A New Method for Building-Level Population Estimation by Integrating LiDAR, Nighttime Light, and POI Data

<div class="floats-full-page floats-full-page-other"><h2>Table 3</h2><div class="floats-full-page-caption"><div>The description and value of random forest model parameters.</div></div><div class="floats-full-page-content"><table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr /></td></tr><tr class="thead"><td class="align_left">Parameter name</td><td class="align_center">Description</td><td class="align_center">Optimal value</td></tr><tr><td class="thead-hr" colspan="3"><hr /></td></tr><tr><td class="align_left"><span style="width: 6.6501ptpx;"><svg height="6.1673pt" id="M14" style="vertical-align:-0.2063904pt" version="1.1" viewbox="-0.0498162 -5.96091 6.6501 6.1673" width="6.6501pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M495 86L479 114C446 82 419 66 409 66C401 66 401 72 406 97C420 166 436 231 453 297C489 435 454 448 428 448C406 448 384 439 354 422C305 394 222 327 161 247H159L183 345C200 415 194 448 173 448C143 448 82 410 23 351L38 325C64 349 95 371 105 371C111 371 116 365 109 336L25 -4L31 -12C50 -4 77 3 107 9C119 69 132 122 145 168C197 254 321 381 370 381C387 381 393 374 378 305L329 95C309 17 320 -12 345 -12C372 -12 430 19 495 86Z"></path></g></svg><i>_estimators</i></span></td><td class="align_center">Number of trees</td><td class="align_center">120</td></tr><tr><td class="align_left"><i>Max_features</i></td><td class="align_center">Maximum number of features that can be selected at each node</td><td class="align_center">20</td></tr><tr><td class="align_left"><i>Max_depth</i></td><td class="align_center">Maximum depth of the tree</td><td class="align_center">16</td></tr><tr><td class="align_left"><i>Min_samples_split</i></td><td class="align_center">Minimum number of samples required to split an internal node</td><td class="align_center">20</td></tr><tr><td class="align_left"><i>Min_samples_leaf</i></td><td class="align_center">Minimum number of samples required to be at a leaf node</td><td class="align_center">1</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr" /></td></tr></table></td></tr></table></div></div>

Table 3 | A New Method for Building-Level Population Estimation by Integrating LiDAR, Nighttime Light, and POI Data

title

Table 3: A New Method for Building-Level Population Estimation by Integrating LiDAR, Nighttime Light, and POI Data

description

Table 3

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<p>The <em>Journal of Remote Sensing</em>, an Open Access journal published in association with AIR-CAS, promotes the theory, science, and technology of remote sensing, as well as interdisciplinary research within earth and information science.</p>


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<p>The <em>Journal of Remote Sensing’s</em> editorial board is led by Yirong Wu (Aerospace Information Research Institute, Chinese Academy of Sciences)&nbsp;and is comprised of experts who have made significant and well recognized contributions to the field.</p>


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