近10 a全球遥感科学研究的时空动态分析

张红月; 李宜展; 陈思明; 黄铭瑞; 孙玉

doi:10.11873/j.issn.1004-0323.2022.1.0045

閬ユ劅鎶�鏈笌搴旂敤鈥衡�� 2022, Vol. 37 鈥衡�� Issue (1): 45-60.DOI: 10.11873/j.issn.1004-0323.2022.1.0045

鈥� 闈掍績浼氬崄鍛ㄥ勾涓撴爮鈥� 涓婁竴绡� 涓嬩竴绡�

杩�10 a鍏ㄧ悆閬ユ劅绉戝鐮旂┒鐨勬椂绌哄姩鎬佸垎鏋�

寮犵孩鏈�¹(),鏉庡疁灞�²,闄堟�濇槑¹,榛勯摥鐟�^3,⁴,瀛欑帀⁵()

^1.闂芥睙瀛﹂櫌鍦扮悊涓庢捣娲嬪闄紝绂忓缓绂忓窞 350108
^2.涓浗绉戝闄㈡枃鐚儏鎶ヤ腑蹇冿紝鍖椾含 100190
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鏀剁鏃ユ湡:2021-08-24 淇洖鏃ユ湡:2021-12-24 鍑虹増鏃ユ湡:2022-02-20 鍙戝竷鏃ユ湡:2022-04-08
閫氳浣滆��: 瀛欑帀
浣滆�呯畝浠�:寮犵孩鏈堬紙1987-锛夛紝濂筹紝灞变笢鑱婂煄浜猴紝璁插笀锛屼富瑕佷粠浜嬬┖闂寸瀛﹁閲忓強GIS寤烘ā鐮旂┒銆侲?mail:zhanghy@mju.edu.cn
鍩洪噾璧勫姪:
绂忓缓鐪佽嚜鐒剁瀛﹀熀閲戦」鐩�(2021J011022);鍥藉鑷劧绉戝鍩洪噾椤圭洰(41801393);绂忓缓鐪佹暀鑲插巺椤圭洰锛堢鎶�绫伙級(JAT190600);闂芥睙瀛﹂櫌绉戠爺鍚姩椤圭洰(MJY19023)

Spatio-temporal Pattern Analysis of Global Remote Sensing Research in Recent 10 Years

Hongyue Zhang¹(),Yizhan Li²,Siming Chen¹,Mingrui Huang^3,⁴,Yu Sun⁵()

^1.Geography and Ocean College锛孧injiang University锛孎uzhou 350108锛孋hina
^2.National Science Library锛孋hinese Academy of Sciences锛孊eijing 100190锛孋hina
^3.Key Laboratory of Digital Earth Science锛孉erospace Information Research Institute锛孋hinese Academy of Sciences锛孊eijing 100094锛孋hina
^4.University of Chinese Academy of Sciences锛孊eijing 100094锛孋hina
^5.Key Laboratory of Data Mining and Sharing of Ministration of Education锛孎uzhou University锛孎uzhou 350108锛孋hina

Received:2021-08-24 Revised:2021-12-24 Online:2022-02-20 Published:2022-04-08
Contact: Yu Sun

鎽樿/Abstract

鎽樿锛�

浠�2010~2019骞碬eb of Science 鏍稿績鍚堥泦鏁版嵁搴撲腑鑷劧绉戝寮曟枃绱㈠紩鍜岀ぞ浼氱瀛﹀紩鏂囩储寮曟敹褰曠殑閬ユ劅绉戝鐩稿叧鏂囩尞涓烘暟鎹簮锛岄噰鐢ㄧ粺璁¤閲忋�佺煡璇嗗浘璋变互鍙婅川蹇冭縼绉绘ā鍨嬬瓑鏂规硶锛屽杩�10 a閬ユ劅绉戝鍙戞枃鐨勬椂绌哄姩鎬併�佸绉戝垎甯冦�佷富棰樼儹鐐硅繘琛屾繁鍏ュ垎鏋愩�傜粨鏋滆〃鏄庯細鍏ㄧ悆閬ユ劅绉戝璁烘枃鐨勪綔鑰呴泦涓簬娆ф床銆佸寳缇庝互鍙婁簹娲蹭笢閮ㄥ湴鍖猴紝10 a闂撮仴鎰熺瀛︾爺绌剁殑鍙戞枃閲忚川蹇冨憟鐜版樉钁楃殑涓滅Щ鐗瑰緛锛屽奖鍝嶅姏璐ㄥ績鏁翠綋鍛堢幇涓滅Щ瓒嬪娍锛屼絾鍙戞枃閲忚川蹇冭縼绉昏窛绂昏繙澶т簬褰卞搷鍔涜川蹇冭縼绉昏窛绂汇�傚寘鎷腑鍥姐�佺編鍥姐�佸痉鍥姐�佹剰澶у埄鍜岃嫳鍥藉湪鍐呯殑5涓珮浜у浗瀹堕仴鎰熺瀛﹁鏂囩殑涓昏浜ゅ弶瀛︾宸紓鏄庢樉锛岀編鍥藉湪13涓富瑕佸绉戜腑鍙戞枃琛ㄧ幇鍧囪　锛屼腑鍥藉湪澶╂枃涓庡ぉ浣撶墿鐞嗐�佺敓鎬佸绛変氦鍙夊绉戝彂鏂囬噺鍋忎綆銆�5涓珮浜у浗瀹剁殑涓婚鐑偣涔熷瓨鍦ㄥ樊鍒紝涓浗瀛﹁�呭叧娉ㄥ叏鐞冨彉鍖栧強闈掕棌楂樺師绛夋柟闈㈢殑鐮旂┒锛岀編鍥藉鑰呯患鍚堥仴鎰熸妧鏈鐏槦銆佹湀鐞冪瓑寮�灞曚簡鎺㈢储銆傝繎10 a鏉ユ皵鍊欏彉鍖栥�佸煄甯傚寲銆佸彉鍖栫洃娴嬬瓑鐨勭爺绌跺彈鍒板叧娉ㄣ�傛湭鏉ュ彲浠ヨ繘涓�姝ョ患鍚堝婧愰仴鎰熸暟鎹紑灞曚氦鍙夊绉戠爺绌讹紝閬ユ劅澶ф暟鎹粨鍚堜汉宸ユ櫤鑳界畻娉曟帹杩涙櫤鎱у湴鐞冪殑寤鸿銆�

鍏抽敭璇�: 閬ユ劅, 鏂囩尞璁￠噺, 璐ㄥ績妯″瀷, 鍏辫瘝鍒嗘瀽, 鍏抽敭璇嶉泦缇�

Abstract:

Scientific publications between 2010 and 2019 with remote sensing backgrounds that are indexed by the Science Citation Index and Social Science Citation Index are retrieved from the Web of Science core collection as data sources. With techniques including statistical analysis锛� co-occurrence matrix and spatial centroid models锛� the spatial-temporal dynamics锛� subject distribution and topic hot spots of global remote sensing publications are analyzed. The results show that the authors of global remote sensing research are concentrated in Europe锛� North America and eastern Asia. During the last decade锛� the gravity center of both the output and influence of remote sensing publications has a prominent eastward shift. However锛� the gravity center of publication output show a significantly larger shift distance than the gravity center of publication influence. The top five productive countries including China锛� the United States锛� Germany锛� Italy and the United Kingdom show clear differences in the main interdisciplinary studies. The United States has balanced performance in all the 13 main interdisciplinary categories. China锛� however锛� has relatively low output in many interdisciplinary subjects such as astronomy and astrophysics锛� as well as ecology. There are also differences in the thematic hot spots for the five productive countries. Chinese scholars are concerned about global change and the Qinghai-Tibet Plateau锛� while American scholars have comprehensively explored the Mars and the Moon with remote sensing technology. In recent years锛� research on climate change锛� urbanization and change detection has attracted broad attention. Research on interdisciplinary application can be carried out comprehensively with multi-source remote sensing data. Combining remote sensing big data with artificial intelligence algorithms to promote the construction of a smart earth.

Key words: Remote Sensing, Bibliometric Analysis, Centroid Model, Co-word Analysis, Keywords Cluster

涓浘鍒嗙被鍙�:

TP79

寮犵孩鏈�,鏉庡疁灞�,闄堟�濇槑,榛勯摥鐟�,瀛欑帀. 杩�10 a鍏ㄧ悆閬ユ劅绉戝鐮旂┒鐨勬椂绌哄姩鎬佸垎鏋怺J]. 閬ユ劅鎶�鏈笌搴旂敤, 2022, 37(1): 45-60.

Hongyue Zhang,Yizhan Li,Siming Chen,Mingrui Huang,Yu Sun. Spatio-temporal Pattern Analysis of Global Remote Sensing Research in Recent 10 Years[J]. Remote Sensing Technology and Application, 2022, 37(1): 45-60.

鍙傝�冩枃鐚�

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Spatio-temporal Pattern Analysis of Global Remote Sensing Research in Recent 10 Years

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