 200 | '2017': 201 | - 0.1365 202 | '2018': 203 | - 0.149 204 | '2019': 205 | - 0.1381 206 | '2022': 207 | - 0.1373 208 | offset: 209 | '2014': 210 | - 0 211 | '2015': 212 | - 0 213 | '2016': 214 | - 0 215 | '2017': 216 | - 0 217 | '2018': 218 | - 0 219 | '2019': 220 | - 0 221 | '2022': 222 | - 0 223 | WFV1: 224 | ESUN: 225 | - 1968.63 226 | - 1849.19 227 | - 1571.46 228 | - 1079.0 229 | gain: 230 | '2013': 231 | - 5.851 232 | - 7.153 233 | - 8.368 234 | - 7.474 235 | '2014': 236 | - 0.2004 237 | - 0.1648 238 | - 0.1243 239 | - 0.1563 240 | '2015': 241 | - 0.1816 242 | - 0.156 243 | - 0.1412 244 | - 0.1368 245 | '2016': 246 | - 0.1843 247 | - 0.1477 248 | - 0.122 249 | - 0.1365 250 | '2017': 251 | - 0.2165 252 | - 0.1685 253 | - 0.1354 254 | - 0.1507 255 | '2018': 256 | - 0.1824 257 | - 0.1546 258 | - 0.127 259 | - 0.1344 260 | '2019': 261 | - 0.2144 262 | - 0.1657 263 | - 0.1228 264 | - 0.1213 265 | '2020': 266 | - 0.19319 267 | - 0.16041 268 | - 0.12796 269 | - 0.13405 270 | '2021': 271 | - 0.1722 272 | - 0.1496 273 | - 0.1227 274 | - 0.1262 275 | '2022': 276 | - 0.1889 277 | - 0.1495 278 | - 0.1228 279 | - 0.1352 280 | offset: 281 | '2013': 282 | - 0.0039 283 | - 0.0047 284 | - 0.003 285 | - 0.0274 286 | '2014': 287 | - 0 288 | - 0 289 | - 0 290 | - 0 291 | '2015': 292 | - 0 293 | - 0 294 | - 0 295 | - 0 296 | '2016': 297 | - 0 298 | - 0 299 | - 0 300 | - 0 301 | '2017': 302 | - 0 303 | - 0 304 | - 0 305 | - 0 306 | '2018': 307 | - 0 308 | - 0 309 | - 0 310 | - 0 311 | '2019': 312 | - 0 313 | - 0 314 | - 0 315 | - 0 316 | '2020': 317 | - 0 318 | - 0 319 | - 0 320 | - 0 321 | '2021': 322 | - 0 323 | - 0 324 | - 0 325 | - 0 326 | '2022': 327 | - 0 328 | - 0 329 | - 0 330 | - 0 331 | WFV2: 332 | ESUN: 333 | - 1955.11 334 | - 1847.22 335 | - 1569.45 336 | - 1087.87 337 | gain: 338 | '2013': 339 | - 6.014 340 | - 6.823 341 | - 9.451 342 | - 8.996 343 | '2014': 344 | - 0.1733 345 | - 0.1383 346 | - 0.1122 347 | - 0.1391 348 | '2015': 349 | - 0.1684 350 | - 0.1527 351 | - 0.1373 352 | - 0.1263 353 | '2016': 354 | - 0.1929 355 | - 0.154 356 | - 0.1349 357 | - 0.1359 358 | '2017': 359 | - 0.2097 360 | - 0.163 361 | - 0.1339 362 | - 0.1521 363 | '2018': 364 | - 0.1851 365 | - 0.1538 366 | - 0.1231 367 | - 0.1314 368 | '2019': 369 | - 0.2368 370 | - 0.1745 371 | - 0.1254 372 | - 0.1163 373 | '2020': 374 | - 0.2057 375 | - 0.1648 376 | - 0.126 377 | - 0.1187 378 | '2021': 379 | - 0.1792 380 | - 0.1534 381 | - 0.1232 382 | - 0.1291 383 | '2022': 384 | - 0.1585 385 | - 0.1223 386 | - 0.0997 387 | - 0.1111 388 | offset: 389 | '2013': 390 | - 0.0125 391 | - 0.0193 392 | - 0.0429 393 | - 0.0011 394 | '2014': 395 | - 0 396 | - 0 397 | - 0 398 | - 0 399 | '2015': 400 | - 0 401 | - 0 402 | - 0 403 | - 0 404 | '2016': 405 | - 0 406 | - 0 407 | - 0 408 | - 0 409 | '2017': 410 | - 0 411 | - 0 412 | - 0 413 | - 0 414 | '2018': 415 | - 0 416 | - 0 417 | - 0 418 | - 0 419 | '2019': 420 | - 0 421 | - 0 422 | - 0 423 | - 0 424 | '2020': 425 | - 0 426 | - 0 427 | - 0 428 | - 0 429 | '2021': 430 | - 0 431 | - 0 432 | - 0 433 | - 0 434 | '2022': 435 | - 0 436 | - 0 437 | - 0 438 | - 0 439 | WFV3: 440 | ESUN: 441 | - 1956.62 442 | - 1840.46 443 | - 1541.45 444 | - 1084.06 445 | gain: 446 | '2013': 447 | - 5.82 448 | - 6.239 449 | - 7.01 450 | - 7.711 451 | '2014': 452 | - 0.1745 453 | - 0.1514 454 | - 0.1257 455 | - 0.1462 456 | '2015': 457 | - 0.177 458 | - 0.1589 459 | - 0.1385 460 | - 0.1344 461 | '2016': 462 | - 0.1753 463 | - 0.1565 464 | - 0.148 465 | - 0.1322 466 | '2017': 467 | - 0.187 468 | - 0.1619 469 | - 0.1295 470 | - 0.1383 471 | '2018': 472 | - 0.1894 473 | - 0.1728 474 | - 0.1343 475 | - 0.1373 476 | '2019': 477 | - 0.2139 478 | - 0.1797 479 | - 0.1344 480 | - 0.1337 481 | '2020': 482 | - 0.2106 483 | - 0.1825 484 | - 0.1346 485 | - 0.1187 486 | '2021': 487 | - 0.2044 488 | - 0.1844 489 | - 0.1429 490 | - 0.1453 491 | '2022': 492 | - 0.2085 493 | - 0.1743 494 | - 0.1385 495 | - 0.1438 496 | offset: 497 | '2013': 498 | - 0.0071 499 | - 0.0334 500 | - 0.0226 501 | - 0.0117 502 | '2014': 503 | - 0 504 | - 0 505 | - 0 506 | - 0 507 | '2015': 508 | - 0 509 | - 0 510 | - 0 511 | - 0 512 | '2016': 513 | - 0 514 | - 0 515 | - 0 516 | - 0 517 | '2017': 518 | - 0 519 | - 0 520 | - 0 521 | - 0 522 | '2018': 523 | - 0 524 | - 0 525 | - 0 526 | - 0 527 | '2019': 528 | - 0 529 | - 0 530 | - 0 531 | - 0 532 | '2020': 533 | - 0 534 | - 0 535 | - 0 536 | - 0 537 | '2021': 538 | - 0 539 | - 0 540 | - 0 541 | - 0 542 | '2022': 543 | - 0 544 | - 0 545 | - 0 546 | - 0 547 | WFV4: 548 | ESUN: 549 | - 1968.08 550 | - 1841.53 551 | - 1540.8 552 | - 1069.6 553 | gain: 554 | '2013': 555 | - 5.35 556 | - 6.235 557 | - 6.992 558 | - 7.462 559 | '2014': 560 | - 0.1713 561 | - 0.16 562 | - 0.1497 563 | - 0.1435 564 | '2015': 565 | - 0.1886 566 | - 0.1645 567 | - 0.1467 568 | - 0.1378 569 | '2016': 570 | - 0.1973 571 | - 0.1714 572 | - 0.15 573 | - 0.1572 574 | '2017': 575 | - 0.177 576 | - 0.1521 577 | - 0.1322 578 | - 0.1349 579 | '2018': 580 | - 0.1866 581 | - 0.1599 582 | - 0.1307 583 | - 0.1251 584 | '2019': 585 | - 0.2442 586 | - 0.1945 587 | - 0.1547 588 | - 0.1037 589 | '2020': 590 | - 0.2522 591 | - 0.2029 592 | - 0.1528 593 | - 0.1031 594 | '2021': 595 | - 0.2102 596 | - 0.1808 597 | - 0.1442 598 | - 0.1362 599 | '2022': 600 | - 0.2148 601 | - 0.1607 602 | - 0.1317 603 | - 0.1288 604 | offset: 605 | '2013': 606 | - 0.0369 607 | - 0.0235 608 | - 0.0217 609 | - 0.005 610 | '2014': 611 | - 0 612 | - 0 613 | - 0 614 | - 0 615 | '2015': 616 | - 0 617 | - 0 618 | - 0 619 | - 0 620 | '2016': 621 | - 0 622 | - 0 623 | - 0 624 | - 0 625 | '2017': 626 | - 0 627 | - 0 628 | - 0 629 | - 0 630 | '2018': 631 | - 0 632 | - 0 633 | - 0 634 | - 0 635 | '2019': 636 | - 0 637 | - 0 638 | - 0 639 | - 0 640 | '2020': 641 | - 0 642 | - 0 643 | - 0 644 | - 0 645 | '2021': 646 | - 0 647 | - 0 648 | - 0 649 | - 0 650 | '2022': 651 | - 0 652 | - 0 653 | - 0 654 | - 0 655 | GF1B: 656 | PMS: 657 | MUX: 658 | ESUN: 659 | - 1945.29 660 | - 1845.1 661 | - 1542.9 662 | - 1080.77 663 | gain: 664 | '2018': 665 | - 0.0333 666 | - 0.0414 667 | - 0.0474 668 | - 0.0435 669 | '2019': 670 | - 0.0292 671 | - 0.0362 672 | - 0.04 673 | - 0.0354 674 | '2020': 675 | - 0.0757 676 | - 0.0618 677 | - 0.0545 678 | - 0.0572 679 | offset: 680 | '2018': 681 | - 0 682 | - 0 683 | - 0 684 | - 0 685 | '2019': 686 | - 0 687 | - 0 688 | - 0 689 | - 0 690 | '2020': 691 | - 0 692 | - 0 693 | - 0 694 | - 0 695 | PAN: 696 | ESUN: 697 | - 1371.79 698 | gain: 699 | '2018': 700 | - 0.0399 701 | '2019': 702 | - 0.0399 703 | '2020': 704 | - 0.0687 705 | offset: 706 | '2018': 707 | - 0 708 | '2019': 709 | - 0 710 | '2020': 711 | - 0 712 | GF1C: 713 | PMS: 714 | MUX: 715 | ESUN: 716 | - 1931.98 717 | - 1848.95 718 | - 1535.31 719 | - 1063.84 720 | gain: 721 | '2018': 722 | - 0.0301 723 | - 0.0392 724 | - 0.0436 725 | - 0.0379 726 | '2019': 727 | - 0.029 728 | - 0.0382 729 | - 0.0421 730 | - 0.0364 731 | '2020': 732 | - 0.0758 733 | - 0.0657 734 | - 0.0543 735 | - 0.0564 736 | offset: 737 | '2018': 738 | - 0 739 | - 0 740 | - 0 741 | - 0 742 | '2019': 743 | - 0 744 | - 0 745 | - 0 746 | - 0 747 | '2020': 748 | - 0 749 | - 0 750 | - 0 751 | - 0 752 | PAN: 753 | ESUN: 754 | - 1383.91 755 | gain: 756 | '2018': 757 | - 0.0401 758 | '2019': 759 | - 0.0417 760 | '2020': 761 | - 0.0709 762 | offset: 763 | '2018': 764 | - 0 765 | '2019': 766 | - 0 767 | '2020': 768 | - 0 769 | GF1D: 770 | PMS: 771 | MUX: 772 | ESUN: 773 | - 1935.67 774 | - 1849.93 775 | - 1556.04 776 | - 1076.39 777 | gain: 778 | '2018': 779 | - 0.0296 780 | - 0.0388 781 | - 0.0444 782 | - 0.039 783 | '2019': 784 | - 0.0284 785 | - 0.0373 786 | - 0.0435 787 | - 0.0371 788 | '2020': 789 | - 0.0738 790 | - 0.0656 791 | - 0.059 792 | - 0.0585 793 | offset: 794 | '2018': 795 | - 0 796 | - 0 797 | - 0 798 | - 0 799 | '2019': 800 | - 0 801 | - 0 802 | - 0 803 | - 0 804 | '2020': 805 | - 0 806 | - 0 807 | - 0 808 | - 0 809 | PAN: 810 | ESUN: 811 | - 1395.3 812 | gain: 813 | '2018': 814 | - 0.0421 815 | '2019': 816 | - 0.0431 817 | '2020': 818 | - 0.0715 819 | offset: 820 | '2018': 821 | - 0 822 | '2019': 823 | - 0 824 | '2020': 825 | - 0 826 | GF2: 827 | PMS1: 828 | MSS: 829 | ESUN: 830 | - 1941.76 831 | - 1853.73 832 | - 1541.79 833 | - 1086.47 834 | gain: 835 | '2014': 836 | - 0.1585 837 | - 0.1883 838 | - 0.174 839 | - 0.1897 840 | '2015': 841 | - 0.1457 842 | - 0.1604 843 | - 0.155 844 | - 0.1731 845 | '2016': 846 | - 0.1322 847 | - 0.155 848 | - 0.1477 849 | - 0.1613 850 | '2017': 851 | - 0.1193 852 | - 0.153 853 | - 0.1424 854 | - 0.1569 855 | '2018': 856 | - 0.1356 857 | - 0.1736 858 | - 0.1644 859 | - 0.1788 860 | '2019': 861 | - 0.1453 862 | - 0.1826 863 | - 0.1727 864 | - 0.1908 865 | '2020': 866 | - 0.1378 867 | - 0.1778 868 | - 0.17 869 | - 0.1858 870 | '2021': 871 | - 0.1374 872 | - 0.1784 873 | - 0.1723 874 | - 0.1894 875 | '2022': 876 | - 0.1374 877 | - 0.1784 878 | - 0.1723 879 | - 0.1894 880 | offset: 881 | '2014': 882 | - -0.8765 883 | - -0.9742 884 | - -0.7652 885 | - -0.7233 886 | '2015': 887 | - 0 888 | - 0 889 | - 0 890 | - 0 891 | '2016': 892 | - 0 893 | - 0 894 | - 0 895 | - 0 896 | '2017': 897 | - 0 898 | - 0 899 | - 0 900 | - 0 901 | '2018': 902 | - 0 903 | - 0 904 | - 0 905 | - 0 906 | '2019': 907 | - 0 908 | - 0 909 | - 0 910 | - 0 911 | '2020': 912 | - 0 913 | - 0 914 | - 0 915 | - 0 916 | '2021': 917 | - 0 918 | - 0 919 | - 0 920 | - 0 921 | '2022': 922 | - 0 923 | - 0 924 | - 0 925 | - 0 926 | PAN: 927 | ESUN: 928 | - 1364.26 929 | gain: 930 | '2014': 931 | - 0.163 932 | '2015': 933 | - 0.1538 934 | '2016': 935 | - 0.1501 936 | '2017': 937 | - 0.1503 938 | '2018': 939 | - 0.1725 940 | '2019': 941 | - 0.1855 942 | '2020': 943 | - 0.1817 944 | '2021': 945 | - 0.1884 946 | '2022': 947 | - 0.1884 948 | offset: 949 | '2014': 950 | - -0.6077 951 | '2015': 952 | - 0 953 | '2016': 954 | - 0 955 | '2017': 956 | - 0 957 | '2018': 958 | - 0 959 | '2019': 960 | - 0 961 | '2020': 962 | - 0 963 | '2021': 964 | - 0 965 | '2022': 966 | - 0 967 | PMS2: 968 | MSS: 969 | ESUN: 970 | - 1941.22 971 | - 1853.61 972 | - 1541.7 973 | - 1086.53 974 | gain: 975 | '2014': 976 | - 0.1748 977 | - 0.1817 978 | - 0.1741 979 | - 0.1975 980 | '2015': 981 | - 0.1761 982 | - 0.1843 983 | - 0.1677 984 | - 0.183 985 | '2016': 986 | - 0.1762 987 | - 0.1856 988 | - 0.1754 989 | - 0.198 990 | '2017': 991 | - 0.1434 992 | - 0.1595 993 | - 0.1511 994 | - 0.1685 995 | '2018': 996 | - 0.1859 997 | - 0.2072 998 | - 0.1934 999 | - 0.218 1000 | '2019': 1001 | - 0.175 1002 | - 0.1902 1003 | - 0.177 1004 | - 0.1968 1005 | '2020': 1006 | - 0.1752 1007 | - 0.1919 1008 | - 0.1804 1009 | - 0.1968 1010 | '2021': 1011 | - 0.1641 1012 | - 0.1830 1013 | - 0.1705 1014 | - 0.1878 1015 | '2022': 1016 | - 0.1743 1017 | - 0.1784 1018 | - 0.1668 1019 | - 0.1912 1020 | offset: 1021 | '2014': 1022 | - -0.593 1023 | - -0.2717 1024 | - -0.2879 1025 | - -0.2773 1026 | '2015': 1027 | - 0 1028 | - 0 1029 | - 0 1030 | - 0 1031 | '2016': 1032 | - 0 1033 | - 0 1034 | - 0 1035 | - 0 1036 | '2017': 1037 | - 0 1038 | - 0 1039 | - 0 1040 | - 0 1041 | '2018': 1042 | - 0 1043 | - 0 1044 | - 0 1045 | - 0 1046 | '2019': 1047 | - 0 1048 | - 0 1049 | - 0 1050 | - 0 1051 | '2020': 1052 | - 0 1053 | - 0 1054 | - 0 1055 | - 0 1056 | '2021': 1057 | - 0 1058 | - 0 1059 | - 0 1060 | - 0 1061 | '2022': 1062 | - 0 1063 | - 0 1064 | - 0 1065 | - 0 1066 | PAN: 1067 | ESUN: 1068 | - 1362.16 1069 | gain: 1070 | '2014': 1071 | - 0.1823 1072 | '2015': 1073 | - 0 1074 | '2016': 1075 | - 0.1863 1076 | '2017': 1077 | - 0.1679 1078 | '2018': 1079 | - 0.2136 1080 | '2019': 1081 | - 0.198 1082 | '2020': 1083 | - 0.2025 1084 | '2021': 1085 | - 0.1959 1086 | '2022': 1087 | - 0.1923 1088 | offset: 1089 | '2014': 1090 | - 0.1654 1091 | '2015': 1092 | - 0 1093 | '2016': 1094 | - 0 1095 | '2017': 1096 | - 0 1097 | '2018': 1098 | - 0 1099 | '2019': 1100 | - 0 1101 | '2020': 1102 | - 0 1103 | '2021': 1104 | - 0 1105 | '2022': 1106 | - 0 1107 | GF5: 1108 | AHSI: 1109 | SW: 1110 | gain: 1111 | '2019': 1112 | - 0.1149 1113 | - 0.1012 1114 | - 0.0895 1115 | - 0.0786 1116 | - 0.0752 1117 | - 0.0697 1118 | - 0.0639 1119 | - 0.0601 1120 | - 0.0576 1121 | - 0.0537 1122 | - 0.0504 1123 | - 0.0485 1124 | - 0.0471 1125 | - 0.0437 1126 | - 0.0427 1127 | - 0.045 1128 | - 0.0444 1129 | - 0.0426 1130 | - 0.0399 1131 | - 0.0366 1132 | - 0.0348 1133 | - 0.0331 1134 | - 0.0319 1135 | - 0.0305 1136 | - 0.0295 1137 | - 0.028 1138 | - 0.0263 1139 | - 0.0247 1140 | - 0.0246 1141 | - 0.0248 1142 | - 0.0255 1143 | - 0.0245 1144 | - 0.0232 1145 | - 0.0218 1146 | - 0.0215 1147 | - 0.0213 1148 | - 0.0218 1149 | - 0.0223 1150 | - 0.0219 1151 | - 0.0232 1152 | - 0.0198 1153 | - 0.0115 1154 | - 0.0009 1155 | - 0.0006 1156 | - 0.0017 1157 | - 0.001 1158 | - 0.0017 1159 | - 0.0035 1160 | - 0.0078 1161 | - 0.0184 1162 | - 0.0245 1163 | - 0.0213 1164 | - 0.025 1165 | - 0.0243 1166 | - 0.0205 1167 | - 0.0198 1168 | - 0.0203 1169 | - 0.0206 1170 | - 0.0192 1171 | - 0.0175 1172 | - 0.0169 1173 | - 0.0166 1174 | - 0.0168 1175 | - 0.016 1176 | - 0.0158 1177 | - 0.0153 1178 | - 0.0153 1179 | - 0.0151 1180 | - 0.0154 1181 | - 0.0152 1182 | - 0.0155 1183 | - 0.0152 1184 | - 0.0152 1185 | - 0.0151 1186 | - 0.0151 1187 | - 0.0146 1188 | - 0.0146 1189 | - 0.0148 1190 | - 0.0146 1191 | - 0.0145 1192 | - 0.0145 1193 | - 0.0143 1194 | - 0.0145 1195 | - 0.0145 1196 | - 0.0145 1197 | - 0.0142 1198 | - 0.0143 1199 | - 0.0143 1200 | - 0.0147 1201 | - 0.0144 1202 | - 0.015 1203 | - 0.0151 1204 | - 0.0156 1205 | - 0.0153 1206 | - 0.0146 1207 | - 0.0082 1208 | - 0.0043 1209 | - 0.0019 1210 | - 0.0003 1211 | - 0.0001 1212 | - 0.0001 1213 | - 0.0001 1214 | - 0.0002 1215 | - 0.0001 1216 | - 0.0005 1217 | - 0.0007 1218 | - 0.0004 1219 | - 0.0001 1220 | - 0.0005 1221 | - 0.0014 1222 | - 0.0027 1223 | - 0.0044 1224 | - 0.0057 1225 | - 0.0053 1226 | - 0.0055 1227 | - 0.006 1228 | - 0.0064 1229 | - 0.0059 1230 | - 0.0055 1231 | - 0.004 1232 | - 0.0045 1233 | - 0.0052 1234 | - 0.0057 1235 | - 0.0056 1236 | - 0.0051 1237 | - 0.005 1238 | - 0.0053 1239 | - 0.0055 1240 | - 0.0057 1241 | - 0.0056 1242 | - 0.0058 1243 | - 0.0056 1244 | - 0.0058 1245 | - 0.0056 1246 | - 0.0056 1247 | - 0.0055 1248 | - 0.0057 1249 | - 0.0056 1250 | - 0.0055 1251 | - 0.0055 1252 | - 0.0056 1253 | - 0.0055 1254 | - 0.0057 1255 | - 0.0055 1256 | - 0.0056 1257 | - 0.0054 1258 | - 0.0055 1259 | - 0.0056 1260 | - 0.0056 1261 | - 0.0057 1262 | - 0.0058 1263 | - 0.0057 1264 | - 0.0059 1265 | - 0.0061 1266 | - 0.006 1267 | - 0.0057 1268 | - 0.0061 1269 | - 0.0059 1270 | - 0.0062 1271 | - 0.0061 1272 | - 0.0063 1273 | - 0.0061 1274 | - 0.0062 1275 | - 0.0063 1276 | - 0.0068 1277 | - 0.0065 1278 | - 0.0067 1279 | - 0.0069 1280 | - 0.007 1281 | - 0.0067 1282 | - 0.007 1283 | - 0.0069 1284 | - 0.007 1285 | - 0.0072 1286 | - 0.0076 1287 | - 0.0072 1288 | - 0.0054 1289 | - 0.006 1290 | - 0.0049 1291 | - 0.0022 1292 | offset: 1293 | '2019': 1294 | - 0 1295 | - 0 1296 | - 0 1297 | - 0 1298 | - 0 1299 | - 0 1300 | - 0 1301 | - 0 1302 | - 0 1303 | - 0 1304 | - 0 1305 | - 0 1306 | - 0 1307 | - 0 1308 | - 0 1309 | - 0 1310 | - 0 1311 | - 0 1312 | - 0 1313 | - 0 1314 | - 0 1315 | - 0 1316 | - 0 1317 | - 0 1318 | - 0 1319 | - 0 1320 | - 0 1321 | - 0 1322 | - 0 1323 | - 0 1324 | - 0 1325 | - 0 1326 | - 0 1327 | - 0 1328 | - 0 1329 | - 0 1330 | - 0 1331 | - 0 1332 | - 0 1333 | - 0 1334 | - 0 1335 | - 0 1336 | - 0 1337 | - 0 1338 | - 0 1339 | - 0 1340 | - 0 1341 | - 0 1342 | - 0 1343 | - 0 1344 | - 0 1345 | - 0 1346 | - 0 1347 | - 0 1348 | - 0 1349 | - 0 1350 | - 0 1351 | - 0 1352 | - 0 1353 | - 0 1354 | - 0 1355 | - 0 1356 | - 0 1357 | - 0 1358 | - 0 1359 | - 0 1360 | - 0 1361 | - 0 1362 | - 0 1363 | - 0 1364 | - 0 1365 | - 0 1366 | - 0 1367 | - 0 1368 | - 0 1369 | - 0 1370 | - 0 1371 | - 0 1372 | - 0 1373 | - 0 1374 | - 0 1375 | - 0 1376 | - 0 1377 | - 0 1378 | - 0 1379 | - 0 1380 | - 0 1381 | - 0 1382 | - 0 1383 | - 0 1384 | - 0 1385 | - 0 1386 | - 0 1387 | - 0 1388 | - 0 1389 | - 0 1390 | - 0 1391 | - 0 1392 | - 0 1393 | - 0 1394 | - 0 1395 | - 0 1396 | - 0 1397 | - 0 1398 | - 0 1399 | - 0 1400 | - 0 1401 | - 0 1402 | - 0 1403 | - 0 1404 | - 0 1405 | - 0 1406 | - 0 1407 | - 0 1408 | - 0 1409 | - 0 1410 | - 0 1411 | - 0 1412 | - 0 1413 | - 0 1414 | - 0 1415 | - 0 1416 | - 0 1417 | - 0 1418 | - 0 1419 | - 0 1420 | - 0 1421 | - 0 1422 | - 0 1423 | - 0 1424 | - 0 1425 | - 0 1426 | - 0 1427 | - 0 1428 | - 0 1429 | - 0 1430 | - 0 1431 | - 0 1432 | - 0 1433 | - 0 1434 | - 0 1435 | - 0 1436 | - 0 1437 | - 0 1438 | - 0 1439 | - 0 1440 | - 0 1441 | - 0 1442 | - 0 1443 | - 0 1444 | - 0 1445 | - 0 1446 | - 0 1447 | - 0 1448 | - 0 1449 | - 0 1450 | - 0 1451 | - 0 1452 | - 0 1453 | - 0 1454 | - 0 1455 | - 0 1456 | - 0 1457 | - 0 1458 | - 0 1459 | - 0 1460 | - 0 1461 | - 0 1462 | - 0 1463 | - 0 1464 | - 0 1465 | - 0 1466 | - 0 1467 | - 0 1468 | - 0 1469 | - 0 1470 | - 0 1471 | - 0 1472 | - 0 1473 | - 0 1474 | VN: 1475 | gain: 1476 | '2019': 1477 | - 0.83 1478 | - 0.5348 1479 | - 0.3756 1480 | - 0.2896 1481 | - 0.2344 1482 | - 0.1969 1483 | - 0.1682 1484 | - 0.1434 1485 | - 0.1273 1486 | - 0.1113 1487 | - 0.1002 1488 | - 0.0953 1489 | - 0.087 1490 | - 0.0821 1491 | - 0.0773 1492 | - 0.0738 1493 | - 0.0698 1494 | - 0.0659 1495 | - 0.0658 1496 | - 0.063 1497 | - 0.0612 1498 | - 0.0583 1499 | - 0.0586 1500 | - 0.0549 1501 | - 0.0541 1502 | - 0.0532 1503 | - 0.0523 1504 | - 0.0516 1505 | - 0.0509 1506 | - 0.0504 1507 | - 0.0481 1508 | - 0.0484 1509 | - 0.0479 1510 | - 0.0477 1511 | - 0.047 1512 | - 0.0473 1513 | - 0.0466 1514 | - 0.046 1515 | - 0.0455 1516 | - 0.0457 1517 | - 0.0478 1518 | - 0.0484 1519 | - 0.0466 1520 | - 0.0456 1521 | - 0.0456 1522 | - 0.0445 1523 | - 0.0451 1524 | - 0.0437 1525 | - 0.0438 1526 | - 0.0438 1527 | - 0.0434 1528 | - 0.0432 1529 | - 0.0422 1530 | - 0.0419 1531 | - 0.0421 1532 | - 0.0423 1533 | - 0.0426 1534 | - 0.042 1535 | - 0.0419 1536 | - 0.0416 1537 | - 0.042 1538 | - 0.0414 1539 | - 0.0422 1540 | - 0.0406 1541 | - 0.0414 1542 | - 0.0417 1543 | - 0.0419 1544 | - 0.0421 1545 | - 0.0425 1546 | - 0.0442 1547 | - 0.0402 1548 | - 0.0429 1549 | - 0.0439 1550 | - 0.0435 1551 | - 0.0428 1552 | - 0.0435 1553 | - 0.0481 1554 | - 0.0461 1555 | - 0.0486 1556 | - 0.048 1557 | - 0.0458 1558 | - 0.0471 1559 | - 0.0463 1560 | - 0.0465 1561 | - 0.047 1562 | - 0.0471 1563 | - 0.0612 1564 | - 0.0377 1565 | - 0.0402 1566 | - 0.0477 1567 | - 0.0497 1568 | - 0.0509 1569 | - 0.0515 1570 | - 0.0534 1571 | - 0.0543 1572 | - 0.0548 1573 | - 0.0559 1574 | - 0.0567 1575 | - 0.0595 1576 | - 0.065 1577 | - 0.0619 1578 | - 0.0637 1579 | - 0.0637 1580 | - 0.0648 1581 | - 0.063 1582 | - 0.0643 1583 | - 0.0655 1584 | - 0.0652 1585 | - 0.0699 1586 | - 0.0639 1587 | - 0.0705 1588 | - 0.0708 1589 | - 0.0703 1590 | - 0.0742 1591 | - 0.0743 1592 | - 0.0776 1593 | - 0.077 1594 | - 0.0847 1595 | - 0.0909 1596 | - 0.0924 1597 | - 0.0886 1598 | - 0.102 1599 | - 0.1017 1600 | - 0.1023 1601 | - 0.107 1602 | - 0.1186 1603 | - 0.1522 1604 | - 0.1477 1605 | - 0.1248 1606 | - 0.1658 1607 | - 0.1466 1608 | - 0.1585 1609 | - 0.1516 1610 | - 0.1656 1611 | - 0.1692 1612 | - 0.1698 1613 | - 0.1963 1614 | - 0.1919 1615 | - 0.2011 1616 | - 0.2068 1617 | - 0.2269 1618 | - 0.2388 1619 | - 0.2543 1620 | - 0.2872 1621 | - 0.2854 1622 | - 0.3273 1623 | - 0.3559 1624 | - 0.3728 1625 | - 0.4503 1626 | - 0.4887 1627 | offset: 1628 | '2019': 1629 | - 0 1630 | - 0 1631 | - 0 1632 | - 0 1633 | - 0 1634 | - 0 1635 | - 0 1636 | - 0 1637 | - 0 1638 | - 0 1639 | - 0 1640 | - 0 1641 | - 0 1642 | - 0 1643 | - 0 1644 | - 0 1645 | - 0 1646 | - 0 1647 | - 0 1648 | - 0 1649 | - 0 1650 | - 0 1651 | - 0 1652 | - 0 1653 | - 0 1654 | - 0 1655 | - 0 1656 | - 0 1657 | - 0 1658 | - 0 1659 | - 0 1660 | - 0 1661 | - 0 1662 | - 0 1663 | - 0 1664 | - 0 1665 | - 0 1666 | - 0 1667 | - 0 1668 | - 0 1669 | - 0 1670 | - 0 1671 | - 0 1672 | - 0 1673 | - 0 1674 | - 0 1675 | - 0 1676 | - 0 1677 | - 0 1678 | - 0 1679 | - 0 1680 | - 0 1681 | - 0 1682 | - 0 1683 | - 0 1684 | - 0 1685 | - 0 1686 | - 0 1687 | - 0 1688 | - 0 1689 | - 0 1690 | - 0 1691 | - 0 1692 | - 0 1693 | - 0 1694 | - 0 1695 | - 0 1696 | - 0 1697 | - 0 1698 | - 0 1699 | - 0 1700 | - 0 1701 | - 0 1702 | - 0 1703 | - 0 1704 | - 0 1705 | - 0 1706 | - 0 1707 | - 0 1708 | - 0 1709 | - 0 1710 | - 0 1711 | - 0 1712 | - 0 1713 | - 0 1714 | - 0 1715 | - 0 1716 | - 0 1717 | - 0 1718 | - 0 1719 | - 0 1720 | - 0 1721 | - 0 1722 | - 0 1723 | - 0 1724 | - 0 1725 | - 0 1726 | - 0 1727 | - 0 1728 | - 0 1729 | - 0 1730 | - 0 1731 | - 0 1732 | - 0 1733 | - 0 1734 | - 0 1735 | - 0 1736 | - 0 1737 | - 0 1738 | - 0 1739 | - 0 1740 | - 0 1741 | - 0 1742 | - 0 1743 | - 0 1744 | - 0 1745 | - 0 1746 | - 0 1747 | - 0 1748 | - 0 1749 | - 0 1750 | - 0 1751 | - 0 1752 | - 0 1753 | - 0 1754 | - 0 1755 | - 0 1756 | - 0 1757 | - 0 1758 | - 0 1759 | - 0 1760 | - 0 1761 | - 0 1762 | - 0 1763 | - 0 1764 | - 0 1765 | - 0 1766 | - 0 1767 | - 0 1768 | - 0 1769 | - 0 1770 | - 0 1771 | - 0 1772 | - 0 1773 | - 0 1774 | - 0 1775 | - 0 1776 | - 0 1777 | - 0 1778 | - 0 1779 | GF6: 1780 | PMS: 1781 | MUX: 1782 | ESUN: 1783 | - 1945.5 1784 | - 1832.38 1785 | - 1558.18 1786 | - 1090.77 1787 | gain: 1788 | '2018': 1789 | - 0.0825 1790 | - 0.0663 1791 | - 0.0513 1792 | - 0.0298 1793 | '2019': 1794 | - 0.0847 1795 | - 0.0653 1796 | - 0.0491 1797 | - 0.0289 1798 | '2020': 1799 | - 0.082 1800 | - 0.0645 1801 | - 0.0489 1802 | - 0.0286 1803 | '2021': 1804 | - 0.0821 1805 | - 0.0671 1806 | - 0.0518 1807 | - 0.0310 1808 | '2022': 1809 | - 0.0892 1810 | - 0.0666 1811 | - 0.0517 1812 | - 0.032 1813 | offset: 1814 | '2018': 1815 | - 0 1816 | - 0 1817 | - 0 1818 | - 0 1819 | '2019': 1820 | - 0 1821 | - 0 1822 | - 0 1823 | - 0 1824 | '2020': 1825 | - 0 1826 | - 0 1827 | - 0 1828 | - 0 1829 | '2021': 1830 | - 0 1831 | - 0 1832 | - 0 1833 | - 0 1834 | '2022': 1835 | - 0 1836 | - 0 1837 | - 0 1838 | - 0 1839 | PAN: 1840 | ESUN: 1841 | - 1497.79 1842 | gain: 1843 | '2018': 1844 | - 0.0505 1845 | '2019': 1846 | - 0.0534 1847 | '2020': 1848 | - 0.0534 1849 | '2021': 1850 | - 0.0577 1851 | '2022': 1852 | - 0.0569 1853 | offset: 1854 | '2018': 1855 | - 0 1856 | '2019': 1857 | - 0 1858 | '2020': 1859 | - 0 1860 | '2021': 1861 | - 0 1862 | '2022': 1863 | - 0 1864 | WFV: 1865 | ESUN: 1866 | - 1952.16 1867 | - 1847.43 1868 | - 1554.76 1869 | - 1074.06 1870 | - 1412.0 1871 | - 1267.39 1872 | - 1792.64 1873 | - 1736.92 1874 | gain: 1875 | '2019': 1876 | - 0.0705 1877 | - 0.0567 1878 | - 0.0516 1879 | - 0.0322 1880 | - 0.0532 1881 | - 0.0453 1882 | - 0.0786 1883 | - 0.0585 1884 | '2020': 1885 | - 0.0675 1886 | - 0.0552 1887 | - 0.0513 1888 | - 0.0314 1889 | - 0.0519 1890 | - 0.0454 1891 | - 0.0718 1892 | - 0.0596 1893 | '2021': 1894 | - 0.0633 1895 | - 0.0532 1896 | - 0.0508 1897 | - 0.0325 1898 | - 0.0523 1899 | - 0.0463 1900 | - 0.0670 1901 | - 0.0591 1902 | '2022': 1903 | - 0.0631 1904 | - 0.0469 1905 | - 0.0443 1906 | - 0.0297 1907 | - 0.0503 1908 | - 0.0439 1909 | - 0.0775 1910 | - 0.0505 1911 | offset: 1912 | '2019': 1913 | - 0 1914 | - 0 1915 | - 0 1916 | - 0 1917 | - 0 1918 | - 0 1919 | - 0 1920 | - 0 1921 | '2020': 1922 | - 0 1923 | - 0 1924 | - 0 1925 | - 0 1926 | - 0 1927 | - 0 1928 | - 0 1929 | - 0 1930 | '2021': 1931 | - 0 1932 | - 0 1933 | - 0 1934 | - 0 1935 | - 0 1936 | - 0 1937 | - 0 1938 | - 0 1939 | '2022': 1940 | - 0 1941 | - 0 1942 | - 0 1943 | - 0 1944 | - 0 1945 | - 0 1946 | - 0 1947 | - 0 1948 | GF7: 1949 | DLC: 1950 | MUX: 1951 | ESUN: 1952 | - 1929.44 1953 | - 1843.61 1954 | - 1554.83 1955 | - 1081.34 1956 | gain: 1957 | '2020': 1958 | - 0.065856 1959 | - 0.07315 1960 | - 0.07339 1961 | - 0.06985 1962 | '2021': 1963 | - 0.0914 1964 | - 0.0981 1965 | - 0.0759 1966 | - 0.0925 1967 | '2022': 1968 | - 0.08703 1969 | - 0.08481 1970 | - 0.06678 1971 | - 0.08285 1972 | offset: 1973 | '2020': 1974 | - 0 1975 | - 0 1976 | - 0 1977 | - 0 1978 | '2021': 1979 | - 0 1980 | - 0 1981 | - 0 1982 | - 0 1983 | '2022': 1984 | - 0 1985 | - 0 1986 | - 0 1987 | - 0 1988 | PAN: 1989 | ESUN: 1990 | - 1414.92 1991 | gain: 1992 | '2020': 1993 | - 0.08032 1994 | '2021': 1995 | - 0.0879 1996 | '2022': 1997 | - 0.07914 1998 | offset: 1999 | '2020': 2000 | - 0 2001 | '2021': 2002 | - 0 2003 | '2022': 2004 | - 0 2005 | BWD: 2006 | MUX: 2007 | ESUN: 2008 | - 1929.44 2009 | - 1843.61 2010 | - 1554.83 2011 | - 1081.34 2012 | gain: 2013 | '2020': 2014 | - 0.065856 2015 | - 0.07315 2016 | - 0.07339 2017 | - 0.06985 2018 | '2021': 2019 | - 0.0914 2020 | - 0.0981 2021 | - 0.0759 2022 | - 0.0925 2023 | '2022': 2024 | - 0.08703 2025 | - 0.08481 2026 | - 0.06678 2027 | - 0.08285 2028 | offset: 2029 | '2020': 2030 | - 0 2031 | - 0 2032 | - 0 2033 | - 0 2034 | '2021': 2035 | - 0 2036 | - 0 2037 | - 0 2038 | - 0 2039 | '2022': 2040 | - 0 2041 | - 0 2042 | - 0 2043 | - 0 2044 | PAN: 2045 | ESUN: 2046 | - 1414.92 2047 | gain: 2048 | '2020': 2049 | - 0.08032 2050 | '2021': 2051 | - 0.0879 2052 | '2022': 2053 | - 0.07914 2054 | offset: 2055 | '2020': 2056 | - 0 2057 | '2021': 2058 | - 0 2059 | '2022': 2060 | - 0 2061 | GFDM01: 2062 | PMS: 2063 | MUX: 2064 | ESUN: 2065 | - 1950.28 2066 | - 1850.84 2067 | - 1663.46 2068 | - 1093.16 2069 | - 1798.07 2070 | - 1724.71 2071 | - 1396.97 2072 | - 886.55 2073 | gain: 2074 | '2020': 2075 | - 0.062696 2076 | - 0.07657 2077 | - 0.052356 2078 | - 0.074683 2079 | - 0.105211 2080 | - 0.145286 2081 | - 0.087972 2082 | - 0.064702 2083 | offset: 2084 | '2020': 2085 | - -3.730408 2086 | - -4.970138 2087 | - -4.273298 2088 | - -4.836445 2089 | - -8.518515 2090 | - -14.559728 2091 | - -8.4777 2092 | - -3.961042 2093 | PAN: 2094 | ESUN: 2095 | - 1453.9 2096 | gain: 2097 | '2020': 2098 | - 0.071225 2099 | offset: 2100 | '2020': 2101 | - -4.358974 2102 | HJ2A: 2103 | CCD1: 2104 | gain: 2105 | '2021': 2106 | - 0.0706 2107 | - 0.0591 2108 | - 0.0508 2109 | - 0.0534 2110 | - 0.0667 2111 | '2022': 2112 | - 0.0718 2113 | - 0.0537 2114 | - 0.0464 2115 | - 0.0503 2116 | - 0.0718 2117 | offset: 2118 | '2021': 2119 | - 0.0 2120 | - 0.0 2121 | - 0.0 2122 | - 0.0 2123 | - 0.0 2124 | '2022': 2125 | - 0.0 2126 | - 0.0 2127 | - 0.0 2128 | - 0.0 2129 | - 0.0 2130 | CCD2: 2131 | gain: 2132 | '2022': 2133 | - 0.0623 2134 | - 0.0538 2135 | - 0.0471 2136 | - 0.052 2137 | - 0.0489 2138 | offset: 2139 | '2022': 2140 | - 0.0 2141 | - 0.0 2142 | - 0.0 2143 | - 0.0 2144 | - 0.0 2145 | CCD3: 2146 | gain: 2147 | '2021': 2148 | - 0.0643 2149 | - 0.0554 2150 | - 0.0499 2151 | - 0.0567 2152 | - 0.0532 2153 | '2022': 2154 | - 0.0657 2155 | - 0.0526 2156 | - 0.0473 2157 | - 0.0555 2158 | - 0.0534 2159 | offset: 2160 | '2021': 2161 | - 0.0 2162 | - 0.0 2163 | - 0.0 2164 | - 0.0 2165 | - 0.0 2166 | '2022': 2167 | - 0.0 2168 | - 0.0 2169 | - 0.0 2170 | - 0.0 2171 | - 0.0 2172 | CCD4: 2173 | gain: 2174 | '2021': 2175 | - 0.0634 2176 | - 0.0547 2177 | - 0.0491 2178 | - 0.0567 2179 | - 0.0522 2180 | '2022': 2181 | - 0.0759 2182 | - 0.0604 2183 | - 0.0543 2184 | - 0.0635 2185 | - 0.0589 2186 | offset: 2187 | '2021': 2188 | - 0.0 2189 | - 0.0 2190 | - 0.0 2191 | - 0.0 2192 | - 0.0 2193 | '2022': 2194 | - 0.0 2195 | - 0.0 2196 | - 0.0 2197 | - 0.0 2198 | - 0.0 2199 | HJ2B: 2200 | CCD1: 2201 | gain: 2202 | '2021': 2203 | - 0.0614 2204 | - 0.0529 2205 | - 0.046 2206 | - 0.0487 2207 | - 0.0473 2208 | '2022': 2209 | - 0.0664 2210 | - 0.0522 2211 | - 0.0459 2212 | - 0.05 2213 | - 0.0478 2214 | offset: 2215 | '2021': 2216 | - 0.0 2217 | - 0.0 2218 | - 0.0 2219 | - 0.0 2220 | - 0.0 2221 | '2022': 2222 | - 0.0 2223 | - 0.0 2224 | - 0.0 2225 | - 0.0 2226 | - 0.0 2227 | CCD2: 2228 | gain: 2229 | '2021': 2230 | - 0.0666 2231 | - 0.0576 2232 | - 0.0502 2233 | - 0.0541 2234 | - 0.0519 2235 | '2022': 2236 | - 0.058 2237 | - 0.0513 2238 | - 0.0454 2239 | - 0.0491 2240 | - 0.0475 2241 | offset: 2242 | '2021': 2243 | - 0.0 2244 | - 0.0 2245 | - 0.0 2246 | - 0.0 2247 | - 0.0 2248 | '2022': 2249 | - 0.0 2250 | - 0.0 2251 | - 0.0 2252 | - 0.0 2253 | - 0.0 2254 | CCD3: 2255 | gain: 2256 | '2021': 2257 | - 0.063 2258 | - 0.0565 2259 | - 0.0502 2260 | - 0.0549 2261 | - 0.0521 2262 | '2022': 2263 | - 0.0692 2264 | - 0.0561 2265 | - 0.0504 2266 | - 0.0571 2267 | - 0.0542 2268 | offset: 2269 | '2021': 2270 | - 0.0 2271 | - 0.0 2272 | - 0.0 2273 | - 0.0 2274 | - 0.0 2275 | '2022': 2276 | - 0.0 2277 | - 0.0 2278 | - 0.0 2279 | - 0.0 2280 | - 0.0 2281 | ZY303: 2282 | TMS: 2283 | BWD: 2284 | ESUN: 2285 | - 1604.62 2286 | gain: 2287 | '2020': 2288 | - 0.23895 2289 | offset: 2290 | '2020': 2291 | - -2.75349 2292 | FWD: 2293 | ESUN: 2294 | - 1603.09 2295 | gain: 2296 | '2020': 2297 | - 0.23034 2298 | offset: 2299 | '2020': 2300 | - -2.99839 2301 | MUX: 2302 | ESUN: 2303 | - 1865.23 2304 | - 1905.01 2305 | - 1716.34 2306 | - 1203.04 2307 | gain: 2308 | '2020': 2309 | - 0.20223 2310 | - 0.19506 2311 | - 0.21429 2312 | - 0.21654 2313 | offset: 2314 | '2020': 2315 | - 0 2316 | - 0 2317 | - 0 2318 | - 0 2319 | NAD: 2320 | ESUN: 2321 | - 1607.13 2322 | gain: 2323 | '2020': 2324 | - 0.20796 2325 | offset: 2326 | '2020': 2327 | - -2.67428 2328 | -------------------------------------------------------------------------------- /data/GMTED2km.tif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GenghisYoung233/Gaofen-Batch/d9bec730168b0c3dd4aa6a7d15e6f40641cc0dd3/data/GMTED2km.tif -------------------------------------------------------------------------------- /index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | Gaofen Batch 6 | 7 | 8 | 10 | 11 | 12 | 13 | 261 | 262 | 263 | 264 |
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322 | 323 | 496 | 497 | 498 | 499 | -------------------------------------------------------------------------------- /main.js: -------------------------------------------------------------------------------- 1 | const { app, BrowserWindow, ipcMain, dialog, Menu } = require('electron'); 2 | const log = require('electron-log'); 3 | const path = require('path'); 4 | 5 | // Configure electron-log 6 | log.transports.file.level = 'info'; 7 | 8 | function createWindow() { 9 | const mainWindow = new BrowserWindow({ 10 | width: 800, 11 | height: 600, 12 | webPreferences: { 13 | nodeIntegration: true, 14 | contextIsolation: false, 15 | }, 16 | icon: path.join(__dirname, './assets/app_icon.ico'), 17 | title: 'Gaofen Batch' 18 | }); 19 | 20 | // Set the default menu to null to remove it 21 | Menu.setApplicationMenu(null); 22 | 23 | mainWindow.loadFile('index.html'); 24 | } 25 | 26 | app.whenReady().then(createWindow); 27 | 28 | app.on('window-all-closed', function () { 29 | if (process.platform !== 'darwin') app.quit(); 30 | }); 31 | 32 | app.on('activate', function () { 33 | if (BrowserWindow.getAllWindows().length === 0) createWindow(); 34 | }); 35 | 36 | ipcMain.on('open-file-dialog', (event) => { 37 | dialog.showOpenDialog({ 38 | properties: ['openFile', 'multiSelections'], 39 | filters: [{ name: 'Tarball Files', extensions: ['tar.gz', 'tar.xz'] }] 40 | }).then(result => { 41 | if (!result.canceled) { 42 | event.sender.send('selected-files', result.filePaths); 43 | } 44 | }).catch(err => { 45 | log.info(err); 46 | }); 47 | }); 48 | 49 | // New listener for directory selection 50 | ipcMain.on('open-directory-dialog', (event) => { 51 | dialog.showOpenDialog({ 52 | properties: ['openDirectory'], 53 | title: '选择输出文件夹' 54 | }).then(result => { 55 | if (!result.canceled && result.filePaths[0]) { 56 | event.sender.send('selected-directory', result.filePaths[0]); 57 | } 58 | }).catch(err => { 59 | log.info(err); 60 | }); 61 | }); 62 | 63 | ipcMain.on('log', (event, text) => { 64 | log.info(text); 65 | }); 66 | -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | import os 2 | import re 3 | import argparse 4 | import traceback 5 | import uuid 6 | import sys 7 | import numpy as np 8 | import subprocess 9 | import tarfile 10 | import yaml 11 | import shutil 12 | import xml.dom.minidom 13 | import rasterio 14 | import rasterio.control 15 | import rasterio.crs 16 | import rasterio.sample 17 | import rasterio.vrt 18 | import rasterio._features 19 | from itertools import product 20 | from tqdm import tqdm 21 | from os.path import join 22 | from glob import glob 23 | from loguru import logger 24 | 25 | 26 | def untar(filePath, extractFolderPath): 27 | logger.info("解压中...") 28 | try: 29 | # Determine the mode based on file extension 30 | if filePath.endswith('.tar.gz'): 31 | mode = 'r:gz' 32 | elif filePath.endswith('.tar.xz'): 33 | mode = 'r:xz' 34 | else: 35 | mode = 'r' 36 | 37 | # Extract the tar file directly to extractFolderPath 38 | with tarfile.open(filePath, mode) as tar: 39 | tar.extractall(path=extractFolderPath) 40 | 41 | # Check for extra nested folders and adjust if necessary 42 | extracted_folders = [f for f in os.listdir(extractFolderPath) if os.path.isdir(join(extractFolderPath, f))] 43 | for folder in extracted_folders: 44 | nested_path = join(extractFolderPath, folder) 45 | if os.path.exists(nested_path): 46 | for item in os.listdir(nested_path): 47 | shutil.move(join(nested_path, item), extractFolderPath) 48 | os.rmdir(nested_path) 49 | except Exception: 50 | logger.error(f"文件{filePath}打开失败: \n", traceback.format_exc()) 51 | 52 | 53 | def rpc_ortho(srcfile, dem, dstfile, pixel_size=None, utm=True): 54 | logger.info("RPC正射校正中...") 55 | pixel_size = f"-tr {pixel_size} {pixel_size} -tap" if pixel_size else "" 56 | if utm: 57 | isNorth = 1 if os.path.basename(srcfile).split('_')[3][0] != 'S' else 0 58 | for string in os.path.basename(srcfile).split('_'): 59 | if re.match(r'^E\d', string) or re.match(r'^W\d', string): 60 | zone = str(int(float(string[1:]) / 6) + 31) # int(longitude / 6) + 31 61 | zone = int('326' + zone) if isNorth == 1 else int('327' + zone) 62 | target_coords = f"EPSG:{zone}" 63 | else: 64 | target_coords = "EPSG:4326" # WGS84 65 | gdalwarp = join(otbPath, r"bin\gdalwarp.exe") 66 | rpc_ortho_cmd = f"{gdalwarp} -t_srs {target_coords} {pixel_size} -rpc -to RPC_DEM={dem} -co COMPRESS=LZW -co PREDICTOR=2 -co BIGTIFF=IF_SAFER -multi -wo NUM_THREADS=ALL_CPUS -co NUM_THREADS=ALL_CPUS -r cubic -dstnodata 0.00 -of GTiff -overwrite {srcfile} {dstfile}" 67 | subprocess.run([x for x in rpc_ortho_cmd.split(" ") if x != ""]) 68 | 69 | 70 | def reproject(input_raster, output_raster, target_coords="EPSG:4326"): 71 | gdalwarp = join(otbPath, r"bin\gdalwarp.exe") 72 | reproj_cmd = f"{gdalwarp} -t_srs {target_coords} -r cubic -of GTiff -co COMPRESS=LZW -co PREDICTOR=2 -co BIGTIFF=IF_SAFER -multi -wo NUM_THREADS=ALL_CPUS -co NUM_THREADS=ALL_CPUS -overwrite {input_raster} {output_raster}" 73 | subprocess.run([x for x in reproj_cmd.split(" ") if x != ""]) 74 | 75 | 76 | def pansharpening_otb(spectral, pancromatic, output): 77 | logger.info("融合中...") 78 | os.environ['OTB_appPath'] = join(otbPath, r"lib\otb\applications") 79 | otb_bat = join(otbPath, r"bin\otbcli_BundleToPerfectSensor.bat") 80 | output_temp = join(os.path.dirname(output), f"temp_{str(uuid.uuid4())[:5]}.tif") 81 | dtype = 'uint16' if args.level == "DN" else 'float' 82 | cmd = f"{otb_bat} -inp {pancromatic} -inxs {spectral} -out {output_temp} {dtype}" 83 | subprocess.run(join(otbPath, "otbenv.bat")) 84 | subprocess.run(cmd) 85 | compress(output_temp, output) 86 | 87 | 88 | def clip_raster_by_mask_layer(input_raster, mask, output_raster, pixel_size=None, target_coords=None): 89 | pixel_size = f"-tr {pixel_size} {pixel_size} -tap" if pixel_size else "" 90 | target_coords = f"-t_srs {target_coords}" if target_coords else "" 91 | mask_name = os.path.splitext(os.path.basename(mask))[0] 92 | gdalwarp = join(otbPath, r"bin\gdalwarp.exe") 93 | clip_cmd = f"{gdalwarp} -of GTiff {target_coords} {pixel_size} -cutline {mask} -cl {mask_name} -crop_to_cutline -r cubic -co COMPRESS=LZW -co PREDICTOR=2 -co BIGTIFF=IF_SAFER -multi -wo NUM_THREADS=ALL_CPUS -co NUM_THREADS=ALL_CPUS -overwrite {input_raster} {output_raster}" 94 | subprocess.run([x for x in clip_cmd.split(" ") if x != ""]) 95 | 96 | 97 | def compress(input, output): 98 | logger.info("压缩中...") 99 | gdal_translate = join(otbPath, r"bin\gdal_translate.exe") 100 | compress_cmd = f"{gdal_translate} -of GTiff -co NUM_THREADS=ALL_CPUS -co COMPRESS=LZW -co PREDICTOR=2 -co BIGTIFF=IF_SAFER {input} {output}" 101 | subprocess.run([x for x in compress_cmd.split(" ") if x != ""]) 102 | os.remove(input) 103 | 104 | 105 | def mosaic(input_files, mosaic_file, resample="cubic"): 106 | logger.info("镶嵌中...") 107 | paths = "" 108 | for file in input_files: 109 | paths = paths + f"{file}\n" 110 | vrt = input_files[0].replace(".tif", ".vrt") 111 | input_file_list = input_files[0].replace(".tif", ".txt") 112 | txt = open(input_file_list, "w") 113 | txt.write(paths) 114 | txt.close() 115 | gdalbuildvrt = join(otbPath, r"bin\gdalbuildvrt.exe") 116 | gdal_translate = join(otbPath, r"bin\gdal_translate.exe") 117 | buildvrt_cmd = f"{gdalbuildvrt} -resolution highest -r {resample} -input_file_list {input_file_list} {vrt}" 118 | translate_cmd = f"{gdal_translate} -of GTiff -co NUM_THREADS=ALL_CPUS -co COMPRESS=LZW -co PREDICTOR=2 -co BIGTIFF=IF_SAFER {vrt} {mosaic_file}" 119 | subprocess.run([x for x in buildvrt_cmd.split(" ") if x != ""]) 120 | subprocess.run([x for x in translate_cmd.split(" ") if x != ""]) 121 | os.remove(input_file_list) 122 | os.remove(vrt) 123 | 124 | 125 | def save_txt(txt_path, contents, mode="a"): 126 | fh = open(txt_path, mode) # 'a'为新增，'w'为覆盖 127 | fh.write('%s\n' % contents) 128 | fh.close() 129 | 130 | 131 | def build_pyramid(file): 132 | logger.info("建金字塔中...") 133 | gdaladdo = join(otbPath, r"bin\gdaladdo.exe") 134 | build_pyramid_cmd = f"{gdaladdo} {file} -r nearest -ro --config COMPRESS_OVERVIEW LZW --config BIGTIFF_OVERVIEW IF_SAFER" 135 | subprocess.run([x for x in build_pyramid_cmd.split(" ") if x != ""]) 136 | return 137 | 138 | 139 | def stack(rasters, out_raster): 140 | logger.info("波段堆叠中...") 141 | count = sum([rasterio.open(raster).count for raster in rasters]) 142 | 143 | with rasterio.open(rasters[0], 'r') as src: 144 | profile = src.profile 145 | profile.update(count=count, BIGTIFF='IF_SAFER') 146 | 147 | with rasterio.open(out_raster, 'w', **profile) as dst: 148 | band_index = 0 149 | for raster in rasters: 150 | with rasterio.open(raster, "r") as src_raster: 151 | for idx in range(1, src_raster.count + 1): 152 | band = src_raster.read(indexes=idx) 153 | band_index += 1 154 | dst.write(band, band_index) 155 | 156 | 157 | class correction(): 158 | def __init__(self, input_raster, metadata): 159 | self.input_raster = input_raster 160 | self.config = yaml.safe_load((open(join(appPath, "data", "AtmosphericCorrectionParameter.yaml")))) 161 | filename_split = os.path.basename(input_raster).split("_") 162 | self.SatelliteID = filename_split[0] 163 | self.SensorID = filename_split[1] 164 | self.Year = filename_split[4][:4] 165 | self.ImageType = "MUX" if "MUX" in filename_split[-1] else "MSS" 166 | self.ImageType = "PAN" if "PAN" in filename_split[-1] else self.ImageType 167 | self.metadata = metadata 168 | 169 | self.supported_sensor = ['GF1-PMS1/2', 170 | 'GF1-WFV1/2/3/4', 171 | 'GF1B/C/D-PMS', 172 | 'GF2-PMS1/2', 173 | 'GF6-PMS', 174 | 'GF6-WFV', 175 | 'GF7-DLC', 176 | 'GF7-BWD', 177 | 'ZY303-TMS'] 178 | 179 | self.is_valid = True 180 | if 'ESUN' not in str(self.config.get(self.SatelliteID, {}).get(self.SensorID, {})): 181 | logger.warning(f"缺少{self.SatelliteID}_{self.SensorID}的太阳辐照度（ESUN）参数，大气校正目前仅支持如下传感器：{self.supported_sensor}") 182 | logger.warning("退出大气校正！") 183 | self.is_valid = False # Set is_valid to False if condition is met 184 | 185 | def apply_corrections(self): 186 | with rasterio.open(self.input_raster) as src: 187 | profile = src.profile 188 | profile.update(dtype=np.float32, blockxsize=100, blockysize=100, BIGTIFF='IF_SAFER') 189 | rasterTOA = self.input_raster.replace(".tif", f"_TOA.tif") 190 | with rasterio.open(rasterTOA, 'w', **profile) as dst: 191 | windows = [window for _, window in dst.block_windows()] 192 | for window in tqdm(windows, desc="大气表观反射率计算中..."): 193 | data = src.read(window=window).astype(np.float32) # Ensure float32 194 | data = self.radiometric_block(data, self.metadata) 195 | dst.write(data.astype(np.float32), window=window) 196 | 197 | dark_object_dns = self.calculate_dark_object(rasterTOA) 198 | with rasterio.open(rasterTOA) as src: 199 | rasterSR = self.input_raster.replace(".tif", f"_SR.tif") 200 | with rasterio.open(rasterSR, 'w', **profile) as dst: 201 | windows = [window for _, window in dst.block_windows()] 202 | for window in tqdm(windows, desc="地表反射率计算中..."): 203 | data = src.read(window=window).astype(np.float32) # Ensure float32 204 | data = self.DOS_correction(data, dark_object_dns) 205 | dst.write(data.astype(np.float32), window=window) 206 | os.remove(self.input_raster) 207 | os.remove(rasterTOA) 208 | os.rename(rasterSR, self.input_raster) 209 | 210 | def calculate_dark_object(self, inImage, patch_size=50, percentile=1): 211 | logger.info("计算暗物体反射率...") 212 | with rasterio.open(inImage, 'r') as src: 213 | nodata = src.profile.get("nodata", None) 214 | num_bands = src.count 215 | min_values_per_band = [[] for _ in range(num_bands)] 216 | # Generate windows based on patch_size if the image is not inherently blocked 217 | nrows, ncols = src.shape 218 | offsets = product(range(0, nrows, patch_size), range(0, ncols, patch_size)) 219 | windows = [((row_start, min(row_start + patch_size, nrows)), 220 | (col_start, min(col_start + patch_size, ncols))) for row_start, col_start in offsets] 221 | 222 | for window in windows: 223 | X = src.read(window=window) 224 | if nodata is not None: 225 | mask = (X != nodata) & (X != 0) 226 | else: 227 | mask = (X != 0) 228 | for band in range(num_bands): 229 | X_masked = X[band][mask[band]] 230 | if X_masked.size > 0: 231 | min_value = np.min(X_masked) 232 | min_values_per_band[band].append(min_value) 233 | 234 | # Compute the dark object DN for the entire image for each band using the min values 235 | dark_object_dns_per_band = [np.percentile(min_values, percentile).astype(np.float32) for min_values in min_values_per_band] 236 | 237 | return dark_object_dns_per_band 238 | 239 | def radiometric_block(self, block, metadata): 240 | """ 241 | Apply radiometric correction on the input block. 242 | """ 243 | block = block.astype(np.float32) 244 | bands, _, _ = block.shape 245 | cosine_solar_zenith = np.cos(np.deg2rad(float(xml.dom.minidom.parse(metadata).getElementsByTagName('SolarZenith')[0].firstChild.data))) 246 | for m in range(bands): 247 | params = self.RadiometricCalibration(m+1) 248 | # TOA calculation 249 | block[m] = (block[m] * params[-2] + params[-1]) 250 | block[m] = (np.pi * block[m]) / (params[0] * cosine_solar_zenith) 251 | return block 252 | 253 | def DOS_correction(self, data, dark_object_dns): 254 | """ 255 | Apply Dark Object Subtraction (DOS) correction on the input data. 256 | """ 257 | data = data.astype(np.float32) # Convert to float32 for calculations 258 | for band in range(data.shape[0]): 259 | data[band] -= dark_object_dns[band] 260 | data[band] = np.clip(data[band], 0, None) 261 | return data 262 | 263 | def RadiometricCalibration(self, bandID): 264 | # 读取增益、偏移、太阳辐照度参数 265 | if self.SensorID.startswith('WFV'): 266 | esun = self.config[self.SatelliteID][self.SensorID]['ESUN'][bandID - 1] 267 | dct = self.config[self.SatelliteID][self.SensorID]['gain'] 268 | self.Year = str(min([int(k) for k in dct if k.isdigit()], key=lambda x: abs(x - int(self.Year)))) 269 | gain = self.config[self.SatelliteID][self.SensorID]['gain'][self.Year][bandID - 1] 270 | offset = self.config[self.SatelliteID][self.SensorID]['offset'][self.Year][bandID - 1] 271 | else: 272 | esun = self.config[self.SatelliteID][self.SensorID][self.ImageType]['ESUN'][bandID - 1] 273 | dct = self.config[self.SatelliteID][self.SensorID][self.ImageType]['gain'] 274 | self.Year = str(min([int(k) for k in dct if k.isdigit()], key=lambda x: abs(x - int(self.Year)))) 275 | gain = self.config[self.SatelliteID][self.SensorID][self.ImageType]['gain'][self.Year][bandID - 1] 276 | offset = self.config[self.SatelliteID][self.SensorID][self.ImageType]['offset'][self.Year][bandID - 1] 277 | return [esun, gain, offset] 278 | 279 | 280 | def main(outputDirectory, dem, level, pansharpen, pyramid, files): 281 | for i, file in enumerate(files): 282 | # logger.warning(f"处理第{i+1}景数据中，共{len(files)}景数据") 283 | logger.info(f"开始处理{file}") 284 | assert " " not in file, "请确保输入数据的路径不包含空格！" 285 | assert ".tar" in file, "仅支持原始tar压缩包，请不要自行解压！" 286 | 287 | # Extract to outputDirectory 288 | dataPath = join(outputDirectory, os.path.basename(file)[:-7]) 289 | try: 290 | untar(file, dataPath) 291 | except: 292 | continue 293 | 294 | # Get spectral rasters and pancromatic rasters 295 | M, P = get_rasters_name(dataPath) 296 | 297 | # RPC Orthorectification for spectral rasters 298 | m_out_list = list() 299 | for m in M: 300 | logger.info("处理多光谱数据中...") 301 | try: 302 | m_in = join(dataPath, m) 303 | m_out = join(outputDirectory, m) 304 | rpc_ortho(m_in, dem, m_out) 305 | m_out_list.append(m_out) 306 | except: 307 | continue 308 | 309 | def ato_cor(m_out, metadata): 310 | correction_obj = correction(m_out, metadata) 311 | if correction_obj.is_valid: 312 | correction_obj.apply_corrections() 313 | return m_out 314 | 315 | if "AHSI" in M[0]: 316 | # Stack GF5(GF5B, ZY1E)-VN, SW 317 | # sort in [VN, SW] order 318 | m_out_list.sort(reverse=True) 319 | m_out = re.sub("_SW.geotiff|_VN.geotiff|_SW.tif|_VN.tif", ".tif", m_out_list[0]) 320 | stack(m_out_list, m_out) 321 | metadata = re.sub("_SW.geotiff|_VN.geotiff", ".xml", m_in) 322 | m_out = ato_cor(m_out, metadata) if level == "Surface_Reflectance" else m_out 323 | elif "GF5B_VIMI" in M[0]: 324 | # Stack GF5B-B1-6, B7-12 325 | # sort in [B1-6, B7-12] order 326 | m_out_list.sort(reverse=False) 327 | m_out = re.sub("_B1_B6.tif[f]", ".tiff", m_out_list[0]) 328 | stack(m_out_list, m_out) 329 | metadata = re.sub(".tiff", ".xml", m_in) 330 | m_out = ato_cor(m_out, metadata) if level == "Surface_Reflectance" else m_out 331 | elif "GF6_WFV" in M[0]: 332 | m_out = re.sub("-[0-9].tiff", ".tiff", join(outputDirectory, M[0])) 333 | mosaic(m_out_list, m_out) 334 | [os.remove(m) for m in m_out_list] 335 | metadata = re.sub("-[0-9].tiff", ".xml", m_in) 336 | m_out = ato_cor(m_out, metadata) if level == "Surface_Reflectance" else m_out 337 | else: 338 | for m_out in m_out_list: 339 | metadata = re.sub(".tiff", ".xml", join(dataPath, os.path.basename(m_out))) 340 | m_out = ato_cor(m_out, metadata) if level == "Surface_Reflectance" else m_out 341 | 342 | # 先大气校正再融合的顺序通常更为推荐，因为这样可以确保影像在融合前已经反映了地物的真实信息，并且可以保持影像的光谱一致性。 343 | fusion_list = [] 344 | if pansharpen and len(P) > 0: 345 | for p in P: 346 | logger.info("处理全色数据中...") 347 | try: 348 | p_in = join(dataPath, p) 349 | p_out = join(outputDirectory, p) 350 | rpc_ortho(p_in, dem, p_out) 351 | p_out = ato_cor(p_out, metadata) if level == "Surface_Reflectance" else p_out 352 | fusion = p_out.replace("PAN", "FUS") 353 | # Trying to find corresponding spectral dataset 354 | m = glob(p_out.rsplit("PAN", 1)[0] + "M*" + p_out.rsplit("PAN", 1)[1])[0] 355 | pansharpening_otb(m, p_out, fusion) 356 | fusion_list.append(fusion) 357 | # os.remove(m) 358 | # os.remove(p_out) 359 | except Exception: 360 | logger.error("Error occurred: \n", traceback.format_exc()) 361 | pass 362 | 363 | # Build pyramid, we only build for the final raster 364 | if pyramid: 365 | if "GF6_WFV" in M[0] or "GF5B_VIMI" in M[0] or "AHSI" in M[0]: 366 | build_pyramid(m_out) 367 | elif pansharpen and len(fusion_list) > 0: 368 | [build_pyramid(fusion) for fusion in fusion_list] 369 | else: 370 | [build_pyramid(m_out) for m_out in m_out_list] 371 | 372 | 373 | def get_rasters_name(dataPath): 374 | all_file = next(os.walk(dataPath))[2] 375 | # M is list of spectral rasters' filenames, P is list of pancromatic rasters' filenames 376 | M = list(filter(lambda x: re.match('.*MUX.*.tiff|.*MSS.*.tiff|.*WFV.*.tiff|GF4_PMS.*.tiff|GF5_AHSI.*geotiff|GF5B_AHSI.*_VN.tif.*|GF5B_AHSI.*_SW.tif.*|GF5B_VIMI.*[0-9].tif.*|ZY1[E-F]_AHSI.*_VN.tif.*|ZY1[E-F]_AHSI.*_SW.tif.*|ZY1F_IRS_NSR.*.tif.*|CB04A_WPM.*MSS.tiff|HJ2[A-B]_CCD.*.tiff', x) != None, all_file)) 377 | P = list(filter(lambda x: re.match('.*PAN.*.tiff', x) != None, all_file)) 378 | assert len(M) > 0, "未找到数据！仅支持如下卫星型号：[CB04A_WPM, GF1_PMS, GF1_WFV, GF1B_PMS, GF1C_PMS, GF1D_PMS, GF2_PMS, GF4_PMI, GF5_AHSI, GF5B_AHSI, GF5B_VIMI, GF6_PMS, GF6_WFV, GF7_BWD, GF7_DLC, HJ2A_CCD, HJ2B_CCD, ZY1E_VNIC, ZY1F_AHSI, ZY303_TMS]" 379 | return M, P 380 | 381 | 382 | if __name__ == "__main__": 383 | # 获取编译后exe或py文本的根目录 384 | if getattr(sys, 'frozen', False): 385 | appPath = os.path.dirname(sys.executable) 386 | else: 387 | appPath = os.path.dirname(__file__) 388 | 389 | parser = argparse.ArgumentParser() 390 | parser.add_argument('--outputDirectory', dest='outputDirectory', 391 | help='Folder to store preprocessed files', 392 | type=str, default=None) 393 | parser.add_argument('--dem', dest='dem', 394 | help='path for dem', 395 | type=str, default=join(appPath, 'data', 'GMTED2km.tif')) 396 | parser.add_argument('--otbPath', dest='otbPath', 397 | help='path for Orfeo Toolbox', 398 | type=str, default=glob(join(appPath, 'OTB-*-Win64'))[0]) 399 | parser.add_argument('--level', dest='level', 400 | help='Processing level, options: DN, Surface_Reflectance', 401 | type=str, default='DN') 402 | parser.add_argument('--pansharpen', dest='pansharpen', 403 | help='Whether to perform pansharpening', 404 | action='store_true', default=False) 405 | parser.add_argument('--pyramid', dest='pyramid', 406 | help='Whether to build pyramid', 407 | action='store_true', default=False) 408 | parser.add_argument('--cache', dest='cache', 409 | help='Set GDAL raster block cache size, may speed up processing with higher percentage, default is 5% of usable physical RAM', 410 | type=str, default='5%') 411 | parser.add_argument('--files', dest='files', 412 | help='List of files to process', 413 | nargs='+', default=None) 414 | args = parser.parse_args() 415 | 416 | if args.pansharpen: 417 | # 确保路径为全英文 418 | for f in args.files: 419 | assert f.isascii(), "镶嵌前，请确保输入数据的路径不包含中文！" 420 | 421 | otbPath = args.otbPath 422 | os.environ['GDAL_DATA'] = join(otbPath, r"share\data") 423 | os.environ['PROJ_LIB'] = join(otbPath, r"share\proj") 424 | os.environ['GDAL_DRIVER_PATH'] = 'disable' 425 | os.environ["GDAL_CACHEMAX"] = args.cache 426 | main(args.outputDirectory, args.dem, args.level, args.pansharpen, args.pyramid, args.files) 427 | -------------------------------------------------------------------------------- /package.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "gaofen-batch", 3 | "version": "0.1.0", 4 | "description": "Gaofen-Batch, streamlines raster preprocessing of China-made satellite. Powered by GDAL and Electron.", 5 | "main": "main.js", 6 | "scripts": { 7 | "pack": "electron-builder --dir", 8 | "dist": "electron-builder" 9 | }, 10 | "build":{ 11 | "appId": "https://github.com/GenghisYoung233/Gaofen-Batch", 12 | "productName": "Gaofen Batch", 13 | "win": { 14 | "target": "portable", 15 | "icon": "./assets/app_icon.ico" 16 | } 17 | }, 18 | "author": "Genghisyang233", 19 | "devDependencies": { 20 | "electron": "^26.0.0", 21 | "electron-builder": "^24.6.3" 22 | }, 23 | "dependencies": { 24 | "electron-log": "^4.4.8", 25 | "iconv-lite": "^0.6.3" 26 | } 27 | } 28 | --------------------------------------------------------------------------------