In remote sensing studies of land surface temperatures (LST), thematic land-use and land-cover (LULC) data are frequently employed for simple correlation analyses between LULC types and their thermal signatures. Development of quantitative surface descriptors could improve our capabilities for modeling urban thermal landscapes and advance urban climate research. This study developed an analytic...

Moderate Resolution Imaging Spectroradiometer (MODIS) data forms the basis for numerous land use and land cover (LULC) mapping and analysis frameworks at regional scale. Compared to other satellite sensors, the spatial, temporal and spectral specifications of MODIS are considered as highly suitable for LULC classifications which support many different aspects of social, environmental and develo...

This study adopted a differential land-use/landcover (LULC) analysis to evaluate dam-triggered land– atmosphere interactions for a number of LULC scenarios. Two specific questions were addressed: (1) can damtriggered LULC heterogeneities modify surface and energy budget, which, in turn, change regional convergence and precipitation patterns? (2) How extensive is the modification in surface mois...

Net primary productivity (NPP) can indicate vegetation ecosystem services ability and reflect variation response to climate change and human activities. This study applied MODIS-1 km NPP products to investigate the NPP variation from 2001 to 2006, a fast urban expansion and adjustment period in Guangzhou, China, and quantify the impacts of weather and land use/land cover (LULC) changes, respect...

Various subpixel mapping (SPM) methods have been proposed as downscaling techniques to reduce uncertainty in classifying mixed pixels. Such methods can provide category maps of a higher spatial resolution than the original input images. The aim of this study was to explore and validate the potential of SPM as an alternative method for obtaining land use/land cover (LULC) maps of regions where h...

[1] In recent decades, the RockyMountainWest has been one of the fastest growing regions in the United States. Headwater streams in mountain environments may be particularly susceptible to nitrogen enrichment from residential and resort development. We utilized stream water chemistry from six synoptic sampling campaigns combined with land use/land cover (LULC) and terrain analysis in geostatist...

Developing a complex region detection algorithm that is aware of its contextual relations with several classes necessitates statistical frameworks that can encode contextual relations rather than simple rule-based applications or heuristics. In this study, we present a conditional random field (CRF) model that is generated over the results of a robust local discriminative classifier in order to...

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...

land use may be regarded as one of the most important factors affecting theenvironment with respect to human activities. so far, destroying the rangelands andchanging them into the waste lands and poor rangelands has been proposed as the mostsignificant variations of land use done by human beings. this paper has been conducted toevaluate the variations of vegetation percentage and land uses in ...

the growing population and increasing socio-economic necessities creates a pressure on land use/land cover. nowadays, land use change detection using remote sensing data provides quantitative and timely information for management and evaluation of natural resources. this study investigates the land use changes in part of hableh rood watershed of iran using landsat 7 and 8 (sensor etm+ and oli) ...