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Displaying 566 - 570 of 661Monitoring changes in land use land cover of Yamuna riverbed in Delhi: a multi-temporal analysis
Impact of anthropogenic activities has led to significant changes in riverbeds over a period of time. The objective of the study was to monitor the land use land cover (LULC) of Yamuna riverbed in Delhi and to assess the changes due to natural and anthropogenic activities. The maximum likelihood classification was carried out by using March 1977, April 1999, April 2002 and February 2009 imageries. An overall accuracy of LULC classification of 2009 imagery was around 88.6% based on ground truth data.
Using MERIS fused images for land-cover mapping and vegetation status assessment in heterogeneous landscapes
In this paper we evaluate the potential of ENVISAT–Medium Resolution Imaging Spectrometer (MERIS) fused images for land-cover mapping and vegetation status assessment in heterogeneous landscapes. A series of MERIS fused images (15 spectral bands; 25 m pixel size) is created using the linear mixing model and a Landsat Thematic Mapper (TM) image acquired over the Netherlands. First, the fused images are classified to produce a map of the eight main land-cover types of the Netherlands. Subsequently, the maps are validated using the Dutch land-cover/land-use database as a reference.
Kudzu Control and Impact on Monetary Returns to Non-Industrial Private Forest Landowners in Mississippi
Kudzu—Pueraria montana var. lobata (Willd.)—was initially planted in the southern United States and subsequently spread throughout the countryside following changes in land use. Kudzu covers more than 2.8 million ha which prevents uses such as timber production and establishment of carbon plantations. Using data collected on sites in Mississippi, this study examines the after-tax monetary trade-offs of controlling kudzu using different herbicide regimes. The results suggest that the most cost-effective way to control kudzu patches is to apply Escort XP using an aerial applicator.
Farm and Forest in Central Africa: Toward an Integrated Rural Development Strategy
The authors explore three problems confronting scientists working in the central African humid forest zone and show their interconnectedness in the context of the sociopolitical history of the area. These problems emerge from different domains at different spatial scales: agricultural development, natural resource management, and landscape scale conservation. Land and livelihoods are severely constrained in central Africa. Agriculture is rarely remunerative: prices are low, technology limited, land rights contested, and labor scarce.
Applying support vector regression to water quality modelling by remote sensing data
This article applies a nonlinear machine learning method, support vector regression (SVR), to construct empirical models retrieving water quality variables using remote sensing images. Based on in situ measurements and high-resolution multispectral SPOT-5 (Satellite Pour l'Observation de la Terre) data, a fittest nonlinear function between input and output was obtained from this method, and SVR model parameters were selected automatically using a genetic algorithm (GA).