Detecting the effect of disturbance on habitat diversity and land cover change in a post-mining area using GIS

2008 ◽  
Vol 87 (1) ◽  
pp. 22-32 ◽  
Author(s):  
Effah Kwabena Antwi ◽  
Rene Krawczynski ◽  
Gerhard Wiegleb
2018 ◽  
Vol 73 ◽  
pp. 04021
Author(s):  
Meike Erthalia ◽  
Supriatna ◽  
Astrid Damayanti

Tin mining is one of the land uses that causes physical damage to the land. Degraded land due to the mining activity requires a conservation. Conservation of post-tin mining land in Perimping Sub Watershed consists of reclamation and revegetation by planting kinds of fast-growing plants and cover crops. As land management, conservation is conducted to establish the diversity of land cover and to recover the land quality to be more productive for the local people. This study aimed to analyze the land cover change in land conservation of post-tin mining area. Moreover, also to identify the condition of post-tin mining land which has been conserved. Land cover map of 2011, 2014, and 2017 were produced from Google Earth imagery. Field validation was conducted to determine the existence of cover types on conservation land and interviews were conducted to find other impact of post-tin mining land conservation for local people. The result shows that land cover change in post-tin mining land conservation area over 6 years dominated by escalation of land cover such as mining, plantations. Monitoring of land cover change in conservation area is important to measure the effectivity of land conservation in post-tin mining area.


2019 ◽  
Vol 11 (3) ◽  
pp. 301 ◽  
Author(s):  
Cangjiao Wang ◽  
Shaogang Lei ◽  
Andrew J. Elmore ◽  
Duo Jia ◽  
Shouguo Mu

Simultaneously considering the spatial and temporal processes is essential for land cover simulation models. A cellular automaton (CA) usually simulates the spatial conversion of land cover through post-classification comparisons between the beginning and the end of the training period. However, such an approach does not consider the temporal evolution of land cover. As a result, a CA model fails to explain the realistic land cover change. This paper proposes a temporal-dimension-extension CA (TDE-CA) by integrating the temporal evolution of land cover with a CA. In the TDE-CA, the Breaks for Additive Season and Trend (BFAST) monitor algorithm was employed in the temporal evolution simulation module (TESM) to simulate the gradual evolution of land cover, and an optimized random forest CA (optimized RF-CA) was used to simulate the spatial conversion driven by many spatial variables. Subsequently, the Ensemble Kalman Filter (EnKF) was employed to integrate the TESM with the optimized RF-CA. The TDE-CA was then tested in the land cover simulation of Shendong mining area during the period 2005–2015. The TDE-CA was compared with a Null model, with its sub-models, and with the traditional CA models, including the Logistic-CA and the MLP-CA (Multilayer Perceptron CA) models. The results show that the TDE-CA is superior to the Null model. Furthermore, the overall accuracy and the Kappa coefficient of the TDE-CA were 79.84% and 71.61%, respectively; compared with the TESM and the optimized RF-CA, the values showed 17.14% and 4.48% improvements in the overall accuracies and 0.2167 and 0.0512 improvements in the Kappa coefficients, respectively. When compared with the Logistic-CA and the MLP-CA, we measured 8.41% and 8.25% improvements in the overall accuracies and 0.0985 and 0.0964 improvements in the Kappa coefficients. These experiments indicate that the TDE-CA not only provides an effective model for the spatiotemporal dynamical simulation of land cover, but also enhances the development of the existing simulation theory.


2011 ◽  
Vol 13 (5) ◽  
pp. 695-700
Author(s):  
Zhihua TANG ◽  
Xianlong ZHU ◽  
Cheng LI

2017 ◽  
Author(s):  
Austin Counts ◽  
◽  
Andrew Phillips ◽  
Andrew Phillips ◽  
Sydney Young ◽  
...  

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