{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T17:03:40Z","timestamp":1775322220115,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,9]],"date-time":"2022-06-09T00:00:00Z","timestamp":1654732800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"National Key Research and Development Program of China","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"National Key Research and Development Program of China","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"National Key Research and Development Program of China","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"National Key Research and Development Program of China","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"National Key Research and Development Program of China","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"National Key Research and Development Program of China","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"National Key Research and Development Program of China","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"National Key Research and Development Program of China","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"National Key Research and Development Program of China","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"National Key Research and Development Program of China","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"National Key Research and Development Program of China","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"National Key Research and Development Program of China","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"National Key Research and Development Program of China","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"National Key Research and Development Program of China","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]},{"name":"National Natural Science Foundation of China","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"National Natural Science Foundation of China","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"National Natural Science Foundation of China","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"National Natural Science Foundation of China","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"National Natural Science Foundation of China","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"National Natural Science Foundation of China","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"National Natural Science Foundation of China","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"National Natural Science Foundation of China","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"National Natural Science Foundation of China","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"National Natural Science Foundation of China","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"National Natural Science Foundation of China","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"National Natural Science Foundation of China","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"National Natural Science Foundation of China","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"National Natural Science Foundation of China","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"National Natural Science Foundation of China","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"Science and Technology Major Project of Guangzhou","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"The Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Fund","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"Second Tibetan Plateau Scientific Expedition and Research Program (STEP)","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"Major Scientific and Technological Projects of Gansu Province","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"Natural Science Foundation of Gansu Province","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"Construction Project of Gansu Technological Innovation Center","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"Geohazard prevention project of Gansu Province","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["2019YFB1703600"],"award-info":[{"award-number":["2019YFB1703600"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["62076102"],"award-info":[{"award-number":["62076102"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["42130709"],"award-info":[{"award-number":["42130709"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["42077230"],"award-info":[{"award-number":["42077230"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["U1813203"],"award-info":[{"award-number":["U1813203"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["U1801262"],"award-info":[{"award-number":["U1801262"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["202007030006"],"award-info":[{"award-number":["202007030006"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["2019016"],"award-info":[{"award-number":["2019016"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["2021QZKK0201"],"award-info":[{"award-number":["2021QZKK0201"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["21JR7RA442"],"award-info":[{"award-number":["21JR7RA442"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["18JR2JA006"],"award-info":[{"award-number":["18JR2JA006"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["CNPC-B-FS2021012"],"award-info":[{"award-number":["CNPC-B-FS2021012"]}]},{"name":"Foundation for Distinguished Young Talents in Higher Education of Guangdong, China","award":["2018KQNCX324"],"award-info":[{"award-number":["2018KQNCX324"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Zhouqu County is located at the intersection of two active structural belts in the east of the Qinghai-Tibet Plateau, which is a rare, high-incidence area of landslides, debris flow, and earthquakes on a global scale. The complex regional geological background, the fragile ecological environment, and the significant tectonic activities have caused great difficulties for the dynamic susceptibility assessment and prediction of landslides in the study area. Specifically, Zhouqu is a typical alpine-canyon region in geomorphology; currently there is still a lack of a landslide susceptibility assessment study for this particular type of area. Therefore, the development of landslide susceptibility mapping (LSM) in this area is of great significance for quickly grasping the regional landslide situation and formulating disaster reduction strategies. In this article, we propose a graph-represented learning algorithm named GBLS within a broad framework in order to better extract the spatially relevant characteristics of the geographical data and to quickly obtain the change pattern of landslide susceptibility according to the frequent variation (increase or decrease) of the data. Based on the broad structure, we construct a group of graph feature nodes through graph-represented learning to make better use of geometric correlation of data to upgrade the precision. The proposed method maintains the efficiency and effectiveness due to its broad structure, and even better, it is able to take advantage of incremental data to complete fast learning methodology without repeated calculation, thus avoiding time waste and massive computation consumption. Empirical results verify the excellent performance with high efficiency and generalization of GBLS on the 407 landslides in the study area inventoried by remote sensing interpretation and field investigation. Then, the landslide susceptibility map is drawn to visualize the landslide susceptibility assessment according to the result of GBLS with the highest AUC (0.982). The four most influential factors were ranked out as rainfall, NDVI, aspect, and Terrain Ruggedness Index. Our research provides a selection criterion that can be referenced for future research where GBLS is of great significance in LSM of the alpine-canyon region. It plays an important role in demonstrating and popularizing the research in the same type of landform environment. The LSM would help the government better prevent and confine the risk of landslide hazards in the alpine-canyon region of Zhouqu.<\/jats:p>","DOI":"10.3390\/rs14122773","type":"journal-article","created":{"date-parts":[[2022,6,12]],"date-time":"2022-06-12T23:55:24Z","timestamp":1655078124000},"page":"2773","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Graph-Represented Broad Learning System for Landslide Susceptibility Mapping in Alpine-Canyon Region"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7766-9808","authenticated-orcid":false,"given":"Lili","family":"Xu","sequence":"first","affiliation":[{"name":"School of Applied Mathematics, Beijing Normal University, Zhuhai 519087, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5451-7230","authenticated-orcid":false,"given":"C. L. Philip","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou 510641, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3234-6367","authenticated-orcid":false,"given":"Feng","family":"Qing","sequence":"additional","affiliation":[{"name":"Institute of Public Safety Research\/Department of Engineering Physics, Tsinghua University, Beijing 100084, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3102-6193","authenticated-orcid":false,"given":"Xingmin","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Earth Sciences, Lanzhou University, Lanzhou 730000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1180-8868","authenticated-orcid":false,"given":"Yan","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Earth Sciences, Lanzhou University, Lanzhou 730000, China"}]},{"given":"Tianjun","family":"Qi","sequence":"additional","affiliation":[{"name":"College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China"}]},{"given":"Tianyao","family":"Miao","sequence":"additional","affiliation":[{"name":"China Re Catastrophe Risk Management Company LYD, Beijing 100052, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1007\/s10346-018-0954-8","article-title":"Investigating slow-moving landslides in the Zhouqu region of China using InSAR time series","volume":"15","author":"Zhang","year":"2018","journal-title":"Landslides"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1007\/s12665-017-6640-7","article-title":"A comparative study of landslide susceptibility mapping using weight of evidence, logistic regression and support vector machine and evaluated by SBAS-InSAR monitoring: Zhouqu to Wudu segment in Bailong River Basin, China","volume":"76","author":"Xie","year":"2017","journal-title":"Environ. Earth Sci."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Meng, X., Qi, T., Chen, G., Li, Y., Yue, D., and Qing, F. (2021). Modeling the Spatial Distribution of Debris Flows and Analysis of the Controlling Factors: A Machine Learning Approach. Remote Sens., 13.","DOI":"10.3390\/rs13234813"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.geomorph.2012.11.009","article-title":"Scale amplification of natural debris flows caused by cascading landslide dam failures","volume":"182","author":"Cui","year":"2013","journal-title":"Geomorphology"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/s10346-009-0148-5","article-title":"Landslide hazards triggered by the 2008 Wenchuan earthquake, Sichuan, China","volume":"6","author":"Yin","year":"2009","journal-title":"Landslides"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1144\/qjegh2013-071","article-title":"Comparison and combination of different models for optimal landslide susceptibility zonation","volume":"47","author":"Chen","year":"2014","journal-title":"Q. J. Eng. Geol. Hydrogeol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.catena.2012.06.012","article-title":"Combined landslide susceptibility mapping after Wenchuan earthquake at the Zhouqu segment in the Bailongjiang Basin, China","volume":"99","author":"Bai","year":"2012","journal-title":"Catena"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Marsala, V., Galli, A., Paglia, G., and Miccadei, E. (2019). Landslide susceptibility assessment of Mauritius Island (Indian ocean). Geosciences, 9.","DOI":"10.3390\/geosciences9120493"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.enggeo.2008.03.014","article-title":"Guidelines for landslide susceptibility, hazard and risk zoning for land-use planning","volume":"102","author":"Fell","year":"2008","journal-title":"Eng. Geol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1919","DOI":"10.1007\/s11629-016-4220-z","article-title":"Landslide initiation and runout susceptibility modeling in the context of hill cutting and rapid urbanization: A combined approach of weights of evidence and spatial multi-criteria","volume":"14","author":"Rahman","year":"2017","journal-title":"J. Mt. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"107125","DOI":"10.1016\/j.geomorph.2020.107125","article-title":"AI-based identification of low-frequency debris flow catchments in the Bailong River basin, China","volume":"359","author":"Zhao","year":"2020","journal-title":"Geomorphology"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"106456","DOI":"10.1016\/j.enggeo.2021.106456","article-title":"AI-based rainfall prediction model for debris flows","volume":"296","author":"Zhao","year":"2022","journal-title":"Eng. Geol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Qing, F., Zhao, Y., Meng, X., Su, X., Qi, T., and Yue, D. (2020). Application of Machine Learning to Debris Flow Susceptibility Mapping along the China\u2013Pakistan Karakoram Highway. Remote Sens., 12.","DOI":"10.3390\/rs12182933"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/S0169-555X(99)00078-1","article-title":"Landslide hazard evaluation: A review of current techniques and their application in a multi-scale study, Central Italy","volume":"31","author":"Guzzetti","year":"1999","journal-title":"Geomorphology"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s100640050066","article-title":"Landslide hazard assessment: Summary review and new perspectives","volume":"58","author":"Aleotti","year":"1999","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.earscirev.2018.03.001","article-title":"A review of statistically-based landslide susceptibility models","volume":"180","author":"Reichenbach","year":"2018","journal-title":"Earth-Sci. Rev."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.cageo.2017.11.019","article-title":"Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China","volume":"112","author":"Zhou","year":"2018","journal-title":"Comput. Geosci."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Qi, T., Zhao, Y., Meng, X., Shi, W., Qing, F., Chen, G., Zhang, Y., Yue, D., and Guo, F. (2021). Distribution Modeling and Factor Correlation Analysis of Landslides in the Large Fault Zone of the Western Qinling Mountains: A Machine Learning Algorithm. Remote Sens., 13.","DOI":"10.3390\/rs13244990"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s10346-013-0391-7","article-title":"Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression","volume":"11","author":"Kavzoglu","year":"2014","journal-title":"Landslides"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.geomorph.2009.09.025","article-title":"GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the Three Gorges area, China","volume":"115","author":"Bai","year":"2010","journal-title":"Geomorphology"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/S0169-555X(01)00087-3","article-title":"Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong","volume":"42","author":"Dai","year":"2002","journal-title":"Geomorphology"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"104833","DOI":"10.1016\/j.catena.2020.104833","article-title":"GIS-based landslide susceptibility assessment using optimized hybrid machine learning methods","volume":"196","author":"Chen","year":"2021","journal-title":"Catena"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1006\/jcss.1997.1504","article-title":"A decision-theoretic generalization of on-line learning and an application to boosting","volume":"55","author":"Freund","year":"1997","journal-title":"J. Comput. Syst. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Kadavi, P.R., Lee, C.W., and Lee, S. (2018). Application of ensemble-based machine learning models to landslide susceptibility mapping. Remote Sens., 10.","DOI":"10.3390\/rs10081252"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"LeCun, Y.A., Bottou, L., Orr, G.B., and M\u00fcller, K.R. (2012). Efficient BackProp BT-Neural Networks: Tricks of the Trade. Neural Networks: Tricks of the Trade, Springer.","DOI":"10.1007\/978-3-642-35289-8_3"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","article-title":"Extreme learning machine: Theory and applications","volume":"70","author":"Huang","year":"2006","journal-title":"Neurocomputing"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"104851","DOI":"10.1016\/j.catena.2020.104851","article-title":"Landslide susceptibility mapping using multiscale sampling strategy and convolutional neural network: A case study in Jiuzhaigou region","volume":"195","author":"Yi","year":"2020","journal-title":"Catena"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1007\/s11069-021-04844-0","article-title":"A hybrid framework integrating physical model and convolutional neural network for regional landslide susceptibility mapping","volume":"109","author":"Wei","year":"2021","journal-title":"Nat. Hazards"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"104445","DOI":"10.1016\/j.cageo.2020.104445","article-title":"Comparative study of landslide susceptibility mapping with different recurrent neural networks","volume":"138","author":"Wang","year":"2020","journal-title":"Comput. Geosci."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zhu, L., Huang, L., Fan, L., Huang, J., Huang, F., Chen, J., Zhang, Z., and Wang, Y. (2020). Landslide susceptibility prediction modeling based on remote sensing and a novel deep learning algorithm of a cascade-parallel recurrent neural network. Sensors, 20.","DOI":"10.3390\/s20061576"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"104451","DOI":"10.1016\/j.catena.2019.104451","article-title":"A spatially explicit deep learning neural network model for the prediction of landslide susceptibility","volume":"188","author":"Jaafari","year":"2020","journal-title":"Catena"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1007\/s10346-019-01274-9","article-title":"A deep learning algorithm using a fully connected sparse autoencoder neural network for landslide susceptibility prediction","volume":"17","author":"Huang","year":"2020","journal-title":"Landslides"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Al-Najjar, H.A., Pradhan, B., Sarkar, R., Beydoun, G., and Alamri, A. (2021). A New Integrated Approach for Landslide Data Balancing and Spatial Prediction Based on Generative Adversarial Networks (GAN). Remote Sens., 13.","DOI":"10.3390\/rs13194011"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wang, Z., Goetz, J., and Brenning, A. (2022). Transfer learning for landslide susceptibility modelling using domain adaptation and case-based reasoning. Geosci. Model Dev. Discuss., 1\u201330.","DOI":"10.5194\/gmd-2022-119"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1109\/TNNLS.2017.2716952","article-title":"Broad learning system: An effective and efficient incremental learning system without the need for deep architecture","volume":"29","author":"Chen","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1109\/TNNLS.2018.2866622","article-title":"Universal approximation capability of broad learning system and its structural variations","volume":"30","author":"Chen","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"56267","DOI":"10.1109\/ACCESS.2020.2982214","article-title":"Sparse Bayesian broad learning system for probabilistic estimation of prediction","volume":"8","author":"Xu","year":"2020","journal-title":"IEEE Access"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.ins.2022.03.037","article-title":"Graph-based sparse bayesian broad learning system for semi-supervised learning","volume":"597","author":"Xu","year":"2022","journal-title":"Inf. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/0925-2312(94)90053-1","article-title":"Learning and generalization characteristics of the random vector functional-link net","volume":"6","author":"Pao","year":"1994","journal-title":"Neurocomputing"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1429","DOI":"10.1007\/s10346-020-01384-9","article-title":"Mechanism of the 2019 Yahuokou landslide reactivation in Gansu, China and its causes","volume":"17","author":"Zhang","year":"2020","journal-title":"Landslides"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.1007\/s10346-015-0631-0","article-title":"A rapid method to identify the potential of debris flow development induced by rainfall in the catchments of the Wenchuan earthquake area","volume":"13","author":"Zhou","year":"2016","journal-title":"Landslides"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"104587","DOI":"10.1016\/j.envsoft.2019.104587","article-title":"An ANN-based emulation modelling framework for flood inundation modelling: Application, challenges and future directions","volume":"124","author":"Chu","year":"2020","journal-title":"Environ. Model. Softw."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/01490410701295962","article-title":"Multiscale terrain analysis of multibeam bathymetry data for habitat mapping on the continental slope","volume":"30","author":"Wilson","year":"2007","journal-title":"Mar. Geod."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1080\/02626667909491834","article-title":"A physically based, variable contributing area model of basin hydrology\/Un mod\u00e8le \u00e0 base physique de zone d\u2019appel variable de l\u2019hydrologie du bassin versant","volume":"24","author":"Beven","year":"1979","journal-title":"Hydrol. Sci. J."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1002\/hyp.3360050103","article-title":"Digital terrain modelling: A review of hydrological, geomorphological, and biological applications","volume":"5","author":"Moore","year":"1991","journal-title":"Hydrol. Process."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1871","DOI":"10.1007\/s10346-019-01195-7","article-title":"Respective influence of geomorphologic and climate conditions on debris-flow occurrence in the Northern French Alps","volume":"16","author":"Jomelli","year":"2019","journal-title":"Landslides"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s11104-012-1572-1","article-title":"Influence of plant root system morphology and architectural traits on soil shear resistance","volume":"377","author":"Ghestem","year":"2014","journal-title":"Plant Soil"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2663","DOI":"10.1007\/s11069-021-04559-2","article-title":"Debris flows in the Lushan earthquake area: Formation characteristics, rainfall conditions, and evolutionary tendency","volume":"106","author":"Guo","year":"2021","journal-title":"Nat. Hazards"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1080\/00401706.1970.10488634","article-title":"Ridge regression: Biased estimation for nonorthogonal problems","volume":"12","author":"Hoerl","year":"1970","journal-title":"Technometrics"},{"key":"ref_52","unstructured":"Belkin, M., and Niyogi, P. (2001, January 3\u20138). Laplacian eigenmaps and spectral techniques for embedding and clustering. Proceedings of the Nips, Whistler, BC, Canada."},{"key":"ref_53","unstructured":"Chung, F.R., and Graham, F.C. (1997). Spectral Graph Theory, American Mathematical Soc."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1109\/TKDE.2015.2499200","article-title":"Incremental Semi-Supervised Clustering Ensemble for High Dimensional Data Clustering","volume":"28","author":"Yu","year":"2016","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2392","DOI":"10.1109\/TNNLS.2017.2677093","article-title":"Uncertain Data Clustering in Distributed Peer-to-Peer Networks","volume":"29","author":"Zhou","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_56","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","year":"2006","journal-title":"J. Mach. Learn. Res."},{"key":"ref_57","first-page":"263","article-title":"Distribution-free multiple comparisons","volume":"Volume 18","author":"Nemenyi","year":"1962","journal-title":"Biometrics"},{"key":"ref_58","first-page":"415","article-title":"A note on the distribution of range in samples of n","volume":"25","author":"McKay","year":"1933","journal-title":"Biometrika"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.catena.2019.03.017","article-title":"Uncertainties of prediction accuracy in shallow landslide modeling: Sample size and raster resolution","volume":"178","author":"Shirzadi","year":"2019","journal-title":"Catena"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2815","DOI":"10.5194\/nhess-13-2815-2013","article-title":"Landslide susceptibility estimation by random forests technique: Sensitivity and scaling issues","volume":"13","author":"Catani","year":"2013","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1023\/A:1012487302797","article-title":"Gene selection for cancer classification using support vector machines","volume":"46","author":"Guyon","year":"2002","journal-title":"Mach. Learn."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/12\/2773\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:27:03Z","timestamp":1760138823000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/12\/2773"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,9]]},"references-count":61,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2022,6]]}},"alternative-id":["rs14122773"],"URL":"https:\/\/doi.org\/10.3390\/rs14122773","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,9]]}}}