We present the first comprehensive multi-temporal analysis of land-cover change for California across its major ecological regions and primary land-cover types. Recently completed satellite-based estimates of land-cover and land-use change information for large portions of the United States allow for consistent measurement and comparison across heterogeneous landscapes. Landsat data were employed within a pure-panel stratified one-stage cluster sample to estimate and characterize land-cover change for 1973-2000. Results indicate anthropogenic and natural disturbances, such as forest cutting and fire, were the dominant changes, followed by large fluctuations between agriculture and rangelands. Contrary to common perception, agriculture remained relatively stable over the 27-year period with an estimated loss of 1.0% of agricultural land. The largest net declines occurred in the grasslands/shrubs class at 5,131 km2 and forest class at 4,722 km2. Developed lands increased by 37.6%, composing an estimated 4.2% of the state's land cover by 2000.
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http://dx.doi.org/10.1007/s10661-010-1385-8 | DOI Listing |
Huan Jing Ke Xue
January 2025
School of Water Conservancy and Environment, University of Jinan, Jinan 250022, China.
Exploring the spatial-temporal evolution characteristics of land use carbon emissions and their influencing factors is of great significance for the optimization of land use structure, the formulation of emission reduction policies, and the development of a regional low-carbon economy. Based on land cover and energy consumption data, a multi-parameter land use carbon emission accounting system was constructed to calculate land use carbon emissions in Shandong Province. Moreover, the spatial-temporal evolution and influencing factors of land use carbon emissions were analyzed based on the Gini coefficient and logarithmic mean Divisia index.
View Article and Find Full Text PDFSci Total Environ
December 2024
Center for Climate Change Adaptation, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan. Electronic address:
Understanding multifaceted climate change risks and their interconnections is essential for effective adaptation strategies, which require comprehensive assessments of both climatic impact variations and social-environmental exposures/vulnerabilities. This study examines these interconnections and creates multitier delineations of future climate risks across Japan by overlaying homogeneous impact zones (HIZs) with exposure-vulnerability complexes (EVCs). We delineated eight EVC regions, each exhibiting similar patterns of exposure and vulnerability, via multivariate clustering and similarity search on the basis of future population and land cover/use data.
View Article and Find Full Text PDFHeliyon
December 2024
Department of Geology, University of Dhaka, Dhaka, 1000, Bangladesh.
Bhasan Char has undergone noteworthy transformations in its geographical characteristics since its emergence in 2003. Driven by sediment transported by the Ganges-Brahmaputra-Meghna river system, the island has gradually transitioned from a stretched-out configuration to a more rounded shape primarily due to continuous accretion, while erosion has been minimal since 2012. Currently, the island is being prepared to accommodate over 1 million Forcefully Displaced Myanmar Nationals (FDMN) refugees.
View Article and Find Full Text PDFEnviron Monit Assess
December 2024
Indian Institute of Technology, Madras, Chennai, Tamil Nadu, India.
Rapid urbanization has altered land use and land cover to accommodate the growing population. This shift towards urbanization has resulted in the UHI effect, where the inner urban core is notably warmer than its surroundings. Existing research on UHI has primarily focused on major cities at the regional scale, leaving a gap in addressing the effect of extreme UHI zones within a city.
View Article and Find Full Text PDFEnviron Monit Assess
December 2024
Instituto de Geografía, Universidad Nacional Autónoma de México, Ciudad Universitaria, C.P. 04510, Coyoacán, Mexico City, Mexico.
This study aims to evaluate the changes in forest cover from 1994 to 2015, identify the key drivers of forest recovery, and predict future trends. Using high-resolution remote sensing data, we mapped forest canopy density into detailed categories (closed > 50%, open 10-50%, and deforested < 10%) to differentiate processes like degradation, deforestation, densification, reforestation, and afforestation. A multinomial logistic regression was used to explore the relationship between the forest processes and socioeconomic, proximity, planning, and policy potential drivers.
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