CICEET Progress Report for the period 2/1/03 through 8/31/03

Project Title: Remotely Sensed Indices of Land Use Intensity for Watershed-level Monitoring
Principal Investigator(s): Richard G. Lathrop Jr., Robert A. Zampella

Accomplishments
Scheduled Tasks:
Conduct statistical analysis of land use intensity indicators vs. water quality parameters for a selected sample of subwatershed in the Mullica River basin study area.

Progress on Tasks
Our objective is to investigate the utility of satellite remotely sensing techniques to map indicators of urban land use intensity: impervious surface and the managed lawn. Using medium scale imagery (e.g. Landsat Thematic Mapper), individual pixels generally represent a mixture of urban land covers. Thus we are concentrating our efforts at developing un-mixing techniques that estimate subpixel proportions of the land covers of interest. Appropriate statistical techniques will be used to examine if the relationship previously documented by the Pinelands Commission between land use alteration and water quality degradation is improved by the new remotely sensed estimates of impervious surface.

Using the results of the SOM model described previously, we have estimated land use intensity for 25 subwatersheds in the Mullica Rivers basin study area. R. Zampella, project co-investigator, has conducted the statistical analysis comparing the subwatershed land uses components vs. water quality data. We also compared our TM derived estimates with the NJDEP land use and impervious surface estimates. Model results were then compared with an additional 20 basins (data not used in model fitting) as further validation. 4 different models were compared:

LU (3 categories) - NJDEP LU/LC: Development, Upland Agriculture, Wetland Agriculture

LU & IS (3 categories) - NJDEP LU/LC: Impervious Surface, Upland Agriculture, Wetland Agriculture

TMIS & L & AG (4 categories) - TM derived Impervious surface, Lawn, NJDEP LU/LC Upland Agriculture, Wetland Agriculture

TMIS+L & AG (3 categories) - TM derived Impervious surface and Lawn combined, NJDEP LU/LC Upland Agriculture, Wetland Agriculture

The statistical analysis shows that the Landsat TM derived results had slightly lower coefficient of determination (R²) than using the NJDEP derived land use or impervious surface data. For example, in the pH model, the NJDEP LU model had an R² of 0.87, the NJDEP IS/AG model had an R² of 0.83 and the TM derived IS, Lawn and NJDEP AG models had R² of 0.79 (see Table 1). The model results for the other chemical constituents showed similar patterns. There was no statistically significant difference between the different models when compared against the validation data (see Table 2). There were no issues related to the residuals of the models (Table 3).

In other words, the Landsat TM derived estimates of land use intensity provided similar explanatory power in understanding nonpoint source pollution levels in various coastal watershed basins as compared to traditional means of measuring human urban land use intensity (e.g., aerial photo interpreted urban area or impervious surface). Thus we think that the remote sensing methods we have developed will find useful application in monitoring upland land use and estimating attendant effects on coastal waters.

Difficulties Encountered
None.

Anticipated Success in Meeting Project Objectives in Scheduled Project Period
We are presently wrapping up the project. Sangbum Lee has finished writing his PhD thesis and successfully defended it in late April, 2003. We presently have two manuscripts in final stages for submission for peer-reviewed publication and have 2 more in preparation.

Preliminary Data
We are finalizing the impervious surface cover maps for the developed areas of the Mullica River basin using Landsat Thematic imagery and based on the three different methodologies. We are preparing to use the SOM methodology to undertake a statewide mapping of impervious surface for a contract to the New Jersey Department of Environmental Protection.

Tasks and activities for the next reporting period

Tasks for the next reporting period
Prepare manuscripts for peer-reviewed publication. Prepare other publications/web material to communicate project results.

Present results to state level project cooperators for possible implementation.

Work plan to accomplish tasks
S. Lee, the Graduate Assistant assigned to this project, J. Bognar, Project Coordinator, R. Zampella, project Co-I, and R. Lathrop, the PI will continue to work on the above tasks.

Concerns or difficulties
None.

Expenditures
The project funding has been spent and the account closed out.