Remote sensing

Hydrologic Modeling of Land Processes in Puerto Rico Using Remotely Sensed Data

Hydrologic Modeling of Land Processes in Puerto Rico Using Remotely Sensed Data
Cruise, J. F.; Miller, R. L.
Journal of the American Water Resources Association, vol. 30, Issue 3, p.419-428

Abstract: 
An integrated, multi-disciplinary effort to model land processes affecting Mayaguez Bay in western Puerto Rico is described. A modeling strategy was developed to take advantage of remotely sensed data. The spatial, interannual, and seasonal variability of sediment discharges to the bay were also evaluated. Classified images of remotely sensed data revealed the spatial distribution and quantities of land use classes in the region and aided in the discretization of the watershed into homogeneous regions. These regions were modeled using a geomorphic modeling technique based upon spatially averaged parameters. Simulation results from the modeling effort compared favorably with observations at two locations within the watershed. Results showed that runoff and sediment loads from the area exhibit a marked seasonal trend and that deforested areas located in the foothill regions of the watershed contribute a disproportionate share of the sediment load to the bay. In years when rainfall distributions are uniformly distributed over the area, the sediment yields may be up to 100 percent higher than years when the rainfall is concentrated in the heavily forested mountainous regions.

Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching

E.H. Helmer and B. Ruefenacht 2005. Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching.. Photogrammetric Engineering & Remote Sensing Vol. 71, No. 9, September 2005, :1079-1089.

Abstract: 
Cloud-free optical satellite imagery simplifies remote sensing, but land-cover phenology limits existing solutions to persistent cloudiness to compositing temporally resolute, spatially coarser imagery. Here, a new strategy for developing cloud-free imagery at finer resolution permits simple automatic change detection. The strategy uses regression trees to predict pixel values underneath clouds and cloud shadows in reference scenes from other scene dates. It then applies improved histogram matching to adjacent scenes. In the study area, the islands of Puerto Rico, Vieques, and Culebra, Landsat image mosaics resulting from this strategy permit accurate detection of land development with only spectral data and maximum likelihood classification. Between about 1991 and 2000, urban/built-up lands increased by 7.2 percent in Puerto Rico and 49 percent in Vieques and Culebra. The regression tree modeling and histogram matching require no manual interpretation. Consequently, they can support large volume processing to distribute cloud-free imagery for simple change detections with common classifiers.

Modelling the impact of recent land-cover changes on the stream flows in northeastern Puerto Rico

Wu W, Hall CAS, Scatena FN. Modelling the impact of recent
land-cover changes on the stream flows in northeastern Puerto
Rico. Hydrol Process 2007; 21: 2944-2956.

Abstract: 
We investigated the influence of recent and future land-cover changes on stream flow of a watershed northeastern Puerto Rico using hydrological modeling and simulation analysis. Monthly and average annual stream flows were compared between an agricultural period (1973–1980) and an urbanized/reforested period (1988–1995) using the revised Generalized Watershed Loading Function model. Our validated results show that a smaller proportion of rainfall became stream flows in the urbanized/forested period compared with the agricultural period, apparently because of reforestation. Sensitivity analysis of the model showed that evapotranspiration, precipitation, and curve number were the most significant factors influencing stream flow. Simulations of projected land-cover scenarios indicate that annual stream flows would increase by 9Ð6% in a total urbanization scenario, decrease by 3Ð6% in a total reforestation scenario, and decrease by 1Ð1% if both reforestation and urbanization continue at their current rates to 2020. An imposed hurricane event that was similar in scale to the largest recent event on the three land-cover scenarios would increase the daily stream flow by 62Ð1%, 68Ð4% and 67Ð1% respectively. Owing to the environmental setting of eastern Puerto Rico, where sea breezes caused by temperature differences between land surface and the ocean dominate the local climate, we suggest that managing local land-cover changes can have important consequences for water management. Copyright  2007 John Wiley & Sons, Ltd.

Spatial modelling of evapotranspiration in the Luquillo experimental forest of Puerto Rico using remotely-sensed data

Wu, Wei; Hall, Charles A.S.; Scatena, Frederick N.; Quackenbush, Lindi J. 2006. Spatial modelling of evapotranspiration in the Luquillo experimental forest of Puerto Rico using remotely-sensed data.. Journal of Hydrology 328, 733- 752.

Abstract: 
Actual evapotranspiration (aET) and related processes in tropical forests can explain 70% of the lateral global energy transport through latent heat, and therefore are very important in the redistribution of water on the Earth’s surface [Mauser, M., Scha¨dlich, S., 1998. Modelling the spatial distribution of evapotranspiration on different scales using remote sensing data. J. Hydrol. 212–213, 250–267]. Unfortunately, there are few spatial studies of these processes in tropical forests. This research integrates one Landsat Thematic Mapper (TM) image and three Moderate Resolution Imaging Spectroradiometer (MODIS) images with a hydrological model [Granger, R.J., Gray, D.M., 1989. Evaporation from natural nonsaturated surfaces. J. Hydrol. 111, 21–29] to estimate the spatial pattern of aET over the Luquillo Experimental Forest (LEF) – a tropical forest in northeastern Puerto Rico – for the month of January, the only month that these remotely sensed images were acquired. The derived aETs ranged from 0 to 7.22 mm/day with a mean of 3.08 ± 1.35 mm/day which were comparable to other estimates. Simulated aET was highest in the low elevation forest and decreased progressively toward higher elevations. Because of differences in solar radiation at different elevations, aspects and topographic positions, aET tended to be higher on south slopes and along ridges than on north slopes and in valleys. In addition, the Bowen ratio (the ratio of sensible heat to latent heat) varied across different vegetation types and increased with elevation, thus reflecting differences in the distribution of net solar radiation incident on the earth’s surface. Over a day, the highest simulated aET occurred at around noon. We also applied this model to simulate the average monthly aET over an entire year based on the cloud patterns derived from at least two MODIS images for each month. The highest simulated aET occurred in February and March and the lowest in May. These observations are consistent with long term data. The simulated values were compared with field measurements of the sap flow velocity of trees at different elevations and in different forest types. These comparisons had good agreement in the low elevation forest but only moderate agreement in the elfin forest at high elevations. ª 2006 Elsevier B.V. All rights reserved.
Syndicate content