Using Remotely Sensed Imagery to Document How Land Use Drives Turbidity of Playa Waters in Texas
نویسندگان
چکیده
Sedimentation (primarily from human land use) is a major threat to runoff-fed wetlands of the Great Plains of North America (playas), but it is unknown how many playas are turbid, how prevalence of turbidity has changed over time, and how turbidity is related to surrounding land use. We used remotely sensed imagery to assess sedimentation in the waters of over 7700 playa basins in Texas on four dates during a 29-year span: 25 July 1986 (a regionally wet time), 3 May 2014 (during drought), 4 June 2014 (after the drought was broken), and 25 July 2015 (one year post-drought). Even on the wettest date examined, 64% of playa basins did not hold water. Turbidity varied over time, was already present in over half of the basins examined in 1986, and prevalence of turbidity was not simply proportional to overall wet playa abundance. There was an increase in total and irrigated cropland in our focal region and a statistically significant association between sedimentation and land use within 100 m of a playa: clear playas were associated with more urban development and pasture/grassland, and turbid playas were surrounded mostly by cropland.
منابع مشابه
Spatiotemporal analysis of remotely sensed Landsat time series data for monitoring 32 years of urbanization
The world is witnessing a dramatic shift of settlement pattern from rural to urban population, particularly in developing countries. The rapid Addis Ababa urbanization reflects this global phenomenon and the subsequent socio-economic and environmental impacts, are causing massive public uproar and political instability. The objective of this study was to use remotely sensed Landsat data to iden...
متن کاملDevelopment of an Automatic Land Use Extraction System in Urban Areas using VHR Aerial Imagery and GIS Vector Data
Lack of detailed land use (LU) information and efficient data collection methods have made the modeling of urban systems difficult. This study aims to develop a novel hierarchical rule-based LU extraction framework using geographic vector and remotely sensed (RS) data, in order to extract detailed subzonal LU information, residential LU in this study. The LU extraction system is developed to ex...
متن کاملA Comparative Study of SVM and RF Methods for Classification of Alteration Zones Using Remotely Sensed Data
Identification and mapping of the significant alterations are the main objectives of the exploration geochemical surveys. The field study is time-consuming and costly to produce the classified maps. Therefore, the processing of remotely sensed data, which provide timely and multi-band (multi-layer) data, can be substituted for the field study. In this study, the ASTER imagery is used for altera...
متن کاملassessment of the probable impacts of land use changes on water quality in shadeghan wetland using remotely sensed data
In this research, the evaluation of possible effects of land-use change on water quality in Shadegan wetland has been provided with the help of remote sensing data. The purpose of this research was to evaluate and compare user variations in 2000 and 2015 using Landsat satellite imagery (with ETM and OLI sensors) from the study area and processing them in the ERDAS software environment using the...
متن کاملCoastal water quality assessment based on the remotely sensed water quality index using time series of satellite images
This study was conducted with the aim of providing a remotely sensed water quality index in Assaluyeh port using remote sensing technology. so, according to the region conditions, studying of scientific resources and access to satellite data, the parameters of heavymetals, dissolved ions, SST, chlorophyll-a and pH were selected. Then, by reviewing sources, the product MYD091km, MYD021km, MOD02...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Remote Sensing
دوره 8 شماره
صفحات -
تاریخ انتشار 2016