Remotely sensed land cover data can be a tremendous resource to land use decision makers, yet there is often a disconnect between the worlds of remote sensing and local government. The Connecticut’s Changing Landscape project is focused on bridging this gap. The project analyzes changes to the state’s landscape using Landsat-derived 30-m land cover and cross-correlation analysis.
Long-term anthropogenic land use and land cover changes (LULCCs) are regarded as an important component of past global change. The past 300 years have witnessed dramatic changes in LULCC in China, and this has resulted in the large-scale conversion of natural vegetation to agricultural landscapes.
Land cover is one of key indicators for modeling ecological, environmental, and climatic processes, which changes frequently due to natural factors and anthropogenic activities. The changes demand various samples for updating land cover maps, although in reality the number of samples is always insufficient.
Understanding the effects of socio-ecological shocks on land use/land cover (LULC) change is essential for developing land management strategies and for reducing adverse environmental pressures. Our study examines the impacts of the armed conflict in Syria, which began in mid-2011, and the related social and economic crisis on LULC between 2010 and 2018.
In fast-developing regions, like Southeast-Asia, monitoring urban areas presents a challenge given the lack of publicly available data. This is an issue that precludes the nuances of a city’s growth and undermines the way land-use is considered with respect to planning. The issue of data availability is very much present in the small nation of Brunei.
Landscape provides many services for human wellbeing through its mosaic of ecosystems. Although different landscape spatial structures limit some access to these services for local residents, their demand for landscape benefits creates a crucial component in landscape planning.
Land as an essential resource is becoming increasingly scarce due to population growth. In the case of the Kenyan coast, population pressure causes land cover changes in the Arabuko Sokoke Forest, which is an important habitat for endangered species.
This paper presents a new approach for rapidly assessing the extent of land use and land cover (LULC) areas in Mato Grosso state, Brazil. The novel idea is the use of an annual time series of fraction images derived from the linear spectral mixing model (LSMM) instead of original bands.
Landscape research involves a large number of scientific disciplines. Different disciplinary and scale approaches have led to the creation of numerous land use/land cover databases with different classification nomenclature.
Measuring, monitoring, and managing biodiversity across agricultural regions depends on methods that can combine high-resolution mapping of landscape patterns with local biodiversity observations. This study explores the potential to monitor biodiversity in agricultural landscapes by linking high-resolution remote sensing with passive acoustic monitoring.
