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[Dynamic change and prediction of vegetation cover in Shenzhen, China from 2000 to 2018]. / 2000­2018年深圳市植被覆盖动态变化与预测.
Wu, Bing-Lun; Sun, Hua; Shi, Jun-Nan; Zhang, Yu-Tian; Shi, Ling-Jie.
Afiliación
  • Wu BL; Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China.
  • Sun H; Hunan Province Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security, Changsha 410004, China.
  • Shi JN; Key Laboratory of National Forestry & Grassland Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China.
  • Zhang YT; Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China.
  • Shi LJ; Hunan Province Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security, Changsha 410004, China.
Ying Yong Sheng Tai Xue Bao ; 31(11): 3777-3785, 2020 Nov.
Article en Zh | MEDLINE | ID: mdl-33300728
ABSTRACT
With landsat-series multi-temporal image data, percentage of vegetation cover (PVC) was estimated by pixel dichotomy. The linear regression analysis and center of gravity migration methods were used to explore the characteristics of the spatiotemporal changes of vegetation cover in Shenzhen from 2000 to 2018. The CA-Markov model was combined to predict future land cover in Shenzhen. The results showed that the PVC in Shenzhen demonstrated obvious regional differentiation characteristics from 2000 to 2018. The eastern region occupied larger proportion than the wes-tern part, while the southern region was larger than the north part. This feature exhibited good consistency with regional topographic effect. The spatial migration characteristic of the center of gravity of PVC was from northwest to southeast, and then from southeast to northwest, with a migration rate of 551.2 m·a-1. This process was closely related to urbanization in Shenzhen. The PVC in Shen-zhen tended to be generally improved from 2000-2018, with a improvement rate of 0.005·a-1. The percentage of significantly improved and degraded PVC area was 30.8% and 12.8%, respectively. The CA-Markov method was used to predict the land cover/use pattern of Shenzhen in 2024 under two scenarios, theoretical scenario and natural scenario. There was no significant difference in proportion of the area of the land cover/use patterns obtained by the two kinds of prediction method, with the difference threshold being 0-1.2%. Compared with the data before 2018, the proportion of arbor forests and arable land converted into construction land in Shenzhen would be significantly reduced in 2024, whereas the contradiction between supply and demand would be still tense.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 2_ODS3 Problema de salud: 2_quimicos_contaminacion Asunto principal: Urbanización / Conservación de los Recursos Naturales Tipo de estudio: Prognostic_studies / Risk_factors_studies País/Región como asunto: Asia Idioma: Zh Revista: Ying Yong Sheng Tai Xue Bao Asunto de la revista: SAUDE AMBIENTAL Año: 2020 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 2_ODS3 Problema de salud: 2_quimicos_contaminacion Asunto principal: Urbanización / Conservación de los Recursos Naturales Tipo de estudio: Prognostic_studies / Risk_factors_studies País/Región como asunto: Asia Idioma: Zh Revista: Ying Yong Sheng Tai Xue Bao Asunto de la revista: SAUDE AMBIENTAL Año: 2020 Tipo del documento: Article País de afiliación: China
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