{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:09:04Z","timestamp":1761808144810,"version":"build-2065373602"},"reference-count":59,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2017,9,22]],"date-time":"2017-09-22T00:00:00Z","timestamp":1506038400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000183","name":"Army Research Office","doi-asserted-by":"publisher","award":["W911NF-11-1-0310"],"award-info":[{"award-number":["W911NF-11-1-0310"]}],"id":[{"id":"10.13039\/100000183","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NASA","award":["NNX14AN39A","NNX14AD81G"],"award-info":[{"award-number":["NNX14AN39A","NNX14AD81G"]}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["EAR-1331872"],"award-info":[{"award-number":["EAR-1331872"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Water-limited ecosystems encompass approximately 40% of terrestrial land mass and play a critical role in modulating Earth\u2019s climate and provisioning ecosystem services to humanity. Spaceborne remote sensing is a critical tool for characterizing ecohydrologic patterns and advancing the understanding of the interactions between atmospheric forcings and ecohydrologic responses. Fine to medium scale spatial and temporal resolutions are needed to capture the spatial heterogeneity and the temporally intermittent response of these ecosystems to environmental forcings. Techniques combining complementary remote sensing datasets have been developed, but the heterogeneous nature of these regions present significant challenges. Here we investigate the capacity of one such approach, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm, to map Normalized Difference Vegetation Index (NDVI) at 30 m spatial resolution and at a daily temporal resolution in an experimental watershed in southwest Idaho, USA. The Dry Creek Experimental Watershed captures an ecotone from a sagebrush steppe ecosystem to evergreen needle-leaf forests along an approximately 1000 m elevation gradient. We used STARFM to fuse NDVI retrievals from the MODerate-resolution Imaging Spectroradiometer (MODIS) and Landsat during the course of a growing season (April to September). Specifically we input to STARFM a pair of Landsat NDVI retrievals bracketing a sequence of daily MODIS NDVI retrievals to yield daily estimates of NDVI at resolutions of 30 m. In a suite of data denial experiments we compared these STARFM predictions against corresponding Landsat NDVI retrievals and characterized errors in predicted NDVI. We investigated how errors vary as a function of vegetation functional type and topographic aspect. We find that errors in predicting NDVI were highest during green-up and senescence and lowest during the middle of the growing season. Absolute errors were generally greatest in tree-covered portions of the watershed and lowest in locations characterized by grasses\/bare ground. On average, relative errors in predicted average NDVI were greatest in grass\/bare ground regions, on south-facing aspects, and at the height of the growing season. We present several ramifications revealed in this study for the use of multi-sensor remote sensing data for the study of spatiotemporal ecohydrologic patterns in dryland ecosystems.<\/jats:p>","DOI":"10.3390\/rs9100981","type":"journal-article","created":{"date-parts":[[2017,9,22]],"date-time":"2017-09-22T11:03:15Z","timestamp":1506078195000},"page":"981","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Assessing a Multi-Platform Data Fusion Technique in Capturing Spatiotemporal Dynamics of Heterogeneous Dryland Ecosystems in Topographically Complex Terrain"],"prefix":"10.3390","volume":"9","author":[{"given":"Peter","family":"Olsoy","sequence":"first","affiliation":[{"name":"Department of Geosciences, Boise State University, Boise, ID 83702, USA"},{"name":"School of the Environment, Washington State University, Pullman, WA 99164, USA"}]},{"given":"Jessica","family":"Mitchell","sequence":"additional","affiliation":[{"name":"Department of Geography and Planning, Appalachian State University, Boone, NC 28608, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2124-7654","authenticated-orcid":false,"given":"Nancy","family":"Glenn","sequence":"additional","affiliation":[{"name":"Department of Geosciences, Boise State University, Boise, ID 83702, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7240-9265","authenticated-orcid":false,"given":"Alejandro","family":"Flores","sequence":"additional","affiliation":[{"name":"Department of Geosciences, Boise State University, Boise, ID 83702, USA"}]}],"member":"1968","published-online":{"date-parts":[[2017,9,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1038\/nature13376","article-title":"Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle","volume":"509","author":"Poulter","year":"2014","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1131","DOI":"10.1007\/s00382-015-2636-8","article-title":"Global semi-arid climate change over last 60 years","volume":"46","author":"Huang","year":"2016","journal-title":"Clim. 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