NASA Land Cover and Land Use Change (LCLUC): an interdisciplinary research program.

Understanding Land Cover/Land Use Change (LCLUC) in diverse regions of the world and at varied spatial scales is one of the important challenges in global change research. In this article, we provide a brief overview of the NASA LCLUC program, its focus areas, and the importance of satellite remote sensing observations in LCLUC research including future directions. The LCLUC Program was designed to be a cross-cutting theme within NASA's Earth Science program. The program aims to develop and use remote sensing technologies to improve understanding of human interactions with the environment. Since 1997, the NASA LCLUC program has supported nearly 280 research projects on diverse topics such as forest loss and carbon, urban expansion, land abandonment, wetland loss, agricultural land use change and land use change in mountain systems. The NASA LCLUC program emphasizes studies where land-use changes are rapid or where there are significant regional or global LCLUC implications. Over a period of years, the LCLUC program has contributed to large regional science programs such as Land Biosphere-Atmosphere (LBA), the Northern Eurasia Earth Science Partnership Initiative (NEESPI), and the Monsoon Area Integrated Regional Study (MAIRS). The primary emphasis of the program will remain on using remote sensing datasets for LCLUC research. The program will continue to emphasize integration of physical and social sciences to address regional to global scale issues of LCLUC for the benefit of society.

[1]  Didier Tanré,et al.  Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview , 1997, IEEE Trans. Geosci. Remote. Sens..

[2]  Keqi Zhang,et al.  Mapping Height and Biomass of Mangrove Forests in Everglades National Park with SRTM Elevation Data , 2006 .

[3]  M. Hansen,et al.  Quantification of global gross forest cover loss , 2010, Proceedings of the National Academy of Sciences.

[4]  D. Roy,et al.  The GOFC-GOLD Fire Mapping and Monitoring Theme: Assessment and Strategic Plans , 2013 .

[5]  Jason Budinoff,et al.  The Thermal Infrared Sensor on the Landsat Data Continuity Mission , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[6]  K. Seto,et al.  Modeling the Drivers of Urban Land Use Change in the Pearl River Delta, China: Integrating Remote Sensing with Socioeconomic Data , 2003, Land Economics.

[7]  David P. Roy,et al.  Continuous fields of land cover for the conterminous United States using Landsat data: first results from the Web-Enabled Landsat Data (WELD) project , 2011 .

[8]  C. Nunes,et al.  Land-Use and Land-Cover Change (LUCC): Implementation Strategy , 1999 .

[9]  C. Justice,et al.  Land cover and global productivity: A measurement strategy for the NASA programme , 2000 .

[10]  D. Roy,et al.  The suitability of decadal image data sets for mapping tropical forest cover change in the Democratic Republic of Congo: implications for the global land survey , 2008 .

[11]  Matthew C. Hansen,et al.  Quantifying changes in the rates of forest clearing in Indonesia from 1990 to 2005 using remotely sensed data sets , 2009 .

[12]  C. Justice,et al.  The Evolution of U.S. Moderate Resolution Optical Land Remote Sensing from AVHRR to VIIRS , 2010 .

[13]  C. Justice,et al.  Global land cover classification by remote sensing: present capabilities and future possibilities , 1991 .

[14]  Darrel L. Williams,et al.  Moderate Spatial Resolution Optical Sensors , 2009 .

[15]  David P. Roy,et al.  MODIS Land Data Products: Generation, Quality Assurance and Validation , 2010 .

[16]  Michael Keller,et al.  A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia , 2009, Remote. Sens..

[17]  D. Roy,et al.  Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States , 2010 .

[18]  R. DeFries,et al.  Toward a whole-landscape approach for sustainable land use in the tropics , 2010, Proceedings of the National Academy of Sciences.

[19]  C. Justice,et al.  Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005 , 2008 .

[20]  Stephen V. Stehman,et al.  Gross forest cover loss in temperate forests: biome-wide monitoring results using MODIS and Landsat data , 2009 .

[21]  C. Justice,et al.  Land and cryosphere products from Suomi NPP VIIRS: Overview and status , 2013, Journal of geophysical research. Atmospheres : JGR.

[22]  Martha C. Anderson,et al.  Landsat-8: Science and Product Vision for Terrestrial Global Change Research , 2014 .

[23]  Darrel L. Williams,et al.  The Future of Landsat-Class Remote Sensing , 2010 .

[24]  Guenther Fischer,et al.  Global Agro-ecological Assessment for Agriculture in the 21st Century , 2002 .

[25]  S. Goward,et al.  An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks , 2010 .

[26]  C. Justice,et al.  Active fires from the Suomi NPP Visible Infrared Imaging Radiometer Suite: Product status and first evaluation results , 2014 .

[27]  Damien Sulla-Menashe,et al.  MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets , 2010 .

[28]  R. K. Dixon,et al.  Carbon Pools and Flux of Global Forest Ecosystems , 1994, Science.

[29]  Valentí Rull,et al.  Unexpected biodiversity loss under global warming in the neotropical Guayana Highlands: a preliminary appraisal , 2006 .

[30]  Christopher O. Justice,et al.  Recent data and information system initiatives for remotely sensed measurements of the land surface , 1995 .

[31]  Bruce W. Pengra,et al.  Monitoring mangrove forest dynamics of the Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000 , 2007 .

[32]  C. Justice,et al.  High-Resolution Global Maps of 21st-Century Forest Cover Change , 2013, Science.

[33]  Christopher O. Justice,et al.  Land remote sensing and global environmental change : NASA's earth observing system and the science of ASTER and MODIS , 2011 .

[34]  A. Watson,et al.  Effect of iron supply on Southern Ocean CO2 uptake and implications for glacial atmospheric CO2 , 2000, Nature.

[35]  S. Pacala,et al.  Projecting the future of the U.S. carbon sink , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[36]  Mark Sullivan,et al.  Monitoring Global Croplands with Coarse Resolution Earth Observations: The Global Agriculture Monitoring (GLAM) Project , 2010, Remote. Sens..

[37]  Jiaguo Qi,et al.  Understanding the coupled natural and human systems in Dryland East Asia , 2012 .

[38]  S. Goward,et al.  Dynamics of national forests assessed using the Landsat record: Case studies in eastern United States , 2009 .

[39]  D. Roy,et al.  An overview of MODIS Land data processing and product status , 2002 .

[40]  C. Woodcock,et al.  Mapping Urban Areas by Fusing Multiple Sources of Coarse Resolution Remotely Sensed Data , 2003 .

[41]  R. DeFries,et al.  Deforestation driven by urban population growth and agricultural trade in the twenty-first century , 2010 .

[42]  Stephen V. Stehman,et al.  International Journal of Applied Earth Observation and Geoinformation: Time-Series Analysis of Multi-Resolution Optical Imagery for Quantifying Forest Cover Loss in Sumatra and Kalimantan, Indonesia , 2011 .

[43]  D. Roy,et al.  The MODIS Land product quality assessment approach , 2002 .

[44]  Feng Gao,et al.  LEDAPS Landsat Calibration, Reflectance, Atmospheric Correction Preprocessing Code , 2012 .

[45]  Jesslyn F. Brown,et al.  Development of a land-cover characteristics database for the conterminous U.S. , 1991 .

[46]  W. Salas,et al.  LAND USE AND LAND COVER CHANGE IN SOUTHEAST ASIA , 2012 .

[47]  C. Justice,et al.  International Coordination of Satellite Land Observations: Integrated Observations of the Land , 2010 .

[48]  C. Justice,et al.  A framework for the validation of MODIS Land products , 2002 .

[49]  J. Townshend,et al.  Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data , 2008, Proceedings of the National Academy of Sciences.

[50]  C. Tucker,et al.  Tropical Deforestation and Habitat Fragmentation in the Amazon: Satellite Data from 1978 to 1988 , 1993, Science.

[51]  Christopher O. Justice,et al.  Cloud cover throughout the agricultural growing season: Impacts on passive optical earth observations , 2015 .

[52]  Christopher O. Justice,et al.  Data sets for global remote sensing: lessons learnt† , 1994 .

[53]  E. Lambin,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:Global land use change, economic globalization, and the looming land scarcity , 2011 .

[54]  J. Townshend,et al.  African Land-Cover Classification Using Satellite Data , 1985, Science.

[55]  C. Woodcock,et al.  The Effects of Land Use Change on Terrestrial Carbon Dynamics in the Black Sea Region , 2009 .

[56]  Thomas R. Karl,et al.  State of the ground : Climatology and changes during the past 69 years over northern eurasia for a rarely used measure of snow cover and frozen land , 2006 .

[57]  S. Malyshev,et al.  The underpinnings of land‐use history: three centuries of global gridded land‐use transitions, wood‐harvest activity, and resulting secondary lands , 2006 .

[58]  J. Townshend,et al.  Assessment of Paraguay's forest cover change using Landsat observations , 2009 .

[59]  R. Deo,et al.  A continent under stress: interactions, feedbacks and risks associated with impact of modified land cover on Australia's climate , 2009 .

[60]  G. Chander,et al.  Assessment of the NASA–USGS Global Land Survey (GLS) datasets , 2013 .

[61]  Curtis E. Woodcock,et al.  Changes in Summer Irrigated Crop Area and Water Use in Southeastern Turkey from 1993 to 2002: Implications for Current and Future Water Resources , 2006 .