Analysis and Prediction of Land Use Changes Related to Invasive Species and Major Driving Forces in the State of Connecticut

نویسندگان

  • Wenjie Wang
  • Chuanrong Zhang
  • Jenica M. Allen
  • Weidong Li
  • Mark A. Boyer
  • Kathleen Segerson
  • John A. Silander
چکیده

Land use and land cover (LULC) patterns play an important role in the establishment and spread of invasive plants. Understanding LULC changes is useful for early detection and management of land-use change to reduce the spread of invasive species. The primary objective of this study is to analyze and predict LULC changes in Connecticut. LULC maps for 1996, 2001 and 2006 were selected to analyze past land cover changes, and then potential LULC distribution in 2018 was predicted using the Multi-Layer Perceptron Markov Chain (MLP_MC) model. This study shows that the total area of forest has been decreasing, mainly caused by urban development and other human activity in Connecticut. The model predicts that the study area will lose 5535 ha of deciduous forest and gain 3502 ha of built-up area from 2006 to 2018. Moreover, forests near built-up areas and agriculture lands appear to be more vulnerable to conversion. Changes in LULC may result in subtle spatial shifts in invasion risk by an abundant invasive shrub, Japanese barberry (Berberis thunbergii). The gain of developed areas at the landscape scale was most closely linked to increased future invasion risk. Our findings suggest that the forest conversion needs to be controlled and well managed to help mitigate future invasion risk.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Identification of driving forces, uncertainties and future scenarios of Iran's environment

Background and Objective: Global macro trends on the one hand, and domestic trends and effective factors on the other, have put the future of the Iran's environment in a state of uncertainty with concern. In a complex and unpredictable environment, the use of scenario thinking (based on identifying and detecting future drivers and uncertainties) can provide tangible and comprehensible images of...

متن کامل

Detection and prediction of land use/ land cover changes using Markov chain model and Cellular Automata (CA-Markov), (Case study: Darab plain)

unprincipled changes in land use are major challenges for many countries and different regions of the world, which in turn have devastating effects on natural resources, Therefore, the study of land-use changes has a fundamental and important role for environmental studies. The purpose of this study is to detect and predicting of land use/ land cover (LULC) changes in Darab plain through the Ma...

متن کامل

Monitoring and Prediction of Land Use/Cover Changes in Shadegan International Wetland, Iran

Quantifying land use/land cover changes is essential to monitor and assess the ecological consequences of human disturbances. Ecological condition and water quality of wetlands are highly related to the landscape characteristics, including land use/land cover (LULC) types and their fractions in the upland and the surrounding landscape. The changing characteristics of LULC in Shadegan Internatio...

متن کامل

Application of Artificial Neural Network in Landscape Change Process in Gharesou Watershed, Golestan Province

Land use change is certainly the most important factor that affects the conservation of natural ecosystems, resulting the conversion of natural lands such as forests and pastures into agricultural, industrial and urban areas. Despite numerous studies investigating landscape patterns due to land use change, the driving forces of landscape change has been less studied in Iran. In this study, Arti...

متن کامل

Land use changes analysis and prediction using remote sensing and QGIS MOLUSCE Plugin in the Siahkal County

Quantifying land use change dynamics is critical in tackling environmental and socio-economic challenges such as climate change in recent years. This study takes Siahkal County in Guilan Province as the research subject and analyzes the land use changes in two different years: 2000 and 2021, and predicts the change in 2031. We carried out land use change analysis using LANDSAT-7 ETM+ and LANDSA...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016