The mean shift (MS) algorithm is based on a statistical approach to the clustering problem. Specifically, the method is a variant of density estimation. We revisit in this article the MS paradigm and its use for clustering of remotely sensed images. Specifically, we investigate further the classification accuracy of remotely sensed images as a function of various MS parameters, such as the variant used, kernel type, dimensionality, kernel bandwidth, etc.

The Soil and Water Assessment Tool (SWAT) has been used for assessing the impact of land cover and land management changes on water resources for a wide range of scales and environmental conditions across the globe. However, originally designed for temperate regions, SWAT must be critically examined for its appropriate use in tropical watersheds. One major concern is the simulation of perennial tropical vegetation due to the absence of dormancy.

Most of China's 24–28 primate species are threatened with extinction. Habitat reduction and fragmentation are perhaps the greatest threats. We used published data from a conservation genetics study of 5 endangered primates in China (Rhinopithecus roxellana, R. bieti, R. brelichi, Trachypithecus francoisi, and T. leucocephalus); distribution data on these species; and the distribution, area, and location of protected areas to inform conservation strategies for these primates. All 5 species were separated into subpopulations with unique genetic components.

Urbanization is a global phenomenon with still unknown consequences for vegetation dynamics of urban ecosystems, especially in subtropical areas of developing countries. In this paper we analyze the vegetation productivity trend associated to urban densification and urban expansion during the last decade, in twelve cities of northern Argentina. We used time series analysis of MODIS-NDVI images to reconstruct the phenological patterns to retrieve a productivity trend under three spatial classes of urban dynamics: (1) urban, (2) expansion and (3) periphery.

The geospatial information is significant for many socio-technical activities like urban planning, the prediction of natural hazards, the monitoring of land use, weather forecasting, cadastral surveys etc. It is possible to acquire geospatial information from a distance using remote sensing technologies, but remotely sensed images don’t have semantics without a previous recognition. The classification of geospatial information is expensive and time consuming process. The paper describes the automatic land cover recognition method, which is based on min-cut/max-flow segmentation.

During recent decades, forests have expanded into new areas throughout the whole of Norway. The processes explained as causing the forest expansion have focused mainly on climate or land use changes. To enable a spatially explicit separation of the effects following these two main drivers behind forest expansion, the authors set out to model the potential for natural forest regeneration following land use abandonment, given the present climatic conditions.

Effectively identifying soil properties in relation to non-point source (NPS) phosphorus pollution is important for NPS pollution management. Previous studies have focused on particulate P loads in relation to agricultural non-point source pollution. In areas undergoing rapid urbanization, dissolved P loads may be important with respect to conditions of surface infiltration and rainfall runoff. The present study developed an integrated model for the analysis of both dissolved P and particulate P loads, applied to the Meiliang Bay watershed, Taihu Lake, China.

Remote sensing applications in water resources management are becoming an essential asset in all different levels of integrated water rational use. Due to remote sensing data availability and different acquisition sensors of satellite images, a wide variability of benchmarks could be conducted under the same theme. Rainwater harvesting is the branch of science where the rainwater is the main target to improve groundwater recharge, stratocumulus clouds are the main source of rain in arid regions.

The role of predation in ecological systems has received considerable attention in scientific literature and is one of the most important, yet least understood aspects of carnivore ecology. Knowledge of factors that improve our ability to detect predation events using animal telemetry data could be used to develop strategies to reduce time and resources required to obtain reliable kill estimates.

This article emphasizes landslide susceptibility mapping along Ghat road of Kolli hills, Tamil Nadu, India, using frequency ratio, relative effect and fuzzy gamma operator models with the help of remote sensing data and GIS technique. The purpose of the study is to generate, compare and validate landslide susceptibility zones. Landslide inventory was done with data collected from the State Highways department.

Habitat loss and climate change pose a double jeopardy for many threatened taxa, making the identification of optimal habitat for the future a conservation priority. Using a case study of the endangered Bornean orang‐utan, we identify environmental refuges by integrating bioclimatic models with projected deforestation and oil‐palm agriculture suitability from the 1950s to 2080s. We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s.

The green vegetation fraction (GVF) and surface albedo are important land surface parameters often used for validation of climate and land surface models that are influenced largely by environmental gradients and human activities. In this study, fine resolution GVF and albedo values derived from Landsat Thematic Mapper/Enhanced Thematic Mapper Plus images from 1990 to 2000 were used to examine the relationship of both GVF and albedo values to the spatial gradients of parameters related to dramatic urbanization in the Greater Guangzhou metropolitan area, Guangdong Province, in South China.