Mapping land use/land cover (LULC) changes at regional scales is essential for a wide range of applications, including landslide, erosion, land planning, global warming etc. LULC alterations (based especially on human activities), negatively effect the patterns of climate, the patterns of natural hazard and socio-economic dynamics in global and local scale. In this study, LULC changes are inves...

Air pollution has been a major topic of debate in highly developed areas over the last quarter century and therefore mitigation of poor air quality for health and environmental reasons has been a primary focus for local governments. Particulate matter, especially finer particles (PM2.5), is detrimental to human health, and urban expansion is thought to be a contributing factor to enhanced level...

Rapid urbanization with intense land use and land cover (LULC) change and explosive population growth has a great impact on water quality. The relationship between LULC characteristics and water quality provides important information for non-point sources (NPS) pollution management. In this study, we first quantified the spatial-temporal patterns of five water quality variables in four watershe...

The paper investigates using PlanetScope satellite images together with LiDAR data for automation of land use/cover (LULC) mapping and 3D vegetation characteristics in the aspect monitoring secondary forest succession areas. study was performed tested area Biskupice district (South Poland), where a occurs on post-agricultural lands. research parcels overgrowing process identified. It verified w...

This study aimed at evaluating the synergistic use of Sentinel-1 and Sentinel-2 data combined with the Support Vector Machines (SVMs) machine learning classifier for mapping land use and land cover (LULC) with emphasis on wetlands. In this context, the added value of spectral information derived from the Principal Component Analysis (PCA), Minimum Noise Fraction (MNF) and Grey Level Co-occurren...

In this article, we present a novel hybrid framework, which integrates spatial-temporal semantic segmentation with postclassification relearning, for multitemporal land use and cover (LULC) classification based on very high resolution (VHR) satellite imagery. To efficiently obtain optimal LULC maps, the framework utilizes model to harness temporal dependency extracting high-level features. addi...

The main purpose of this paper is to assess the land use and cover (LULC) changes for thirty years, from 1990–2020, in Dong Thap Muoi, a flooded area Mekong River Delta Vietnam using Google Earth Engine random forest algorithm. specific purposes are: (1) determine LULC classes (2) compute analyze magnitude rate these classes. For above purposes, 128 Landsat images, topographic maps, status cada...

Land use/land cover (LULC) changes in response to natural factors and human activities constitute a pressing issue for the conservation of Protected Areas urban–rural landscapes. The present study investigated LULC Jajrud Area (JPA) Kavdeh Wildlife Refuge (KWR) Tehran province, Iran, between 1989 2019. To inform ecological measures JPA KWR, were identified monitored using Landsat imagery from I...

The diurnal temperature range (DTR) at weather observation stations that make up the U.S. Historical Climatology Network was evaluated with respect to the predominant land uselland cover associated with the stations within three radii intervals ( 100, 1000, and 10 000 m) of the stations. Those stations that were associated with predominantly rural land uselland cover (LULC) usually displayed th...

Malacca River water quality is affected due to rapid urbanization development. The present study applied LULC changes towards water quality detection in Malacca River. The method uses LULC, PCA, CCA, HCA, NHCA, and ANOVA. PCA confirmed DS, EC, salinity, turbidity, TSS, DO, BOD, COD, As, Hg, Zn, Fe, E. coli, and total coliform. CCA confirmed 14 variables into two variates; first variate involves...