NDLI: SAND - a hyperspectral sensor for the analysis of dryland degradation

Content Provider	IEEE Xplore Digital Library
Author	Kaufmann, H. Chabrillat, S. Hill, J. Langemann, M. Muller, A. Staenz, K.
Copyright Year	2002
Description	Author affiliation: GeoResearchCentre Potsdam, Germany (Kaufmann, H.; Chabrillat, S.)
Abstract	SAND proposes a space-borne imaging spectrometer (hyperspectral) mission measuring bio-geochemical/bio-geophysical variables to determine land degradation processes in semi-arid geographical areas. Arid and semi-arid lands cover approximately one third of the continental surface of the Earth. They include the deserts and their semi-arid and sub-humid dry margins, and the subtropical Mediterranean latitudes. The semi-arid ecosystems provide important land resources for adapted agricultural production and grazing systems. The importance of thoroughly monitoring the state of the environment in areas considered at risk, in the context of global climatic change and worldwide desertification dynamics, has long been recognised. These facts have led to the ratification of the UN Convention to Combat Desertification (UNCCD) by almost 200 nations worldwide. This agreement emphasises the need to assess land degradation and desertification processes. The status of dryland systems is controlled to a large extent by a fragile equilibrium between soil, vegetation and water resources. Precipitation rates are generally low and rainfall events are known to be irregular and of high intensity. Natural ecosystems and traditional land use practices have largely adapted to these conditions over time, and thus, assure an optimum use of available resources. Dryland degradation may be triggered by (global) climatic change and/or human mismanagement. While the former may result in longer and more frequent drought events, the latter one mainly consists of inappropriate land use practices. Both may induce changes in surface properties, impacting the type and density of the vegetation cover. Many of these changes can be detected remotely by measuring the spectral characteristics of the land surfaces. Accordingly, a high-spectral resolution remote sensing system such as the proposed SAND substantially increases these detection capabilities. This paper presents a sensor concept providing global coverage at a reasonable spatial and very high spectral resolution for a quantitative derivation of land surface variables. This includes vegetation parameters and soil-related information such as foliage chemistry, water content, fractional cover, chemical composition, organic matter content and information about the lithological background for selected targets.
Sponsorship	IEEE IEEE Geosci. & Remote Sensing Soc. Canadian Remote Sensing Soc. Univ. Waterloo Natural Resources Canada (NRCan) Canadian Space Agency (CSA) Environ. Canada NASA Nat. Oceanic & Atmos. Adm. (NOAA) Office of Naval Res.(ONR) Nat. Space Dev. Agency of Japan (NASDA) Nat. Polar-orbiting Environ. Satellite Syst. (NPOESS)
Starting Page	986
Ending Page	988
File Size	267992
Page Count	3
File Format	PDF
ISBN	078037536X
DOI	10.1109/IGARSS.2002.1025751
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-06-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hyperspectral sensors Degradation Land surface Hyperspectral imaging Ecosystems Vegetation mapping Spatial resolution Spectroscopy Area measurement Earth
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

EnMAP A Hyperspectral Sensor for Environmental Mapping and Analysis

Mapping submerged aquatic vegetation with hyperspectral techniques

Vegetable green coverage estimation from an airborne hyperspectral image

HYPXIM: A new hyperspectral sensor combining science/defence applications

Exploiting spectral and spatial information for classifying hyperspectral data in urban areas

Comparison of AVIRIS and AISA for chemistry mapping

Application of spectroscopial, hyperspectral and multispectral data to study wetlands in semi-arid environments (Central Spain)

Imaging Spectrometry: Sensors And Data Analysis

Grid pattern based residential area detection from Hyperion data

SAND - a hyperspectral sensor for the analysis of dryland degradation

Similar Documents

EnMAP A Hyperspectral Sensor for Environmental Mapping and Analysis

Mapping submerged aquatic vegetation with hyperspectral techniques

Vegetable green coverage estimation from an airborne hyperspectral image

HYPXIM: A new hyperspectral sensor combining science/defence applications

Exploiting spectral and spatial information for classifying hyperspectral data in urban areas

Comparison of AVIRIS and AISA for chemistry mapping

Application of spectroscopial, hyperspectral and multispectral data to study wetlands in semi-arid environments (Central Spain)

Imaging Spectrometry: Sensors And Data Analysis

Grid pattern based residential area detection from Hyperion data

SAND - a hyperspectral sensor for the analysis of dryland degradation